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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

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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

February 2021 (Revised March 2022)
Case

Marvin: A Personalized Telehealth Approach to Mental Health

By: Regina E. Herzlinger, Eshani Sharma, Andrew Nguyen, Thomas Arsenault, Carin-Isabel Knoop and Julia Kelley

More than one third of Americans were said to suffer some type of behavioral health ailment at some point in their lifetime, with many people requiring chronic therapy or intervention. Despite significant clinical needs, access to reliable treatment has been difficult... View Details

Keywords: Mental Health; Applications; Startup Management; Telehealth; Health Care Entrepreneurship; Health ＆ Wellness; Health Care; Health Care and Treatment; Customization and Personalization; Internet and the Web; Entrepreneurship; Growth and Development Strategy; Applications and Software

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

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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

Research Summary

Overview

By: Himabindu Lakkaraju

I develop machine learning tools and techniques which enable human decision makers to make better decisions. More specifically, my research addresses the following fundamental questions pertaining to human and algorithmic decision-making:

1. How to build... View Details

Keywords: Artificial Intelligence; Machine Learning; Decision Analysis; Decision Support

08 Nov 2016
First Look

November 8, 2016

in power. A mass shooting increases the number of enacted laws that loosen gun restrictions by 75% in states with Republican-controlled legislatures. We find no significant effect of mass shootings on laws enacted when there is a Democrat-controlled legislature. View Details

Keywords: Sean Silverthorne

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

2020
Working Paper

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury

Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used as an observation for further inductive or abductive research, but should not be treated as the result of a... View Details

Keywords: Machine Learning; Theory Building; Induction; Decision Trees; Random Forests; K-nearest Neighbors; Neural Network; P-hacking; Analytics and Data Science; Analysis

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

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Article

Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions

By: Andrea Blasco, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian and Karim R. Lakhani

Open data science and algorithm development competitions offer a unique avenue for rapid discovery of better computational strategies. We highlight three examples in computational biology and bioinformatics research where the use of competitions has yielded significant... View Details

Keywords: Computational Biology; Bioinformatics; Innovation Competitions; Research; Collaborative Innovation and Invention

August 2021 (Revised November 2024)
Case

Intenseye: Powering Workplace Health and Safety with AI (A)

By: Michael W. Toffel and Youssef Abdel Aal

Intenseye was a Turkey-based technology startup that deployed machine learning algorithms to workplace camera feeds in order to identify unsafe worker actions and unsafe working conditions, in order to help improve worker safety. The case describes how Intenseye’s... View Details

Keywords: Privacy; Product Development; Operations; Technological Innovation; Value Creation; Production; Distribution; Safety; Risk and Uncertainty; Technology Industry; Manufacturing Industry; Distribution Industry; Turkey; Middle East; United States

Article

Adaptive Machine Unlearning

By: Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi and Chris Waites

Data deletion algorithms aim to remove the influence of deleted data points from trained models at a cheaper computational cost than fully retraining those models. However, for sequences of deletions, most prior work in the non-convex setting gives valid guarantees... View Details

Keywords: Machine Learning; AI and Machine Learning

21 Mar 2019
Working Paper Summaries

Advancing Computational Biology and Bioinformatics Research Through Open Innovation Competitions

Keywords: by Blasco, Andrea, Michael G. Endres, Rinat A. Sergeev, Anup Jonchhe, Max Macaluso, Rajiv Narayan, Ted Natoli, Jin H. Paik, Bryan Briney, Chunlei Wu, Andrew I. Su, Aravind Subramanian, and Karim R. Lakhani; Health

28 Mar 2017
Working Paper Summaries

CEO Behavior and Firm Performance

Keywords: by Oriana Bandiera, Stephen Hansen, Andrea Pratt, and Raffaella Sadun

September 2015
Article

Design and Implementation of a Privacy Preserving Electronic Health Record Linkage Tool in Chicago

By: Abel Kho, John Cashy, Kathryn Jackson, Adam Pah, Satyender Goel, Jorn Boehnke, John Eric Humphries, Scott Duke Kominers and et al.

Objective
To design and implement a tool that creates a secure, privacy preserving linkage of electronic health record (EHR) data across multiple sites in a large metropolitan area in the United States (Chicago, IL), for use in clinical... View Details

Keywords: Information; Customers; Safety; Rights; Ethics; Entrepreneurship; Health Care and Treatment; Health Industry; Chicago

February 26, 2024
Article

Making Workplaces Safer Through Machine Learning

By: Matthew S. Johnson, David I. Levine and Michael W. Toffel

Machine learning algorithms can dramatically improve regulatory effectiveness. This short article describes the authors' scholarly work that shows how the U.S. Occupational Safety and Health Administration (OSHA) could have reduced nearly twice as many occupational... View Details

Keywords: Government Experimentation; Auditing; Inspection; Evaluation; Process Improvement; Government Administration; AI and Machine Learning; Safety; Governing Rules, Regulations, and Reforms

September–October 2023
Article

Interpretable Matrix Completion: A Discrete Optimization Approach

By: Dimitris Bertsimas and Michael Lingzhi Li

We consider the problem of matrix completion on an n × m matrix. We introduce the problem of interpretable matrix completion that aims to provide meaningful insights for the low-rank matrix using side information. We show that the problem can be... View Details

Keywords: Mathematical Methods

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Winter 2017
Article

Why Big Data Isn't Enough

By: Sen Chai and Willy C. Shih

There is a growing belief that sophisticated algorithms can explore huge databases and find relationships independent of any preconceived hypotheses. But in businesses that involve scientific research and technological innovation, this approach is misguided and... View Details

Keywords: Big Data; Science-based; Science; Scientific Research; Data Analytics; Data Science; Data-driven Management; Data Scientists; Technological Innovation; Analytics and Data Science; Mathematical Methods; Theory

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March 2019
Case

DayTwo: Going to Market with Gut Microbiome

By: Ayelet Israeli and David Lane

DayTwo is a young Israeli startup that applies research on the gut microbiome and machine learning algorithms to deliver personalized nutritional recommendations to its users in order to minimize blood sugar spikes after meals. After a first year of trial rollout in... View Details

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