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Article

Unconscious Bias Training That Works

By: Francesca Gino and Katherine Coffman

To become more diverse, equitable, and inclusive, many companies have turned to unconscious bias (UB) training. By raising awareness of the mental shortcuts that lead to snap judgments—often based on race and gender—about people’s talents or character, it strives to... View Details

Keywords: Implicit Bias; Social Integration; Empathy; Prejudice and Bias; Employees; Training; Attitudes; Behavior; Organizational Change and Adaptation

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May 2014
Article

Bias in Reduced-form Estimates of Pass-through

By: Alexander MacKay, Nathan H. Miller, Marc Remer and Gloria Sheu

We show that, in general, consistent estimates of cost pass-through are not obtained from reduced-form regressions of price on cost. We derive a formal approximation for the bias that arises even under standard orthogonality conditions. We provide guidance on the... View Details

Keywords: Pass-through; Reduced-form Aggression; Bias

Article

Present Bias Causes and Then Dissipates Auto-enrollment Savings Effects

By: John Beshears, James J. Choi, David Laibson and Peter Maxted

Present bias causes procrastination, which leads households to stick with auto-enrollment defaults. However, present bias also engenders overconsumption. Separation from each employer generates a rollover of 401(k) balances to an individual retirement account (IRA)... View Details

Keywords: Present Bias; Procrastination; Personal Finance; Decision Making; Social Psychology; Retirement

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Article

Mitigating Bias in Adaptive Data Gathering via Differential Privacy

By: Seth Neel and Aaron Leon Roth

Data that is gathered adaptively—via bandit algorithms, for example—exhibits bias. This is true both when gathering simple numeric valued data—the empirical means kept track of by stochastic bandit algorithms are biased downwards—and when gathering more complicated... View Details

Keywords: Bandit Algorithms; Bias; Analytics and Data Science; Mathematical Methods; Theory

June 2013
Article

Opting-in: Participation Bias in Economic Experiments

By: Robert Slonim, Carmen Wang, Ellen Garbarino and Danielle Merrett

Assuming individuals rationally decide whether to participate or not to participate in lab experiments, we hypothesize several non-representative biases in the characteristics of lab participants. We test the hypotheses by first collecting survey and experimental data... View Details

Keywords: Participation Bias; Laboratory Experiments; Prejudice and Bias; Research

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September 2020 (Revised July 2022)
Exercise

Artea (D): Discrimination through Algorithmic Bias in Targeting

By: Eva Ascarza and Ayelet Israeli

This collection of exercises aims to teach students about 1)Targeting Policies; and 2)Algorithmic bias in marketing—implications, causes, and possible solutions. Part (A) focuses on A/B testing analysis and targeting. Parts (B),(C),(D) Introduce algorithmic bias. The... View Details

Keywords: Targeted Advertising; Discrimination; Algorithmic Data; Bias; Advertising; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Analytics and Data Science; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States

August 2020
Article

Machine Learning and Human Capital Complementarities: Experimental Evidence on Bias Mitigation

By: Prithwiraj Choudhury, Evan Starr and Rajshree Agarwal

The use of machine learning (ML) for productivity in the knowledge economy requires considerations of important biases that may arise from ML predictions. We define a new source of bias related to incompleteness in real time inputs, which may result from strategic... View Details

Keywords: Machine Learning; Bias; Human Capital; Management; Strategy

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September 2020 (Revised July 2022)
Technical Note

Algorithmic Bias in Marketing

By: Ayelet Israeli and Eva Ascarza

This note focuses on algorithmic bias in marketing. First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P’s of marketing – promotion, price, place and product—characterizing the marketing... View Details

17 Nov 2013
News

Time to Tackle Workplace Gender Bias

Keywords: Nohria, Nitin; gender bias; women in business; Educational Services

Article

A Fair Game? Racial Bias and Repeated Interaction between NBA Coaches and Players

By: Letian Zhang

There is strong evidence of racial bias in organizations but little understanding of how it changes with repeated interaction. This study proposes that repeated interaction has the potential to reduce racial bias, but its moderating effects are limited to the treatment... View Details

Keywords: Discrimination; Bias; Interaction; NBA; Prejudice and Bias; Race; Equality and Inequality; Interpersonal Communication; Sports

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September 2020 (Revised July 2022)
Teaching Note

Algorithmic Bias in Marketing

By: Ayelet Israeli and Eva Ascarza

Teaching Note for HBS No. 521-020. This note focuses on algorithmic bias in marketing. First, it presents a variety of marketing examples in which algorithmic bias may occur. The examples are organized around the 4 P’s of marketing – promotion, price, place and... View Details

Keywords: Marketing; Race; Ethnicity; Gender; Diversity; Prejudice and Bias; Decision Making; Ethics; Customer Relationship Management; Retail Industry; Technology Industry; Apparel and Accessories Industry; United States

2009
Dictionary Entry

Negativity Bias

By: Todd Rogers and Max H. Bazerman

Keywords: Prejudice and Bias

13 Sep 2013
News

Educate Everyone About Second-Generation Gender Bias

Keywords: Herminia Ibarra; Deborah Kolb; Ely, Robin; gender; bias; women in business; Management

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

2018
Working Paper

How Scheduling Can Bias Quality Assessment: Evidence from Food Safety Inspections

By: Maria Ibanez and Michael W. Toffel

Many production processes are subject to inspection to ensure they meet quality, safety, and environmental standards imposed by companies and regulators. Inspection accuracy is critical to inspections being a useful input to assessing risks, allocating quality... View Details

Keywords: Assessment; Bias; Inspection; Scheduling; Econometric Analysis; Empirical Research; Regulation; Health; Food; Safety; Quality; Performance Consistency; Performance Evaluation; Food and Beverage Industry; Service Industry

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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Sampling Bias in Entrepreneurial Experiments

Using data from a prominent online platform for launching new digital products, we document that ‘sampling bias’—defined as the difference between a startup’s target customer base and the actual sample on which early ‘beta tests’ are conducted—has a systematic and... View Details

04 Mar 2019
Working Paper Summaries

The Revision Bias

Keywords: by Ximena Garcia-Rada, Leslie John, Ed O’Brien, and Michael I. Norton

Article

Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

By: Eva Ascarza and Ayelet Israeli

An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details

Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods

Article

Fighting Bias on the Front Lines

By: Alexandra C. Feldberg and Tami Kim

Most companies aim for exceptional customer service, but too few are attentive to the subtle discrimination by frontline employees that can alienate customers, lead to lawsuits, or even cause lasting brand damage by going viral.
This article presents research... View Details

Keywords: Customer Service; Customer Focus and Relationships; Service Delivery; Diversity; Prejudice and Bias; Organizational Change and Adaptation

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