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- Faculty Publications (31)
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- 2021
- Chapter
Towards a Unified Framework for Fair and Stable Graph Representation Learning
By: Chirag Agarwal, Himabindu Lakkaraju and Marinka Zitnik
As the representations output by Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes important to ensure that these representations are fair and stable. In this work, we establish a key connection between counterfactual... View Details
Agarwal, Chirag, Himabindu Lakkaraju, and Marinka Zitnik. "Towards a Unified Framework for Fair and Stable Graph Representation Learning." In Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence, edited by Cassio de Campos and Marloes H. Maathuis, 2114–2124. AUAI Press, 2021.
- 27 Jun 2024
- Research & Ideas
Gen AI Marketing: How Some 'Gibberish' Code Can Give Products an Edge
their products listed on top, is that a good thing or a bad thing? It just depends on which side you’re looking from,” says Lakkaraju. The coffee machine experiment The study involves a hypothetical search for an “affordable” new coffee... View Details
- 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
Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
- 10 Mar 2011
- What Do You Think?
To What Degree Does the Job Make the Person?
new job. In other words, is there a self-selection bias in studies of the effects of job on a person's chemical makeup? As Stephanie Smith put it, "Perhaps it's a case of either the hormones and natural adaptability of the person... View Details
Keywords: by James Heskett
- January 2025
- Article
Reducing Prejudice with Counter-stereotypical AI
By: Erik Hermann, Julian De Freitas and Stefano Puntoni
Based on a review of relevant literature, we propose that the proliferation of AI with human-like and social features presents an unprecedented opportunity to address the underlying cognitive and affective drivers of prejudice. An approach informed by the psychology of... View Details
Keywords: Prejudice and Bias; AI and Machine Learning; Interpersonal Communication; Social and Collaborative Networks
Hermann, Erik, Julian De Freitas, and Stefano Puntoni. "Reducing Prejudice with Counter-stereotypical AI." Consumer Psychology Review 8, no. 1 (January 2025): 75–86.
- 26 Jan 2016
- First Look
January 26, 2016
disclosure. Publisher's link: https://www.hbs.edu/faculty/Pages/item.aspx?num=50424 forthcoming American Economic Review: Papers and Proceedings Productivity and Selection of Human Capital with Machine Learning By: Chalfin, Aaron, Oren... View Details
Keywords: Sean Silverthorne
- 30 Jun 2009
- First Look
First Look: June 30
provided a one-time tax holiday for the repatriation of foreign earnings by U.S. multinationals. The analysis controls for endogeneity and omitted variable bias by using instruments that identify the firms likely to receive the largest... View Details
Keywords: Martha Lagace