Lecture Candidates: Jaeseung Jeong, Joanna Bryson/Bath

7.6B AI Governance 

  Class Outline 

   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