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(1,112)
- News (189)
- Research (737)
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- Faculty Publications (486)
Show Results For
- All HBS Web
(1,112)
- News (189)
- Research (737)
- Events (5)
- Multimedia (18)
- Faculty Publications (486)
- 2008
- Chapter
Business Archives and Overcoming Survivor Bias
By: G. Jones
Among the most longstanding criticisms of business history as an academic discipline is the bias caused towards studying successful firms rather than failures, and the related use of longevity as a major criterion for success. The grand narratives of business history... View Details
- Forthcoming
- Article
Sampling Bias in Entrepreneurial Experiments
By: Ruiqing Cao, Rembrand Koning and Ramana Nanda
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
Cao, Ruiqing, Rembrand Koning, and Ramana Nanda. "Sampling Bias in Entrepreneurial Experiments." Management Science (forthcoming). (Pre-published online December 14, 2023.)
- 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
Ascarza, Eva, and Ayelet Israeli. "Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)." e2115126119. Proceedings of the National Academy of Sciences 119, no. 11 (March 8, 2022).
- Article
Deep Down My Enemy Is Good: Thinking about the True Self Reduces Intergroup Bias
By: Julian De Freitas and Mina Cikara
Intergroup bias—preference for one's in-group relative to out-groups—is one of the most robust phenomena in all of psychology. Here we investigate whether a positive bias that operates at the individual-level, belief in a good true self, may be leveraged to reduce... View Details
De Freitas, Julian, and Mina Cikara. "Deep Down My Enemy Is Good: Thinking about the True Self Reduces Intergroup Bias." Journal of Experimental Social Psychology 74 (January 2018): 307–316.
- 2023
- Working Paper
Feature Importance Disparities for Data Bias Investigations
By: Peter W. Chang, Leor Fishman and Seth Neel
It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection... View Details
Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
- 01 Jun 2011
- News
Racial Bias Pervades Health Care
Distinguished Professor of Medical Education and professor of orthopedic surgery at Harvard Medical School and was the first African American department chief at Harvard’s teaching hospitals. In his new book, Seeing Patients: Unconscious View Details
- January 1982
- Article
A Negativity Bias in Interpersonal Evaluation
By: T. M. Amabile and A. H. Glazebrook
Two studies were conducted to demonstrate a bias toward negativity in evaluations of persons or their work in particular social circumstances. In Study 1, subjects evaluated materials written by peers. Those working under conditions that placed them in low status... View Details
Keywords: Social Psychology; Status and Position; Prejudice and Bias; Performance Evaluation; Situation or Environment; Perception; Attitudes
Amabile, T. M., and A. H. Glazebrook. "A Negativity Bias in Interpersonal Evaluation." Journal of Experimental Social Psychology 18 (January 1982): 1–22.
- 21 Jul 2020
- News
Starbucks Commits to Raising Awareness of Racial Bias
- 20 Jan 2014
- News
Online marketplaces may encourage bias
- 18 Feb 2021
- News
Jumping In, Fighting Bias
Photo via LinkedIn Photo via LinkedIn Growing up in suburban Chicago, Sumaiya Balbale (MBA 2009) and her Indian immigrant parents didn’t see many other Muslims. At school she was teased and bullied—an experience that no doubt shaped her as she moved from a history... View Details
- 21 Jul 2020
- News
Starbucks Commits to Raising Awareness of Racial Bias
- 2011
- Article
Bias in Search Results?: Diagnosis and Response
By: Benjamin Edelman
I explore allegations of search engine bias, including understanding a search engine's incentives to bias results, identifying possible forms of bias, and evaluating methods of verifying whether bias in fact occurs. I then consider possible legal and policy responses,... View Details
Keywords: Prejudice and Bias; Motivation and Incentives; Outcome or Result; Markets; Legal Liability; Policy; Search Technology; Performance Evaluation; Governing Rules, Regulations, and Reforms
Edelman, Benjamin. "Bias in Search Results?: Diagnosis and Response." Indian Journal of Law and Technology 7 (2011): 16–32.
- 11 Jan 2019
- News
Case Study: Beating Bias
school years and more recently at Nickelodeon’s strategy department, Patel realized he (like many others) had been consuming media that only confirmed his own political bias and, in so doing, had failed to get the full picture of the... View Details
Keywords: Jen McFarland Flint
- 09 Aug 2022
- Cold Call Podcast
A Lesson from Google: Can AI Bias be Monitored Internally?
Keywords: Re: Tsedal Neeley
- 16 Jun 2023
- Blog Post
Actively Addressing Unconscious Bias in Recruiting
School, along with actions you can take now to make a lasting difference. What is Unconscious Bias? Unconscious or implicit bias is the term for the mental processes that cause a person to act in ways that reinforce stereotypes even when... View Details
Keywords: All Industries
Eliminating unintended bias in personalized policies using Bias Eliminating Adapted Trees (BEAT) - PNAS
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... View Details
- 2022
- Working Paper
Confidence, Self-Selection and Bias in the Aggregate
By: Benjamin Enke, Thomas Graeber and Ryan Oprea
The influence of behavioral biases on aggregate outcomes like prices and allocations depends in part on self-selection: whether rational people opt more strongly into aggregate interactions than biased individuals. We conduct a series of betting market, auction and... View Details
Enke, Benjamin, Thomas Graeber, and Ryan Oprea. "Confidence, Self-Selection and Bias in the Aggregate." NBER Working Paper Series, No. 30262, July 2022.
- 10 May 2016
- Video