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TECH 38 — The US-China AI Race and the Battle for Technological Supremacy

Quarter: Winter
Instructor(s): Nestor Maslej
Duration: 5 weeks
Location: Online
Date(s): Jan 21—Feb 18
Class Recording Available: Yes
Class Meeting Day: Wednesdays
Grade Restriction: NGR only; no credit/letter grade
Class Meeting Time: 6:00—7:30 pm (PT)
Tuition: $355
   
Refund Deadline: Jan 23
 
Unit(s): 0
   
Status: Open
 
Quarter: Winter
Day: Wednesdays
Duration: 5 weeks
Time: 6:00—7:30 pm (PT)
Date(s): Jan 21—Feb 18
Unit(s): 0
Location: Online
 
Tuition: $355
 
Refund Deadline: Jan 23
 
Instructor(s): Nestor Maslej
 
Grade Restriction: NGR only; no credit/letter grade
 
Recording Available: Yes
 
Status: Open
 
As artificial intelligence reshapes the global balance of power, two nations stand at the forefront: the United States and China. This course examines the unfolding geopolitical contest between these AI superpowers, tracing how the race has evolved, the strategies both nations have employed, and the multidimensional nature of the competition, from talent and research to infrastructure, regulation, and military applications.

Students will explore the historical roots of the rivalry, key inflection points in AI development, and how national policy, industrial ecosystems, and global alliances have shaped each country’s approach. Through data-driven analyses and real-world case studies, the course will illuminate the complex interdependencies and tensions that define this critical relationship. We will also look ahead: What are the likely trajectories for the US and China in AI over the next decade? How might this competition influence global norms, innovation, and security? This course is ideal for anyone interested in international affairs, technology policy, or the strategic impact of AI on the global stage.

NESTOR MASLEJ
Research Associate, Institute for Human-Centered Artificial Intelligence, Stanford

Nestor Maslej is a co-author of the "AI Index" at Stanford's Institute for Human-Centered Artificial Intelligence (HAI). He is the author of the forthcoming "International AI Safety Report." He aims to make the complex AI landscape accessible to policymakers, business leaders, and the public. For the past two summers, he has taught “Demystifying AI,” a popular Stanford course on trends in AI. He is now expanding on this expertise as a JD candidate at Stanford Law School, where he focuses on the intersection of technology, corporate governance, and law.

Textbooks for this course:

There are no required textbooks; however, some fee-based online readings may be assigned.