Trained as a social psychologist, Leiden University social psychologist Carsten de Dreu uses behavioral science, history, economics, archaeology, primatology and biology, among other disciplines to study the basis of conflict and cooperation among humans.
As a math professor who teaches students to use data to make informed decisions, I am familiar with common mistakes people make when dealing with numbers. The Dunning-Kruger effect is the idea that the least skilled people overestimate their abilities more than anyone else. This sounds convincing on the surface and makes for excellent comedy. But in a recent paper, my colleagues and I suggest that the mathematical approach used to show this effect may be incorrect.
Machine learning tools like chatbots and virtual assistants can emulate the work of psychologists and psychotherapists and are even helping to address people’s basic therapeutic needs.
The paper “The Nature and Organization of Individual Differences in Executive Functions: Four General Conclusions,” published in Current Directions in Psychological Science in 2012, is a recipient of Sage’s fourth annual 10-Year Impact Awards. The paper has been cited 2,172 times.
We are “less aware of the reasons for our choices than we think we are,” Petter Johansson and his partner Lars Hall have determined, and reasoning, as we call it, is often conducted post hoc.
Sales promotions usually list the discount before the restriction. But is this “good news then bad news” structure really the best practice?
Social psychologists David Dunning of the University of Michigan and Justin Kruger of New York University, whose research captured the public imagination by suggesting that unskilled people often overrate their own abilities, have received the 2023 University of Louisville Grawemeyer Award in Psychology.
The Dunning-Kruger Effect, explains David Dunning, comes when “people who are incompetent or unskilled or not expert in a field lack expertise to recognize that they lack expertise. So they come to conclusions, decisions, opinions that they think are just fine when they’re, well, wrong.”
Drawing on discussions with academics who have oriented their work around public engagement and social impact, Daniel Pearson suggests these academics present an opportunity to rethink the existing structures of reward and recognition in higher education. “We are, as a species, addicted to story,” says English professor Jonathan Gottschall in his book, The Storytelling Animal. “Even when the […] Tom Burns, whose combination of play — and plays – with teaching in higher education added a light, collaborative and engaging model […] A 2024 report by the National Academies explores the latest advances in artificial intelligence (AI) technology and their potential effects on economic productivity, job stability, and income inequality. It also highlights key research opportunities and data needs to help workers and policymakers adapt to the evolving AI landscape. In this post, co-authors Frank T. Piller, Tucker J. Marion, and Mahdi Srour reflect on the inspiration behind their research article, “Generative […] During the final stages of editing the proofs for Artificial Intelligence and Work: Transforming Work, Organizations, and Society in an Age of Insecurity, […]
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Impact
Young Scholars Can’t Take the Field in Game of Academic Metrics
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Canada’s Storytellers Challenge Seeks Compelling Narratives About Student Research
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Tom Burns, 1959-2024: A Pioneer in Learning Development
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Innovation
NAS Report Examines Nexus of AI and Workplace
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When Do You Need to Trust a GenAI’s Input to Your Innovation Process?
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The Authors of ‘Artificial Intelligence and Work’ on Future Risk
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