Publications

May–June 2024
Article

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: Prejudice and Bias; Gender; Training; Recruitment; Personal Development and Career

2024
Working Paper

What Is Newsworthy? Theory and Evidence

By: Luis Armona, Matthew Gentzkow, Emir Kamenica and Jesse M. Shapiro

We study newsworthiness in theory and practice. We focus on situations in which a news outlet observes the realization of a state of the world and must decide whether to report the realization to a consumer who pays an opportunity cost to consume the report. The... View Details

Keywords: News; Mathematical Methods; Prejudice and Bias; Media and Broadcasting Industry

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April 3, 2024
Article

How Automakers Can Address Resistance to Self-Driving Cars

By: Stuti Agarwal, Julian De Freitas and Carey K. Morewedge

Research involving multiple experiments found that consumers have biased views of their driving abilities relative to those of other drivers and automated vehicles. These findings have implications for the adoption of partly or fully automated vehicles, which one day... View Details

Keywords: Technology Adoption; Consumer Behavior; Government Legislation; Prejudice and Bias; Auto Industry; Technology Industry

2025
Working Paper

Greenlighting Innovative Projects: How Evaluation Format Shapes the Perceived Feasibility of Early-Stage Ideas

By: Jacqueline N. Lane, Simon Friis, Tianxi Cai, Michael Menietti, Griffin Weber and Eva C. Guinan

The evaluation of innovative early-stage projects is essential for allocating limited resources. We investigate how the evaluation format affects the identification of feasibility issues through a field experiment at a leading research university. Experts were... View Details

Keywords: Innovation Evaluation; Evaluation Criteria; Feasibility Assessment; Attention Allocation; Cognitive Mechanisms; Field Experiment; Research; Performance Evaluation; Innovation and Invention; Prejudice and Bias

March 2024
Case

Unintended Consequences of Algorithmic Personalization

By: Eva Ascarza and Ayelet Israeli

“Unintended Consequences of Algorithmic Personalization” (HBS No. 524-052) investigates algorithmic bias in marketing through four case studies featuring Apple, Uber, Facebook, and Amazon. Each study presents scenarios where these companies faced public criticism for... View Details

Keywords: Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Customization and Personalization; Technology Industry; Retail Industry; United States

2025
Working Paper

Choosing and Using Information in Evaluation Decisions

By: Katherine Baldiga Coffman, Scott Kostyshak and Perihan O. Saygin

We use a controlled experiment to study how information acquisition impacts candidate evaluations. We provide evaluators with group-level information on performance and the opportunity to acquire additional, individual-level performance information before making a... View Details

Keywords: Discrimination; Beliefs; Stereotypes; Gender; Prejudice and Bias; Selection and Staffing; Performance Evaluation

January 2024
Case

Deion Sanders: The Prime Effect

By: Hise O. Gibson, Nicole Gilmore and Alicia Dadlani

In 2023, Deion Sanders, known as “Coach Prime,” became head football coach of the University of Colorado Boulder (CU). Sanders was tasked with leading CU’s struggling football program, which had only achieved one winning season in the last 15 years, back to glory. Many... View Details

Keywords: Leadership Style; Leading Change; Management Style; Race; Prejudice and Bias; Sports; Experience and Expertise; Sports Industry; United States; Colorado

January 2024 (Revised May 2024)
Case

Uncle Nearest: Creating a Legacy

By: Hise Gibson, Archie L. Jones, Nicole Gilmore and Ai-Ling Jamila Malone

Fawn Weaver, as a Black woman and industry outsider in a capital-intensive, highly regulated, competitive and male-dominated spirits industry, successfully overcame numerous obstacles to launch a premium American whiskey brand, Uncle Nearest in 2017, which became the... View Details

December 4, 2023
Article

Stop Assuming Introverts Aren't Passionate About Work

By: Kai Krautter, Anabel Büchner and Jon M. Jachimowicz

Society often assumes that the only way to be passionate is to act extroverted, but that is simply not true. In their new research, the authors found that regardless of their actual level of passion, extroverted employees are perceived as more passionate than... View Details

Keywords: Passion; Personality; Extraversion; Scale Development; Personal Characteristics; Perception; Employees; Prejudice and Bias

November–December 2023
Article

Look the Part? The Role of Profile Pictures in Online Labor Markets

By: Isamar Troncoso and Lan Luo

Profile pictures are a key component of many freelancing platforms, a design choice that can impact hiring and matching outcomes. In this paper, we examine how appearance-based perceptions of a freelancer’s fit for the job (i.e., whether a freelancer "looks the part"... View Details

Keywords: Freelancers; Gig Workers; Demographics; Prejudice and Bias; Selection and Staffing; Jobs and Positions; Analytics and Data Science

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October 2023
Case

Making Progress at Progress Software (A)

By: Katherine Coffman, Hannah Riley Bowles and Alexis Lefort

In this case, the Human Capital team at Progress Software has identified that some employees have a hard time understanding how to advance within Progress. This realization leads the team to develop several major people-process innovations: the introduction of... View Details

Keywords: Leading Change; Organizational Culture; Performance Evaluation; Prejudice and Bias; Personal Development and Career; Human Capital; Employee Relationship Management; Technology Industry; Bulgaria

October 2023
Teaching Note

Timnit Gebru: 'SILENCED No More' on AI Bias and The Harms of Large Language Models

By: Tsedal Neeley and Tim Englehart

Teaching Note for HBS Case No. 422-085. Dr. Timnit Gebru—a leading artificial intelligence (AI) computer scientist and co-lead of Google’s Ethical AI team—was messaging with one of her colleagues when she saw the words: “Did you resign?? Megan sent an email saying that... View Details

Keywords: Ethics; Employment; Corporate Social Responsibility and Impact; Technological Innovation; AI and Machine Learning; Diversity; Prejudice and Bias; Technology Industry

October 2023
Supplement

Making Progress at Progress Software (B)

By: Katherine Coffman, Hannah Riley Bowles and Alexis Lefort

In this case, the Human Capital team at Progress Software has identified that some employees have a hard time understanding how to advance within Progress. This realization leads the team to develop several major people-process innovations: the introduction of... View Details

Keywords: Leading Change; Negotiation; Organizational Culture; Performance Evaluation; Prejudice and Bias; Talent and Talent Management; Employees; Technology Industry; United States; Bulgaria

September 29, 2023
Article

Eliminating Algorithmic Bias Is Just the Beginning of Equitable AI

By: Simon Friis and James Riley

When it comes to artificial intelligence and inequality, algorithmic bias rightly receives a lot of attention. But it’s just one way that AI can lead to inequitable outcomes. To truly create equitable AI, we need to consider three forces through which it might make... View Details

Keywords: AI and Machine Learning; Prejudice and Bias; Equality and Inequality

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September 2023
Exercise

Irrationality in Action: Decision-Making Exercise

By: Alison Wood Brooks, Michael I. Norton and Oliver Hauser

This teaching exercise highlights the obstacle of biases in decision-making, allowing students to generate examples of potentially poor decision-making rooted in abundant and unwanted bias. This exercise has two parts: a pre-class, online survey in which students... View Details

Keywords: Prejudice and Bias; Decision Making

2023
Working Paper

Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness

By: Neil Menghani, Edward McFowland III and Daniel B. Neill

In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details

Keywords: AI and Machine Learning; Forecasting and Prediction; Prejudice and Bias

June 2023
Article

Amplification of Emotion on Social Media

By: Amit Goldenberg and Robb Willer

Why do expressions of emotion seem so heightened on social media? Brady et al. argue that extreme moral outrage on social media is not only driven by the producers and sharers of emotional expressions, but also by systematic biases in the way people that perceive moral... View Details

Keywords: Emotion; Perception; Prejudice and Bias; Emotions; Social Media

May 9, 2023
Article

8 Questions About Using AI Responsibly, Answered

By: Tsedal Neeley

Generative AI tools are poised to change the way every business operates. As your own organization begins strategizing which to use, and how, operational and ethical considerations are inevitable. This article delves into eight of them, including how your organization... View Details

Keywords: AI and Machine Learning; Organizational Change and Adaptation; Prejudice and Bias; Ethics

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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