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  • 2023
  • Working Paper

How People Use Statistics
By: Pedro Bordalo, John J. Conlon, Nicola Gennaioli, Spencer Yongwook Kwon and Andrei Shleifer
We document two new facts about the distributions of answers in famous statistical problems: they are i) multi-modal and ii) unstable with respect to irrelevant changes in the problem. We offer a model in which, when solving a problem, people represent each hypothesis...  View Details
Keywords: Decision Choices and Conditions; Microeconomics; Mathematical Methods; Behavioral Finance
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  • 2023
  • Working Paper

Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs
By: Jacqueline N. Lane, Karim R. Lakhani and Roberto Fernandez
Competence development in digital technologies, analytics, and artificial intelligence is increasingly important to all types of organizations and their workforce. Universities and corporations are investing heavily in developing training programs, at all tenure...  View Details
Keywords: STEM; Selection and Staffing; Gender; Prejudice and Bias; Training; Equality and Inequality; Competency and Skills
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  • 2022
  • Working Paper

Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence
By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
Even if algorithms make better predictions than humans on average, humans may sometimes have “private” information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by...  View Details
Keywords: Cognitive Biases; Algorithm Transparency; Forecasting and Prediction; Behavior; AI and Machine Learning; Analytics and Data Science; Cognition and Thinking
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  • 2022
  • Chapter

Redirecting Rawlsian Reasoning Toward the Greater Good
By: Joshua D. Greene, Karen Huang and Max Bazerman
In A Theory of Justice, John Rawls employed the ‘veil of Ignorance’ as a moral reasoning device designed to promote impartial thinking. By imagining the choices of decision-makers who are blind to biasing information, one might see more clearly the organizing...  View Details
Keywords: Moral Sensibility; Judgments; Prejudice and Bias; Decision Making
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  • May 2022 (Revised April 2023)
  • Case

LOOP: Driving Change in Auto Insurance Pricing
By: Elie Ofek and Alicia Dadlani
John Henry and Carey Anne Nadeau, co-founders and co-CEOs of LOOP, an insurtech startup based in Austin, Texas, were on a mission to modernize the archaic $250 billion automobile insurance market. They sought to create equitably priced insurance by eliminating pricing...  View Details
Keywords: AI and Machine Learning; Technological Innovation; Equality and Inequality; Prejudice and Bias; Growth and Development Strategy; Customer Relationship Management; Price; Insurance Industry; Financial Services Industry
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  • October 2021
  • Article

Changing Gambling Behavior through Experiential Learning
By: Shawn A. Cole, Martin Abel and Bilal Zia
This paper tests experiential learning as a debiasing tool to reduce gambling in South Africa, through a randomized field experiment. The study implements a simple, interactive game that simulates the odds of winning the national lottery through dice rolling....  View Details
Keywords: Debiasing; Experiential Learning; Behavioral Economics; Financial Education; Learning; Games, Gaming, and Gambling; Behavior; Decision Making
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  • September 2021
  • Article

Gender Stereotypes in Deliberation and Team Decisions
By: Katherine B. Coffman, Clio Bryant Flikkema and Olga Shurchkov
We explore how groups deliberate and decide on ideas in an experiment with communication. We find that gender biases play a significant role in which group members are chosen to answer on behalf of the group. Conditional on the quality of their ideas, individuals are...  View Details
Keywords: Gender Differences; Stereotypes; Teams; Economic Experiments; Gender; Prejudice and Bias; Groups and Teams; Perception
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  • 2021
  • Working Paper

Cognitive Biases: Mistakes or Missing Stakes?
By: Benjamin Enke, Uri Gneezy, Brian Hall, David Martin, Vadim Nelidov, Theo Offerman and Jeroen van de Ven
Despite decades of research on heuristics and biases, empirical evidence on the effect of large incentives—as present in relevant economic decisions—on cognitive biases is scant. This paper tests the effect of incentives on four widely documented biases: base rate...  View Details
Keywords: Cognitive Biases; Incentives; Motivation and Incentives; Decision Making; Performance
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  • March 2021 (Revised September 2021)
  • Case

Applied: Using Behavioral Science to Debias Hiring
By: Ashley Whillans and Jeff Polzer
The UK government’s Behavioural Insights Team (BIT) needed to hire a new associate and were trying to increase the diversity of their job candidates. This decision was based on academic research showing that recruiters and managers often fell into common traps like...  View Details
Keywords: Hiring; Bias; Behavioral Science; Selection and Staffing; Diversity; Prejudice and Bias; Information Technology; Recruitment
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  • March 2021
  • Article

Bayesian Signatures of Confidence and Central Tendency in Perceptual Judgment
By: Yang Xiang, Thomas Graeber, Benjamin Enke and Samuel Gershman
This paper theoretically and empirically investigates the role of Bayesian noisy cognition in perceptual judgment, focusing on the central tendency effect: the well-known empirical regularity that perceptual judgments are biased towards the center of the...  View Details
Keywords: Visual Perception; Bayesian Modeling; Perception; Judgments
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  • January 2021
  • Article

Veil-of-Ignorance Reasoning Mitigates Self-Serving Bias in Resource Allocation During the COVID-19 Crisis
By: Karen Huang, Regan Bernhard, Netta Barak-Corren, Max Bazerman and Joshua D. Greene
The COVID-19 crisis has forced healthcare professionals to make tragic decisions concerning which patients to save. Furthermore, the COVID-19 crisis has foregrounded the influence of self-serving bias in debates on how to allocate scarce resources. A utilitarian...  View Details
Keywords: Self-serving Bias; Procedural Justice; Bioethics; COVID-19; Fairness; Health Pandemics; Resource Allocation; Decision Making
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  • Article

Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses
By: Kaivalya Rawal and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision-making, there has been a lot of interest in developing algorithms which can provide recourses to affected individuals. While developing such tools is important, it is even more critical to...  View Details
Keywords: Predictive Models; Decision Making; Framework; Mathematical Methods
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  • October 2020 (Revised May 2023)
  • Exercise

SenseAim Technologies: Pricing to Win
By: Elie Ofek, Eyal Biyalogorsky, Marco Bertini and Oded Koenigsberg
This exercise serves to help students understand the proper role and use of costs in a firm’s pricing decisions. The exercise is designed such that the learning of students evolves across a classroom session, starting from understanding which costs are relevant when...  View Details
Keywords: Pricing Decisions; Cost; Information; Price; Decision Making
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  • August 2020 (Revised December 2020)
  • Background Note

A Note on Ethical Analysis
By: Nien-hê Hsieh
To engage in ethical analysis is to answer such questions as “What is the right thing to do?” “What does it mean to be a good person?” “How should I live my life?” Ethical analysis, on its own, is often not adequate for doing the right thing or being a good...  View Details
Keywords: Ethics; Framework; Decision Making; Prejudice and Bias
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  • June 2020
  • Article

How Scheduling Can Bias Quality Assessment: Evidence from Food Safety Inspections
By: Maria Ibanez and Michael W. Toffel
Accuracy and consistency are critical for inspections to be an effective, fair, and useful tool for assessing risks, quality, and suppliers—and for making decisions based on those assessments. We examine how inspector schedules could introduce bias that erodes...  View Details
Keywords: Assessment; Bias; Inspection; Scheduling; Econometric Analysis; Empirical Research; Regulation; Health; Food; Safety; Quality; Performance Consistency; Governing Rules, Regulations, and Reforms
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  • November 26, 2019
  • Article

Veil-of-Ignorance Reasoning Favors the Greater Good
By: Karen Huang, Joshua D. Greene and Max Bazerman
The “veil of ignorance” is a moral reasoning device designed to promote impartial decision-making by denying decision-makers access to potentially biasing information about who will benefit most or least from the available options. Veil-of-ignorance reasoning was...  View Details
Keywords: Policy Making; Procedural Justice; Ethics; Decision Making; Policy; Fairness
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  • November–December 2019
  • Article

Making Sense of Soft Information: Interpretation Bias and Loan Quality
By: Dennis Campbell, Maria Loumioti and Regina Wittenberg Moerman
We explore whether behavioral biases impede the effective processing and interpretation of soft information in private lending. Taking advantage of the internal reporting system of a large federal credit union, we delineate three important biases likely to affect the...  View Details
Keywords: Soft Information; Lending; Banking; Information; Financing and Loans; Banks and Banking; Decision Making
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  • 2019
  • Working Paper

Veil-of-Ignorance Reasoning Favors the Greater Good
By: Karen Huang, Joshua D. Greene and Max Bazerman
The “veil of ignorance” is a moral reasoning device designed to promote impartial decision-making by denying decision-makers access to potentially biasing information about who will benefit most or least from the available options. Veil-of-ignorance reasoning was...  View Details
Keywords: Policy-making; Procedural Justice; Ethics; Decision Making; Fairness
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  • 2010
  • Article

Fretting About Modest Risks Is a Mistake
By: Matthew Rabin and Max Bazerman
Managers often engage in risk-averse behavior, and economists, decision analysts, and managers treat risk aversion as a preference. In many cases, acting in a risk-averse manner is a mistake, but managers can correct this mistake with greater reflection. This article...  View Details
Keywords: Decision Biases; Risk Management; Risk and Uncertainty; Decision Making
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  • 2019
  • Working Paper

Reflexivity in Credit Markets
By: Robin Greenwood, Samuel G. Hanson and Lawrence J. Jin
Reflexivity is the idea that investors' biased beliefs affect market outcomes, and that market outcomes in turn affect investors' beliefs. We develop a behavioral model of the credit cycle featuring such a two-way feedback loop. In our model, investors form beliefs...  View Details
Keywords: Reflexivity; Attitudes; Financial Markets; Forecasting and Prediction; Investment; Credit
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