7.6A AI - Introduction
Class Outline AI History Machine Learning and AI Autonomous Systems Super Intelligence Applications
Class Description (AI for Everybody by Andrew Ng; short course(6 hours) from Coursera) What is AI? Building AI Projects Building AI in Your Company AI and Society
What is AI?
AI Problem Solving
Real World AI
Machine Learning
Neural Networks
Implications
Class Description (Kilnam Chon, AI: Past and Present; ppt) AI Introduction: History AI Economy and Industry Super Intelligence
Complex Systems and Narrow AI
AI Governance
Future of AI References
Class Video (UC Berkeley CS 188; First Class as AI Introduction) Lecture Pool: Kilnam Chon/KAIST
Lecture Candidates: Jaeseung Jeong/KAIST, Joanna Bryson/Bath, Yudho Giri Sucahyu/Indonesia
7.6B AI Governance
Class Outline AI History AI Principles AI Policies Governance Algorithm Accountability and Explainability Ethics Safety and Security Impact: Society and Economy General AI and Its Implication
Class Description (Danit Gal)
This lecture on AI governance will be divided into three sections. The first will provide an overview of the ethical, inclusive, and societal aspects of AI. We will examine key documents such as the IEEE’s Ethically Aligned Design v.2, the Asilomar Principles, and the AI Now report. The lecturer will also offer first-hand insights from relevant conferences on these topics. The second will discuss the economic and regulatory aspects of AI. We will examine government regulations, policies, and standards from around the world and key documents such as the AI Index, reports from global firms, and other relevant documents. The third will examine the technical aspects of AI governance, including safety, robustness, and security. We will examine outputs and insights from leading institutions and thinkers in the field, and review existing best practices in the field. Each section will provide a brief overview of existing materials to inform participants of ongoing discourses in these fields, and offer questions for discussion. The following discussion will be themed around the relevance and application of these global discourses to Asia, with an emphasis on East and Southeast Asia.
Class Description (Sunyoung Yang) Applicability of Existing Global Governance Models for the Formation of Global AI Governance Recent innovations in Artificial Intelligence (AI) have been accelerated by computing technologies and big data. AI can be defined as “activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment” (Nilsson 2010). AI is both creating new frontiers for social experience, public infrastructure, and industrial innovation, but it also threatens to accelerate automation, social alienation, and global inequities. The impact of AI has worldwide implications, which calls for globally collaborative efforts to develop a joint governance of AI, as well as the need to allow diverse groups to contribute to the process. New regulations for self-driving cars and aircrafts, imposition of taxes for robot labor, and banning of autonomous weapons are examples where AI governance is needed. This lecture intends to articulate the components required to develop a global governance of AI based on the model of multi-stakeholder processes (Hemmati 2002). This lecture will determine what factors will be pertinent to AI governance from existing examples of global governance, including Internet Governance, the Intergovernmental Panel on Climate Change, more broadly the UN Environment, and global governance of nuclear technology. This lecture will then synthesize the existing examples of global governance and analyze the applicability of those examples for AI governance, examining Internet governance and AI governance within the broader context of digital governance.
Class Description (Thematic Pillars by Partnership of AI) Safety-critical AI Fair, Transparent and Accountable AI Collaboration between People and AI AI, Labor and Economy Social and Societal Influences of AI AI and Social Good
Class Description (Kilnam Chon) Internet Governance and Digital Governance Is Internet governance scheme applicable to AI governance? AI History Narrow AI and General AI Areas of AI Governance Principles, Policy, Social and Economic Impacts Algorithm, Accountability and Explainability, Ethics, Security, Safety, Data General AI, Existential Risk
Lecture Pool: Danit Gal, Woodrow Herzog
Lecture Candidates: Kilnam Chon, Sunyoung Yang, Ema Arisa, Alan Dafoe
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AI Conferences
AAAI Annual Conference, since 1980s ACM/AAAI AI, Ethics and Society, since 2018 (and AAAI Workshop in 2016 and 2017) EU European AI Alliance, Futurium (many workshops and seminars) FLI Beneficial AI, 2015, 2017, 2019 IJCAI International Joint Conference of AI (2019-08-10~16, Macao) ITU AI for Good, since 2017 OECD AI: Intelligent Machines and Smart Policies, 2017 SGAI International Conference on AI, since 1980s SNU AI Conference: Governance and Accountability, 2017~ Tokyo University AI and Society, 2017 World Gov Sum Global Governance of AI and World Government Summit, Dubai, February 2019. [Summary Report]
References
Acceptable Intelligence with Responsibility (AIR) AI4ALL AAAI AIDC, Opening; Breakthrough Theory, Intel AI, 2018. AI and Inclusion, Rio de Janeiro, 2017.6 and 2017.11. AI Democratization AAAI Workshop on AI, Ethics and Society. [2016], [2017] AI Today, Seoul National University, Seoul, 2018.8.24. Isaac Asimov, Three laws of robots.AIsaturdays. (nepal) ASU Origins Project, AI: Who is in control; Part 1, Part 2, 2017 Gnneieve Bell, Beyond Trolly Problem: Ethics in AI, AIDC 2018, Intel, 2018.6. Nick Bostrom, Superintelligence, 2014. AI will be the greatest revolution in the history, 2017. [youtube] Kilnam Chon, AI Governance, 2019. [ppt], [article] CMU, Carnegie Mellon is set to offer the first undergrad AI degree in the US, 2018.5. Columbia University, Introduction to AI, edX. Alan Dafoe, AI Governance: Research Agenda, Center for Governance on AI, FHI, Oxford University, 2018. DARPA, Explainable Artificial Intelligence (XAI) by David Gunning, 2018. DARPA, DARPA Perspective on AI, 2018. EU Agenda 2030. European Parliament, Report with Recommendation to Commission on Civil Law Rules on Robotics, 2017. Edward Felton, AI and Explainability: A computer science perspective, 2018. Forbes, This AI Can Recognize Anger, Awe, Desire, Fear, Hate, Grief, Love ... By How You Touch Your Phone, 2018.8. G7 (ICT) Ministry Meeting, 2016, 2017. Stephen Hawking, Brief ansers to the big questions, 2018. (Chapter 9. Will AI outsmart us?) Demis Hassabis, Power of Self-learning systems,CBMM, 2019. Helsinki University, Elements of AI, 2018. International Conference on Love & Sex with Robots, 2018. Japanese Government (Soumusho), Conference Toward AI Network Society. (also AI R&D Principles), 2017. Japanese Government (METI), 2016 White Paper on Information and Communications. [ppt] [article] David Gunning, Explainable AI (XAI), Darpa, Proceedings of AI Today, Seoul, 2018.8.24. Medium, “Brain signals translated into speech using artificial intelligence” published by Giorgia Guglielmi, 2019.5. Microsoft, A developer's guide to AI applications, Microsoft Azure, 2018.8. MIT Media Lab, AI & Governance Symposium, 2016. MIT Media Lab, AI Ethics and Governance Projects. MIT Technology Review, AI is a new space race, and US needs Sputnik moment, 2018.7. MIT, Artificial General Intelligence, MIT 6.S099 (by Lex Fridman), 2018. Andrew Ng, AI for Everybody, Coursera, 2019. NHK, Global Agenda: AI * Ethics, 2017.12. [selner vrubgshirdm frabcius cgikketm bart selman, kanaya/araya] OECD, Digital Economy Outlook, 2017. ["ensuring transparency and oversight of AI-powered decisions that impact people," p.305 for AI governance. A. Penel,
Ethics, the new frontier of technology, Medium, 2019.4.23. Mag Tegmark, Life 3.0. [video] Clive Thompson, Coders, 2019.5. UC Berkeley, Introduction to AI, CS188. [First class as Introduction to AI in 85 minutes] UK, Intelligent future? - Maximizing the opportunities and minimizing the risk of AI in UK, 2016.10.25. Amy Webb, The Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity, 2019. [swsx] Wired, How to teach AI some common sense, 2018.11.
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