Guardians of the Algorithm: Emerging AI Governance Strategies

This course provides a comprehensive overview of the evolving landscape of artificial intelligence (AI) governance, focusing on policy frameworks, regulatory approaches, and ethical considerations shaping AI's role in society. Participants will explore key governance challenges, such as balancing innovation with accountability, managing risks associated with AI deployment, and addressing global disparities in AI regulation. Through case studies, policy analysis, and expert-led discussions, the course equips participants with practical tools and strategies to navigate AI governance in various sectors, from public policy to private enterprise, ensuring responsible AI development and deployment.

Class dates: February 3, 10, 17, 24; March 3, 10, 17, 31 
Class times: 5:30 - 7:30 pm PT via ZOOM

Instructor: Dr. Brandie Nonnecke, Associate Research Professor, Goldman School of Public Policy and Director, CITRIS Policy Lab, UC Berkeley

COURSE OBJECTIVES

At the end of this course, participants will be capable of:

• Understanding responsible AI governance challenges and opportunities. 
• Applying skills to assess and mitigate risks associated with AI development and deployment.  
• Designing and implementing responsible AI governance strategies in diverse sectors.  
• Advocating for responsible AI policies at organizational and governmental levels. 

COURSE REQUIREMENTS

Participants will complete a group project that brings together key learnings from the course. There are no prerequisites required for this class.

Readings

We will not use a textbook, but you will be expected to read cases, publicly available news articles, reports and journal articles posted to Google Drive.

In-Class Work

Class sessions are designed to foster active participation, collaborative learning, and hands-on application of course concepts. Attendance is fundamental as is active and quality participation in class exercises with the whole class and in small groups. Attendance will be tracked automatically through Zoom. 

Homework

All students will be assigned to a working group. All homework will be completed collaboratively within your group. You will be expected to work on your group project outside of class. 

1. Case Study Analysis and Preparation: Analyze assigned case studies to identify governance challenges, risks, and mitigation strategies. Use these insights to inform your final group project.
2. Final Project: Meet with your team regularly to discuss, draft, and refine your final group project (see deliverables below). 

Deliverables

The key deliverable is the development of either a policy brief or formal submission to a federal or California request for comments (RFC) on an AI governance policy (see this NIST RFC). However, student working groups are encouraged to identify other impactful policy deliverables as a substitution to the policy brief or formal comment submission. For example, production of a podcast episode explaining a pressing AI governance challenge and potential policy strategies or a briefing to members of the California Legislature. (Prof. Nonnecke can help arrange)

COURSE COMPLETION

Registered participants will be in a mixed online cohort that includes students from UC Berkeley and the Goldman School of Public Policy. Non-matriculated participants who successfully meet the course requirements will receive a certificate of completion but are not eligible for academic credit.