Expert Political Judgment: How Good Is It? How Can We Know?

By Gerald F. Gaus. 2007

376 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Political Science and International Relations, Social Sciences & Humanities

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Citations in the corpus

When Will AI Exceed Human Performance? Evidence from AI Experts (2017, background): “Why think AI experts have any ability to foresee AI progress? In the domain of political science, a long-term study found that experts were worse than crude statistical extrapolations at predicting political outcomes (Tetlock, 2005).”
Top Ten Behavioral Biases in Project Management: An Overview (2021, background): “In other words, people are attracted to, and willing to pay for, confidence, more than expertise (Kahneman, 2011, p. 263; Tetlock, 2005).”
Acculturation Strategies and Integrative Complexity (2009, background): “Admittedly, complexity is not always a good thing; in some settings, it has been linked to unwillingness to take risks and make tough decisions (Tetlock, 1992, 2005).”
When overconfidence is revealed to others: Testing the status-enhancement theory of overconfidence (2013, background): “This could provide one explanation for why experts update their judgments less often and more slowly than one might expect (Tetlock, 1998; Tetlock, 2005).”
Compromising Talent: Issues in Identifying and Selecting Talent in Sport (2018, background): “Importantly, research suggests ascribing rigidly to one theory or way of thinking is associated with decreased accuracy in predictions (Tetlock, 2005).”
Why Propensity Scores Should Not Be Used for Matching (2019, background): “To make matters worse, subject matter experts overestimate their ability to control their personal biases more than nonexperts, and more prominent experts are the most overconfident (Tetlock, 2005).”
Efficiently encoding and modeling subjective probability distributions for quantitative variables. (2016, methodology): “…in human forecasts that otherwise have random components in them (Dawes et al., 1989; Goldberg, 1970) but also minimizes close-call counterfactuals (Tetlock, 2005) and provides decision makers with a tool for extracting probability estimates associated with any values or dates of interest—not…”
Defining Misinformation and Understanding its Bounded Nature: Using Expertise and Evidence for Describing Misinformation (2020, background): “Notably, these bases echo Tetlock (2005)’s definition of expert judgment as dependent on the correspondence between the judgment and reality and the coherence of the rationale for making the judgment.”
Elo Ratings and the Sports Model: A Neglected Topic in Applied Probability? (2017, background): “The fascinating book (Tetlock, 2006) describes this basic mathematics in the course of detailed study of the accuracy of “expert judgement” in geopolitics.”