Publications

Educators

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

Keywords: AI and Machine Learning; Analytics and Data Science; Prejudice and Bias

July 2024 (Revised January 2025)
Case

Dynamic Pricing at Wendy’s: Where’s the Beef?

By: Elie Ofek, Alicia Dadlani and Martha Hostetter

In early 2024, Wendy’s new CEO announced on an earnings call that the company would install digital menus in its US locations so it could begin testing dynamic pricing—changing prices up or down in response to shifts in supply and demand – as well as allow engaging in... View Details

Keywords: Dynamic Pricing; Marketing Strategy; Price; Technology Adoption; Consumer Behavior; AI and Machine Learning; Customer Focus and Relationships; Policy; Food and Beverage Industry

Educators

2019
Book

Fintech, Small Business & the American Dream: How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity

By: Karen G. Mills

Fintech, Small Business & the American Dream describes the needs of small businesses for capital and demonstrates how technology—novel data sources, artificial intelligence, machine learning—will transform the small business lending market. This market has been... View Details

Find at Harvard

Working Paper

Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application

By: Flora Feng, Charis Li and Shunyuan Zhang

Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely... View Details

Keywords: Peer-to-peer Markets; Marketplace Matching; AI and Machine Learning; Demand and Consumers; Digital Platforms; Marketing

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

2023
Working Paper

The Customer Journey as a Source of Information

By: Nicolas Padilla, Eva Ascarza and Oded Netzer

In the face of heightened data privacy concerns and diminishing third-party data access, firms are placing increased emphasis on first-party data (1PD) for marketing decisions. However, in environments with infrequent purchases, reliance on past purchases 1PD... View Details

Keywords: Customer Journey; Privacy; Consumer Behavior; Analytics and Data Science; AI and Machine Learning; Customer Focus and Relationships

February 2024
Case

Continuity & Change at Boston Consulting Group

By: David G. Fubini, Suraj Srinivasan and David Lane

As the new CEO of Boston Consulting Group (BCG) since autumn 2021, Christoph Schweizer had big shoes to fill—his predecessor, Rich Lesser, had tripled the partnership’s total revenues and created digital initiatives that contributed 40+% of 2021 revenues, more than... View Details

Keywords: Business Organization; Change Management; Talent and Talent Management; Governance; AI and Machine Learning; Environmental Sustainability; Leading Change; Risk Management; Organizational Culture; Partners and Partnerships; Revenue; Growth and Development Strategy; Management Succession; Consulting Industry

Educators

Forthcoming
Article

Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation

By: Maya Balakrishnan, Kris Ferreira and Jordan Tong

Even if algorithms make better predictions than humans on average, humans may sometimes have private information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by... View Details

Keywords: AI and Machine Learning; Analytics and Data Science; Forecasting and Prediction; Digital Marketing

2021
Article

To Thine Own Self Be True? Incentive Problems in Personalized Law

By: Jordan M. Barry, John William Hatfield and Scott Duke Kominers

Recent years have seen an explosion of scholarship on “personalized law.” Commentators foresee a world in which regulators armed with big data and machine learning techniques determine the optimal legal rule for every regulated party, then instantaneously disseminate... View Details

Keywords: Personalized Law; Regulation; Regulatory Avoidance; Regulatory Arbitrage; Law And Economics; Law And Technology; Law And Artificial Intelligence; Futurism; Moral Hazard; Elicitation; Signaling; Privacy; Law; Governing Rules, Regulations, and Reforms; Information Technology; AI and Machine Learning

SSRN

2022
Working Paper

Rethinking Explainability as a Dialogue: A Practitioner's Perspective

By: Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan and Sameer Singh

As practitioners increasingly deploy machine learning models in critical domains such as healthcare, finance, and policy, it becomes vital to ensure that domain experts function effectively alongside these models. Explainability is one way to bridge the gap between... View Details

Keywords: Natural Language Conversations; AI and Machine Learning; Experience and Expertise; Interactive Communication; Business and Stakeholder Relations

2023
Other Article

The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications

By: Mirac Suzgun, Luke Melas-Kyriazi, Suproteem K. Sarkar, Scott Duke Kominers and Stuart Shieber

Innovation is a major driver of economic and social development, and information about many kinds of innovation is embedded in semi-structured data from patents and patent applications. Though the impact and novelty of innovations expressed in patent data are difficult... View Details

Keywords: USPTO; Natural Language Processing; Classification; Summarization; Patent Novelty; Patent Trolls; Patent Enforceability; Patents; Innovation and Invention; Intellectual Property; AI and Machine Learning; Analytics and Data Science

19 Mar 2019
First Look

New Research and Ideas, March 19, 2019

forthcoming Academy of Management Discoveries Creativity, Artificial Intelligence, and a World of Surprises By: Amabile, Teresa M. Abstract—In recent years, progress has been made toward AI Creativity, which I define as the production of... View Details

Keywords: Dina Gerdeman

2023
Working Paper

Black-box Training Data Identification in GANs via Detector Networks

By: Lukman Olagoke, Salil Vadhan and Seth Neel

Since their inception Generative Adversarial Networks (GANs) have been popular generative models across images, audio, video, and tabular data. In this paper we study whether given access to a trained GAN, as well as fresh samples from the underlying distribution, if... View Details

Keywords: Cybersecurity; Copyright; AI and Machine Learning; Analytics and Data Science