{"product_id":"the-ai-illusion-why-machines-arent-creative-hardback-9781394412174","title":"The AI Illusion; Why Machines Aren't Creative (Hardback) 9781394412174","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eThe AI Illusion\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eWhy Machines Aren't Creative\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eLuc Julia (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394412174, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 30 March 2026\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e192 pages\u003cbr\u003e23.1 x 15.8 x 2 cm, 0.363 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eDiscover the truth behind AI's most dangerous myth: that machines can truly create\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIn \u003ci\u003eThe AI Illusion: Why Machines Aren't Creative\u003c\/i\u003e, Luc Julia, co-creator of Siri and Chief Scientific Officer for the Renault Group, dismantles the hype surrounding generative AI by revealing what these technologies can actually do (as of today) versus what their promoters claim. Drawing on over 35 years' experience in the tech industry, Julia exposes the fundamental truth that generative AI doesn't create – it recombines existing data in response to prompts, producing impressive but ultimately derivative outputs that lack genuine creativity and understanding.\u003c\/p\u003e \u003cp\u003eThis essential guide takes readers on a comprehensive journey through AI's past, present, and future, systematically debunking seven pervasive myths that shape public perception of artificial intelligence. Julia examines the technical limitations, societal implications, and environmental costs of generative AI while providing practical insights into how these tools function and where they're headed.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eThe book:\u003c\/b\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eReveals the technical reality behind generative AI's \"hallucinations,\" biases, and inability to reason or understand language\u003c\/li\u003e \u003cli\u003eExposes the environmental disaster created by energy-intensive AI training and deployment processes\u003c\/li\u003e \u003cli\u003eAnalyzes the economic and employment impacts of AI adoption across industries and society\u003c\/li\u003e \u003cli\u003eDemonstrates why artificial general intelligence (AGI) remains scientifically impossible with current approaches\u003c\/li\u003e \u003cli\u003eProvides actionable solutions for more responsible AI development and regulation\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ePerfect for technology professionals, business leaders, policymakers, and curious readers trying to understand AI's true capabilities and limitations, \u003ci\u003eThe AI Illusion\u003c\/i\u003e offers a clear-eyed perspective to help you navigate our AI-influenced future. It provides the critical thinking tools you'll need to see past the marketing hype and science fiction fantasies that dominate AI discourse.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I The History of AI 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1956: The Dartmouth Conference, Where It All Began 1\u003c\/p\u003e \u003cp\u003eBut Was AI Really Invented in 1956? 2\u003c\/p\u003e \u003cp\u003eThe Winter of AI: The First One 3\u003c\/p\u003e \u003cp\u003eThe Expert Systems: AI Is Back! 4\u003c\/p\u003e \u003cp\u003eThe First “Defeat” of Man Against AI 5\u003c\/p\u003e \u003cp\u003eThe Rise of Statistical AIs and Machine Learning 5\u003c\/p\u003e \u003cp\u003eOne of the First Image Recognizers in History 6\u003c\/p\u003e \u003cp\u003eThe Second “Defeat” of Man Against AI 8\u003c\/p\u003e \u003cp\u003eData: A Major Challenge 9\u003c\/p\u003e \u003cp\u003eTay: The AI That Went Awry 10\u003c\/p\u003e \u003cp\u003e“Autonomous” Cars 12\u003c\/p\u003e \u003cp\u003eWhat About GenAI? 16\u003c\/p\u003e \u003cp\u003eGenAI for All of Us 18\u003c\/p\u003e \u003cp\u003eThe “True” AI 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Is Genai the Holy Grail of Technology? 21\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA Revolution, but Not the One You Think 22\u003c\/p\u003e \u003cp\u003eGood Choice of Words This Time 23\u003c\/p\u003e \u003cp\u003eThe Gartner Hype Cycle at Full Speed! 25\u003c\/p\u003e \u003cp\u003eWhat Are the Concrete Applications for GenAI? 27\u003c\/p\u003e \u003cp\u003eWeakness #1: Hallucinations 28\u003c\/p\u003e \u003cp\u003eThe One Prompt Too Many for Steven Schwartz 28\u003c\/p\u003e \u003cp\u003eMy Always Evolving Bio 29\u003c\/p\u003e \u003cp\u003eWeakness #2: Lack of Accuracy 30\u003c\/p\u003e \u003cp\u003eDoes Being Wrong One Third of the Time Really Matter? 30\u003c\/p\u003e \u003cp\u003eWeakness #3: They Can’t Think 31\u003c\/p\u003e \u003cp\u003eWeakness #4: Jailbreaking— A Security Breach 33\u003c\/p\u003e \u003cp\u003eWhat to Make of the Jailbreaking Story? 38\u003c\/p\u003e \u003cp\u003eSolution #1: Fine-Tuning and RAG 39\u003c\/p\u003e \u003cp\u003eSolution #2: Use the Data We Own and\/or Trust 40\u003c\/p\u003e \u003cp\u003eIs Data Theft Inherent on Training GenAI? 40\u003c\/p\u003e \u003cp\u003eA Marketing Argument 43\u003c\/p\u003e \u003cp\u003eAre AIs More and More Stupid? 44\u003c\/p\u003e \u003cp\u003eSolution #3: Watermarking Is the Savior 45\u003c\/p\u003e \u003cp\u003eIs It Possible to Watermark Text? 46\u003c\/p\u003e \u003cp\u003eAn AI to Control Another AI: Is It a Good Idea? 47\u003c\/p\u003e \u003cp\u003eSolution #4: Open Source—A Source of Creativity 49\u003c\/p\u003e \u003cp\u003eSolution #5: Small Language Models and Edge Computing 51\u003c\/p\u003e \u003cp\u003eSolution #6: Hybrid AI and the End of GenAI 53\u003c\/p\u003e \u003cp\u003eAGI Is Still an Inaccessible Dream 53\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III the Seven Myths of Ai 55\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eMyth Number 0(Riginal) 56\u003c\/p\u003e \u003cp\u003eAI Is Creative 56\u003c\/p\u003e \u003cp\u003eWhat’s Creativity Anyway? 56\u003c\/p\u003e \u003cp\u003eThere Is “Create” and “create” 57\u003c\/p\u003e \u003cp\u003eCan’t We Be Creative with an AI? 58\u003c\/p\u003e \u003cp\u003eThe Two Dimensions of Creativity 60\u003c\/p\u003e \u003cp\u003eAI Will Never Innovate 61\u003c\/p\u003e \u003cp\u003eThen AIs Are Useless? 62\u003c\/p\u003e \u003cp\u003eAre AIs and Auto-Tune the Same? 63\u003c\/p\u003e \u003cp\u003eMyth Number 1: AI Understands What It’s Telling You and Can Reflect Upon It 63\u003c\/p\u003e \u003cp\u003eCognitive Bias Plays Tricks on Us 64\u003c\/p\u003e \u003cp\u003eThe Characteristics of Intelligence 65\u003c\/p\u003e \u003cp\u003eIs AI Really Better Than Humans at Recognizing Speech? 66\u003c\/p\u003e \u003cp\u003eAre Humans Really Better Than AI at Understanding Language? 67\u003c\/p\u003e \u003cp\u003eThe Three Phases of Natural Language Understanding 67\u003c\/p\u003e \u003cp\u003eAI Invents a New Language: Too Smart for a Human to Understand? 71\u003c\/p\u003e \u003cp\u003eThe True Failure of AI 73\u003c\/p\u003e \u003cp\u003eAre AIs Better Than Humans at Communicating with Humans? 74\u003c\/p\u003e \u003cp\u003eMyth Number 2: AIs Are Inexplicable Black Boxes 75\u003c\/p\u003e \u003cp\u003eThe Story of Gaston Julia and Fractals 76\u003c\/p\u003e \u003cp\u003eThe Unexpected and the Inexplicable: The Reason for the Black Box Myth 77\u003c\/p\u003e \u003cp\u003eThe Three Sources of the Unexpected 78\u003c\/p\u003e \u003cp\u003eExample: The Screw-Driving Robot from Tesla 79\u003c\/p\u003e \u003cp\u003eIs Explicability an Achievable Goal? 80\u003c\/p\u003e \u003cp\u003eMyth Number 3: AI Is Going to Kill Us All 81\u003c\/p\u003e \u003cp\u003eTerminator, by James Cameron 82\u003c\/p\u003e \u003cp\u003eAvengers: Age of Ultron, by Joss Whedon 83\u003c\/p\u003e \u003cp\u003eSo, Killer AIs Do Not Exist? 84\u003c\/p\u003e \u003cp\u003eEaster Eggs: The Poisoned Chalice of AI 85\u003c\/p\u003e \u003cp\u003eThe Story of the American Killer Drone 86\u003c\/p\u003e \u003cp\u003eScoop: Socrates Explains Why AIs Aren’t Yet Intelligent 87\u003c\/p\u003e \u003cp\u003eGenAIs Need Humans 88\u003c\/p\u003e \u003cp\u003eMyth Number 4: AI Is Objective 88\u003c\/p\u003e \u003cp\u003eColor Blindness: An Example of a Subjective World 89\u003c\/p\u003e \u003cp\u003eWar: The Quintessence of Subjectivity 90\u003c\/p\u003e \u003cp\u003eBiases Are Inherent in AI 90\u003c\/p\u003e \u003cp\u003eAIs: Tools for Profit 91\u003c\/p\u003e \u003cp\u003eThe Ultimate Proof of AI’s Subjectivity 92\u003c\/p\u003e \u003cp\u003eMyth Number 5: AI Will Lead to a Widespread Job Loss 93\u003c\/p\u003e \u003cp\u003eThere Have Been Other Revolutions Before AI 93\u003c\/p\u003e \u003cp\u003eInnovation: Less Lethal Than We Think 94\u003c\/p\u003e \u003cp\u003eWill Gen AIs Soon Be Executives’ Only Staff? 94\u003c\/p\u003e \u003cp\u003eThe Two Levels of AI’s Mastery 95\u003c\/p\u003e \u003cp\u003eWhat Are the Consequences for the Organization of Companies? 96\u003c\/p\u003e \u003cp\u003eAI: An Asset for Employability Rather Than a Hindrance 97\u003c\/p\u003e \u003cp\u003eAI: The Least Job-Destroying Revolution 98\u003c\/p\u003e \u003cp\u003eMyth Number 6: AI Can Learn Anything (Acquired versus Innate) 98\u003c\/p\u003e \u003cp\u003eThe Foundation of the Discussion 99\u003c\/p\u003e \u003cp\u003eDescartes and the Beginning of Reconciliation 100\u003c\/p\u003e \u003cp\u003eThe Age of Enlightenment and the End of the Debate 100\u003c\/p\u003e \u003cp\u003eAnd What About AI in All This? 101\u003c\/p\u003e \u003cp\u003eIs Incomplete AI an Issue? 102\u003c\/p\u003e \u003cp\u003eMyth Number 7: AI Cares and Does Everything Right 102\u003c\/p\u003e \u003cp\u003eEthics and Its Multiple Dimensions 102\u003c\/p\u003e \u003cp\u003eAre GenAIs Built to Be Unethical? 103\u003c\/p\u003e \u003cp\u003eWho’s Really in Charge of AI’s Ethics? 104\u003c\/p\u003e \u003cp\u003eIs a Hammer Ethical? 105\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV What Ai Will Change in Our Lives 107\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Ecological Disaster of GenAI 108\u003c\/p\u003e \u003cp\u003eThe Three Energy-Hungry Activities 108\u003c\/p\u003e \u003cp\u003eChatGPT: Pandora’s Box of AI 112\u003c\/p\u003e \u003cp\u003eDrying Up Humanity to Feed the Machine? 114\u003c\/p\u003e \u003cp\u003eHow to Meet AI Resource Demands 115\u003c\/p\u003e \u003cp\u003eData Centers: The Sine Qua Non Condition for GenAI 116\u003c\/p\u003e \u003cp\u003eSome Shocking Figures on Data Centers 117\u003c\/p\u003e \u003cp\u003eGreed Is a Bad Thing 118\u003c\/p\u003e \u003cp\u003eThere Is No Plan(et) B 120\u003c\/p\u003e \u003cp\u003eAI Washing and the Gold Rush of GenAI 120\u003c\/p\u003e \u003cp\u003eGetting Rich Thanks to AI or by Lying About It 121\u003c\/p\u003e \u003cp\u003eAI Washing: Out of Greed or Fear? 122\u003c\/p\u003e \u003cp\u003eThe Tortoise and the Hare of GenAI 124\u003c\/p\u003e \u003cp\u003eBut What Does the AI Police Do? 126\u003c\/p\u003e \u003cp\u003e“Out of Sight, Out of Mind” or Paying the Full Price 128\u003c\/p\u003e \u003cp\u003eAI Forcing and the Obsolescence of Classic AI 130\u003c\/p\u003e \u003cp\u003eThe End of the GenAI Bubble? 132\u003c\/p\u003e \u003cp\u003eBanning AI: A Necessary Evil? 133\u003c\/p\u003e \u003cp\u003eRegulate, Yes; Ban, No 134\u003c\/p\u003e \u003cp\u003eGDPR’s Shortcoming 135\u003c\/p\u003e \u003cp\u003eWhat Does the AI Act Look Like in Detail? 137\u003c\/p\u003e \u003cp\u003eAllow Technology but Ban Some Applications 140\u003c\/p\u003e \u003cp\u003eData Theft and AI 141\u003c\/p\u003e \u003cp\u003eWho Is Really Responsible for AI-Generated Content? 143\u003c\/p\u003e \u003cp\u003eAI and the Data Industry 145\u003c\/p\u003e \u003cp\u003eRegulation’s Big Miss: The Ecology 147\u003c\/p\u003e \u003cp\u003eMalicious Uses of GenAI 147\u003c\/p\u003e \u003cp\u003eFake News 148\u003c\/p\u003e \u003cp\u003eWhat About Deepfakes? 149\u003c\/p\u003e \u003cp\u003eEmotion Detectors 151\u003c\/p\u003e \u003cp\u003eHacking and Cybersecurity 152\u003c\/p\u003e \u003cp\u003eWhat About GenAI? 153\u003c\/p\u003e \u003cp\u003eA Quick Discussion on Quantum Computers 153\u003c\/p\u003e \u003cp\u003eThe Hidden Flaws of GenAI 154\u003c\/p\u003e \u003cp\u003eBeing Manipulated Without Realizing It 154\u003c\/p\u003e \u003cp\u003eCultures Cancelling 155\u003c\/p\u003e \u003cp\u003eEvolution of Teaching and Working Methods 156\u003c\/p\u003e \u003cp\u003eAI and Teaching: An Explosive Cocktail? 156\u003c\/p\u003e \u003cp\u003eIs AI Going to Perform Tasks on Our Behalf? 157\u003c\/p\u003e \u003cp\u003eAn AI Monopoly? 157\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart V Our Future with Ai 159\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSolution #1: Make AIs More Frugal 159\u003c\/p\u003e \u003cp\u003eSolution #2: Regulate to Encourage Less Consumption 160\u003c\/p\u003e \u003cp\u003eSolution #3: Limit Unnecessary Uses 161\u003c\/p\u003e \u003cp\u003eAI and IoT 161\u003c\/p\u003e \u003cp\u003eConclusion 163\u003c\/p\u003e \u003cp\u003eAbout the Author 165\u003c\/p\u003e \u003cp\u003eIndex 167\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand New","offer_id":52460732973336,"sku":"9781394412174","price":17.76,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394412174.jpg?v=1785459752","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/the-ai-illusion-why-machines-arent-creative-hardback-9781394412174","provider":"Freshly Printed Books","version":"1.0","type":"link"}