Publications

08 May 2018
First Look

First Look at New Research and Ideas, May 8, 2018

https://www.hbs.edu/faculty/Pages/item.aspx?num=52570 Algorithm Appreciation: People Prefer Algorithmic to Human Judgment By: Logg, Jennifer M., Julia A. Minson, and Don A. Moore Abstract—Even though... View Details

Keywords: Sean Silverthorne

Article

How to Use Heuristics for Differential Privacy

By: Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu

We develop theory for using heuristics to solve computationally hard problems in differential privacy. Heuristic approaches have enjoyed tremendous success in machine learning, for which performance can be empirically evaluated. However, privacy guarantees cannot be... View Details

2019
Article

An Empirical Study of Rich Subgroup Fairness for Machine Learning

By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu

Kearns et al. [2018] recently proposed a notion of rich subgroup fairness intended to bridge the gap between statistical and individual notions of fairness. Rich subgroup fairness picks a statistical fairness constraint (say, equalizing false positive rates across... View Details

Keywords: Machine Learning; Fairness; AI and Machine Learning

2022
Working Paper

Human-Computer Interactions in Demand Forecasting and Labor Scheduling Decisions

By: Caleb Kwon, Ananth Raman and Jorge Tamayo

We empirically analyze how managerial overrides to a commercial algorithm that forecasts demand and schedules labor affect store performance. We analyze administrative data from a large grocery retailer that utilizes a commercial algorithm to forecast demand and... View Details

Keywords: Employees; Human Capital; Performance; Applications and Software; Management Skills; Management Practices and Processes; Retail Industry

SSRN

Article

Conversational Receptiveness: Expressing Engagement with Opposing Views

By: M. Yeomans, J. Minson, H. Collins, H. Chen and F. Gino

We examine “conversational receptiveness”—the use of language to communicate one’s willingness to thoughtfully engage with opposing views. We develop an interpretable machine-learning algorithm to identify the linguistic profile of receptiveness (Studies 1A-B). We then... View Details

Keywords: Receptiveness; Natural Language Processing; Disagreement; Interpersonal Communication; Relationships; Conflict Management

2025
Article

Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments

By: Kosuke Imai and Michael Lingzhi Li

Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details

Keywords: AI and Machine Learning; Mathematical Methods; Analytics and Data Science

2023
Article

On the Impact of Actionable Explanations on Social Segregation

By: Ruijiang Gao and Himabindu Lakkaraju

As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research... View Details

Keywords: Forecasting and Prediction; AI and Machine Learning; Outcome or Result

December 2019
Article

Costly Concessions: An Empirical Framework for Matching with Imperfectly Transferable Utility

By: Alfred Galichon, Scott Duke Kominers and Simon Weber

We introduce an empirical framework for models of matching with imperfectly transferable utility and unobserved heterogeneity in tastes. Our framework allows us to characterize matching equilibrium in a flexible way that includes as special cases the classic fully- and... View Details

Keywords: Sorting; Matching; Marriage Market; Intrahousehold Allocation; Imperfectly Transferable Utility; Marketplace Matching; Mathematical Methods

SSRN

2023
Article

Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten

By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma

The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details

Keywords: Analytics and Data Science; AI and Machine Learning; Decision Making; Governing Rules, Regulations, and Reforms

February 2011 (Revised February 2012)
Case

Online Marketing at Big Skinny

By: Benjamin Edelman and Scott Duke Kominers

Describes a wallet maker's application of seven Internet marketing technologies: display ads, algorithmic search, sponsored search, social media, interactive content, online distributors, and A/B testing. Provides concise introductions to the key features of each... View Details

Keywords: Advertising Campaigns; Digital Marketing; Resource Allocation; Marketing Strategy; Performance Evaluation; Internet and the Web; Retail Industry

Educators

05 Oct 2015
Working Paper Summaries

Online Network Revenue Management Using Thompson Sampling

Keywords: by Kris Johnson Ferreira, David Simchi-Levi & He Wang; Retail

September 2020 (Revised February 2024)
Teaching Note

Artea (A), (B), (C), and (D): Designing Targeting Strategies

By: Eva Ascarza and Ayelet Israeli

Teaching Note for HBS No. 521-021,521-022,521-037,521-043. 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... View Details

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

Article

Vungle Inc. Improves Monetization Using Big-Data Analytics

By: Bert De Reyck, Ioannis Fragkos, Yael Grushka-Cockayne, Casey Lichtendahl, Hammond Guerin and Andrew Kritzer

The advent of big data has created opportunities for firms to customize their products and services to unprecedented levels of granularity. Using big data to personalize an offering in real time, however, remains a major challenge. In the mobile advertising industry,... View Details

Keywords: Big Data; Monetization; Data and Data Sets; Advertising; Mobile Technology; Customization and Personalization; Performance Improvement

2010
Chapter

Deferred Acceptance Algorithms: History, Theory, Practice

By: Alvin E. Roth

The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and indirectly, by raising new theoretical questions. Deferred acceptance algorithms... View Details

Keywords: Labor; Market Design; Marketplace Matching; Failure; Mathematical Methods

March 2008
Article

Deferred Acceptance Algorithms: History, Theory, Practice, and Open Questions

By: Alvin E. Roth

The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and, indirectly, by raising new theoretical questions. Deferred acceptance... View Details

Keywords: History; Market Design; Labor; System; Practice; Performance; Theory; Boston; New York (city, NY)

2007
Working Paper

Deferred Acceptance Algorithms: History, Theory, Practice, and Open Questions

By: Alvin E. Roth

The deferred acceptance algorithm proposed by Gale and Shapley (1962) has had a profound influence on market design, both directly, by being adapted into practical matching mechanisms, and, indirectly, by raising new theoretical questions. Deferred acceptance... View Details

Keywords: Education; Marketplace Matching; Market Design; Mathematical Methods; Theory; Practice

September 2017
Article

It Doesn't Hurt to Ask: Question-asking Increases Liking

By: K. Huang, M. Yeomans, A.W. Brooks, J. Minson and F. Gino

Conversation is a fundamental human experience, one that is necessary to pursue intrapersonal and interpersonal goals across myriad contexts, relationships, and modes of communication. In the current research, we isolate the role of an understudied conversational... View Details

Keywords: Question-asking; Liking; Responsiveness; Conversation; Natural Language Processing; Interpersonal Communication; Behavior