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d-28328House OversightOther

Personal reflections on academic influences and modeling approaches

The passage is a memoir-style description of the author's academic background and theoretical interests, containing no specific allegations, names, transactions, or actionable leads involving powerful Discusses interdisciplinary studies at Stanford, including economics, psychology, and game theory. Mentions scholars Amos Tversky, Daniel Kahneman, James G. March, and Seymour Martin Lipset. Critique

Date
November 11, 2025
Source
House Oversight
Reference
House Oversight #028034
Pages
1
Persons
0
Integrity
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Summary

The passage is a memoir-style description of the author's academic background and theoretical interests, containing no specific allegations, names, transactions, or actionable leads involving powerful Discusses interdisciplinary studies at Stanford, including economics, psychology, and game theory. Mentions scholars Amos Tversky, Daniel Kahneman, James G. March, and Seymour Martin Lipset. Critique

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academiabehavioral-economicspersonal-memoirhouse-oversightmethodology-critique

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organizations” such as private companies or government departments. Or the armed forces of Israel. The theorists at Stanford were leaders in the field. But from the start, I was drawn to other disciplines as well: business, economics, political science, history, sociology, psychology. I studied game theory at the business school, and the evolution of political systems under the sociologist Seymour Martin Lipset. I also went to lectures by James G. March, on how psychological, social and other factors influenced decision-making. I particularly enjoyed learning from Professor Amos Tversky. Born in Haifa, he was half of an academic partnership with the psychologist Daniel Kahneman, who was also Israeli. They were investigating the effect of human bias and other subjective factors on how we perceive reality, and thus make decisions. Tversky’s work especially fascinated me, because it questioned a basic assumption in the kind of predictive formulas my own department was advancing: that we make choices rationally, calculating the outcomes of competing alternatives. Tversky had found that the human brain didn’t always work that way. For choices with a fairly obvious outcome — 90 percent of cases, say — the assumption did hold. But at the margins, the brain didn’t, or couldn’t, always gauge the implications of a decision accurately. A couple of decades later, he would also show that an individual’s choice could vary significantly depending on the way the options were presented. These behavioural and psychological approaches were at odds with what was being taught in my home faculty. Its prevailing orthodoxy was that by using specifically designed interview techniques, alongside mathematical modelling of the predicted outcomes, we could isolate the effect of human agency on how, and what, decisions were made. Yet the wider my studies had ranged, the more sceptical I became that the complexities of human decision-making could be accommodated by such models. I also saw problems in the methodology we were using. Since it was based partly on interviews with participants in the decision-making process, it seemed to me that this introduced a subjective element into our ostensibly objective conclusions. My department wasn’t enamored with my views on our modeling approach. But one of the things I most valued about my time in Stanford was that, far from discouraging my excursions into other departments, my professors combined a confidence in their own approach with a genuine open-mindedness to other ideas: the hallmark of true intellectuals, and of great universities. I got something else from my studies at Stanford, although I didn’t speak about it at the time, not even to Nava. I became aware that I had a particular 186

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