Problem of AI: Emerg Gov Flash

3 Credits · Level: Graduate, Undergraduate

Artificial intelligence and new digital technologies are transforming society in profound ways. The same technologies advancing medicine, finance, and every industrial sector are creating generational disruptions to everything from work, the environment, and the creative economy to family life, the wellbeing of children, and what it means to be human in the age of AI. Difficult governance questions follow. Who owns creative works and culture? How do we keep humans in the loop of machine decisions with consequences for national security, privacy, speech, and human safety? Who is responsible when autonomous technologies cause harm and how can the most vulnerable members of society be protected? How can discriminatory bias be identified and mitigated in opaque technologies hidden from view? How can systems authenticate whether someone is a live human or whether a video or image is real or a deepfake? How should cyber governance evolve when hacks are no longer carried out by humans? What regulatory structures are necessary to promote innovation and productivity while addressing these societal concerns? How these many questions unfold will shape humanity for decades. Yet, regulatory frameworks around agentic AI, companion robots, chatbots, and nearly every other manifestation of artificial intelligence are lagging behind technological change. Students in this course will confront the major AI governance flashpoints of our time and analyze emerging frameworks of technology governance rising to address these concerns. Learning objectives include: 1. Develop Sociotechnical Thinking. Through real-life case studies in AI and theoretical frameworks from Science & Technology Studies (STS) and global technology governance, understand the societal implications of AI systems, including: chatbots and companion robots; chips and compute hardware; generative AI and Large Language Models (LLMs); AI cloud infrastructure, data centers, and hyperscalers; cybersecurity systems; AI applications and AI agents; and supporting energy systems. 2. Understand Multistakeholder Points of Power in AI Governance. Learn how technology governance involves distributed levers of control across technical design and standardization, the policymaking role of private industry, algorithmic ordering, traditional regulation, global technical coordination, and arrangements of digital infrastructure as arrangements of power. 3. Analyze Real-World AI Governance Flashpoints. Become well-versed in contemporary AI governance debates, identifying what is at stake, explaining alternatives, and articulating stakeholder positions. Flashpoint examples include: proof of liveness; cybersecurity and hacks without humans; governance of agentic AI; inauthentic behavior, information integrity and deepfakes; the wellbeing of children; the future of work; governance of companion robots; algorithmic bias and discrimination; national security and human safety; and data governance and privacy. 4. Develop Evidence-Based, Ethical Stances. Students will have the opportunity to stake out evidence-based, personal, ethical stances on the major AI governance debates of the contemporary era, making feasible and practicable recommendations for a technological future for the good of humanity.