What do Socrates, Herb Simon, and Andrew Gelman have in common? A love of the oral tradition

2026-02-19 · Source: Statistical Modeling, Causal Inference, and Social Science · Field: Education & Learning — Educational Technology (EdTech), Educational Psychology & Learning Sciences, Academic Research & Higher Education · Depth: Fundamental Awareness, short

Summary

This post explores historical and contemporary perspectives on the oral tradition versus written communication and digital tools, drawing parallels between Socrates's skepticism about writing and modern concerns about generative AI. Socrates, as channeled by Plato in "Phaedrus," argued that writing would diminish memory and offer only the "semblance of wisdom." The author notes similar arguments against calculators, personal computers, and the internet. The discussion then highlights Herb Simon's teaching method at Carnegie Mellon in the late 1980s, where he discouraged note-taking to promote attention. Finally, it examines Andrew Gelman's current practice of banning phones and computers in class and delivering public talks without slides, emphasizing a dedication to the oral tradition in teaching and presenting statistics.

Key takeaway

For educators and presenters concerned about student engagement and deep learning, consider adopting methods that prioritize direct attention over external aids. Limiting digital devices and even traditional note-taking, as practiced by Herb Simon and Andrew Gelman, can encourage students to rely more on internal processing and active listening, potentially fostering a more profound understanding of the material.

Key insights

Skepticism towards new communication technologies, from writing to AI, often centers on perceived cognitive decline.

Principles

• Direct attention enhances learning.
• Oral tradition fosters deeper engagement.

In practice

• Consider device bans in learning settings.
• Experiment with slide-free presentations.

Topics

• Oral Tradition
• Cognitive Science
• Pedagogical Methods
• Learning and Memory
• Attention and Distraction

Best for: AI Researcher, Research Scientist, General Interest

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Editorial summary, takeaway, and curation by AIssential. Original article published by Statistical Modeling, Causal Inference, and Social Science.