Type of Credit: Elective
Credit(s)
Number of Students
壹、 課程目標
（一）從人文社科角度認識AI，從AI角度再思人文議題。
（二）尋找和發現人文社會專業在AI時代的定位和貢獻。
（三）介紹相關議題，盤點相關文獻，建立研究和實務之知識背景。
（四）培養在不確定年代，學習和決策的能力。
具體而言，本課程試圖探討以下幾個問題：
貳、怎麼讀這門課？
為了因應AI，教學和學習方式都必須跳出傳統的框架。本課程設計遵循以下幾個原則：
一、討論當週主題
（一）課前教師將提出討論大綱以供參考。但同學也「必須」提出自己關心的問題。
（二）整理和討論相關事實、概念和論述。
（三）提出對未來之想像、對問題之對策、個人因應之方案（如：創業計劃）
同學除閱讀指定讀物外，應自行蒐集資料，和AI討論，提出初步之見解。
為便於自主學習，我開了一份很長的書單。理由是：
二、期末研究報告
有兩個選擇：
以上報告，建議多利用AI完成，但最終版本應註明「人」的貢獻。對報告評估將以口試方式進行。
四、個別晤談： 學期中，學生應至少和老師約談一次（不限次數），討論構想中之提案或其他問題。
能力項目說明
課程目標
（一）從人文社科角度認識AI，從AI角度再思人文議題。
（二）尋找和發現人文社會專業在AI時代的定位和貢獻。
（三）介紹相關議題，盤點相關文獻，建立研究之知識背景。
具體而言，本課程分作以下部分：
（一）AI是什麼？從計算、智能/知識和傳播等角度認識AI，以掌握其邏輯和本質。
（二）AI之後的人文世界。探討AI 對個人和社會之衝擊，並試圖發現其中隱藏之契機。
（三）尋找人的定位。新科技的出現，經常迫使人再思自己在宇宙的定位，相關的問題有： AI出現後，人的獨特性何在？如何和AI共處？又如何善用強化個人和社會？
（四）探討未來AI社會之輪廓。重點在遠眺AI的地平線，思考如何形塑未來的AI世紀。
（五）「AI和人文社科」之研究取徑。 探討在研究AI之之人文社科議題時，可能需要什麼新典範、理論和方法。
| 教學週次Course Week | 彈性補充教學週次Flexible Supplemental Instruction Week | 彈性補充教學類別Flexible Supplemental Instruction Type |
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肆 課程進度
9/13 課程介紹
9/20 AI是計算（AI as computing）
繳交「好奇的問題」說明（1-2頁）
本週主題 AI其計算機理論基礎為何？其核心概念為何？其演化歷程為何？對AI之發展有何影響？
必讀 Mitchel, Melainie. (2020). Artificial Intelligence: A Guide for Thinking Humans. New York，NY: Farrar, Straus, and Giroux，Chap. 11, “Words, and the company they keep”, pp. 177-196.
參考讀物
理論基礎 Turing, Alan. (1950). Computing machinery and intelligence. Mind, 59:236, pp. 433-60. Newell, Allen; & Simon, Herbert A. (1976). Computer Science as Empirical Inquiry: Symbols and Search. In Communications of the Association for Computing Machinery, 19, 1976, pp. 113-126. Russell, Stuart, & Norvig, Peter. (2021). Artificial Intelligence: A Modern Approach. Fourth Edition. Prentice Hall. Ananthaswamy, Anil. (2024). Why Machines Learn: The Elegant Math Behind Modern AI. Dutton. Marcus, G. (2018). Deep learning: A critical appraisal. arXiv preprint. arXiv:1801.00631.
歷史和文化中的AI想像 Mayor, Andrienne. (2021). 愷易緯(譯). 當神成為機器人： 希臘神話如何透過科幻想像，探問人類生命的本質. 台北：讀書共和國. Cave, Stehphen; Dihal, Kanta; & Dillon, Sarah. (2020). AI Narratives: A History of Imaginative Thinking about Intelligent Machines. Oxford University Press. Ford, Martin. (2018). Architects of Intelligence: The Truth about AI from the People Building It. Packet. Cave, Stephen; & Dihal, Kanta. (2023). Imaging AI: How the World Sees Intelligent Machines. Oxford University Press. Tenen, Dennis Yi. (2024). Literary Theory for Robots: How Computers Learn to Write. W. W. Norton & Company. Nilsson, Nils J. (2009). The Quest for Artificial Intelligence: A History of Ideas and Achievements. Cambrige University Press. Sejnowski, Terrence, J. (2018). The Deep Learning Revolution: Artificial Intelligence Meets Human Intelligence. The MIT Press.
AI的思維模式 Toon, Nigel. (2024). How AI Thinks: How We Built It, How It Can Help Us, and How We Can Control It. Torva. Towner, George. 吳國慶（譯）. (2023). 電腦如何學會思考？ 台北：讀書共和國. Denning, Peter J.; & Tedre, Matt. (2019). Computational Thinking. The MIT Press. Gerrish, Sean. (2018). How Smart Machines Think. The MIT Press. Agrawal, Ajay; Gans, Joshua; & Goldfarb, Avi. (2022). Prediction Machines: The Simple Economics of Artificial Intelligence. Harvard Business Review Press. Hofstadter, Douglas R. (1979). Godel, Escher, Bach: An Eternal Golden Braid. Basic Books. Joque, Justin. (2024). Revolutionary Mathematics: Artificial Intelligence, Statistics and the Logic of Capitalism. Verso. Hunt, Jamer. (2021). 劉盈成（譯）. 重新丈量世界. 漫遊者.
神經網路 Dhaliwal, Ranjodh Singh; Lepage-Richer; & Suchman, Lucy. (2024). Neural Networks: In Search of Media. University of Minnesota Press. Krauss, Patrick. (2024). Artificial Intelligence and Brain Research: Neural Networks, Deep Learning and the Future of Cognition. Springer.
生成式AI Kaplan, Jerry. (2024). Generative Artificial Intelligence: What Everyone Needs to Know. Oxford University Press，Chap. 1, “The history of Artificial Intelligence”, pp. 14-29; Chap. 2, “General Artificial Intelligence”, pp. 30-66. Marr, B. (2024). Generative AI in practice: 100+ amazing ways generative artificial intelligence is changing business and society. Wiley. Wolfram, Stephen. (2023). What is GPT Doing…?And Why Does It Matter? Wolfram Media Inc. Reidi, Mark. (2023). A very gentle introduction to large language models without the hype. Medium. Bommasani, R.; & Liang, P. (2021). Reflections on Foundation Models. Retrieved from Stanford HAI, https:/hai.stanford..edu/news/reflections-in-foundation-models. Sarkis, Anthony. (2023). Training Data for Machine Learning: Human Supervision from 王維嘉. (2019). 暗知識：機器認知如何顛覆商業和社會。 中信出版集團. 萬維綱. (2024). 拐點: 站在AI顛覆世界的前夜. 台海出版社。 Narayana, Arvind ;& Kapoor, Sayash. (2024). AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t; and How to Tell the Difference. Princeton University Press.
有關AI的迷思 Narayana, Arvind; & Kapoor, Sayash. (2024). AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference. Princeton University Press.
AI趨勢：現在和未來 Stanford Human-centered Artificial Intelligence. (2024). Artificial Intelligence index Report 2024. Stanford University. 陳昇瑋、溫怡玲. (2019). 人工智慧在台灣： 產業轉型的契機與挑戰. 天下出版社Skidelsky. Robert. (2023). The Machine Age: An Idea, A History, A Warning. Penguin Books. Suleyman, Mustafa. (2023). The Coming Age: AI, Power and the 21st Century's Greatest Dilemma. The Bodley Head.
9/27 AI是智能和知識
本週主題 智能是什麼？如何定義和評估？人/自然和人工智能有何異同？
指定讀物 Thagard, P. (2021). Bots and Beasts: What Makes Machines, Animals, and People Smart? The MIT Press Chap. 2, “Prodigious people”; Chap. 3, “ Marvelous machines”, pp. 21-90. 參考讀物
智能: 一千種定義 Sternberg, R. J., & Wagner, R. K. (Eds.). (1986). Practical intelligence: Nature and origin of competence in the everyday life. Cambridge University Press Lachman, Lachman, & Butterfield. (1979). Cognitive Psychology and Information Processing: An Introduction. Lawrence Erlbaum. Hawkins, Jeff. (2021). A Thousand Brains: A New Theory of Intelligence. Basic Books. Eisner, Elliot. (Ed.). Learning and Teaching the Ways of Knowing. The University of Chicago Press.
智能的歷史 Bennett, Max. (2023). A Brief History of Intelligence: Why the Evolution of the Brain Holds the Key to the Future of AI. Willian Collins. Joshi, Ameet. (2023). Artificial Intelligence and Human Evolution: Contextualizing AI in Human History. Apress. Bates, David W. (2024). An Artificial History of Natural Intelligence: Thinking with Machines from Descartes to the Digital Age. University of Chicago Press.
生物智能 De Waal, Frans. (2017). Are We Smart Enough to Know How Smart Animals Are? W. W. Norton. Godfrey-Smith, Peter. 王惟芬（譯）. (2017). 章魚，心智，演化： 探尋大海及意識的起源. 城邦. Mancuso, Stefano; & Viola, Alessandra. 謝孟宗（譯）. (2024). 植物比你想的聰明： 植物智能的探索之旅. 商周.
延伸智能 Donald，Merlin. (2010). The exographic revolution: Neuropsychologic sequelae. In Malafouris, Lambros, & Renfrew,Colin (Eds.), The Cognitive Life of Things. University of Cambridge, pp. 71-80. Ihde, Don. (1990). Technology and the Lifeworld: From Garden to Earth. Indiana University Press. Egan, Kieran. (1997). The Educated Mind: How Cognitive Tools Shape Our Understanding. Chicago University Press. Vygotsky, L. S. (1978). 蔡敏玲、陳正乾(譯). 社會中的心智. 台北：心理出版社. Grusin, Richard (Ed.). (2015). The Nonhuman Turn. Minneapolis, MI: University of Minnesota Press.
10/4 AI是傳播/溝通/空氣
本週主題： AI可以視為溝通和傳播的夥伴嗎？如果是，在AI時代，傳播是什麼？溝通是什麼？互動的形式和內容和以往有何不同？另一個問題是：AI 會不會慢慢地成了空氣？它常相左右，但你再也感覺不到它的存在？它會以什麼「隱形」的方式存在？會產生什麼影響？
必讀 Esposito, Elena. (2022). Artificial Communication: How Algorithms Produce Social Intelligence? The MIT Press, Chap. 1, “Artificial communication? Algorithms as interaction partners”, pp. 1-19; Chap. 4, “Getting personal. With algorithms”, pp. 47-64. .
參考讀物
AI是媒介 Manovich, Lev. (2013). Software Takes Command. Bloomsbury. Gunkel, David J. (2020). An Introduction to Communication and Artificial Intelligence. Polity. Guzman, Andrea L. & McEwen, Rhonda; & Jones, Steve. (2023). The Sage Handbook of Human-Machine Communication. Sage. Lee, Peter; Goldberg, Carey;l & Kohane, Isaac. (2023). The AI Revolution in Medicine: GPT-4 and Beyond. Pearson.
AI是空氣 Hayles, N. Katherine. (2017). Unthought: The Power of the Cognitive Nonconscious. The University of Chicago Press. McCullough, Malcolm. (2013). Ambient Commons: Attention in the Age of Embodied Information. The MIT Press. Elliot, Anthony. (2019). The Culture of AI: Everyday Life and the Digital Revolution. Routledge. Lindgren, Simon. (2024). Critical Theory of AI. Polity.
貳：AI之後的人文世界：專業、工作和日常生活
10/11 AI社會
當週主題： AI時代，相較於過去，有何顯著不同？出現了那些特別的現象？工作的樣貌為何？
必讀 Fourcade, Marion; & Healy, Kieran. (2024). The Ordinal Society. Cambridge, MI: Harvard University Press, Chap. 1, “The box of delights”, pp. 33-58; Chap. 3, “Classification situations”, pp. 100-131.
參考讀物 AI社會的歷史脈絡 Acemogu, Daroj; & Johnson, Simon. (2023). 林俊宏（譯）. 權力與進步：科技變革與共享繁榮之間的千年辯證. 天下文化. Schinkel，Willem. (2023). Steps to an ecology of algorithms. In Brenneis, Donald; & Strier, Karen B. (Eds.), Annual Review of Anthropology, 52, pp. 171-186. Wiggins, Chris; & Jones, Matthew L. (2023). How Data Happened: A History from the Age of Reason to the Age of Algorithms. W. W. Norton. Pasquinelli, Matteo. (2024). The Eye of the Master: A Social History of Artificial Intelligence. Verso. Popenici, Stefan. (2023). Artificial Intelligence and Learning Futures: Critical Narratives of Technology and Imagination in Higher Education. Routledge.
浮現中的社會 Harari, Yuval Noah. (2024). Nexus: A Brief History of Informaion Networks from the Stone Age to AI. Random House. Nye, David E. (1992). Electrifying America: Social Meanings of a New Technology. The MIT Press. Varoufakis, Yains. 許瑞宋（譯）. (2024). 雲端封建時代. 衛城. Scharre, Paul. 李紹廷（譯）. (2024). AI的無硝煙戰場. 好優文化. Webb, Amy. (2020). 黃庭敏（譯）. AI未來賽局: 中美競合框架下，科技9巨頭建構的未來. 八旗文化. Punchiman, David. (2023). The Handover: How We Gave Control of Our Lives to Corporations, States and AIS. Liveright. Kowalkiewwicz, Marek. (2024). The Economy of Algorithms: AI and the Rise of the Digital Minions. Bristol University Press. Pei, Minxin. (2024). The Sentinel State: Surveillance and the Survival of Dictatorship in China. Harvard University Press. Tau, Byron. (2024). Means of Control: How the Hidden Alliance of Tech and Government Is Creating a New American Surveillance State. Crown. Zuboff, Shoshana. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York: PublicAffairs. Susskind, Jamie. (2022). The Digital Republic: On Freedom and Democracy in the 21st Century. Pegasus. Bradford, Anu. (2023). Digital Empires: The Global Battle to Regulate Technology. Oxford University Press.
工作趨勢 Eloundou, Tyna; Mannning, Sam; Mishkin, Pamela; & Rock, Danniel. (2023). GPTs are GPTs: An early look at the labor market impact potential of Large Language Models. arXiv: 2303. 10130v5 World Economic Forum. (2023). Future of Jobs Report. Geneva. Ford, Martin. (2015). Rise of the Robots: Technology and the Threats of a Jobless Future. Basic Books. Leicht, Kevin T.; & Fennell, Mary L. (2023). Crisis in the Professions: The New Dark Age. Routledge. Susskind, Richard; & Susskind, Daniel. The Future of the Professions: How Technology will Transform the Work of Human Experts. Oxford University Press. 尹惠槙. 黃子玲（譯）. (2023). AI生成時代的工作革命. 台北：天下.
Susskind, Daniel. (2020). A World Without Work: Technology, Automation, and How We should Respond. New York: Henry Holt and Common, Chap. 12, pp. 215-236.
10/18 專業2.0： 傳播
本週主題 目前浮現的趨勢為何？依照科技、社會的邏輯，未來的趨勢（scenario）為何？ 必讀 Marconi, Francesco. (2020). Newsmakers: Artificial Intelligence and the Future of Journalism. Cambridge University Press, Chap. 3, “Workflow: A scalable process for newsroom transformation”, pp. 129-152.
參考讀物
新聞 Diakopoulos, N. (2019). Automating the News: How Algorithms are Rewriting the Media. Cambridge, MA: Harvard University Press. Graefe, Andreas. (2016). Guide to Automated Journalism. Tow Center for Digital. Journalism.http://www.cjr.org/tow_center_reports/guide_to_automated_journalism.php/ Kung, Lucy. (2015). Innovators in Digial News. I. B. Tauris. Nagourney, Adam. (2023). The Times: How the Newspaper of Record Survived Scandal, Scorn, and the Transformation of Journalism. Crown. Val-Alvarez，Marin； & Lainez-Reche，Juanjo. (2023)， Recommedation systems in major media platforms: Design tendencies and purposes. In Garcia-Orosa, Berta; & Perez-Seijo, Sara; & Vizoso, Angel (Eds.), Emerging Practices in the Age of Automated Digital Journalism: Models, Langauges, and Stroytelling. Routledge, pp. 105-114. Carlson, Matt. (2016). Automated journalism: A posthuman future for digital news. In Franklin, Bob; & Eldridge, Scott II (Eds.), The Routledge Companion to Digital Journalism Studies. Routledge. Biswal, Sanrosh Kumar; & Kulkarni, Anand J. (2024). Exploring the Interaction of Artificial Intelligence and Journalism. Routledge. Du, Roselyn. (2023). Algorithmic Audiences in the Age of Artificial Intelligence: Tailored Communication, Information Cocoons, Algorithmic Literacy. And News Literacy. NY: Peter Lang. Pizzo, Antonio; Lombardo, Vincenzo; & Damiano, Rossana. (2024). Interactive Storytelling: A Cross-media Approach to Writing, Producing and Editing with AI. Routledge. Perez, Rafael Perez; & Sharples, Mike. (2023). An Introduction to Narrative Generators: How Computers Create Works of Fiction. Oxford University Press.
書/出版 Hayles, N Katherine. (2021). Postprint: Books and Becoming Computational. Columbia University Press. Sadek, Nadim. (2023). Shimmer, Don’t Shake. How Publishing Can Embrace AI. Forbes Books.
網路 Dixon, Chris. (2024). Read Write Own: Building the Next Era of the Internet. Random House. Tapscott, Alex. (2023). Web3: Charting the Internet’s Next Economic and Cultural Frontier. Harper Business.
閱讀 Hayles, N Katherine. (2012). How We Think: Digital Media and Contemporary Technogenesis. Chicago University Press. Baron, Naomi S. (2021). How We Read Now: Strategic. Choices for Print, Screen, & Audio. Oxford University Press.
聲音 Vlahos, James. (2019). 孔令新（譯）. 聲控未來. 商周. Wilf, Eitan Y. (2023). The Inspiration Machine: Computational Creativity in Poetry and Jazz. The University of Chicago Press. Dengel, Tobias. (2023). The Sound of the Future: The Coming Age of Voice Technology. Public Affairs.
影像 Zylinska, Joanna. The Perception Machine: Our Photographic Future Between the Eye and AI. The MIT Press. Parikka, Jussi. (2024). Operational Images: From the Visual to the Invisual. University of Minnesota Press.
行銷 Kotler, Philip; Kartajaya, Hermawan; & Setiawan, Iwan. (2024). Marketing 6.0: The Future is Immersive. Wiley. Ltifi, Moez. (Ed.). (2024). Advances in Digital Marketing in the Era of Artificial Studies: Case Studies and Data Analysis for Business Problem Solving,. CRC Press. Rodrigues, Caroline. (2023). ChatGPT: Artificial Intelligence as a Strategic Marketing Tool. Sudhir, K.; & Toubia, Olivier. (2023). Artificial Intelligence in Marketing. Emerald Publishing. Seaver, Nick. (2022). Sudhir, K.; & Toubia, Olivier (Eds.). (2022). Artificial Intelligence in Marketing. Emerald Publishing. Seaver, Nick. (2022). Computing Taste: Algorithms and the Makers of Music Recommendation. Chicago University Press. Sudhir, K.; & Toubia, Olivier (Eds.). (2022). Artificial Intelligence in Marketing. Emerald Publishing.
創意
Du Sautoy, Marcus. (2019). The Creativity Code: Art and Innovation in the Age of AI. The Belknap Press of Harvard University Press. Penny, Simon. (2017). Making Sense: Cogniton, Computing, Art, and Embodiment. The MIT Press.
10/25 專業2.0: 教育
本週主題 目前浮現的趨勢為何？ 必讀 Office of Educational Technology. (2023). Artificial Intelligence and the Future of Teaching and Learning, pp.18-36.
參考讀物
教育 2.0 Aoun, Joseph E. (2024). Robot-Proof: Higher Education in the Age of Artificial Intelligence. Revised and Updated Edition. The MIT Press. Khan, Salman. (2024). Brave New Words: How Will AI Will Revolutionize Education (And Why That’s a Good Thing). Viking. Stanley, David J. (2019). Alternative Universities: Speculative Design for Innovation in Higher Education. John Hopkins University. Araya, Daniel; & Marber, Peter. (Eds.). (2023). Augumented Education in the Global Age:Artificial Intelligence and the Future of Learning and Work. Routledge. UNESCO. (2023). Guidance for Generative AI in Education and Research. Aoun, Joseph E. (2018). Robot-proof: Higher Education in the Age of Artificial Intelligence. The MIT Press. Valiant, Leslie. (2024). The Importance of Being Educable: A New Theory of Human Uniqueness. Princeton and Oxford: Princeton University Press. Beane, Matt. (2024). The Skill Code: How to Save Human Ability in an Age of Intelligent Machines. Harper Business.
11/1 專業 2.0. （其他領域）
11/8 AI時代的友情、愛情和修身
當週主題 當前的人際關係如友情、愛情有何特色？AI興起，會有那些趨勢消失？那些更為顯著？會產生什麼突變？如何因應？就個人而言，提供了什麼契機?
必讀 Elliot, Anthony. (2022). Algorithmic Intimacy: The Digital Revolution in Personal Relationships. Polity, Chap. 3, “Relationship tech”, pp. 51-161.
參考讀物 Pugh, Allison. (2024). The Last Human Job: The Work of Connecting in a Disconneted World. Princeton University Press. Gross, Jessica. Are we happy yet? New York Times, August 8, 2024. McStay, Andrew. (2023). Automating Empathy: Decoding Technologies that Guage Intimate Life. Oxford University Press. Coeckelbergh, Mark. (2022). Self-improvement: Technologies of the Soul in the Age of Artificial Intelligence. Columbia University Press. Herzfeld Noreen. (2023). The Artifice of. Intelligence: Divine and Human Relationship in a Robotic Age. Fortress Press. Kisley, Elvyakim. (2022). Relationships 5.0: How AI, VR, and Robots will Reshape Our Emotional Lives. Oxford University Press. Strengers, Yolande; & Kennedy, Jenny. (2023). 智慧妻子：Siri, Alexa與AI 家電也需要女性主義？ 陽明交大出版社. Turkle, Sherry. (2015). Reclaiming Conversation: The Power of Talk in a Digital Age. New York: AloneTogether .
11/15 AI時代的事實和幻象
當週主題 什麼是事實？真實？AI興起，會有那些趨勢消失？那些更為顯著？會產生什麼突變？如何因應？就個人而言，提供了什麼契機?
必讀 Van Der Sloot, Bart. (2024). Regulating the Synthetic Society: Generative AI, Legal Questions and Soceital Challeges. Chap. 3, “Under the hoods: Architecture and design of synthesis”. Pp. 38-58; Chap. 4 “Soceital challenges”, pp. 59-90, HAET,
參考讀物 Meikle, Graham. (2023). Deep Fakes. Polity. Vallor，Shannon. (2024). The AI Mirror: How to Reclaim Our Humanity in An Age of Machine Thinking. Oxford University Press. Bucher, Taina. (2021). 蔡妍伶、羅亞琪（譯）. 被操弄的真實：演算法中隱藏的政治與權力. 商務印書館. Scheirer, Walter J. (2024). A History of Fake Things on the Internet. Stanford University Press. Hutchens, Justin. (2024). The Languge of Deception: Weaponizing Next Generation AI. Hoboken, Wiley.. Wosk, Julie. (2024). Artificial Women: Sex Dolls, Robot Caregivers, and More Facsimile Females. Indiana University Press. Schellmann, Hilke. (2024). The Algorithm: How AI Decides Who Gets Hired, Monitored, Promotecd & Fired & Why We Need to Fight Back Now. Hachette. Chun, Wendy Hui Kyong. (2021). Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition. The MIT Press. Linden, Sander. (2024). Foolproof: Why Misinformation Infects Our Minds and How to Build Immunity. W. W. Norton & Company.
參、如何和AI共處？尋找人文社科的定位
11/22 人異於機器者幾希？尋找人和機器的分野
本週主題 AI拿走了什麼？人還有什麼獨特的能力？作為人文和社科人，有什麼可在AI 時代獨擅勝場的地方？就個人而言，有何啓示？
必讀 鍾蔚文、江靜之、陳百齡. 當人類碰見AI：探尋傳播智能與知識演化的策略. 新聞學研究，159: pp, 1-48. 參考讀物 經典論述 Agre, P. E. (1997). Computation and Human Experience. Cambridge University Press. Dreyfus, H. L. (1992). What Computers Still Can’t Do: A Critique of Artificial Intelligence. The MIT Press. Drefus, Hubert L. ; & Drefus, Stuart E. (1986). The Power of Human Intuition and Expertise in the Era of the Computer. The Free Press.
身體/無體 Brooks, Rodney A. (1997). Intelligence without representations. In Haugeland, John (Ed.), Mind Design II: Philosophy, Psychology, Artificial Intelligence. The MIT Press., pp. 395-420. Adams, Z. & Browning, J. (Eds.). (2016). Giving a damn: Essays in dialogue with John Haugeland. The MIT Press. Chung, Wei-Wen. (2020). Words for the wordless: The tension between science and experience. In Deboos, Salome (Ed.), From Science to Beliefs: Between Practices and Theory. Editions de L’ill, pp. 93-102. Clark, A. (1997). Being there: Putting brain, body, and world together again. The MIT Press. Gallagher, S. (2015). Do we (or our brains) actively represent or enactively engage with the world? In A. K. Engel, K. J. Friston, & D. Kragic, (Eds.), The pragmatic turn: Toward action-oriented views in cognitive science (pp. 285-296). The MIT Press. Johnson, M. (2007). The meaning of the body: Aesthetics of human understanding. The University of Chicago. Pfeifer, R., & Bongard, J. (2006). How the body shapes the way we think? A new view of intelligence. The MIT Press.
情境中認知 Lave, J. (1988). Cognition in practice: Mind, mathematics and culture in everyday life. Cambridge University Press.
人的獨特性 Boyle, James. (2024). The Line: AI and the Future of Personhood. The MIT Press. Marks, Rovert J. II. (2022). Non-computable You: What You Do That Artificial Intelligence Never Will. Discovery Institute Press. O’Gieblyn, Meghan. (2021). God, Human Animal Machine: Technology, Metaphor, and the Search for Meaning. Anchor Books. Christian, Brian. 朱怡康(譯). (2018). 人性較量：我們憑什麼勝過人工智慧? 行路 Mitchel, Melainie. (2020). Artificial Intelligence: A Guide for Thinking Humans. Farrar, Straus, and Giroux. Smith, Brian Cantwell. (2019). The Promise of Artificial Intelligence: Reckoning and Judgment. The MIT Press. Pugh, Allison. (2024). The Last Human Job: The Work of Connecting in a Disconnected World. Princeton University Press. Lawrence, Neil D. (2024). The Atomic Human: What Makes Us Unique in the Age of AI. Public Affairs. Nagi, Ludwig. (2022). Merits and limits of AI: Philosophical reflections on the difference between instrumental rationality and praxis-related hermeneutic reason. In Nagl-Docekal, Herta; & Zacharasiewicz, Waldemar (Eds.), Artificial Intelligence and Human Enhancement: Affirmative and Critical Approaches in the Humanities. De Gruyter, pp. 33-50. Choe, Yoonsuck. (2024). Meaning versus information, prediction versus memory, and question versus answer. In Kozma, Robert; Alippi, Cesare; Choe, Yoonsuck; & Morabito, Francesco Carlo (Eds.), Artificial Intelligence in the Age of Neural Networks and Brain Computing. Academic Press, pp. 61-76. Mubeen, Junaid. (2022). Mathematical Intelligence: A Story of Human Superiority over Machines. Pesagus. Larson, Erik J. (2021). The Myth of Artificial Intelligence: Why Computers Can’t Think the Way We Do. The Belknap Press of Harvard University Press. Cukier, Kenneth; Mayer-Schonberger, Viktor; & de Vericourt, Francis. 林俊宏（譯）. (2021). 超越AI的思考架構. 天下文化. Sunstein, Cass R. (2023). Decisions about Decisions: Political Reason in Ordinary Life. Cambridge University Press, Chap. 9, “Deciding by algorithm” , pp. 159-193. Kasparov, Garry. (2018). 王年愷 (譯). 深度思考. 臉譜. 王銘琬. (2018). 林依璇（譯）. 棋士與AI: ALPHAGO開啓的未來. 大塊文化.
11/29人機協作/共處
本週主題 在未來是人機協作社會的大前提下，人機應如何協作？彼此的角色為何？如何相加大於2? 有那些成功的先例？
必讀 Mollick, Ethan. (2024). Co-intelligence: Living and Working with AI. Portfolio/Penguin.
參考讀物
分散智能 New Perkins, D. N. (1993). Person-plus: A distributed view of thinking and learning. In Salomon, Gavriel (Ed.), Distributed Cogntions: Psychological and Educational Considerations. Cambridge University Press, pp. 88-110. Beynon, M., Nehaniv, C. L., & Dautenhahn, K. (Eds.), (2001). Cognitive technology: instruments of mind. Springer. Clark, A. (2008). Supersizing the mind: Embodiment, action, and cognitive extension. Oxford University Press.
當代相關論述 Lee，Edward Ashford. (2017). Plato and the Nerd: The Creative Partnership of Humans and Technology. The MIT Press. Sanders, N. R., & Wood, J. D. (2020). The Humachine: Humankind, Machines, and the Future of Enterprise. Routledge. Daugherty, R.; & Wilson, H. James. (2018). Human + Machine: Reimaging Work in the Age of AI. Harvard Businessd Review Press. Malone, Thomas W. (2018). Superminds: The Surprising Power of People and Computers Thinking Together. Little, Brown and Company. People in the loop Harding, Venty. (2024). AI Needs You: How We Can Change AI’s Future and Save Our Own. Princeton University Press. Dumouchel, Paul; & Damiano, Luisa. (2017). Living with Robots. Harvard University Press. Gamper., Florian. (2023). The limits of AI decision: Are there. Decisions Artificial Intelligence should not make? In Quintavalla, Alberto; & Temperman, Jeroen (Eds.). (2023). Artificial Intelligence and Human Rights. Oxford University Press, pp. 484-500. Nowotny, Helga. 姚怡平（譯）. 未來的錯覺：人類如何與AI共處？ 中文大學出版社. Gelven, Michael. (2000). The Asking Mystery: A Philosophical Inquiry. The Pennsylvania University Press.
人機協作：個案 Shin, Don Donghee. (2023). Algorithms, Humans, and Interactions: How Do Algorithms Interact with People? Designing Meaningful Experiences. Routreldge. Davenport, T. H. & Miller, S.M. (2022). Working with AI: Real stories of human0machine collaboration. The MIT Press Broussard, Meredith. (2019). Artificial Unintelligence: How Computers Misunderstand the World. The MIT Press. Baron, Naomi S. (2023). Who Wrote this? How AI and the Lure of Efficiency Threatens Human Writing. Stanford University Press. Gupta, Suman; & Tu, Peter H. (2024). The Practical Philosophy of AI-Assistants: An Engineering-Humanities Conversation. World Scientific, Part 2, “Communication”, pp. 79-144. Office of Educational Technology. (2023). Artificial Intelligence and the Future of Teaching and Learning, pp.18-36.
往賽博格邁進 Suchman, L.[u1] (2007). Human-Machine Reconfigurations: Plans and Situated Actions (2nd. Ed.). Cambridge University Press. Clark, Andy. (2003). Natural-born Cyborgs: Minds, Technology, and the Future of Human Intelligence. Oxford University Press. Taylor, Mark. C. (2021). Intervolution: Smart Bodies, Smart Things. Columbia University Press.
12/6 用AI： 解決問題，探索和創造新境界
本週主題 如何用AI? 如何發揮創意，創造更為美好的解決方案？接近未知的世界？ 必讀 甘偵蓉. (2024). 為何應該以人工智慧強化倫理衝突的緊急決策？In林文源、王道維、杜文苓、李建良（主編），公共化AI: 思維、協作與法學的基礎設施. 國立清華大學出版社，pp. 95-136.
參考讀物 AI如何開拓新視野？ Manu, Alexander. (2024). Transcending Imagination: Artificial Intelligence and the Future of Creativity. Chapman and Hall. Bakker, Karen. 楊詠翔（譯）. (2023). 聽見生命之聲：用數位科技打開我們的耳朵與心，深度聆聽自然，重啓與大地的連結. 日出出版. Pentland, Alex. (2018). Honest Signals: How They Shape Our World. The MIT Press. Lobel，Orly. (2022). The Equality Machine: Harnessing Digital Technology for a Brighter, More Inclusive Future. PublicAffairs. Norman, Donald A. (2023). Design for a Better World: Meaningful, Sustainable, Humanity-Centered. The MIT Press. Ferres, Lavista Juan M.; & Weeks, William B. (2024), AI for Good: Applications in Sustainability, Humanitarian Action, and Health. Wiley. Stanley，Kenneth; & Lehman, Joel. (2023). 彭相珍（譯）. 為什麼偉大不能被計劃？對創意、創新和創造的自由探索. 中譯出版社.
AI如何使生活更美好？ Bapna, Ravi; & Ghose, Anindya. (2024). Thrive: Maximizing Well-Being in the Age of AI. The MIT Press. Engelhart, Douglas, C. (2001). Augumenting Human Intellect: A Conceptual Framework. In Araya, Daniel; & Marber, Peter. (2023). Augumented Education in the Global Age: Artificial Intelligence and the Future of Learning and Work. New York and London: Routledge, pp. 13-29. 蘇經天. (2023). 新AI與新人類：學習、認知與生命的進化新路程. 大塊文化. Neuman, W. Russell. (2023). Evolutionary Intelligence: How Technology Will Make Us Smarter. The MIT Press. Finn, Ed. (2018). What Algorithms Want: Imagination in the Age of Computing. Reprint Edition. Cambridge, MI: The MIT Press.
12/13 駕AI： 批判、反思和政策
本週主題 如何對AI本質有深刻的認識？如何形塑以人為本的AI？人文社科的角色為何？
必讀 Pasquale, Frank. (2023). 李姿儀（譯）. 二十一世紀機器人新律. 讀書共和國，Chap1， “緒論”，pp. 21-64; Chap. 7, “反思自動化的政治經濟”，pp. 257-296.
參考讀物 批判 Bonini, Tiziano; & Trere, Emiliano. (2024). Algorithms of Resistence: The Everyday Fight against Platform Power. The MIT Press. Firshmann, Brett; Selinger, Evan. (2018). Re-engineering Humanity. Cambridge University Press. Moini，Bijan. (2024). 陳冠宇（譯）. 演算人生. 堡壘文化. Coeckelbergh, Mark. 鄭楷立 （譯）. AI時代：從政治哲學反思人工智慧的衝擊. 商周出版. Pasquinelli, Matteo. (2024). The Eye of the Master: A Social History of Artificial Intelligence. Verso. Popenici, Stefan. (2023). Artificial Intelligence and Learning Futures: Critical Narratives of Technology and Imagination in Higher Education. Routledge. Moini, Bijan. 李健良（譯）. 拯救我們的自由： 數位時代的起床號. 遠流. Thompson, Erica. (2022). Escape from Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do about It. Basic Books. Checketts, Levi. (2024). Poor Technology: Artificial Intelligence and the Experience of Poverty. Fortress Press. Goodman, Marc. (2016). 林俊宏(譯). 未來的犯罪. 遠足文化. Zuboff, Shoshana. (2019). The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. PublicAffairs.
如何成為一個人？ Lanier, Jaron. (2011). You are Not a Gadget. Vintage Books.Rogers, Carl R. (2023). 鄧伯宸（譯）. 存在之道. 心靈工坊. Gazzaniga, Michael. (2008). Human: The Science Behind What Makes Us Unique. Ecco. Bruner, Jerome. (1990). Acts of Meaning. Harvard University Press. Nowotny, Helga. 姚怡平（譯）. 未來的錯覺：人類如何與AI共處？ 中文大學出版社.
校準 Christian, Brian. (2020). The Alignment Problem: Machine Learning and Human Values. W. W. Norton & Company. Montemayor, Carlos. (2024). The Prospect of a Humanitarian Artificial Intelligence: Agency and Value Alignment. Bloomsbury Academic.
規範和政策 林文源、王道維、杜文苓、李建良（主編）. (2024). 公共化AI: 思維、協作與法學的基礎設施. 國立清華大學出版社. 科技部. (2024). 人工智慧基本法草案. Van Der Sloot, Bart. (2024). Regulating the Synthetic Society: Generative AI, Legal Questions and Societal Challenges. Hart Publishing. Kaplpkiene, Julija. (2024). Law, Human Creativity and Generative Artificial Intelligence: Regulatory Options. Routledge. O’Shea, Lizzie. (2019). 韓翔中（譯）. 數位時代的人權思辨. 商務印書館. Quintavalla, Alberto; & Temperman, Jeroen (Eds.). (2023). Artificial Intelligence and Human Rights. Oxford University Press. Braunschweig, Bertrand; & Ghallab, Malik. (Eds.). (2021). Reflections on Artificial Intelligence for Humanity. Springer. 李建良、林文源. (編). (2022). 人文社會的跨領域探索. 國立清華大學出版社. Khanna, Ro. (2023). Progressive Capitalism: How to Make Tech Work for All of Us. Simon & Schuster.
12/20 未來的智能和生活 本週主題 瞻望5年10年後的未來，AI、社會、生活的形貌為何？
必讀 Kurzweil, Ray. (2024). The Singularity is Nearer: When We Merge with AI. Viking, Chap. 2, “Reinventing intelligence”, pp. 11-74; Chap. 3, “Who am I?”, pp. 75-110.
參考讀物
末來人工智能 Togeluis, Julian. (2024). Artificial General Intelligence. The MIT Press. Sejnowski, Terrence J. (2024). ChatGPT and the Future of AI: The Deep Language Revolution. The MIT Press.
未來思考 Simon, Herbert A. (1996). The Science of the Artificial. Third Edition. Cambridge, MA: The MIT Press. Shneiderman，Ben. (2022). Human-centered AI. Oxford: Oxford University Press. MacAskill, William. (2023). What We Owe the Future. Fisher, Richard. 張毓如（譯）. (2024). 深時遠見. 台北：麥田出版社.
未來想像 Bostrom, Nick. (2024). Deep Utopia: Life and Meaning in a Solved World. IdeapressPublishing. Tegmark, Max. (2018). Life 3.0: Being Human in the Age of Artificial Intelligence. Vintge. Lovelace, James. (2020). Novacene: The Coming Age of Intelligene. . The MIT Press. Davidson, James Dale; & Rees-Mogg, Lord William. (1997). The Sovereign Individual: Mastering the Transition to the Information Age. Touchstone. Lee, Kai-fu; & Chen, Qiufan. (2024). AI 2041: Ten Visions for Our Future. Crown Currency. Roitbolt, Herbert. (2020). Algorithms are not Enough: Creating General Artificial Intelligence. The MIT Press. Pearl, Judea. 甘鍚安（譯）. (2019). 因果革命. 人工智慧的大未來. 行路出版. 金相均. 金學民（譯）. (2023). AI X 人類演化未來報告書. 高寶. Kelly, Kevin. 黃品玟（譯）. (2023). 5000天後的世界. 貓頭鷹出版社.
12/27 AI時代的人文社科專業
本週主題 AI時代人文社科的定位為何？如何和AI共同演化？其未來的面貌為何？
必讀
Smuclerova，Martina； Krail，Lubos； & Drchal，Jan。 (2023). AI life cycle and human rights: Risks and remedies. In Quintavalla, Alberto; & Temperman, Jeroen (Eds.), Artificial Intelligence and Human Rights. Oxford University Press, pp. 16-44.
工作
Houlne, Tim. (2024). The Intelligent Workforce: How Humans & Machines Will Co-Create a Better Future. Forbes Books. Autor, David; Mindell, David Al; & Reynolds, Elisabeth B. (2021). The Work of the Future: Building Better Jobs in an Age of Intelligent Machines. The MIT Press. Pugh, Allison. (2024). The Last Human Job: The Work of Connecting in a Disconnected World. Princeton University Press.Shirky, Clay. (2010). Cognitive Surplus: Creativity and Generosity in a Connected Age. New York: The Penquin Press. Cowen, Tyler. (2015). 洪慧芳（譯）. 再見平庸年代：你在未來經濟裡的位子. 早安財經文化.
研究： 尋找新理論和方法
Kuhn, Thomas S. (1970). The Structure of Scientific Revolutions. Second Edition, Enlarged. University of Chicago Press. Varela, F. J., Thompson, E., & Rosch, E. (2017). The Embodied Mind: Cognitive Science and Human Experience (2nd. Ed.). Cambridge, MA: MIT Press. Winner, Langdon. (2020). The Whale and the Reactor: A Search for Limits in an Age of High Techology. Second Edition. The University of Chicago Press. Frank, Adam; Gleiser, Marcelo;p & Thompson, Evan. (2024). The Blind Spot: Why Science Cannot Ignore Human Experience. The MIT Press. Hesse-Biber，Sharlene Nagy (Eds.). The Handbook of Emergent Technologies in Social Research. Oxford: Oxford University Press. McLevey, John. (2022). Doing Computational Social Science: A Practical Introduction. Los Angeles, CA: Sage.
1/3 – 1/10 期末口頭報告
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一、上課出席率、參與情形 （40%）
二、晤談(20%)
三、期末研究/實務計劃提案 （40%, 其中善用AI, 10%）
詳見每週課程進度