Research map / Large language models / AI and society
Artificial Intelligence for Future Presidents: Teaching AI Literacy to Everyone
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Describes the design, structure, and first (Spring 2024) offering of a no-prerequisite, no-math, no-programming AI literacy course at Yale for non-technical students, with qualitative and formal course-evaluation results.
Problem
Non-technical students across medicine, law, business, and the arts want a sufficient understanding of AI to be informed users, but existing AI courses assume programming and mathematics prerequisites and few are designed for broad audiences.
Approach
A single-instructor, 24-lecture AI literacy course built on five guiding principles (no prerequisites, literate users not programmers, critical consumers, balanced viewpoint, interdisciplinary relevance), using news-headline discussions, hands-on problem sets with existing tools, audience-tailored video explanations, and skepticism-focused essays rather than math or coding.
Key results
- Formal assessment (54 of 67 enrolled students responded): overall course rating 4.0 vs. 3.6 department and 3.5 division averages.
- Course well-organized item scored 4.1 vs. 3.8 department and 3.7 division averages.
- Feedback-improved-learning item scored 3.6, versus 3.5 department and 3.6 division averages; the authors note they were less successful at providing timely feedback than hoped.
Surprising findings
- Students' predictions about AI often became more optimistic on some topics and more pessimistic on others, rather than uniformly shifting.
Limitations
- Feedback to students was less timely and constructive than intended, per the authors.
- Course evaluations are not a direct measure of learning, and comparison averages are not the most apt reference points.
- Discussion sections were sometimes dominated by students from one professional school, and news-driven lecture ordering sometimes introduced topics before instruction.
Experimental setup
Metrics: university course evaluation scores (1-5 scale) student free-response feedback
Builds on: Physics for Future Presidents
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