[
  {
    "canonical": true,
    "canonical_title": "The Nvidia Way: Jensen Huang and the Making of a Tech Giant",
    "conflict_flag": false,
    "editorial": {
      "author": "Tae Kim",
      "category": "Journalism & Biography",
      "desc_confidence": "High",
      "description": "A business biography of Nvidia and its founder Jensen Huang, written by a financial journalist. It traces the company from a precarious 1990s graphics-card startup to the dominant supplier of GPUs that power modern AI. Kim argues that Nvidia's culture, not just its silicon, explains its success: flat structure, brutal candor, and an obsession with anticipating markets that do not yet exist. The book covers near-death moments where a single product bet could have ended the company. It explains how the CUDA software platform turned graphics chips into general-purpose compute engines and locked in developers. Huang emerges as a demanding, mission-driven operator who runs with an unusually wide span of control. The narrative connects the deep-learning boom to Nvidia's hardware becoming the default training substrate. It is reported through interviews with employees and executives rather than technical exposition. The throughline is strategic patience: investing for a decade before a market arrives. For a governance reader it is a case study in platform lock-in and concentrated infrastructure power.",
      "source": "Appelo core"
    },
    "id": "book-0001",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "2084 and the AI Revolution (Updated and Expanded Edition): How Artificial Intelligence Informs Our Future",
    "conflict_flag": false,
    "editorial": {
      "author": "John C. Lennox",
      "category": "Futures",
      "desc_confidence": "High",
      "description": "Lennox, an Oxford mathematician and Christian apologist, examines artificial intelligence through a theological and ethical lens. The title plays on Orwell's 1984, projecting forward to imagined futures of narrow and general AI. He distinguishes carefully between today's task-specific systems and speculative superintelligence, cautioning against conflating them. The book surveys transhumanist ambitions to enhance or transcend the human body and treats them as quasi-religious aspirations. Lennox argues that questions of meaning, personhood, and morality cannot be resolved by engineering alone. He engages with thinkers such as Harari and Kurzweil and contests their materialist assumptions. A central claim is that a worldview shapes how one interprets technological power. The updated edition incorporates the rise of generative models and large language models. It is written for a general audience rather than specialists. The work is best read as a faith-informed critique of techno-utopianism rather than a technical guide.",
      "source": "Appelo core"
    },
    "id": "book-0002",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Boom: Bubbles and the End of Stagnation",
    "conflict_flag": false,
    "editorial": {
      "author": "Byrne Hobart, Tobias Huber",
      "category": "Economics & Labour",
      "desc_confidence": "Medium",
      "description": "Hobart and Huber make a contrarian case that financial bubbles can be engines of progress rather than only destructive manias. They argue that periods of speculative excess concentrate capital and talent on ambitious technological bets that ordinary markets would not fund. The book reads economic history, from railways to the internet, as evidence that overshoot leaves durable infrastructure behind. The authors connect this to a critique of contemporary stagnation, low growth, and risk-averse institutions. AI and frontier technology feature as the kind of high-variance domain bubbles can accelerate. They distinguish productive bubbles that build lasting capacity from purely extractive ones. The argument draws on finance, philosophy of science, and Girardian ideas about mimetic desire. It is provocative and essayistic rather than empirical in the academic sense. The implication is that society may need coordinated, almost millenarian belief to fund breakthroughs. For an AI investor it frames the current capital surge as potentially civilization-shaping.",
      "source": "Appelo core"
    },
    "id": "book-0003",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Genesis: Artificial Intelligence, Hope, and the Human Spirit",
    "conflict_flag": false,
    "editorial": {
      "author": "Henry A. Kissinger, Eric Schmidt, Craig Mundie",
      "category": "Philosophy of Mind",
      "desc_confidence": "High",
      "description": "A high-level essay on AI's implications for geopolitics, governance, and the human condition, completed around Kissinger's death. It follows the earlier Kissinger-Schmidt collaboration and argues that AI represents an epochal shift comparable to the Enlightenment. The authors worry that machine reasoning may outstrip human comprehension, eroding the basis of accountable decision-making. They examine implications for warfare, scientific discovery, and the balance of power between states. A recurring theme is the need to preserve human agency and dignity as machines assume cognitive labor. The book calls for new institutions and norms to govern systems whose logic humans cannot fully audit. It treats AI as both a source of hope, especially in science and medicine, and existential risk. The tone is statesmanlike and abstract rather than technical. It urges leaders to engage now rather than react later. For governance readers it is a manifesto for anticipatory oversight by political elites.",
      "source": "Appelo core"
    },
    "id": "book-0004",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "ChatGPT and the Future of AI: The Deep Language Revolution",
    "conflict_flag": false,
    "editorial": {
      "author": "Terrence J. Sejnowski",
      "category": "Popular Science",
      "desc_confidence": "High",
      "description": "Sejnowski, a computational neuroscientist and pioneer of deep learning, explains how large language models work and why they surprised even their builders. He situates ChatGPT within the longer history of neural networks and the Boltzmann machine he helped develop. The book explores the analogy and disanalogy between artificial and biological learning. Sejnowski discusses emergent capabilities that appear at scale and were not explicitly engineered. He treats prompting as a new interface that elicits behavior rather than programs it. The author reflects on what language models reveal about the nature of intelligence and language itself. He is measured about both hype and dismissal, acknowledging genuine novelty and real limits. There are sections on hallucination, alignment, and the interpretability problem. He draws on conversations with leading researchers. The book is accessible to non-specialists while grounded in the science of learning systems.",
      "source": "Appelo core"
    },
    "id": "book-0005",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Tech Agnostic: How Technology Became the World's Most Powerful Religion, and Why It Desperately Needs a Reformation",
    "conflict_flag": false,
    "editorial": {
      "author": "Greg Epstein",
      "category": "Critique & Skepticism",
      "desc_confidence": "Medium",
      "description": "Epstein, a humanist chaplain at Harvard and MIT, argues that technology now functions as society's dominant religion. He maps the rituals, prophets, scriptures, and devotional habits of tech culture, with Silicon Valley as its clergy. The book treats smartphones, platforms, and AI as objects of faith demanding obedience and attention. Epstein is not anti-technology; he calls for a reformation that subordinates tools to human flourishing. He examines how techno-optimism and longtermism resemble eschatology. The argument draws on the sociology of religion and his own work as a secular chaplain. He critiques the surrender of moral judgment to engineers and founders. The book asks readers to reclaim agency over the systems they venerate. It is cultural criticism rather than technical analysis. For governance readers it frames AI adoption as partly a matter of belief and authority, not only capability.",
      "source": "Appelo core"
    },
    "id": "book-0006",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The Line: AI and the Future of Personhood",
    "conflict_flag": false,
    "editorial": {
      "author": "James Boyle",
      "category": "Governance & Policy",
      "desc_confidence": "High",
      "description": "Boyle, a law professor and intellectual-property scholar, asks where we will draw the line between persons and things as AI advances. He examines the legal and moral criteria by which we grant or deny personhood. The book uses thought experiments, science fiction, and case law to probe our intuitions. Boyle compares the AI question to historical expansions of legal personhood, including corporations and the contested status of enslaved people and animals. He argues our categories will be tested by entities that seem to think or suffer. The book resists easy answers, treating the question as genuinely open. It connects to debates about rights, liability, and consciousness. Boyle is skeptical of both reflexive denial and naive attribution of personhood. The style is witty and accessible for a legal-philosophy text. It is published open access, reflecting his commitments on knowledge sharing.",
      "source": "Appelo core"
    },
    "id": "book-0007",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Personalized: Customer Strategy in the Age of AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Mark Abraham, David C. Edelman",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "A management book on how AI enables personalization at scale across the customer lifecycle. The authors, from Boston Consulting Group and Harvard Business School circles, frame personalization as a strategic capability rather than a marketing tactic. They describe a model for delivering the right message, product, and experience to each customer in real time. The book stresses data infrastructure, decisioning engines, and organizational design as prerequisites. It offers cases of firms that built closed-loop systems linking signals to actions. The authors argue personalization improves both customer value and economics when done well. They address privacy, trust, and the risk of intrusive targeting. The framing is practical and aimed at executives leading transformation. It treats AI as the enabler of one-to-one relationships at mass scale. The implicit governance angle is consent, data quality, and the line between helpful and manipulative.",
      "source": "Appelo core"
    },
    "id": "book-0008",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Robot-Proof (Revised and Updated Edition): Higher Education in the Age of Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Joseph E. Aoun",
      "category": "Education",
      "desc_confidence": "Medium",
      "description": "Aoun, president of Northeastern University, argues that higher education must prepare graduates to do what machines cannot. He proposes a new literacy he calls humanics, combining technological, data, and human skills. The book champions experiential learning and lifelong education as defenses against automation. Aoun contends that creativity, entrepreneurship, and cultural agility are durable human advantages. The revised edition incorporates generative AI's impact on curricula and assessment. He criticizes rote, content-delivery models of teaching as exactly what AI displaces. The argument is institutional: universities must restructure, not just add courses. He draws on cognitive science and labor-market trends. The book is aimed at educators, administrators, and policymakers. Its thesis is optimistic that education can adapt if it centers distinctly human capacities.",
      "source": "Appelo core"
    },
    "id": "book-0009",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Hands-On Large Language Models: Language Understanding and Generation",
    "conflict_flag": false,
    "editorial": {
      "author": "Jay Alammar, Maarten Grootendorst",
      "category": "LLM Engineering",
      "desc_confidence": "High",
      "description": "A practical, visual technical guide to building with large language models, from two well-known explainers of NLP. Alammar is famous for illustrated tutorials on transformers and attention. The book covers tokenization, embeddings, transformer architecture, and the mechanics of generation. It is hands-on, with code and worked examples for tasks like classification, search, and retrieval-augmented generation. The authors explain fine-tuning, prompting, and evaluation in accessible terms. Diagrams carry much of the conceptual load, making internals legible. It targets practitioners and engineers rather than researchers. The book bridges intuition and implementation without heavy mathematics. It covers semantic search and clustering using embeddings. For an applied team it is a reference for moving from concept to working pipeline.",
      "source": "Appelo core"
    },
    "id": "book-0010",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI Snake Oil: What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference",
    "conflict_flag": false,
    "editorial": {
      "author": "Arvind Narayanan, Sayash Kapoor",
      "category": "Critique & Skepticism",
      "desc_confidence": "High",
      "description": "Two Princeton researchers distinguish genuine AI advances from overhyped or fraudulent claims. Their central distinction is between generative AI, which has improved rapidly, and predictive AI used for consequential decisions, which they argue often fails. They show that predictive systems for hiring, recidivism, and welfare frequently perform little better than simple baselines while causing real harm. The book documents how flawed evaluations and data leakage inflate reported accuracy. The authors are skeptical of existential-risk framing crowding out present harms. They give readers heuristics to spot snake oil in vendor claims and media coverage. The tone is empirical and debunking but not anti-AI. They emphasize accountability, transparency, and the limits of prediction in social systems. It draws on their widely read newsletter of the same name. For governance work it is a rigorous antidote to capability hype.",
      "source": "Appelo core"
    },
    "id": "book-0011",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Artificial General Intelligence: The MIT Press Essential Knowledge series",
    "conflict_flag": false,
    "editorial": {
      "author": "Julian Togelius",
      "category": "Futures",
      "desc_confidence": "Medium",
      "description": "A concise primer on the idea of artificial general intelligence from an AI and games researcher. Togelius examines what generality would mean and why it is hard to define or measure. He surveys historical and current approaches, from symbolic AI to deep learning and reinforcement learning. The book is skeptical of confident timelines while taking the goal seriously. It discusses benchmarks, the role of embodiment, and the difficulty of testing for general capability. Togelius uses games as a recurring testbed for intelligence research. He addresses both the scientific and the hype-driven framings of AGI. The Essential Knowledge format keeps it short and accessible. It is balanced rather than alarmist or evangelical. For a general reader it clarifies a term that is used loosely and inconsistently.",
      "source": "Appelo core"
    },
    "id": "book-0012",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The Digitalist Papers: Artificial Intelligence and Democracy in America",
    "conflict_flag": false,
    "editorial": {
      "author": "Erik Brynjolfsson, et al.",
      "category": "Governance & Policy",
      "desc_confidence": "Medium",
      "description": "A collection of essays, echoing the Federalist Papers, on how AI will reshape American democracy and institutions. Edited around Stanford scholars including Brynjolfsson, it gathers economists, technologists, and political thinkers. Contributions address governance, civic participation, labor, and the information ecosystem. The collection asks how democratic institutions can harness AI while guarding against concentration of power. Several essays propose new mechanisms for accountability and public deliberation. It treats AI as a structural force on the social contract, not only an economic input. The essays vary in stance from optimistic to cautionary. It is aimed at policymakers and engaged citizens. The framing is deliberative: society must choose institutional responses now. For governance readers it is a source of policy-design ideas rather than a single argument.",
      "source": "Appelo core"
    },
    "id": "book-0013",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Taming Silicon Valley: How We Can Ensure That AI Works for Us",
    "conflict_flag": false,
    "editorial": {
      "author": "Gary Marcus",
      "category": "Governance & Policy",
      "desc_confidence": "High",
      "description": "Marcus, a cognitive scientist and prominent AI critic, argues that current AI is unreliable and that industry incentives make it dangerous. He catalogs failures of large language models, including hallucination, bias, and brittleness. The book contends that hype outpaces capability and that profit motives override safety. Marcus calls for robust regulation, independent oversight, and liability for harms. He is critical of both reckless deployment and the concentration of power in a few firms. The argument distinguishes near-term harms like misinformation from speculative long-term risk. He proposes concrete policy measures, including transparency and pre-deployment testing. The tone is urgent and combative toward the major labs. It draws on his long-running public disputes about deep learning's limits. For governance readers it is an accessible policy brief from a leading skeptic.",
      "source": "Appelo core"
    },
    "id": "book-0014",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The AI-Driven Leader: Harnessing AI to Make Faster, Smarter Decisions",
    "conflict_flag": false,
    "editorial": {
      "author": "Geoff Woods",
      "category": "Business & Strategy",
      "desc_confidence": "Low",
      "description": "A practitioner-oriented business book on using AI, especially chat assistants, as a thinking partner for executives. The stated thesis is that leaders should treat AI as an advisor for strategy and decision-making rather than only a task tool. It offers frameworks and prompts for applying AI to leadership problems. Reliable independent detail on the content is limited; this description is based on the title, subtitle, and positioning. Treat specifics as unverified until checked against the text.",
      "source": "Appelo core"
    },
    "id": "book-0015",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Mastering AI Prompt Engineering: The Ultimate Guide for ChatGPT Users",
    "conflict_flag": false,
    "editorial": {
      "author": "Adriano Damiao",
      "category": "LLM Engineering",
      "desc_confidence": "Low",
      "description": "A self-published how-to guide on writing effective prompts for ChatGPT and similar tools. It presents prompting patterns, examples, and templates for common tasks. The audience is general users seeking better outputs from chat assistants. Independent information on the book's depth and originality is sparse; this summary is inferred from the title and category. Treat content specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0016",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Human+Machine: Reimagining Work in the Age of AI (Updated and Expanded)",
    "conflict_flag": false,
    "editorial": {
      "author": "Paul R. Daugherty, H. James Wilson",
      "category": "Business & Strategy",
      "desc_confidence": "High",
      "description": "Two Accenture leaders argue that the future of work lies in collaboration between humans and machines, not replacement. They describe a missing middle of hybrid roles where humans train, explain, and sustain AI, and AI amplifies human judgment. The book introduces the idea of the fusion skills needed to work alongside intelligent systems. It draws on numerous corporate cases of process redesign around AI. The updated edition incorporates generative AI's effect on knowledge work. The authors stress responsible AI, transparency, and reskilling. They frame AI adoption as an organizational and managerial challenge as much as a technical one. The argument is optimistic but practical about implementation. It targets executives leading transformation programs. For governance readers it foregrounds human oversight roles as a design principle.",
      "source": "Appelo core"
    },
    "id": "book-0017",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Nexus: A Brief History of Information Networks from the Stone Age to AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Yuval Noah Harari",
      "category": "History",
      "desc_confidence": "High",
      "description": "Harari traces how information networks, from myth and scripture to bureaucracy and computers, have shaped human power. His central claim is that information is not truth but connection, and networks can spread fictions as easily as facts. He argues that AI is a new kind of agent in these networks, able to generate stories and make decisions on its own. The book warns that AI could create powerful, self-reinforcing information systems beyond human control. Harari contrasts democratic self-correcting networks with totalitarian ones. He examines the risk of AI undermining the shared narratives that hold societies together. The work spans deep history and speculative future in his characteristic sweep. It treats alignment and oversight as civilizational questions. He is cautious about both utopian and catastrophic framings. For governance readers it is a wide-lens argument for institutional self-correction.",
      "source": "Appelo core"
    },
    "id": "book-0018",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Supremacy: AI, ChatGPT, and the Race that Will Change the World",
    "conflict_flag": false,
    "editorial": {
      "author": "Parmy Olson",
      "category": "Journalism & Biography",
      "desc_confidence": "High",
      "description": "A reported account of the rivalry between OpenAI and DeepMind, and their absorption into Microsoft and Google. Olson, a technology journalist, profiles Sam Altman and Demis Hassabis as contrasting figures driving the field. The book chronicles how idealistic mission statements collided with commercial pressure and corporate capture. It covers the founding ideals, funding crises, and governance disputes of the leading labs. Olson examines how the race dynamic eroded earlier safety commitments. The narrative connects research breakthroughs to the scramble for power and market dominance. It won recognition as a business book of the year. The reporting draws on interviews and internal accounts. The throughline is concentration: two labs and two giants shaping the technology. For governance readers it documents how mission and money interact in frontier AI.",
      "source": "Appelo core"
    },
    "id": "book-0019",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Irreplaceable: The Art of Standing Out in the Age of Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Pascal Bornet",
      "category": "Economics & Labour",
      "desc_confidence": "Medium",
      "description": "Bornet, an automation expert, argues that humans can remain irreplaceable by cultivating distinctly human capabilities. He identifies traits like empathy, creativity, and ethical judgment that machines do not possess. The book offers practical guidance for individuals to future-proof their careers. It frames AI as augmenting rather than wholly replacing human work, if people adapt. Bornet draws on his earlier work on intelligent automation. He stresses lifelong learning and emotional intelligence as differentiators. The tone is pragmatic and motivational rather than alarmist. It includes self-assessment and actionable steps. The audience is professionals navigating automation anxiety. The thesis is that human distinctiveness is a skill to be developed deliberately.",
      "source": "Appelo core"
    },
    "id": "book-0020",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The Atomic Human: What Makes Us Unique in the Age of AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Neil D. Lawrence",
      "category": "Philosophy of Mind",
      "desc_confidence": "High",
      "description": "Lawrence, a Cambridge machine-learning professor, explores what remains essentially human as machines grow capable. The atomic human is the irreducible core left after stripping away functions machines can perform. He draws on his career in AI and on history, physics, and biology to frame the question. The book emphasizes the vast difference in information bandwidth between human communication and machine computation. Lawrence argues that our limitations, embodiment, and vulnerability are sources of meaning, not just deficits. He is critical of careless anthropomorphism and of treating intelligence as a single scalar. The work blends memoir, science, and philosophy. It addresses how to deploy AI responsibly given these differences. He resists both doom and hype. For governance readers it grounds human oversight in a serious account of what humans uniquely contribute.",
      "source": "Appelo core"
    },
    "id": "book-0021",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The AI Agent Mandate: Reimagining Work in the Age of AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Marco Buchbinder",
      "category": "Business & Strategy",
      "desc_confidence": "Low",
      "description": "A business-oriented book on autonomous AI agents and their effect on organizations and work. The premise is that agentic systems, which plan and act rather than just respond, will reshape roles and processes. It positions agents as a mandate leaders must address. Independent detail on the argument and evidence base is limited; this description is inferred from the title and category. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0022",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The Mind's Mirror: Risk and Reward in the Age of AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Daniela Rus, Gregory Mone",
      "category": "Popular Science",
      "desc_confidence": "Medium",
      "description": "Rus, director of MIT's CSAIL, with co-author Mone, offers a balanced account of AI's promise and peril. The book argues AI mirrors human intelligence in partial and sometimes distorting ways. It surveys robotics, machine learning, and applications in science and medicine. Rus emphasizes designing systems that complement human strengths. She addresses safety, bias, and the gap between narrow tools and general intelligence. The tone is measured, weighing reward against risk rather than choosing a side. It draws on her robotics research and lab leadership. The book is accessible to general readers. It advocates thoughtful, human-centered deployment. For governance readers it reflects an insider's pragmatic optimism.",
      "source": "Appelo core"
    },
    "id": "book-0023",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The Hidden Human Labor Powering A.I.",
    "conflict_flag": false,
    "editorial": {
      "author": "Callum Cant, James Muldoon, Mark Graham",
      "category": "Society & Ethics",
      "desc_confidence": "Medium",
      "description": "Often titled Feeding the Machine, this book exposes the human workforce behind supposedly automated AI. The authors document data annotators, content moderators, and gig workers, often in the Global South, who label and clean training data. They describe poor pay, traumatic content exposure, and precarious conditions. The argument is that AI is not autonomous but built on hidden, exploited labor. It draws on fieldwork and interviews across the global supply chain. The book connects AI's gleaming outputs to extractive working conditions. It situates this within debates on platform capitalism and labor rights. The authors call for transparency and worker protections. The tone is investigative and critical. For governance readers it foregrounds supply-chain ethics and labor accountability in AI.",
      "source": "Appelo core"
    },
    "id": "book-0024",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Humanity Redefined: How AI is Going to Reshape Our Shared Destiny in the Next 40 Years",
    "conflict_flag": false,
    "editorial": {
      "author": "Val Kaplan",
      "category": "Futures",
      "desc_confidence": "Low",
      "description": "A forward-looking book speculating on how AI will transform society, identity, and human destiny over coming decades. It addresses themes of augmentation, work, and meaning. The framing is broad and futurist. Independent information on the book is limited; this summary is inferred from the title and subtitle. Treat content specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0025",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI Money Making Strategies for Beginners: With Zero Experience Master ChatGPT & Leverage AI",
    "conflict_flag": false,
    "editorial": {
      "author": "William Harrow",
      "category": "Business & Strategy",
      "desc_confidence": "Low",
      "description": "A self-published guide pitching ways to earn income using ChatGPT and AI tools without prior experience. It belongs to a large genre of beginner monetization manuals. Content likely covers freelancing, content creation, and side hustles using AI. Independent verification of the book's quality or specifics is not available; this description is inferred from the title. Treat all specifics as unverified, and approach claims in this genre with caution.",
      "source": "Appelo core"
    },
    "id": "book-0026",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Why Machines Learn: The Elegant Math Behind Modern AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Anil Ananthaswamy",
      "category": "Popular Science",
      "desc_confidence": "High",
      "description": "Ananthaswamy, a science writer, explains the mathematics that makes machine learning work. The book builds from linear algebra, calculus, and probability to the algorithms behind modern AI. It covers perceptrons, gradient descent, backpropagation, and neural networks with worked intuition. The aim is to make the underlying math genuinely understandable, not just gestured at. He profiles the mathematicians and researchers whose ideas underpin the field. The book balances rigor with narrative, using historical context to motivate concepts. It explains why certain methods work, addressing the surprising effectiveness of these techniques. The audience is curious readers willing to engage with equations. It demystifies learning as optimization over data. For technical readers it connects abstract math to the systems shaping society.",
      "source": "Appelo core"
    },
    "id": "book-0027",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Mastering AI: A Survival Guide to Our Superpowered Future",
    "conflict_flag": false,
    "editorial": {
      "author": "Jeremy Kahn",
      "category": "Futures",
      "desc_confidence": "Medium",
      "description": "Kahn, an AI journalist at Fortune, surveys how AI will affect work, creativity, democracy, and daily life. The book aims to be a practical and policy-aware guide to navigating disruption. It weighs benefits in medicine and productivity against risks of misinformation and concentration. Kahn argues outcomes depend on choices made now by firms, governments, and individuals. He covers generative AI's capabilities and limits in accessible terms. The book includes recommendations for individuals and policymakers. The tone is pragmatic, neither utopian nor catastrophist. It draws on his reporting and interviews across the field. It frames AI as powerful but steerable. For governance readers it links capability trends to actionable policy stakes.",
      "source": "Appelo core"
    },
    "id": "book-0028",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI for Beginners Made Easy: Master Artificial Intelligence from Generative AI to Machine Learning",
    "conflict_flag": false,
    "editorial": {
      "author": "Alex Bennett",
      "category": "Popular Science",
      "desc_confidence": "Low",
      "description": "An introductory primer aimed at newcomers covering generative AI and machine learning basics. It belongs to the crowded beginner-explainer category. Likely content includes core concepts, terminology, and everyday applications. Independent detail on the book is sparse; this description is inferred from the title. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0029",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Prompt Engineering for Generative AI: Future-Proof Inputs for Reliable AI Outputs",
    "conflict_flag": false,
    "editorial": {
      "author": "James Phoenix, Mike Taylor",
      "category": "LLM Engineering",
      "desc_confidence": "Medium",
      "description": "An O'Reilly technical guide to prompting large language and image models for reliable results. It treats prompt engineering as a discipline with patterns, evaluation, and reproducibility. The book covers text and image generation, chaining, and tool use. It addresses techniques like few-shot prompting, structured output, and retrieval augmentation. The authors emphasize building robust, maintainable AI applications rather than one-off tricks. It includes code and practical workflows for developers. The aim is durable practices that survive model changes. It targets engineers and product builders. The framing is applied and systematic. For practitioners it is a working reference rather than an introduction.",
      "source": "Appelo core"
    },
    "id": "book-0030",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The Singularity Is Nearer: When We Merge with AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Ray Kurzweil",
      "category": "Futures",
      "desc_confidence": "High",
      "description": "Kurzweil updates his long-running thesis that exponential progress will lead to a technological singularity. He reaffirms predictions of human-level AI by around 2029 and a singularity around 2045. The book argues humans will merge with AI through brain-computer interfaces and nanotechnology. Kurzweil presents charts of accelerating returns across computing and biotechnology. He addresses life extension, radical health improvement, and the transformation of intelligence. The work responds to critics and revisits his earlier forecasts. It is unabashedly optimistic about transcending biological limits. He treats the merger of human and machine as both feasible and desirable. The tone is futurist and technophilic. For governance readers it is the canonical statement of techno-optimist acceleration.",
      "source": "Appelo core"
    },
    "id": "book-0031",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Code Dependent: Living in the Shadow of AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Madhumita Murgia",
      "category": "Society & Ethics",
      "desc_confidence": "High",
      "description": "Murgia, the Financial Times' AI editor, reports on how algorithms already shape ordinary lives, especially of the vulnerable. The book follows individuals affected by AI systems across continents, from gig workers to welfare recipients. It centers human stories over technical exposition, documenting surveillance, bias, and loss of agency. Murgia shows how automated decisions can be opaque and hard to contest. She covers data labelers, facial recognition, and predictive systems in public services. The reporting spans the Global South as well as wealthy countries. The argument is that AI's harms fall unevenly and often invisibly. It was shortlisted for major nonfiction prizes. The tone is humane and investigative. For governance readers it grounds abstract risk in lived, documented experience.",
      "source": "Appelo core"
    },
    "id": "book-0032",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The AI-Savvy Leader: Nine Ways to Take Back Control and Make AI Work",
    "conflict_flag": false,
    "editorial": {
      "author": "David De Cremer",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "De Cremer, a management scholar, argues that leaders too often abdicate AI strategy to technologists. He offers nine leadership behaviors to keep humans in control of AI adoption. The book stresses that AI transformation is a leadership and culture problem, not just a technical one. He warns against passive deference to vendors and data teams. The argument centers on purpose, judgment, and responsibility staying with leaders. It includes guidance on aligning AI with organizational values. The tone is practical and aimed at executives. De Cremer draws on behavioral and organizational research. He treats human oversight as a leadership duty. For governance readers it reinforces accountability residing with decision-makers.",
      "source": "Appelo core"
    },
    "id": "book-0033",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI in Business: A Winning Guide to Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Sebastian Forbes",
      "category": "Business & Strategy",
      "desc_confidence": "Low",
      "description": "A general business guide to applying AI in organizations. Likely content covers use cases, adoption steps, and competitive positioning. It belongs to the broad practitioner-introduction category. Independent detail on the book is limited; this summary is inferred from the title. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0034",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The Skill Code: How to Save Human Ability in an Age of Intelligent Machines",
    "conflict_flag": false,
    "editorial": {
      "author": "Matt Beane",
      "category": "Economics & Labour",
      "desc_confidence": "High",
      "description": "Beane, a management researcher, examines how automation threatens the way humans learn skills through apprenticeship. His core finding is that intelligent machines often sever the novice-expert relationship that builds mastery. Drawing on fieldwork in surgery, he shows trainees losing hands-on experience to robotic systems. The book identifies challenge, complexity, and connection as the ingredients of real skill development. Beane warns that efficiency-driven automation can quietly erode the pipeline of expertise. He offers principles for preserving learning while adopting AI. The argument generalizes from surgery to many professions facing similar dynamics. It is based on years of observational research. The tone is constructive, not anti-technology. For governance readers it raises long-term capability and workforce risks from automation.",
      "source": "Appelo core"
    },
    "id": "book-0035",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI Driven: Staying Alive in the Age of Digital Darwinism",
    "conflict_flag": false,
    "editorial": {
      "author": "Wolf Ruzicka, Victor Shilo",
      "category": "Business & Strategy",
      "desc_confidence": "Low",
      "description": "A business book framing AI adoption as survival in a fast-evolving competitive landscape, invoking digital Darwinism. The premise is that firms must adapt to AI or face extinction. Likely content covers strategy, transformation, and organizational change. Independent detail is sparse; this description is inferred from the title and subtitle. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0036",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The AI Mirror: How to Reclaim Our Humanity in an Age of Machine Thinking",
    "conflict_flag": false,
    "editorial": {
      "author": "Shannon Vallor",
      "category": "Philosophy of Mind",
      "desc_confidence": "High",
      "description": "Vallor, a philosopher of technology at Edinburgh, argues AI is a mirror reflecting humanity's past, not a window to the future. Because models are trained on historical human data, they reproduce and amplify our biases and limits. The central metaphor warns against mistaking the reflection for genuine new intelligence or wisdom. Vallor critiques the framing of AI as superior to human moral reasoning. She defends human virtues, agency, and the capacity to imagine better futures. The book draws on virtue ethics and the philosophy of technology. It resists both doom and techno-utopianism. Vallor argues we risk diminishing ourselves by deferring to machine outputs. The work is rigorous yet accessible. For governance readers it is a philosophical case for keeping human judgment central.",
      "source": "Appelo core"
    },
    "id": "book-0037",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "As If Human: Ethics and Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Nigel Shadbolt, Roger Hampson",
      "category": "Society & Ethics",
      "desc_confidence": "Medium",
      "description": "Shadbolt, a leading AI scientist, with Hampson, examines the ethical questions raised by increasingly capable AI. The title flags the temptation to treat machines as if they were human. The book addresses responsibility, rights, and the moral status of artificial systems. It draws on Shadbolt's deep technical knowledge and policy experience. The authors are skeptical of attributing genuine agency or consciousness to current AI. They explore how we should treat systems that mimic human behavior. The work spans practical ethics and philosophical questions. It addresses accountability for AI decisions. The tone is reasoned and grounded. For governance readers it clarifies where moral responsibility properly sits.",
      "source": "Appelo core"
    },
    "id": "book-0038",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Brave New Words: How AI Will Revolutionize Education (and Why That's a Good Thing)",
    "conflict_flag": false,
    "editorial": {
      "author": "Salman Khan",
      "category": "Education",
      "desc_confidence": "High",
      "description": "Khan, founder of Khan Academy, makes an optimistic case for AI tutors transforming education. He describes Khanmigo, an AI tutor built on GPT-4, as a tireless personalized guide for every student. The book argues AI can deliver one-on-one tutoring at scale, addressing long-standing inequities. Khan addresses cheating fears by reframing AI as a Socratic coach rather than an answer machine. He covers teachers' changing roles, assessment, and parental concerns. The tone is hopeful but attentive to risks and guardrails. He draws on Khan Academy's early deployment experience. The book targets educators, parents, and policymakers. It treats AI as a force multiplier for human teachers. For governance readers it is a builder's view of responsible educational AI.",
      "source": "Appelo core"
    },
    "id": "book-0039",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "How AI Ate the World: A Brief History of Artificial Intelligence - And Its Long Future",
    "conflict_flag": false,
    "editorial": {
      "author": "Chris Stokel-Walker",
      "category": "History",
      "desc_confidence": "Medium",
      "description": "Stokel-Walker, a technology journalist, narrates the history and rapid rise of AI for a general audience. The book traces the field from early research through the generative-AI boom. It explains how AI quietly came to underpin search, social media, and daily tools. The author profiles key figures, breakthroughs, and turning points. He addresses both the benefits and the disruptions of pervasive AI. The narrative is journalistic and accessible rather than technical. It speculates about the longer-term trajectory of the technology. The book covers controversies around data, jobs, and power. The tone is engaging and balanced. For general readers it is a readable history and orientation.",
      "source": "Appelo core"
    },
    "id": "book-0040",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Teaching with AI: A Practical Guide to a New Era of Human Learning",
    "conflict_flag": false,
    "editorial": {
      "author": "José Antonio Bowen, C. Edward Watson",
      "category": "Education",
      "desc_confidence": "Medium",
      "description": "A practical handbook for educators on integrating generative AI into teaching. The authors offer strategies for assignment design, assessment, and academic integrity in the AI era. The book treats AI as an unavoidable presence that teaching must adapt to rather than ban. It includes concrete techniques, prompts, and policy suggestions for classrooms. The authors address equity, critical thinking, and the risk of over-reliance. They argue for redesigning learning to leverage AI productively. The audience is faculty and instructional designers. The tone is constructive and applied. It balances enthusiasm with caution about misuse. For institutions it is an implementation guide for AI-aware pedagogy.",
      "source": "Appelo core"
    },
    "id": "book-0041",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Your AI Survival Guide: Scraped Knees, Bruised Elbows, and Lessons Learned from Real-World AI Deployments",
    "conflict_flag": false,
    "editorial": {
      "author": "Sol Rashidi",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "Rashidi, a veteran chief data and AI officer, shares hard-won lessons from leading enterprise AI projects. The book is candid about failures, organizational politics, and the gap between hype and delivery. It frames AI adoption as messy, people-driven work rather than a clean technical rollout. Rashidi offers practical frameworks for prioritizing use cases and managing stakeholders. She covers data readiness, change management, and executive expectations. The tone is conversational and experience-based. It targets leaders responsible for delivering AI value. The book emphasizes pragmatism over technical sophistication. It treats deployment, not modeling, as the hard part. For governance readers it surfaces the operational realities behind AI programs.",
      "source": "Appelo core"
    },
    "id": "book-0042",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The Ordinal Society",
    "conflict_flag": false,
    "editorial": {
      "author": "Marion Fourcade, Kieran Healy",
      "category": "Society & Ethics",
      "desc_confidence": "High",
      "description": "Two sociologists analyze how digital scoring, ranking, and classification reshape social life. Their concept of the ordinal society describes a world where people are continuously measured, sorted, and ranked by data systems. The book examines how algorithms assign worth and opportunity, creating new hierarchies. It connects credit scores, ratings, and recommendation systems to long-standing questions of class and status. The authors argue these systems produce the very differences they claim merely to measure. They draw on economic sociology and the study of valuation. The work is critical of how data infrastructures naturalize inequality. It is scholarly but readable. AI and machine learning feature as engines of ordinal sorting. For governance readers it offers a sociological frame for algorithmic stratification.",
      "source": "Appelo core"
    },
    "id": "book-0043",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Generative AI for the Rest of Us: Your Future, Decoded",
    "conflict_flag": false,
    "editorial": {
      "author": "Aymen El Amri",
      "category": "Popular Science",
      "desc_confidence": "Low",
      "description": "An accessible introduction to generative AI for non-specialists. Likely content covers how the technology works, its applications, and practical implications. It aims to demystify the field for a general audience. Independent detail on the book is limited; this summary is inferred from the title and subtitle. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0044",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The AI Glossary: Demystifying 101 Essential Artificial Intelligence Terms for Everyone",
    "conflict_flag": false,
    "editorial": {
      "author": "Richard R. Khan",
      "category": "Popular Science",
      "desc_confidence": "Low",
      "description": "A reference book defining common AI terms for general readers. The format is a glossary of essential concepts and jargon. Its purpose is to help newcomers follow AI conversations. Independent detail on coverage and quality is sparse; this description is inferred from the title. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0045",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI Entrepreneur's Handbook: Build a Profitable Business and Make Money by Unleashing the Power of ChatGPT and Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Kartikeya Malhotra",
      "category": "Business & Strategy",
      "desc_confidence": "Low",
      "description": "A self-published guide to starting AI-powered businesses and monetizing tools like ChatGPT. It belongs to the entrepreneurship-and-monetization genre. Likely content covers business ideas, tools, and go-to-market basics. Independent verification of substance is not available; this summary is inferred from the title. Treat claims in this genre with caution and specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0046",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Co-Intelligence: Living and Working with AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Ethan Mollick",
      "category": "Business & Strategy",
      "desc_confidence": "High",
      "description": "Mollick, a Wharton professor, argues we should treat AI as a co-worker, co-teacher, and collaborator. He proposes practical principles, including always inviting AI to the table and treating it like a person but knowing what it is. The book is grounded in his hands-on experimentation and research on AI in work and education. Mollick describes large language models as jagged, brilliant in some tasks and failing unpredictably in others. He emphasizes learning AI's contours through direct use rather than theory. The tone is pragmatic, curious, and broadly optimistic. He addresses productivity, creativity, and the disruption of expertise. The book offers concrete tactics for individuals and organizations. It avoids both doom and uncritical hype. For practitioners it is among the most actionable popular guides to working with AI.",
      "source": "Appelo core"
    },
    "id": "book-0047",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Generative Artificial Intelligence for Beginners",
    "conflict_flag": false,
    "editorial": {
      "author": "Gwen Taylor",
      "category": "Popular Science",
      "desc_confidence": "Low",
      "description": "A beginner-level introduction to generative AI emphasizing practical use and ethical considerations. It belongs to the introductory-explainer category. Likely content covers core concepts and real-world applications. Independent detail is limited; this summary is inferred from the title and subtitle. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0048",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI Literacy Fundamentals: Helping You Join the AI Conversation",
    "conflict_flag": false,
    "editorial": {
      "author": "Ben Jones",
      "category": "Popular Science",
      "desc_confidence": "Low",
      "description": "An introductory book aimed at building basic AI literacy for general readers and professionals. The goal is to equip people to participate in discussions about AI. Likely content covers foundational concepts and terminology. Independent detail is sparse; this description is inferred from the title. Treat specifics as unverified. Note: relevant to AI-literacy obligations under regulation such as EU AI Act Article 4, though the book is a general primer rather than a legal text.",
      "source": "Appelo core"
    },
    "id": "book-0049",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Deep Utopia: Life and Meaning in a Solved World",
    "conflict_flag": false,
    "editorial": {
      "author": "Nick Bostrom",
      "category": "Futures",
      "desc_confidence": "High",
      "description": "Bostrom turns from existential risk to the opposite problem: what gives life meaning if AI solves all our problems. The book imagines a post-scarcity, post-work world where technology can satisfy nearly every need. It asks whether humans can find purpose when struggle and necessity disappear. Bostrom distinguishes a plastic utopia where even our values can be engineered. The work blends rigorous philosophy with playful, unconventional structure. He examines boredom, purpose, and the risk of a solved but hollow existence. It is a sequel in spirit to his earlier Superintelligence. The argument is exploratory rather than prescriptive. It treats utopia as a genuine intellectual challenge, not a given. For thoughtful readers it reframes the AI endgame around meaning rather than survival.",
      "source": "Appelo core"
    },
    "id": "book-0050",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Generative AI in Practice: 100+ Amazing Ways Generative Artificial Intelligence is Changing Business and Society",
    "conflict_flag": false,
    "editorial": {
      "author": "Bernard Marr",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "Marr, a prolific business-technology author, catalogs concrete applications of generative AI across industries. The book is organized around numerous real-world examples and use cases. It surveys impacts on marketing, operations, healthcare, education, and creative work. Marr aims to make the technology tangible for business readers through breadth of illustration. He addresses opportunities alongside risks and ethical concerns. The tone is accessible and example-driven rather than technical. It targets managers seeking to understand where AI applies. The book functions partly as an idea catalog. It emphasizes practical adoption. For leaders it is a survey of the application landscape.",
      "source": "Appelo core"
    },
    "id": "book-0051",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Mastering the Data Paradox: Key to Winning in the AI Age",
    "conflict_flag": false,
    "editorial": {
      "author": "Nitin Seth",
      "category": "Business & Strategy",
      "desc_confidence": "Low",
      "description": "A business book on the strategic role of data in the AI era, framed around a data paradox. Likely content addresses why organizations struggle to extract value from abundant data. It probably covers data strategy, culture, and capability building. Independent detail is limited; this summary is inferred from the title and subtitle. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0052",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Write with AI: Conquer Writer's Block, Unleash Your Creativity, and Write Your Book Using Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Rob Kosberg",
      "category": "Creativity & Art",
      "desc_confidence": "Low",
      "description": "A practical guide to using AI tools to assist book and content writing. It targets authors and creators wanting to overcome writer's block and speed up drafting. Likely content covers prompting, structuring, and editing workflows with AI. Independent detail is sparse; this description is inferred from the title. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0053",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI Needs You: How We Can Change AI's Future and Save Our Own",
    "conflict_flag": false,
    "editorial": {
      "author": "Verity Harding",
      "category": "Governance & Policy",
      "desc_confidence": "High",
      "description": "Harding, a former policy leader at DeepMind and Google, argues that AI's future should be shaped democratically, not left to technologists. She draws lessons from past governance of transformative technologies: space, IVF, and the internet. Each historical case shows that public values, law, and politics successfully steered powerful technology. The book pushes back against fatalism that AI's trajectory is fixed or beyond control. Harding argues ordinary citizens and institutions have agency over outcomes. She combines policy experience with historical analysis. The tone is hopeful and civic-minded. It calls for inclusive, value-driven governance. The work is accessible to non-experts. For governance readers it is a constructive argument for democratic oversight grounded in precedent.",
      "source": "Appelo core"
    },
    "id": "book-0054",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Fusion Strategy: How Real-Time Data and AI Will Power the Industrial Future",
    "conflict_flag": false,
    "editorial": {
      "author": "Vijay Govindarajan, Venkat Venkatraman",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "Two strategy scholars argue that industrial firms must fuse physical products with real-time data and AI. The book describes how sensors and connected products create continuous data streams that enable new value. The authors call the result digital fusion, blending atoms and bits into smart offerings. They use cases from manufacturing and heavy industry to illustrate the shift. The argument is that data-enabled products and AI-driven services will redefine competitive advantage. They address strategy, business models, and organizational change. The framing targets industrial and B2B leaders. It treats AI as embedded in operations rather than standalone. The tone is strategic and forward-looking. For leaders it maps a transformation path for asset-heavy industries.",
      "source": "Appelo core"
    },
    "id": "book-0055",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The AI Accelerator: How to 10X Your Productivity, Clone Your Smartest Employees, and Monetize Your IP in the New AI-Economy",
    "conflict_flag": false,
    "editorial": {
      "author": "Mike Koenigs",
      "category": "Business & Strategy",
      "desc_confidence": "Low",
      "description": "A marketing-oriented business book promising productivity gains and new revenue using AI. The pitch centers on cloning expertise and monetizing intellectual property with AI tools. It belongs to the entrepreneurial-hype genre. Independent verification of substance is not available; this summary is inferred from the title and subtitle. Treat bold claims with caution and specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0056",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Guardrails: Guiding Human Decisions in the Age of AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Urs Gasser, Viktor Mayer-Schönberger",
      "category": "Governance & Policy",
      "desc_confidence": "High",
      "description": "Two scholars of law and information argue for designing guardrails that guide human decision-making rather than dictate it. They contrast guardrails with rigid rules and with opaque algorithmic control. The book examines how AI systems increasingly nudge or constrain human choices. The authors defend the value of human agency, error, and the freedom to decide. They propose principles for guardrails that are transparent, contestable, and respectful of autonomy. The work draws on law, governance, and decision theory. It critiques both heavy-handed regulation and unchecked algorithmic steering. The argument is that good systems support judgment instead of replacing it. The tone is scholarly and policy-relevant. For governance readers it is a framework for human-centered oversight of decision systems.",
      "source": "Appelo core"
    },
    "id": "book-0057",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The Heart and the Chip: Our Bright Future with Robots",
    "conflict_flag": false,
    "editorial": {
      "author": "Daniela Rus, Gregory Mone",
      "category": "Robotics",
      "desc_confidence": "Medium",
      "description": "Rus, MIT's robotics leader, presents an optimistic vision of robots augmenting human capability. The book surveys advances in soft robotics, swarms, and machine learning for physical systems. Rus argues robots should extend human reach rather than replace people. She addresses safety, trust, and the design of collaborative machines. The work blends technical insight with accessible storytelling. It covers applications from medicine to disaster response. Rus is candid about current limitations of robotics and AI. The tone is hopeful and grounded in research. It treats human-robot partnership as the goal. For general readers it is an insider's optimistic survey of robotics.",
      "source": "Appelo core"
    },
    "id": "book-0058",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Future of Work: From Cubicle to Tribe",
    "conflict_flag": false,
    "editorial": {
      "author": "Paul Lalovich, et al.",
      "category": "Economics & Labour",
      "desc_confidence": "Low",
      "description": "A book on how work and organizations are changing, including the influence of AI and automation. The cubicle-to-tribe framing suggests a shift toward networked, team-based structures. Likely content covers organizational design, talent, and digital transformation. Independent detail is limited; this summary is inferred from the title. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0059",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI: Unexplainable, Unpredictable, Uncontrollable",
    "conflict_flag": false,
    "editorial": {
      "author": "Roman V. Yampolskiy",
      "category": "Safety & Alignment",
      "desc_confidence": "High",
      "description": "Yampolskiy, an AI safety researcher, argues that advanced AI may be fundamentally impossible to control, explain, or predict. The book makes a rigorous case that key safety properties are unachievable in principle, not just in practice. He surveys explainability, predictability, and controllability and finds each deeply limited. Yampolskiy is among the more pessimistic voices on AI alignment. He argues that as capability grows, our ability to verify safety shrinks. The work draws on computer science, logic, and the limits of computation. It is more technical and uncompromising than most popular safety books. He treats uncontrollability as a serious existential concern. The tone is sober and warning. For governance readers it is a strong statement of the irreducible-risk position.",
      "source": "Appelo core"
    },
    "id": "book-0060",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Generative Artificial Intelligence: What Everyone Needs to Know",
    "conflict_flag": false,
    "editorial": {
      "author": "Jerry Kaplan",
      "category": "Popular Science",
      "desc_confidence": "High",
      "description": "Kaplan, a long-time AI entrepreneur and academic, provides a clear primer on generative AI in question-and-answer format. The book explains how these systems work, what they can and cannot do, and their broad implications. It covers economics, jobs, creativity, ethics, and regulation in accessible terms. Kaplan is measured, separating realistic concerns from speculation. The Oxford What Everyone Needs to Know format keeps it concise and balanced. He addresses intellectual property, misinformation, and bias. The audience is the general reader seeking grounding without hype. He draws on decades in the field. The tone is calm and explanatory. For non-specialists it is a reliable orientation to the technology.",
      "source": "Appelo core"
    },
    "id": "book-0061",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Applied Artificial Intelligence: A Handbook For Business Leaders (Second Edition)",
    "conflict_flag": false,
    "editorial": {
      "author": "Mariya Yao, Adelyn Zhou, Marlene Jia",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "A practical handbook for executives on planning and executing AI initiatives. It covers strategy, use-case selection, data readiness, talent, and vendor decisions. The book aims to translate AI concepts into business action without heavy technical detail. It includes frameworks for prioritizing projects and measuring ROI. The authors address organizational change and common pitfalls. The second edition updates for newer developments. The audience is non-technical business leaders. The tone is pragmatic and structured. It treats AI as a portfolio of business investments. For leaders it is an operational planning reference.",
      "source": "Appelo core"
    },
    "id": "book-0062",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "How AI Thinks: How we built it, how it can help us, and how we can control it",
    "conflict_flag": false,
    "editorial": {
      "author": "Nigel Toon",
      "category": "Popular Science",
      "desc_confidence": "Medium",
      "description": "Toon, a semiconductor entrepreneur and co-founder of Graphcore, explains how modern AI works and how to govern it. The book covers the history, the hardware, and the mechanics of machine learning for a general audience. Toon offers an insider's view from someone building AI chips. He addresses both the benefits and the need for control and regulation. The work balances technical explanation with policy reflection. He is broadly optimistic but attentive to risks. The audience is curious general readers and decision-makers. The tone is clear and grounded in industry experience. It treats understanding the technology as a prerequisite for controlling it. For governance readers it links technical reality to oversight.",
      "source": "Appelo core"
    },
    "id": "book-0063",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Moral AI: And How We Get There",
    "conflict_flag": false,
    "editorial": {
      "author": "Jana Schaich Borg, Walter Sinnott-Armstrong, Vincent Conitzer",
      "category": "Society & Ethics",
      "desc_confidence": "High",
      "description": "Three scholars from neuroscience, philosophy, and computer science examine how to make AI behave morally. The book addresses whether and how machines can be designed to act ethically. It surveys bias, safety, privacy, and responsibility across real applications. The authors discuss technical approaches to encoding values and their limits. They argue moral AI requires interdisciplinary collaboration, not just engineering. The work is balanced, neither alarmist nor dismissive. It covers self-driving cars, medical AI, and other consequential domains. The tone is rigorous yet accessible. It treats ethics as an engineering and governance challenge. For governance readers it is a serious primer on operationalizing AI ethics.",
      "source": "Appelo core"
    },
    "id": "book-0064",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Literary Theory for Robots: How Computers Learned to Write",
    "conflict_flag": false,
    "editorial": {
      "author": "Dennis Yi Tenen",
      "category": "History",
      "desc_confidence": "High",
      "description": "Tenen, a literature scholar and former software engineer, traces the long history behind machine-generated text. He argues that AI writing is the culmination of centuries of collaborative, templated, and mechanical text production. The book connects medieval writing aids, indexes, and dictionaries to modern language models. Tenen reframes authorship as always partly collective and technological. He demystifies large language models by placing them in literary and intellectual history. The work challenges romantic notions of solitary genius. It is erudite, concise, and essayistic. He treats AI text generation as continuous with human craft, not a rupture. The tone is curious and scholarly. For readers it reframes generative writing through the history of literary technique.",
      "source": "Appelo core"
    },
    "id": "book-0065",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The AI Playbook: Mastering the Rare Art of Machine Learning Deployment",
    "conflict_flag": false,
    "editorial": {
      "author": "Eric Siegel",
      "category": "ML Engineering",
      "desc_confidence": "High",
      "description": "Siegel, an expert in predictive analytics, focuses on why machine learning projects fail to reach deployment. His core argument is that the bottleneck is organizational, not algorithmic. He introduces a structured process, bizML, to align business and data-science teams from the start. The book stresses defining the business deployment goal before modeling. Siegel covers common failure modes and how to avoid them. He emphasizes stakeholder collaboration and clear value framing. The audience is leaders and practitioners delivering ML projects. The tone is practical and process-oriented. It treats deployment as the central challenge of applied ML. For governance readers it foregrounds the operational discipline behind successful systems.",
      "source": "Appelo core"
    },
    "id": "book-0066",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Generative AI: The Insights You Need from Harvard Business Review",
    "conflict_flag": false,
    "editorial": {
      "author": "Harvard Business Review",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "A curated collection of HBR articles on generative AI for managers and executives. It gathers expert perspectives on strategy, productivity, and risk. The book addresses how generative AI changes work, decision-making, and competitive dynamics. It includes practical guidance on adoption and governance. The essays vary by author and focus. The framing is managerial and strategic. It targets leaders seeking concise, authoritative takes. The tone is professional and applied. It treats generative AI as a business priority. For leaders it is a compact briefing from a trusted source.",
      "source": "Appelo core"
    },
    "id": "book-0067",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI for Good: Applications in Sustainability, Humanitarian Action, and Health",
    "conflict_flag": false,
    "editorial": {
      "author": "Juan M. Lavista Ferres, William B. Weeks",
      "category": "Society & Ethics",
      "desc_confidence": "Medium",
      "description": "From Microsoft's AI for Good lab, this book showcases AI applications addressing social and environmental challenges. It presents projects in sustainability, disaster response, and global health. The authors document how machine learning supports conservation, humanitarian work, and medicine. The book emphasizes responsible, impact-oriented deployment. It includes case studies with real outcomes. The tone is constructive and example-driven. It addresses partnerships between technologists and domain experts. The audience is practitioners and funders of social-impact AI. It treats AI as a tool for public good when applied carefully. For governance readers it illustrates beneficial deployment with attention to ethics.",
      "source": "Appelo core"
    },
    "id": "book-0068",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI for Defence and Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Dr. Patrick T. Biltgen",
      "category": "Defence & Security",
      "desc_confidence": "Low",
      "description": "A specialist book on applying AI in defense and intelligence contexts. Likely content covers analytics, surveillance, decision support, and operational use cases. The audience is defense and national-security professionals. Independent detail is limited; this summary is inferred from the title. Treat specifics as unverified. The topic carries significant governance and ethics considerations around autonomy and oversight.",
      "source": "Appelo core"
    },
    "id": "book-0069",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "The Algorithm: How AI Decides Who Gets Hired, Monitored, Promoted, and Fired and Why We Need to Fight Back Now",
    "conflict_flag": false,
    "editorial": {
      "author": "Hilke Schellmann",
      "category": "Society & Ethics",
      "desc_confidence": "High",
      "description": "Schellmann, an investigative journalist, exposes how AI tools increasingly govern the workplace. The book documents hiring algorithms, video interview analysis, productivity monitoring, and automated firing. She tests many systems herself and finds them often biased, pseudoscientific, or arbitrary. The reporting shows job seekers and workers harmed by opaque, unaccountable tools. Schellmann argues regulation and transparency are urgently needed. The book covers vendors' claims versus actual performance. It centers the human cost of automated employment decisions. The tone is investigative and alarmed but evidence-based. It calls for workers to resist and lawmakers to act. For governance readers it is a detailed account of employment-AI harms and accountability gaps.",
      "source": "Appelo core"
    },
    "id": "book-0070",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Critical Theory of AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Simon Lindgren",
      "category": "Critique & Skepticism",
      "desc_confidence": "Medium",
      "description": "Lindgren, a sociologist, applies critical theory to artificial intelligence and its social effects. The book examines power, ideology, and inequality embedded in AI systems. It draws on the Frankfurt School and contemporary critical scholarship. Lindgren critiques techno-solutionism and the politics of automation. The work treats AI as a social and political phenomenon, not merely technical. It addresses surveillance, datafication, and algorithmic control. The audience is students and scholars of media, sociology, and technology. The tone is academic and analytical. It situates AI within structures of capital and power. For governance readers it provides a critical-theoretical vocabulary for AI's social stakes.",
      "source": "Appelo core"
    },
    "id": "book-0071",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Trust: Responsible AI, Innovation, Privacy and Data Leadership",
    "conflict_flag": false,
    "editorial": {
      "author": "Dominique Shelton Leipzig",
      "category": "Governance & Policy",
      "desc_confidence": "Medium",
      "description": "Shelton Leipzig, a data-privacy lawyer, offers leaders a framework for trustworthy AI and data governance. The book argues that trust is a strategic asset built through responsible practices. It covers privacy, compliance, transparency, and ethical innovation. The author provides practical guidance for boards and executives. She draws on legal expertise and real cases. The work emphasizes proactive governance over reactive damage control. It addresses regulation and the rising expectations of regulators and customers. The audience is senior leaders and counsel. The tone is practical and authoritative. For governance readers it links responsible AI to legal and reputational risk management.",
      "source": "Appelo core"
    },
    "id": "book-0072",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "From Deep Learning to Rational Machines: What the History of Philosophy Can Teach Us about the Future of Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Cameron J. Buckner",
      "category": "Philosophy of Mind",
      "desc_confidence": "High",
      "description": "Buckner, a philosopher, argues that empiricist philosophy illuminates how deep learning achieves intelligence. He connects classic empiricist thinkers to the capabilities of neural networks. The book proposes that abstraction and learning from experience explain deep learning's power. Buckner addresses debates about whether these systems truly reason. He offers a measured account between hype and dismissal. The work is technically informed and philosophically rigorous. It examines perception, abstraction, and the building blocks of rational thought. The audience is philosophers and serious students of AI. It treats the history of philosophy as a resource for understanding machines. For thoughtful readers it bridges cognitive science, philosophy, and AI.",
      "source": "Appelo core"
    },
    "id": "book-0073",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Artificial Intelligence & Generative AI for Beginners: The Complete Guide",
    "conflict_flag": false,
    "editorial": {
      "author": "David M. Patel",
      "category": "Popular Science",
      "desc_confidence": "Low",
      "description": "A beginner's guide covering AI and generative AI fundamentals. Likely content includes core concepts, tools, and applications for newcomers. It belongs to the introductory-explainer category. Independent detail is limited; this summary is inferred from the title. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0074",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "The Worlds I See: Curiosity, Exploration, and Discovery at the Dawn of AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Fei-Fei Li",
      "category": "Journalism & Biography",
      "desc_confidence": "High",
      "description": "Li, a pioneering computer-vision scientist, weaves memoir with the history of modern AI. She recounts her journey as an immigrant from China and her rise to scientific leadership at Stanford. The book centers on ImageNet, the dataset and benchmark she created that helped ignite the deep-learning revolution. Li reflects on the human curiosity driving science and the responsibility that comes with powerful technology. She champions human-centered AI that serves people and dignity. The narrative blends personal struggle with research breakthroughs. She addresses diversity, ethics, and the field's blind spots. The tone is reflective and humane. It treats AI as a human endeavor shaped by values. For readers it is both a scientific history and a moral perspective from an insider.",
      "source": "Appelo core"
    },
    "id": "book-0075",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Unmasking AI: My Mission to Protect What Is Human in a World of Machines",
    "conflict_flag": false,
    "editorial": {
      "author": "Joy Buolamwini",
      "category": "Society & Ethics",
      "desc_confidence": "High",
      "description": "Buolamwini, founder of the Algorithmic Justice League, recounts her research exposing bias in facial-recognition systems. She describes discovering that commercial systems failed to detect darker-skinned and female faces accurately. The book documents her Gender Shades research and its impact on industry and policy. Buolamwini coins the term coded gaze for embedded discrimination in algorithms. She blends memoir, research, and activism. The work argues for accountability, audits, and the rights of the excoded, those harmed by AI. She covers her confrontations with major tech companies. The tone is personal and mission-driven. It centers justice and human dignity. For governance readers it is a foundational account of algorithmic bias and advocacy.",
      "source": "Appelo core"
    },
    "id": "book-0076",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "A Brief History of Intelligence: Evolution, AI, and the Five Breakthroughs That Made Our Brains",
    "conflict_flag": false,
    "editorial": {
      "author": "Max Bennett",
      "category": "Neuroscience",
      "desc_confidence": "High",
      "description": "Bennett, an AI entrepreneur, traces the evolution of intelligence through five major breakthroughs in brain development. He connects the history of biological intelligence to insights for building artificial intelligence. The book spans from early nervous systems to human reasoning and language. Each breakthrough, such as steering, reinforcing, and simulating, maps to capabilities relevant to AI. Bennett argues understanding the brain's evolution illuminates what current AI lacks. The work synthesizes neuroscience, evolutionary biology, and machine learning. It is accessible and narrative-driven. He treats human cognition as a layered product of evolution. The tone is explanatory and ambitious in scope. For readers it links the biology of mind to the design of machines.",
      "source": "Appelo core"
    },
    "id": "book-0077",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "How AI Works: From Sorcery to Science",
    "conflict_flag": false,
    "editorial": {
      "author": "Ronald T. Kneusel",
      "category": "Popular Science",
      "desc_confidence": "Medium",
      "description": "Kneusel demystifies how AI and machine learning actually function for a general audience. The book explains neural networks, training, and modern models without heavy mathematics. It aims to replace mystery with clear understanding. Kneusel covers what AI can and cannot do and why. The work addresses common misconceptions and hype. It is accessible and concept-focused. The audience is curious non-specialists. The tone is clear and grounded. It treats AI as understandable science rather than magic. For readers it is a solid, jargon-light explainer.",
      "source": "Appelo core"
    },
    "id": "book-0078",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Prompt Design Patterns: Mastering the Art and Science of Prompt Engineering",
    "conflict_flag": false,
    "editorial": {
      "author": "Yu Zhou",
      "category": "LLM Engineering",
      "desc_confidence": "Low",
      "description": "A guide to prompt engineering organized around reusable design patterns. Likely content includes structured techniques for eliciting reliable outputs from language models. The audience is users and builders of AI applications. Independent detail is limited; this summary is inferred from the title. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0079",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "AI Made Simple: A Beginner's Guide to Generative Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Rajeev Kapur",
      "category": "Popular Science",
      "desc_confidence": "Low",
      "description": "An accessible introduction to generative AI for beginners and business readers. Likely content covers fundamentals, applications, and practical implications. It belongs to the introductory category. Independent detail is sparse; this summary is inferred from the title. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0080",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Your Face Belongs to Us: A Secretive Startup's Quest to End Privacy as We Know It",
    "conflict_flag": false,
    "editorial": {
      "author": "Kashmir Hill",
      "category": "Journalism & Biography",
      "desc_confidence": "High",
      "description": "Hill, a New York Times reporter, investigates Clearview AI, a facial-recognition startup that scraped billions of online photos. The book documents how the company built a tool to identify almost anyone from a single image. It traces Clearview's quiet spread to police, businesses, and wealthy individuals. Hill examines the legal, ethical, and societal stakes of ubiquitous face recognition. The reporting reveals the people and ideologies behind the company. The work raises alarms about the end of public anonymity. It connects the technology to surveillance and authoritarian risks. The tone is investigative and gripping. It centers privacy as a vanishing right. For governance readers it is a definitive account of facial-recognition's threat to privacy.",
      "source": "Appelo core"
    },
    "id": "book-0081",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "The AI Edge: Sales Strategies for Unleashing the Power of AI to Save Time, Sell More, and Crush the Competition",
    "conflict_flag": false,
    "editorial": {
      "author": "Jeb Blount, Anthony Iannarino",
      "category": "Business & Strategy",
      "desc_confidence": "Low",
      "description": "A sales-focused business book on using AI to improve prospecting, productivity, and deal-making. Likely content covers practical AI tactics for sales professionals. The audience is salespeople and sales leaders. Independent detail is limited; this summary is inferred from the title. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0082",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "AI and the Future of Education: Teaching in the Age of Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Priten Shah",
      "category": "Education",
      "desc_confidence": "Medium",
      "description": "Shah offers educators a practical guide to integrating AI into teaching and learning. The book addresses classroom applications, lesson design, and assessment in the AI era. It covers academic integrity, equity, and ethical concerns. Shah provides strategies for using AI to personalize and enhance instruction. The tone is constructive and applied. The audience is teachers and administrators. It treats AI as a tool to be adopted thoughtfully. The work balances opportunities with cautions. It includes actionable guidance. For educators it is an implementation-oriented resource.",
      "source": "Appelo core"
    },
    "id": "book-0083",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "The Coming Wave: Technology, Power, and the Twenty-first Century's Greatest Dilemma",
    "conflict_flag": false,
    "editorial": {
      "author": "Mustafa Suleyman, Michael Bhaskar",
      "category": "Futures",
      "desc_confidence": "High",
      "description": "Suleyman, co-founder of DeepMind and now leading Microsoft AI, warns of a coming wave of AI and synthetic biology. The central dilemma is containment: how to capture benefits while preventing catastrophic misuse and proliferation. He argues these technologies are general-purpose, fast-spreading, and hard to control. The book describes risks from empowered bad actors and from state and corporate power. Suleyman proposes a containment agenda of technical, regulatory, and cultural measures. He is candid as an insider about both promise and peril. The work treats AI and biotech as intertwined existential challenges. The tone is urgent but constructive. It calls for a narrow path between stagnation and catastrophe. For governance readers it is a leading practitioner's case for containment and oversight.",
      "source": "Appelo core"
    },
    "id": "book-0084",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype",
    "conflict_flag": false,
    "editorial": {
      "author": "I. Almeida",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "Almeida provides executives with a grounded introduction to large language models and their business uses. The book aims to move past both fear and hype toward responsible strategy. It explains how LLMs work and where they add value. The author addresses risks, limitations, and governance. It includes practical guidance for adoption. The tone is balanced and strategic. The audience is business leaders. It emphasizes responsible AI practices. The work covers competitive implications. For leaders it is a measured strategic primer.",
      "source": "Appelo core"
    },
    "id": "book-0085",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Practical Uncertainty: Useful Ideas in Decision-Making, Risk, Randomness & AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Hossein Pishro-Nik",
      "category": "Math & Stats",
      "desc_confidence": "Low",
      "description": "A book connecting probability, decision-making, risk, and AI for practical reasoning. Likely content covers how to think clearly about uncertainty and randomness. The audience is general readers and decision-makers. Independent detail is limited; this summary is inferred from the title and subtitle. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0086",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Machine Learning: Advanced Topics",
    "conflict_flag": false,
    "editorial": {
      "author": "Kevin P. Murphy",
      "category": "Textbook ML",
      "desc_confidence": "High",
      "description": "Murphy's advanced volume is a comprehensive graduate-level reference on modern machine learning. It follows his earlier probabilistic machine learning textbooks and covers cutting-edge methods. Topics include deep generative models, variational inference, and advanced probabilistic techniques. The book is mathematically rigorous and aimed at researchers and graduate students. It treats machine learning through a unified probabilistic lens. The work is dense, thorough, and reference-oriented. It assumes substantial mathematical background. Murphy is a respected authority whose texts are widely used. The tone is academic and precise. For technical readers it is a definitive advanced reference.",
      "source": "Appelo core"
    },
    "id": "book-0087",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Artificial Intelligence Fundamentals for Business Leaders: Up to Date With Generative AI",
    "conflict_flag": false,
    "editorial": {
      "author": "I. Almeida",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "A companion primer by Almeida covering AI fundamentals for non-technical executives. The book explains core concepts, capabilities, and business implications. It is updated to include generative AI. The author emphasizes responsible and strategic adoption. It addresses risks and governance alongside opportunities. The tone is accessible and practical. The audience is business leaders. It aims to build foundational literacy. The work avoids heavy technical detail. For leaders it is an entry-level strategic foundation.",
      "source": "Appelo core"
    },
    "id": "book-0088",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Neural Networks and Deep Learning: A Textbook (Second Edition)",
    "conflict_flag": false,
    "editorial": {
      "author": "Charu C. Aggarwal",
      "category": "Textbook DL",
      "desc_confidence": "Medium",
      "description": "A graduate textbook providing a thorough treatment of neural networks and deep learning. It covers fundamentals from the perceptron through modern architectures. The book balances theory, mathematics, and practical considerations. Topics include backpropagation, convolutional and recurrent networks, and attention. It is structured for coursework and self-study. The second edition updates for recent advances. The audience is students and practitioners with technical background. The treatment is rigorous and comprehensive. (Note: the source list attributes this to Michael Nelson, likely an error; the widely known textbook of this exact title is by Charu C. Aggarwal. Verify the intended edition.) For technical readers it is a standard deep-learning reference.",
      "source": "Appelo core"
    },
    "id": "book-0089",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Rewired: The McKinsey Guide to Outcompeting in the Age of Digital and AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Eric Lamarre, Kate Smaje, Rodney Zemmel",
      "category": "Business & Strategy",
      "desc_confidence": "High",
      "description": "Three McKinsey senior partners distill the firm's playbook for digital and AI transformation. The book argues that transformation is a capability to be built, not a project to be bought. It covers six core areas: strategy, talent, operating model, technology, data, and adoption. The authors stress that value comes from rewiring how an organization works end to end. They draw on McKinsey's transformation engagements and benchmarks. The work provides frameworks, roadmaps, and metrics for leaders. It emphasizes scaling beyond pilots to enterprise impact. The tone is prescriptive and structured. It treats AI as embedded in a broader digital operating model. For leaders it is a comprehensive transformation reference, and a natural target for adversarial review of its claims and assumptions.",
      "source": "Appelo core"
    },
    "id": "book-0090",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "The Chief AI Officer Blueprint: Harness The Power Of AI For Business And Beyond",
    "conflict_flag": false,
    "editorial": {
      "author": "Chris Daigle",
      "category": "Business & Strategy",
      "desc_confidence": "Low",
      "description": "A guide to the emerging chief AI officer role and how to lead enterprise AI. Likely content covers responsibilities, strategy, and building AI capability. The audience is executives and aspiring AI leaders. Independent detail is limited; this summary is inferred from the title. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0091",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2024
  },
  {
    "canonical": true,
    "canonical_title": "Smart Until It's Dumb: Why artificial intelligence keeps making epic mistakes (and why the AI bubble will burst)",
    "conflict_flag": false,
    "editorial": {
      "author": "Emmanuel Maggiori",
      "category": "Critique & Skepticism",
      "desc_confidence": "Medium",
      "description": "Maggiori, an AI engineer, offers a skeptical, insider critique of AI hype. The book argues that AI systems often fail in revealing ways despite impressive demos. He explains why brittleness and overpromising are endemic to the field. Maggiori predicts an AI bubble fueled by inflated expectations. He draws on hands-on experience to puncture marketing claims. The work is accessible and candid about industry incentives. It distinguishes genuine capability from theater. The tone is wry and debunking. It treats hype as a recurring pattern. For readers it is a grounded counterweight to AI exuberance.",
      "source": "Appelo core"
    },
    "id": "book-0092",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "The AI Revolution in Medicine: GPT-4 and Beyond",
    "conflict_flag": false,
    "editorial": {
      "author": "Peter Lee, Carey Goldberg, Isaac Kohane",
      "category": "Healthcare",
      "desc_confidence": "High",
      "description": "Written partly by Microsoft's research leadership with early GPT-4 access, this book explores AI's potential in healthcare. It documents GPT-4's striking abilities and unsettling errors in clinical reasoning. The authors show transcripts of the model diagnosing, explaining, and sometimes confidently failing. They argue medicine could be transformed by AI assistance for clinicians and patients. The book is candid about hallucination and the need for verification. It addresses ethics, safety, and the doctor-patient relationship. The authors include a physician-scientist and a journalist for balance. The tone is excited but cautionary. It treats AI as a powerful, imperfect medical tool requiring oversight. For governance readers it is an early, grounded look at high-stakes deployment.",
      "source": "Appelo core"
    },
    "id": "book-0093",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "AI for Educators: Learning Strategies, Teacher Efficiencies, and a Vision for an Artificial Intelligence Future",
    "conflict_flag": false,
    "editorial": {
      "author": "Matt Miller",
      "category": "Education",
      "desc_confidence": "Medium",
      "description": "Miller, an education author, provides teachers with practical strategies for using AI in the classroom. The book offers ideas for saving time, enhancing lessons, and engaging students with AI tools. It addresses how to adapt teaching as AI becomes common. Miller covers prompts, activities, and workflow efficiencies. He balances enthusiasm with attention to integrity and ethics. The tone is upbeat and hands-on. The audience is K-12 and higher-ed teachers. It treats AI as a partner for educators. The work is example-rich. For teachers it is an accessible, actionable guide.",
      "source": "Appelo core"
    },
    "id": "book-0094",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Impromptu: Amplifying Our Humanity Through AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Reid Hoffman",
      "category": "Futures",
      "desc_confidence": "High",
      "description": "Hoffman, LinkedIn co-founder and an OpenAI investor, co-wrote this book with GPT-4 itself. It explores how AI could amplify human capabilities across education, work, creativity, and more. The book includes Hoffman's dialogues with the model, showing its strengths and quirks. He takes an optimistic, techno-humanist stance on AI's potential. The work argues for embracing AI to expand human flourishing. It covers many domains through conversational vignettes. Hoffman acknowledges risks but emphasizes upside. The tone is enthusiastic and exploratory. It treats AI as a collaborator and amplifier. For readers it is an accessible, optimistic case study in human-AI partnership.",
      "source": "Appelo core"
    },
    "id": "book-0095",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "What Is ChatGPT Doing ... and Why Does It Work?",
    "conflict_flag": false,
    "editorial": {
      "author": "Stephen Wolfram",
      "category": "Popular Science",
      "desc_confidence": "High",
      "description": "Wolfram explains the mechanics of large language models in clear, intuitive terms. The book describes how next-token prediction, trained on vast text, produces coherent output. He explores why such a simple objective yields surprisingly capable behavior. Wolfram connects this to his ideas about computation and the nature of language. He discusses embeddings, neural networks, and the role of scale. The work is rich with examples and Wolfram's characteristic visualizations. He reflects on what ChatGPT reveals about meaning and thought. The tone is technical yet accessible. It treats the system as a window into computation and language. For curious readers it is a lucid, first-principles explanation.",
      "source": "Appelo core"
    },
    "id": "book-0096",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "Four Battlegrounds: Power in the Age of Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Paul Scharre",
      "category": "Geopolitics",
      "desc_confidence": "High",
      "description": "Scharre, a defense expert, analyzes AI as a domain of geopolitical competition, especially between the US and China. He identifies four battlegrounds: data, compute, talent, and institutions. The book examines military applications, autonomous weapons, and surveillance. Scharre details China's AI ambitions and the stakes for democratic societies. He argues that AI advantage will shape the global balance of power. The work draws on policy and military expertise. It addresses ethics, safety, and the risks of an arms race. The tone is authoritative and sober. It treats AI as central to twenty-first-century security. For governance readers it is a leading analysis of AI geopolitics.",
      "source": "Appelo core"
    },
    "id": "book-0097",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
  },
  {
    "canonical": true,
    "canonical_title": "AI Bullseye Tactics for Non-technical Business Leaders",
    "conflict_flag": false,
    "editorial": {
      "author": "Thomas Gilbertson",
      "category": "Business & Strategy",
      "desc_confidence": "Low",
      "description": "A practical guide for non-technical leaders to apply AI to business value. Likely content covers identifying high-value problems and generating returns. The audience is executives without deep technical backgrounds. Independent detail is limited; this summary is inferred from the title and subtitle. Treat specifics as unverified.",
      "source": "Appelo core"
    },
    "id": "book-0098",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2023
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  {
    "canonical": true,
    "canonical_title": "All-in on AI: How Smart Companies Win Big with Artificial Intelligence",
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    "editorial": {
      "author": "Thomas H. Davenport, Nitin Mittal",
      "category": "Business & Strategy",
      "desc_confidence": "High",
      "description": "Davenport and Mittal profile companies that have made AI central to their strategy and identity. They distinguish AI-fueled firms that go all in from those that merely dabble. The book offers cases across industries, from finance to manufacturing. The authors identify common practices: leadership commitment, data foundations, and aggressive deployment. They argue half-measures yield little while full commitment compounds advantage. The work covers culture, talent, and ethics. It is practical and example-driven for executives. The tone is prescriptive and grounded in research. It treats AI as a strategic core, not a side project. For leaders it is a benchmark of what serious AI commitment looks like.",
      "source": "Appelo core"
    },
    "id": "book-0099",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2022
  },
  {
    "canonical": true,
    "canonical_title": "Power and Prediction: The Disruptive Economics of Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Ajay Agrawal, Joshua Gans, Avi Goldfarb",
      "category": "Business & Strategy",
      "desc_confidence": "High",
      "description": "The authors extend their economic analysis of AI to its disruptive, system-level effects. They argue AI's biggest impact comes not from point solutions but from redesigning entire systems around cheap prediction. The book distinguishes point, application, and system-level disruption. It explains why transformative value often requires rebuilding processes and decisions. The authors use the analogy of electricity reshaping factory design. They address why adoption lags and where power and value will shift. The work is grounded in economics and decision theory. The tone is analytical and strategic. It treats AI as prediction that unbundles and rebundles decisions. For leaders it explains why systemic change, not pilots, captures AI's value.",
      "source": "Appelo core"
    },
    "id": "book-0100",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2022
  },
  {
    "canonical": true,
    "canonical_title": "Prediction Machines: The Simple Economics of Artificial Intelligence (Updated and Expanded)",
    "conflict_flag": false,
    "editorial": {
      "author": "Ajay Agrawal, Joshua Gans, Avi Goldfarb",
      "category": "Business & Strategy",
      "desc_confidence": "High",
      "description": "This influential book reframes AI as a drop in the cost of prediction. The authors argue that when prediction becomes cheap, it is used more widely and changes the value of complements like judgment and data. The framework helps leaders decide where AI creates value in decision-making. It separates prediction from judgment, action, and outcomes. The book uses clear economic reasoning rather than technical detail. The updated edition refreshes examples and implications. It addresses strategy, jobs, and organizational design. The tone is lucid and pragmatic. It treats AI through the simple lens of economics. For leaders it is a foundational mental model for AI strategy.",
      "source": "Appelo core"
    },
    "id": "book-0101",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2022
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  {
    "canonical": true,
    "canonical_title": "Hacking Healthcare: How AI and the Intelligence Revolution Will Reboot an Ailing System",
    "conflict_flag": false,
    "editorial": {
      "author": "Tom Lawry",
      "category": "Healthcare",
      "desc_confidence": "Medium",
      "description": "Lawry, a healthcare-AI leader, argues AI can fix systemic dysfunction in healthcare. The book covers applications in diagnosis, operations, and population health. It addresses why healthcare lags in adoption and how to change that. Lawry emphasizes responsible, human-centered implementation. He draws on experience advising health systems. The work balances optimism with practical caution. The audience is healthcare leaders and policymakers. The tone is constructive and strategic. It treats AI as a remedy for inefficiency and inequity. For leaders it is a sector-specific transformation guide.",
      "source": "Appelo core"
    },
    "id": "book-0102",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2022
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  {
    "canonical": true,
    "canonical_title": "Ethical Machines: Your Concise Guide to Totally Unbiased, Transparent, and Respectful AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Reid Blackman",
      "category": "Governance & Policy",
      "desc_confidence": "High",
      "description": "Blackman, an ethicist and consultant, offers a practical guide to operationalizing AI ethics in business. He focuses on three pillars: bias, explainability, and privacy. The book argues ethics must be built into AI development, not bolted on. Blackman provides concrete steps for governance structures and risk assessment. He is skeptical of vague principles without implementation. The work targets executives and practitioners responsible for AI. It treats ethics as risk management and good business. The tone is no-nonsense and actionable. It addresses how to build organizational guardrails. For governance readers it is a hands-on manual for responsible AI programs.",
      "source": "Appelo core"
    },
    "id": "book-0103",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2022
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  {
    "canonical": true,
    "canonical_title": "Marketing Artificial Intelligence: AI, Marketing, and the Future of Business",
    "conflict_flag": false,
    "editorial": {
      "author": "Paul Roetzer, Mike Kaput",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "Roetzer and Kaput explain how AI will transform marketing and business. The book demystifies AI for marketers and maps practical applications. It covers content, personalization, analytics, and automation. The authors offer a framework for piloting and scaling AI in marketing. They address the skills and mindset shifts required. The work is accessible and example-driven. The audience is marketers and business leaders. The tone is practical and forward-looking. It treats AI as a near-term competitive necessity. For practitioners it is an applied marketing-AI guide.",
      "source": "Appelo core"
    },
    "id": "book-0104",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2022
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  {
    "canonical": true,
    "canonical_title": "Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications",
    "conflict_flag": false,
    "editorial": {
      "author": "Chip Huyen",
      "category": "ML Engineering",
      "desc_confidence": "High",
      "description": "Huyen provides an authoritative guide to building reliable, production-grade machine learning systems. The book covers the full lifecycle: data, feature engineering, training, deployment, and monitoring. It emphasizes MLOps, reliability, and the realities of systems that drift and fail. Huyen addresses data distribution shifts, infrastructure, and continual learning. The work is grounded in industry practice rather than academic modeling. It treats ML as an engineering discipline with operational demands. The audience is ML engineers and technical leads. The tone is practical and systems-oriented. It stresses iteration and maintainability. For practitioners it is a leading reference on operationalizing ML.",
      "source": "Appelo core"
    },
    "id": "book-0105",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
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  {
    "canonical": true,
    "canonical_title": "The Business Case for AI: A Leader's Guide to AI Strategies, Best Practices & Real-World Applications",
    "conflict_flag": false,
    "editorial": {
      "author": "Kavita Ganesan",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "Ganesan, a data-science practitioner, helps leaders build and justify AI initiatives. The book covers identifying opportunities, avoiding pitfalls, and measuring value. It demystifies AI for non-technical decision-makers. Ganesan offers frameworks for strategy, use-case selection, and execution. She draws on real applications across industries. The work emphasizes practical adoption over technical depth. The audience is business and technical leaders. The tone is pragmatic and structured. It treats AI as a business investment requiring clear cases. For leaders it is an applied strategy and execution guide.",
      "source": "Appelo core"
    },
    "id": "book-0106",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
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  {
    "canonical": true,
    "canonical_title": "The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI",
    "conflict_flag": false,
    "editorial": {
      "author": "Paul Leonardi, Tsedal Neeley",
      "category": "Business & Strategy",
      "desc_confidence": "High",
      "description": "Leonardi and Neeley argue that thriving with AI requires a digital mindset, not deep technical expertise. They contend most people need only enough fluency to collaborate with data and machines, framed as the 30 percent threshold. The book builds literacy across three areas: collaboration, computation, and change. It explains key concepts like machine learning and algorithms for non-technical professionals. The authors draw on research and corporate examples. They address how to interpret data, work alongside AI, and adapt to constant change. The work is practical and reassuring for anxious workers. The tone is accessible and empowering. It treats mindset, not coding, as the key capability. For leaders and employees it is a literacy-building guide.",
      "source": "Appelo core"
    },
    "id": "book-0107",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2022
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  {
    "canonical": true,
    "canonical_title": "Artificial Intelligence for Dummies",
    "conflict_flag": false,
    "editorial": {
      "author": "John Paul Mueller, Luca Massaron",
      "category": "Popular Science",
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    "canonical_title": "The Book of Why: The New Science of Cause and Effect",
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      "description": "Scharre, a former Army Ranger and defense expert, examines autonomous weapons. He explains the technology, the military incentives, and the ethical stakes of removing humans from lethal decisions. The book draws on his policy and battlefield experience. Scharre treats accountability, escalation risk, and international law. He argues for meaningful human control. The tone is authoritative and balanced. The audience is policymakers, military readers, and informed citizens. It is widely regarded as the leading accessible account of the subject. The analysis avoids both alarmism and complacency. It addresses real programs and near-term decisions. For AI and security governance it is essential reading.",
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    "original_title": null,
    "work_type": "book",
    "year": 2018
  },
  {
    "canonical": true,
    "canonical_title": "Artificial Intelligence: 101 Things You Must Know Today About Our Future",
    "conflict_flag": false,
    "editorial": {
      "author": "Lasse Rouhiainen",
      "category": "Popular Science",
      "desc_confidence": "Low",
      "description": "This is a popular introductory overview of AI organized as short numbered points. The title and structure indicate a beginner-facing book covering AI applications, business uses, and future trends. Treat specifics as unverified. It appears aimed at general readers and entrepreneurs new to AI. The format favors brevity and breadth over depth. Likely topics include automation, jobs, marketing, and everyday AI. The tone is accessible and upbeat. The audience is newcomers wanting a quick survey. As a self-published introduction, rigor and currency may be limited. The list format suits casual reading. For a substantive treatment, more authoritative titles are preferable.",
      "source": "Appelo core"
    },
    "id": "book-0162",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2018
  },
  {
    "canonical": true,
    "canonical_title": "Artificial Unintelligence: How Computers Misunderstand the World",
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    "editorial": {
      "author": "Meredith Broussard",
      "category": "Critique & Skepticism",
      "desc_confidence": "High",
      "description": "Broussard, a data journalist and academic, critiques technochauvinism, the belief that tech is always the solution. She explains how computers actually work and where AI systems fail. The book uses hands-on examples, including her own projects, to show limits. Broussard treats bias, broken civic tech, and overhyped claims. She argues for realistic expectations and human oversight. The tone is sharp, witty, and skeptical. The audience is general readers and technologists. It is a well-regarded corrective to AI hype. The critique is grounded in technical understanding. It champions human judgment over automation worship. For a critical perspective on AI's real capabilities it is excellent.",
      "source": "Appelo core"
    },
    "id": "book-0163",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2018
  },
  {
    "canonical": true,
    "canonical_title": "The Economic Singularity: Artificial intelligence and the death of capitalism (Third Edition)",
    "conflict_flag": false,
    "editorial": {
      "author": "Calum Chace",
      "category": "Economics & Labour",
      "desc_confidence": "Medium",
      "description": "Chace argues that AI-driven automation could make most human labor uneconomic. He explores the prospect of widespread technological unemployment. The book considers responses including universal basic income and a post-scarcity economy. Chace treats the transition risks and political challenges. He distinguishes this economic singularity from the AI superintelligence singularity. The tone is speculative but argued. The audience is general readers interested in the future of work. The third edition updates earlier analysis. The claims are forecasts, not settled outcomes. It leans toward dramatic disruption scenarios. For debates on automation and jobs it is a clear statement of the disruption thesis.",
      "source": "Appelo core"
    },
    "id": "book-0164",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2018
  },
  {
    "canonical": true,
    "canonical_title": "The Sentient Machine: The Coming Age of Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Amir Husain",
      "category": "Futures",
      "desc_confidence": "Medium",
      "description": "Husain, a technologist and entrepreneur, offers an optimistic view of advanced AI. He addresses fears about machine intelligence and argues for embracing its potential. The book covers consciousness, autonomy, and economic transformation. Husain draws on his work building AI systems. He treats both promise and risk, favoring engagement over fear. The tone is enthusiastic and philosophical. The audience is general readers. It blends technical perspective with speculation about meaning. The argument leans toward techno-optimism. It is concise rather than exhaustive. For an upbeat founder's-eye view of AI's future it is a readable account.",
      "source": "Appelo core"
    },
    "id": "book-0165",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2017
  },
  {
    "canonical": true,
    "canonical_title": "Life 3.0: Being Human in the Age of Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Max Tegmark",
      "category": "Futures",
      "desc_confidence": "High",
      "description": "Tegmark, an MIT physicist, explores the long-term future of life with advanced AI. He frames life's stages by the ability to redesign hardware and software, culminating in Life 3.0. The book opens with a fictional scenario of an AI takeoff, then examines goals, consciousness, and control. Tegmark covers AI safety, alignment, and possible futures ranging from utopian to catastrophic. He co-founded the Future of Life Institute and writes from that vantage. The tone is wide-ranging and thoughtful. The audience is general readers. It became a central popular text on AI risk. The scenarios are deliberately broad. It treats both physics and philosophy. For long-term AI futures it is a foundational popular work.",
      "source": "Appelo core"
    },
    "id": "book-0166",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2017
  },
  {
    "canonical": true,
    "canonical_title": "Machine, Platform, Crowd: Harnessing Our Digital Future",
    "conflict_flag": false,
    "editorial": {
      "author": "Andrew McAfee, Erik Brynjolfsson",
      "category": "Business & Strategy",
      "desc_confidence": "High",
      "description": "McAfee and Brynjolfsson analyze three rebalancings in the digital economy. The first is between human minds and machines, the second between products and platforms, the third between core firms and the crowd. The book gives managers a framework for these shifts. It draws on economic research and company examples. AI and machine learning feature prominently in the machine dimension. The tone is analytical and managerial. The audience is business leaders and strategists. The triad structure organizes the argument. It follows the authors' earlier work on automation. The cases illustrate each rebalancing. For digital strategy it offers a clear, research-backed framework.",
      "source": "Appelo core"
    },
    "id": "book-0167",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2017
  },
  {
    "canonical": true,
    "canonical_title": "Deep Thinking: Where Machine Intelligence Ends and Human Creativity Begins",
    "conflict_flag": false,
    "editorial": {
      "author": "Gary Kasparov",
      "category": "Journalism & Biography",
      "desc_confidence": "High",
      "description": "Kasparov, the chess champion defeated by IBM's Deep Blue, reflects on humans versus machines. He recounts his matches and what they revealed about machine intelligence. The book argues for human-machine collaboration rather than rivalry. Kasparov is optimistic that AI augments rather than replaces human creativity. He treats automation, jobs, and the value of human ambition. The tone is reflective and spirited. The audience is general readers. The personal narrative gives unusual authority. He resists fatalism about human obsolescence. The lessons extend beyond chess to work and society. For a firsthand meditation on competing with machines it is compelling.",
      "source": "Appelo core"
    },
    "id": "book-0168",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2017
  },
  {
    "canonical": true,
    "canonical_title": "Deep Learning: Adaptive Computation and Machine Learning series",
    "conflict_flag": false,
    "editorial": {
      "author": "Ian Goodfellow, Yoshua Bengio, Aaron Courville",
      "category": "Textbook DL",
      "desc_confidence": "High",
      "description": "This is the standard graduate textbook on deep learning, written by three central figures in the field. It builds from mathematical foundations through modern architectures and research frontiers. Part one covers linear algebra, probability, and machine learning basics. Part two develops deep networks, optimization, convolutional and recurrent models. Part three surveys research topics including generative models. The treatment is rigorous and comprehensive. The audience is graduate students and researchers. It is among the most cited references in the field. The mathematics is demanding. It assumes strong technical background. For serious study of deep learning it is the canonical text.",
      "source": "Appelo core"
    },
    "id": "book-0169",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2016
  },
  {
    "canonical": true,
    "canonical_title": "Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy",
    "conflict_flag": false,
    "editorial": {
      "author": "Cathy O'Neil",
      "category": "Society & Ethics",
      "desc_confidence": "High",
      "description": "O'Neil, a mathematician and former quant, exposes harmful algorithmic models. She calls them weapons of math destruction when they are opaque, scaled, and damaging. The book covers credit scoring, hiring, policing, education, and insurance. O'Neil shows how such models entrench inequality while claiming objectivity. She draws on finance and data science experience. The tone is forceful and accessible. The audience is general readers and policymakers. It became a landmark in the algorithmic accountability movement. The examples are concrete and troubling. It calls for transparency and regulation. For fairness and accountability work it is a foundational text.",
      "source": "Appelo core"
    },
    "id": "book-0170",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2016
  },
  {
    "canonical": true,
    "canonical_title": "Artificial Intelligence: What Everyone Needs to Know",
    "conflict_flag": false,
    "editorial": {
      "author": "Jerry Kaplan",
      "category": "Popular Science",
      "desc_confidence": "High",
      "description": "Kaplan, a Silicon Valley entrepreneur and Stanford lecturer, gives a balanced primer on AI. Structured as questions and answers, it covers what AI is, how it works, and its social effects. The book treats jobs, ethics, law, and autonomous systems. Kaplan keeps technical detail accessible. He is measured about both benefits and risks. The tone is clear and even-handed. The audience is general readers wanting a reliable overview. As part of the What Everyone Needs to Know series it favors clarity. It predates the generative AI wave. The Q&A format aids navigation. For a trustworthy short introduction it is a solid choice.",
      "source": "Appelo core"
    },
    "id": "book-0171",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2016
  },
  {
    "canonical": true,
    "canonical_title": "Pattern Recognition and Machine Learning",
    "conflict_flag": false,
    "editorial": {
      "author": "Christopher M. Bishop",
      "category": "Textbook ML",
      "desc_confidence": "High",
      "description": "Bishop's text is a classic graduate reference on statistical machine learning. It develops probabilistic methods for pattern recognition from first principles. Topics include Bayesian inference, graphical models, kernel methods, and mixture models. The treatment is mathematically rigorous and complete. The book predates the deep learning wave but remains foundational. The audience is graduate students and researchers. It is widely used in machine learning courses. The exposition is careful and self-contained. It assumes strong mathematical background. The probabilistic perspective is central throughout. For rigorous study of classical machine learning it is a standard text.",
      "source": "Appelo core"
    },
    "id": "book-0172",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2016
  },
  {
    "canonical": true,
    "canonical_title": "The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future",
    "conflict_flag": false,
    "editorial": {
      "author": "Kevin Kelly",
      "category": "Futures",
      "desc_confidence": "High",
      "description": "Kelly, founding editor of Wired, identifies twelve ongoing technological trends. Each is framed as a verb such as becoming, cognifying, and filtering. Cognifying, the spread of AI into everything, is central. The book argues these forces are largely unstoppable and worth understanding. Kelly is broadly optimistic about adaptation. He treats AI, sharing, tracking, and the cloud. The tone is sweeping and reflective. The audience is general readers and futurists. The trend framework organizes the argument. Predictions are directional rather than precise. For a big-picture view of technological direction it is influential and readable.",
      "source": "Appelo core"
    },
    "id": "book-0173",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2016
  },
  {
    "canonical": true,
    "canonical_title": "Algorithms to Live By: The Computer Science of Human Decisions",
    "conflict_flag": false,
    "editorial": {
      "author": "Brian Christian, Tom Griffiths",
      "category": "Popular Science",
      "desc_confidence": "High",
      "description": "Christian and Griffiths apply computer science algorithms to everyday human decisions. They cover optimal stopping, explore-exploit tradeoffs, scheduling, and caching. The book translates formal results into practical life advice. It blends cognitive science with algorithm design. Examples range from dating to organizing your desk. The tone is witty and clear. The audience is general readers. It makes technical ideas genuinely useful. The treatment is accurate as well as entertaining. It shows how computational thinking illuminates choice. For an accessible bridge between algorithms and life it is widely praised.",
      "source": "Appelo core"
    },
    "id": "book-0174",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2016
  },
  {
    "canonical": true,
    "canonical_title": "The Age of Em: Work, Love, and Life when Robots Rule the Earth",
    "conflict_flag": false,
    "editorial": {
      "author": "Robin Hanson",
      "category": "Futures",
      "desc_confidence": "High",
      "description": "Hanson, an economist, models a future dominated by emulated human minds, or ems. He assumes brain emulation arrives before general AI and reasons out the consequences. The book applies economics, physics, and social science to this scenario in detail. Hanson describes em labor, cities, relationships, and politics. The method is unusual: rigorous extrapolation from one premise. The tone is analytical and deadpan. The audience is futurists and curious readers. It is a singular, deeply worked-out thought experiment. The conclusions are speculative by design. It is dense and idiosyncratic. For a rigorous alternative AI future it is unlike anything else.",
      "source": "Appelo core"
    },
    "id": "book-0175",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2016
  },
  {
    "canonical": true,
    "canonical_title": "Make Your Own Neural Network",
    "conflict_flag": false,
    "editorial": {
      "author": "Tariq Rashid",
      "category": "Practitioner",
      "desc_confidence": "High",
      "description": "Rashid teaches neural networks from scratch with a gentle, hands-on approach. The book builds the mathematics step by step, then implements a network in Python. It targets readers with no prior machine learning background. Rashid explains gradient descent and backpropagation intuitively. The project recognizes handwritten digits. The tone is patient and encouraging. The audience is beginners and hobbyists. It is praised for demystifying the core mechanics. The code is simple and followable. It favors understanding over performance. For a true beginner wanting to build a network themselves it is an excellent starting point.",
      "source": "Appelo core"
    },
    "id": "book-0176",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2016
  },
  {
    "canonical": true,
    "canonical_title": "The Industries of the Future",
    "conflict_flag": false,
    "editorial": {
      "author": "Alec Ross",
      "category": "Business & Strategy",
      "desc_confidence": "Medium",
      "description": "Ross, a former State Department innovation adviser, surveys emerging technology sectors. He covers robotics, genomics, cybersecurity, big data, and digital finance. The book assesses where economic and geopolitical advantage will shift. AI and automation feature across several chapters. Ross draws on travel and policy experience. The tone is accessible and globally minded. The audience is general readers and policymakers. It frames opportunity and disruption by country and sector. The treatment is broad rather than deep. Some forecasts reflect its mid-2010s vantage. For a policy-flavored survey of future industries it is readable.",
      "source": "Appelo core"
    },
    "id": "book-0177",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2016
  },
  {
    "canonical": true,
    "canonical_title": "What to Think About Machines That Think: Today's Leading Thinkers on the Age of Machine Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "John Brockman",
      "category": "Philosophy of Mind",
      "desc_confidence": "High",
      "description": "Brockman collects short responses from many leading thinkers to a single question about thinking machines. Contributors span science, technology, and philosophy. The answers range from enthusiasm to deep concern. Each entry is brief, often a page or two. The collection captures elite opinion before the deep learning boom matured. Topics include consciousness, risk, and the nature of intelligence. The tone is varied and provocative. The audience is educated general readers. As an anthology it offers breadth over argument. The format suits sampling many views quickly. For a snapshot of expert sentiment circa 2015 it is a rich record.",
      "source": "Appelo core"
    },
    "id": "book-0178",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2015
  },
  {
    "canonical": true,
    "canonical_title": "The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World",
    "conflict_flag": false,
    "editorial": {
      "author": "Pedro Domingos",
      "category": "Popular Science",
      "desc_confidence": "High",
      "description": "Domingos, a machine learning researcher, surveys the field through five tribes. Each tribe, from symbolists to connectionists to Bayesians, has its own master algorithm. The book imagines a unifying learner combining their strengths. Domingos explains core ideas without heavy mathematics. He treats the promise and societal stakes of learning machines. The tone is ambitious and accessible. The audience is general readers and aspiring data scientists. The five-tribes framing is a useful map of the field. The unification vision is speculative. It conveys how machine learning actually works conceptually. For an intelligent popular overview of ML it is well regarded.",
      "source": "Appelo core"
    },
    "id": "book-0179",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2015
  },
  {
    "canonical": true,
    "canonical_title": "The Future of Professions: How Technology Will Transform the Work of Human Experts",
    "conflict_flag": false,
    "editorial": {
      "author": "Richard Susskind, Daniel Susskind",
      "category": "Economics & Labour",
      "desc_confidence": "High",
      "description": "The Susskinds argue technology will dismantle the traditional model of professional expertise. They examine law, medicine, accounting, education, and other fields. The book contends that machines and networks will make expert knowledge more widely accessible. It predicts the decomposition of professional work into tasks, many automatable. The authors treat both gains in access and threats to jobs. The tone is analytical and thorough. The audience is professionals, educators, and policymakers. The argument is systematic and influential. It anticipates AI's impact on knowledge work. The forecasts are directional. For debates on professional disruption it is a key reference.",
      "source": "Appelo core"
    },
    "id": "book-0180",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2015
  },
  {
    "canonical": true,
    "canonical_title": "Humans Need Not Apply: A Guide to Wealth and Work in the Age of Artificial Intelligence",
    "conflict_flag": false,
    "editorial": {
      "author": "Jerry Kaplan",
      "category": "Economics & Labour",
      "desc_confidence": "High",
      "description": "Kaplan examines how AI and automation will reshape work and wealth. He warns of job displacement and rising inequality from intelligent machines. The book proposes economic mechanisms to spread the gains, including new financial instruments. Kaplan writes from a Silicon Valley and academic vantage. He treats labor markets, education, and policy. The tone is clear and pragmatic. The audience is general readers and policymakers. The economic proposals distinguish it from pure forecasting. It balances concern with constructive ideas. The analysis predates the generative AI wave. For automation-and-jobs debates it is a thoughtful contribution.",
      "source": "Appelo core"
    },
    "id": "book-0181",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2015
  },
  {
    "canonical": true,
    "canonical_title": "Surviving AI: The promise and peril of artificial intelligence (Third Edition)",
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    "editorial": {
      "author": "Calum Chace",
      "category": "Safety & Alignment",
      "desc_confidence": "Medium",
      "description": "Chace surveys both the benefits and dangers of advancing AI. He covers narrow AI, the path to general intelligence, and superintelligence risk. The book treats automation, the control problem, and possible futures. Chace writes for a general audience without technical prerequisites. He aims to inform rather than alarm. The tone is accessible and balanced. The audience is newcomers to AI risk debates. It synthesizes arguments from researchers like Bostrom. The third edition updates earlier material. It is a primer rather than original research. For a readable overview of AI promise and peril it serves well.",
      "source": "Appelo core"
    },
    "id": "book-0182",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2015
  },
  {
    "canonical": true,
    "canonical_title": "Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots",
    "conflict_flag": false,
    "editorial": {
      "author": "John Markoff",
      "category": "History",
      "desc_confidence": "High",
      "description": "Markoff, a veteran technology journalist, traces the tension between AI and intelligence augmentation. He contrasts efforts to replace humans with efforts to extend them. The book draws on the history of computing and robotics in Silicon Valley. Markoff profiles key researchers and their competing philosophies. He asks who controls the machines and to what end. The tone is journalistic and historically grounded. The audience is general readers. The augment-versus-automate framing is central. It is rich in personalities and context. The narrative spans decades of research. For the human dimension of AI history it is a strong account.",
      "source": "Appelo core"
    },
    "id": "book-0183",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2015
  },
  {
    "canonical": true,
    "canonical_title": "Rise of the Robots: Technology and the Threat of a Jobless Future",
    "conflict_flag": false,
    "editorial": {
      "author": "Martin Ford",
      "category": "Economics & Labour",
      "desc_confidence": "High",
      "description": "Ford argues that automation threatens to eliminate jobs across skill levels, not just routine ones. He contends this time differs from past technological shifts. The book documents automation in manufacturing, services, and white-collar work. Ford warns of structural unemployment and inequality. He proposes responses including a basic income. The tone is urgent and evidence-driven. The audience is general readers and policymakers. It won a major business book award and shaped the jobs debate. The thesis is that machines increasingly substitute for, not complement, labor. The argument is forceful. For technological unemployment debates it is a landmark popular text.",
      "source": "Appelo core"
    },
    "id": "book-0184",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2015
  },
  {
    "canonical": true,
    "canonical_title": "Homo Deus: A Brief History of Tomorrow",
    "conflict_flag": false,
    "editorial": {
      "author": "Yuval Noah Harari",
      "category": "Futures",
      "desc_confidence": "High",
      "description": "Harari extends his sweeping history into the future of humanity. He argues that having tackled famine, plague, and war, humans now seek immortality, happiness, and divinity. The book contends that data, algorithms, and AI may displace human authority and individualism. Harari introduces dataism as an emerging worldview. He warns of a future where most humans become economically irrelevant. The tone is provocative and synthetic. The audience is broad general readers. It became a global bestseller. The arguments are bold and contested. It treats AI within a grand civilizational narrative. For big-picture reflection on AI and humanity's future it is widely read.",
      "source": "Appelo core"
    },
    "id": "book-0185",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2015
  },
  {
    "canonical": true,
    "canonical_title": "The Future of the Brain: Essays by the World's Leading Neuroscientists",
    "conflict_flag": false,
    "editorial": {
      "author": "Gary Marcus, Jeremy Freeman",
      "category": "Neuroscience",
      "desc_confidence": "Medium",
      "description": "Marcus and Freeman edit essays by prominent neuroscientists on understanding the brain. The collection covers brain mapping, big neuroscience projects, and computational approaches. Contributors discuss how new tools may reveal how minds work. Several essays touch on connections to artificial intelligence. The book reflects the state of the field in the mid-2010s. The tone is scientific and varied. The audience is informed readers and students. As an anthology it offers breadth across topics and viewpoints. The AI relevance is indirect but real, given brain-inspired computing. Depth varies by contributor. For the science of understanding the brain it is a substantive collection.",
      "source": "Appelo core"
    },
    "id": "book-0186",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2014
  },
  {
    "canonical": true,
    "canonical_title": "Superintelligence: Paths, Dangers, Strategies",
    "conflict_flag": false,
    "editorial": {
      "author": "Nick Bostrom",
      "category": "Safety & Alignment",
      "desc_confidence": "High",
      "description": "Bostrom, an Oxford philosopher, presents a rigorous analysis of machine superintelligence and its risks. He examines paths to superintelligence and the dynamics of an intelligence explosion. The book introduces the control problem and the difficulty of aligning advanced AI with human values. Bostrom analyzes instrumental convergence and the treacherous turn. He argues the stakes are existential. The tone is dense, careful, and philosophical. The audience is researchers, policymakers, and serious readers. It is the foundational text of the AI existential risk field. The arguments shaped much subsequent safety work. It is demanding but influential. For AI alignment and risk it is essential reading.",
      "source": "Appelo core"
    },
    "id": "book-0187",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2014
  },
  {
    "canonical": true,
    "canonical_title": "The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies",
    "conflict_flag": false,
    "editorial": {
      "author": "Erik Brynjolfsson, Andrew McAfee",
      "category": "Economics & Labour",
      "desc_confidence": "High",
      "description": "Brynjolfsson and McAfee, MIT economists, argue digital technologies are transforming the economy as steam once did. They show how computing, data, and AI drive growth while disrupting labor. The book treats the spread of digital abundance and the decoupling of productivity from wages. It addresses inequality and policy responses. The authors balance optimism about innovation with concern about distribution. The tone is analytical and accessible. The audience is general readers and policymakers. It became a defining text on technology and the economy. The bounty-and-spread framing is central. The evidence is economic. For technology's economic impact it is a key reference.",
      "source": "Appelo core"
    },
    "id": "book-0188",
    "language": "EN",
    "level": null,
    "original_title": null,
    "work_type": "book",
    "year": 2014
  },
  {
    "canonical": true,
    "canonical_title": "Our Final Invention: Artificial Intelligence and the End of the Human Era",
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      "source": "Appelo core"
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      "author": "Ray Kurzweil",
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      "description": "Kurzweil, with physician Terry Grossman, argues readers can live long enough to benefit from future life-extension technology. The book combines health advice with futurist projection. It outlines bridges from current medicine to biotechnology and nanotechnology. The AI relevance is indirect, tied to Kurzweil's broader acceleration thesis. The health recommendations reflect mid-2000s thinking. The tone is optimistic and prescriptive. The audience is general readers interested in longevity. It is more a wellness-and-futurism book than an AI text. The science is dated in parts. For Kurzweil's life-extension framing it is the relevant title, though peripheral to AI proper.",
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      "source": "Appelo core"
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    "id": "book-0197",
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    "level": null,
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    "work_type": "book",
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      "author": "David J.C. MacKay",
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      "description": "MacKay's textbook unifies information theory, probabilistic inference, and machine learning. It develops coding, entropy, and Bayesian methods alongside neural networks. The book is known for clear exposition and rich exercises. MacKay connects communication theory to learning algorithms throughout. The treatment is rigorous and original. The audience is graduate students and researchers. It is widely admired and freely available. The probabilistic perspective ties the topics together. It assumes mathematical maturity. The integration of fields is its distinctive strength. For information theory and Bayesian learning it is a respected reference.",
      "source": "Appelo core"
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    "id": "book-0198",
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    "original_title": null,
    "work_type": "book",
    "year": 2002
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      "author": "Ray Kurzweil",
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      "desc_confidence": "High",
      "description": "Kurzweil forecasts a future where machines match and exceed human intelligence. He develops his law of accelerating returns to project exponential progress. The book imagines computing, consciousness, and society across coming decades. Kurzweil predicts intimate human-machine integration. He treats the blurring of human and artificial minds. The tone is visionary and optimistic. The audience is general readers and futurists. It established many themes he later expanded. Some near-term predictions have been assessed against outcomes. The long-range claims remain speculative. For the early statement of Kurzweil's futurism it is a foundational popular work.",
      "source": "Appelo core"
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      "author": "Ray Kurzweil",
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      "description": "Kurzweil's first major book surveys the history and future of artificial intelligence. Written around 1990, it traces AI's origins and projects its trajectory. The book combines essays, illustrations, and contributions from other thinkers. Kurzweil introduces early versions of his acceleration arguments. He treats pattern recognition, neural networks, and machine cognition. The tone is broad and forward-looking. The audience is general readers of its era. It is historically significant as an early popular AI synthesis. Some predictions can now be evaluated. It set the stage for his later work. For the roots of Kurzweil's thinking it is the original text.",
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    "level": null,
    "original_title": null,
    "work_type": "book",
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      "author": "Trevor Hastie, Robert Tibshirani, Jerome Friedman",
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      "source": "Canon hunt"
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    "id": "book-0202",
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      "author": "Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani",
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      "source": "Canon hunt"
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    "id": "book-0203",
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    "original_title": null,
    "work_type": "book",
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    "canonical_title": "Machine Learning",
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      "author": "Tom M. Mitchell",
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      "source": "Canon hunt"
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    "id": "book-0204",
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    "canonical_title": "Pattern Classification (2nd ed.)",
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      "author": "Richard O. Duda, Peter E. Hart, David G. Stork",
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    "canonical_title": "Machine Learning: A Probabilistic Perspective",
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      "author": "Kevin P. Murphy",
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      "source": "Canon hunt"
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      "description": "York, a free-expression advocate, examines how platform content-moderation regimes shape global speech, often opaquely and inconsistently, under commercial and political pressure. Drawing on years of digital-rights work, the book documents the human costs of moderation choices. Relevant to AI content-moderation governance.",
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      "description": "Daub dissects the borrowed and often shallow ideas, disruption, genius, dropping out, that Silicon Valley uses to justify itself, showing their intellectual histories and limits. A literate, critical examination of tech-world ideology. Useful for understanding the rhetoric around AI.",
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      "desc_confidence": "Low",
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      "description": "Golumbia argues that computationalism, the belief that computation explains and should govern ever more of human life, carries a conservative political logic that concentrates power. An early and theoretically serious critique predating the deep-learning era. Frequently cited as a foundational text in critical computing studies.",
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    "id": "book-0565",
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      "description": "Based on her 1989 Massey Lectures, the physicist Ursula Franklin distinguishes holistic from prescriptive technologies and argues that technology is a system of practices that reshapes social relations and power, not a neutral set of tools. A foundational and humane work of technology criticism, still widely taught. Predates AI debates but frames them clearly.",
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    "level": null,
    "original_title": null,
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      "desc_confidence": "Medium",
      "description": "Borsook's early critique skewers the libertarian ideology pervading 1990s high-tech culture, presciently identifying the political worldview that would shape the industry for decades. A historically important account of tech-world politics. Recently reissued, underscoring its renewed relevance.",
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      "author": "Diana E. Forsythe",
      "category": "History",
      "desc_confidence": "High",
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