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Show Results For
- All HBS Web
(1,145)
- News (193)
- Research (741)
- Events (8)
- Multimedia (18)
- Faculty Publications (496)
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- 30 May 2024
- Research & Ideas
Racial Bias Might Be Infecting Patient Portals. Can AI Help?
messages. That’s part of the reason the authors say there may be other factors besides direct racial bias driving the results—and a key reason that they are keen to explore this data in future research. One potential factor they... View Details
- 12 Oct 2022
- Research & Ideas
When Design Enables Discrimination: Learning from Anti-Asian Bias on Airbnb
they may inadvertently exacerbate. While Airbnb has addressed bias concerns with site changes in the past, further steps could be taken to bring more anonymity to the site, Luca says. Platform design and discrimination Renting out... View Details
- June 2010
- Article
Correspondence Bias in Performance Evaluation: Why Grade Inflation Works
By: D. A. Moore, S. A. Swift, Z. S. Sharek and F. Gino
Moore, D. A., S. A. Swift, Z. S. Sharek, and F. Gino. "Correspondence Bias in Performance Evaluation: Why Grade Inflation Works." Personality and Social Psychology Bulletin 36, no. 6 (June 2010): 843–852.
- May 2022
- Case
Timnit Gebru: 'SILENCED No More' on AI Bias and The Harms of Large Language Models
By: Tsedal Neeley and Stefani Ruper
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 she accepted your resignation.” Heart... View Details
Neeley, Tsedal, and Stefani Ruper. "Timnit Gebru: 'SILENCED No More' on AI Bias and The Harms of Large Language Models." Harvard Business School Case 422-085, May 2022.
- 2003
- Working Paper
Auditor Independence, Conflict of Interest, and the Unconscious Intrusion of Bias
By: Don A. Moore, George Loewenstein, Lloyd Tanlu and Max H. Bazerman
- Article
Home Bias at Home: Local Equity Preference in Domestic Portfolios
By: Joshua D. Coval and Tobias J. Moskowitz
Coval, Joshua D., and Tobias J. Moskowitz. "Home Bias at Home: Local Equity Preference in Domestic Portfolios." Journal of Finance 54, no. 6 (December 1999). (Winner of Smith Breeden Prize. Best Paper For the best finance research paper published in the Journal of Finance presented by Smith Breeden Associates, Inc.)
- Summer 2021
- Article
Predictable Country-level Bias in the Reporting of COVID-19 Deaths
By: Botir Kobilov, Ethan Rouen and George Serafeim
We examine whether a country’s management of the COVID-19 pandemic relate to the downward biasing of the number of reported deaths from COVID-19. Using deviations from historical averages of the total number of monthly deaths within a country, we find that the... View Details
Keywords: COVID-19; Deaths; Reporting; Incentives; Government Policy; Health Pandemics; Health Care and Treatment; Country; Crisis Management; Outcome or Result; Reports; Policy
Kobilov, Botir, Ethan Rouen, and George Serafeim. "Predictable Country-level Bias in the Reporting of COVID-19 Deaths." Journal of Government and Economics 2 (Summer 2021).
- 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
Campbell, Dennis, Maria Loumioti, and Regina Wittenberg Moerman. "Making Sense of Soft Information: Interpretation Bias and Loan Quality." Art. 101240. Journal of Accounting & Economics 68, nos. 2-3 (November–December 2019).
- November 30, 2020
- Editorial
Don't Focus on the Most Expressive Face in the Audience
By: Amit Goldenberg and Erika Weisz
Research has shown that when speaking in front of a group, people’s attention tends to gets stuck on the most emotional faces, causing them to overestimate the group’s average emotional state. In this piece, the authors share two additional findings: First, the larger... View Details
Goldenberg, Amit, and Erika Weisz. "Don't Focus on the Most Expressive Face in the Audience." Harvard Business Review (website) (November 30, 2020).
- 2003
- Article
Don't Blame the Computer: When Self-Disclosure Moderates the Self-Serving Bias
By: Youngme Moon
Moon, Youngme. "Don't Blame the Computer: When Self-Disclosure Moderates the Self-Serving Bias." Journal of Consumer Psychology 13, nos. 1-2 (2003).
- September 2020 (Revised July 2022)
- Exercise
Artea (C): Potential Discrimination through Algorithmic 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: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
Ascarza, Eva, and Ayelet Israeli. "Artea (C): Potential Discrimination through Algorithmic Targeting." Harvard Business School Exercise 521-037, September 2020. (Revised July 2022.)
- 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
Lane, Jacqueline N., Karim R. Lakhani, and Roberto Fernandez. "Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs." Organization Science 35, no. 3 (May–June 2024): 911–927.
- 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
Lane, Jacqueline N., Karim R. Lakhani, and Roberto Fernandez. "Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs." Harvard Business School Working Paper, No. 23-066, April 2023. (Accepted by Organization Science.)
- 17 May 2018
- Sharpening Your Skills
You Probably Have a Bias for Making Bad Decisions. Here's Why.
entrepreneurs, even when the content of the pitches is identical. And handsome men fare best of all. Why Employers Favor Men Why are women discriminated against in hiring decisions? The answer is more subtle than expected. Simple Ways to Take Gender View Details
Keywords: by Sean Silverthorne
- 2023
- Working Paper
Auditing Predictive Models for Intersectional Biases
By: Kate S. Boxer, Edward McFowland III and Daniel B. Neill
Predictive models that satisfy group fairness criteria in aggregate for members of a protected class, but do not guarantee subgroup fairness, could produce biased predictions for individuals at the intersection of two or more protected classes. To address this risk, we... View Details
Boxer, Kate S., Edward McFowland III, and Daniel B. Neill. "Auditing Predictive Models for Intersectional Biases." Working Paper, June 2023.
- May 28, 2018
- Article
How Companies Can Identify Racial and Gender Bias in Their Customer Service
By: Alexandra C. Feldberg and Tami Kim
Research shows that minority customers — blacks and Asians — regularly receive worse customer service than whites in ways that are not immediately obvious to onlookers (or even managers). These results prompt a couple of questions for executives and managers. One, does... View Details
Keywords: Internal Audit; Customers; Service Delivery; Prejudice and Bias; Race; Gender; Organizational Change and Adaptation
Feldberg, Alexandra C., and Tami Kim. "How Companies Can Identify Racial and Gender Bias in Their Customer Service." Harvard Business Review (website) (May 28, 2018).
- 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
- September 2020 (Revised July 2022)
- Exercise
Artea (B): Including Customer-Level Demographic Data
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: Targeting; Algorithmic Bias; Race; Gender; Marketing; Diversity; Customer Relationship Management; Demographics; Prejudice and Bias; Retail Industry; Apparel and Accessories Industry; Technology Industry; United States
Ascarza, Eva, and Ayelet Israeli. "Artea (B): Including Customer-Level Demographic Data." Harvard Business School Exercise 521-022, September 2020. (Revised July 2022.)
- Article
Whites See Racism as a Zero-Sum Game That They Are Now Losing
By: Michael I. Norton and Samuel R. Sommers
Although some have heralded recent political and cultural developments as signaling the arrival of a post-racial era in America, several legal and social controversies regarding "reverse racism" highlight Whites' increasing concern about anti-White bias. We show that... View Details
Keywords: Racism; Zero-sum Game; Bias; Affirmative Action; Prejudice and Bias; Race; Social Issues; United States
Norton, Michael I., and Samuel R. Sommers. "Whites See Racism as a Zero-Sum Game That They Are Now Losing." Perspectives on Psychological Science 6, no. 3 (May 2011): 215–218.