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
Class Description (Helsinki University, Elements of AI)
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
please contact APSIG-sec@googlegroups.com if you want to subscribe to APSIG-AI mailint list.
check AI Governance - APSIG.asia webpage for further information.
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
KAIST Taming AI, 2018
KIAS AI, Ethics, Governance, 2018
NeurIPS Montreal, 2018.12.2-8
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
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AI4ALL
AAAI
AI and Society, Tokyo, 2017.10.
AI Democratization
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Woodraw Hartzog, Ethical and accountable AI, 2018.
Demis Hassabis, Power of Self-learning systems,CBMM, 2019.
Geoffrey Hinton, Andrew Ng's Interview of Geoggrey Hinton, 2018. [in youtube]
Helsinki University, Elements of AI, 2018.
HITE, "Human and AI - Co-development Symposium", 2018.3.14. [in Japanese]
IBM, PowerAI Vision overview, 2019.
IEEE Spectrum, Untold history of AI(6 parts), 2019.
Indian Government, Report of Task Force on Artificial Intelligence | Department of Industrial Policy & Promotion | MoCI | GoI, 2018.
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