Supervised Machine Learning - Publications - Faculty & Research - Harvard Business School

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August 25, 2022
Article

Find the Right Pace for Your AI Rollout

By: Rebecca Karp and Aticus Peterson

Implementing AI can introduce disruptive change and disfranchise staff and employees. When members are reluctant to adopt a new technology, they might hesitate to use it, push back against its deployment, or use it in limited capacity — which affects the benefits an... View Details

Keywords: AI and Machine Learning; Technology Adoption; Change Management

Article

Fake AI People Won't Fix Online Dating

By: Scott Duke Kominers

Computer-generated images may inspire even more distrust and surely won’t lead to the love of a lifetime. View Details

Keywords: Artificial Intelligence; Dating Services; Internet and the Web; Ethics; AI and Machine Learning

September 23, 2024
Article

AI Wants to Make You Less Lonely. Does It Work?

By: Julian De Freitas

Keywords: AI and Machine Learning; Well-being

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2023
Working Paper

Distributionally Robust Causal Inference with Observational Data

By: Dimitris Bertsimas, Kosuke Imai and Michael Lingzhi Li

We consider the estimation of average treatment effects in observational studies and propose a new framework of robust causal inference with unobserved confounders. Our approach is based on distributionally robust optimization and proceeds in two steps. We first... View Details

Keywords: AI and Machine Learning; Mathematical Methods

October 31, 2022
Article

Achieving Individual—and Organizational—Value with AI

By: Sam Ransbotham, David Kiron, François Candelon, Shervin Khodabandeh and Michael Chu

New research shows that employees derive individual value from AI when using the technology improves their sense of competency, autonomy, and relatedness. Likewise, organizations are far more likely to obtain value from AI when their workers do. This report offers key... View Details

Keywords: AI and Machine Learning; Value; Competency and Skills

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January–February 2025
Article

Why People Resist Embracing AI

By: Julian De Freitas

The success of AI depends not only on its capabilities, which are becoming more advanced each day, but on people’s willingness to harness them. Unfortunately, many people view AI negatively, fearing it will cause job losses, increase the likelihood that their personal... View Details

Keywords: AI and Machine Learning; Technology Adoption; Perception

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June 2025
Article

Ideation with Generative AI—In Consumer Research and Beyond

By: Julian De Freitas, G. Nave and Stefano Puntoni

The use of large language models (LLMs) in consumer research is rapidly evolving, with applications including synthetic data generation, data analysis, and more. However, their role in creative ideation—a cornerstone of consumer research—remains underexplored. Drawing... View Details

Keywords: Large Language Model; AI and Machine Learning; Creativity; Innovation Strategy

June 2024
Teaching Note

Numenta in 2020: The Future of AI

By: David B. Yoffie

In 2020, Numenta’s co-founder, Jeff Hawkins, completed his pathbreaking research on artificial intelligence. His co-founder and CEO, Donna Dubinsky, had to find a business model to monetize the technology. This teaching note explores the challenges of building a... View Details

Keywords: Artificial Intelligence; Monetization; Strategy; Intellectual Property; AI and Machine Learning; Business Model; Entrepreneurship; Technology Industry

July 2024
Case

Replika AI: Alleviating Loneliness (A)

By: Shikhar Ghosh and Shweta Bagai

Eugenia Kuyda launched Replika AI in 2017 as an empathetic digital companion to combat loneliness and provide emotional support. The platform surged in popularity during the COVID-19 pandemic, offering non-judgmental support to isolated users. By 2023, Replika boasted... View Details

Keywords: Entrepreneurship; Ethics; Health Pandemics; AI and Machine Learning; Well-being; Technology Industry

Working Paper

Shifting Work Patterns with Generative AI

By: Eleanor W. Dillon, Sonia Jaffe, Nicole Immorlica and Christopher T. Stanton

We present evidence on how generative AI changes the work patterns of knowledge workers using data from a 6-month-long, cross-industry, randomized field experiment. Half of the 7,137 workers in the study received access to a generative AI tool integrated into the... View Details

Keywords: AI and Machine Learning; Behavior; Time Management

January 2025
Technical Note

AI vs Human: Analyzing Acceptable Error Rates Using the Confusion Matrix

By: Tsedal Neeley and Tim Englehart

This technical note introduces the confusion matrix as a foundational tool in artificial intelligence (AI) and large language models (LLMs) for assessing the performance of classification models, focusing on their reliability for decision-making. A confusion matrix... View Details

Keywords: Reliability; Confusion Matrix; AI and Machine Learning; Decision Making; Measurement and Metrics; Performance

September 2024
Exercise

Finding Your 'Jagged Frontier': A Generative AI Exercise

By: Mitchell Weiss

In 2023 a set of scholars set out to study the effect of artificial intelligence (AI) on the quality and productivity of knowledge workers—in this specific instance, management consultants. They wanted to know across a range of tasks in a workflow, which, if any, would... View Details

Keywords: AI and Machine Learning; Performance Productivity; Performance Evaluation; Consulting Industry

November 2, 2021
Article

The Cultural Benefits of Artificial Intelligence in the Enterprise

By: Sam Ransbotham, François Candelon, David Kiron, Burt LaFountain and Shervin Khodabandeh

The 2021 MIT SMR-BCG report identifies a wide range of AI-related cultural benefits at both the team and organizational levels. Whether it’s reconsidering business assumptions or empowering teams, managing the dynamics across culture, AI use, and organizational... View Details

Keywords: AI and Machine Learning; Organizational Culture; Performance Effectiveness

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20 Oct 2022 - 22 Oct 2022
Talk

Stigma Against AI Companion Applications

By: Julian De Freitas, A. Ragnhildstveit and A.K. Uğuralp

Keywords: AI and Machine Learning; Attitudes; Perception

01 Sep 2011
News

Rolling Stock in Baker Exhibit

Railroads and the Transformation of Capitalism, an exhibit in the Baker Library | Bloomberg Center, confirms there is still much to learn about railroads, whose scale and complexity spawned modern business’s management model. Recent... View Details

Keywords: Museums, Historical Sites, and Similar Institutions; Arts, Entertainment; Colleges, Universities, and Professional Schools; Educational Services; Rail Transportation; Transportation

2025
Working Paper

Narrative AI and the Human-AI Oversight Paradox in Evaluating Early-Stage Innovations

By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang

Do AI-generated narrative explanations enhance human oversight or diminish it? We investigate this question through a field experiment with 228 evaluators screening 48 early-stage innovations under three conditions: human-only, black-box AI recommendations without... View Details

Keywords: Large Language Models; AI and Machine Learning; Innovation and Invention; Decision Making

02 Oct 2018
First Look

New Research and Ideas, October 2, 2018

policies. Download working paper: https://www.hbs.edu/faculty/Pages/item.aspx?num=55050 "Developing Theory Using Machine Learning Methods By: Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres... View Details

Keywords: Dina Gerdeman

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 2024 (Revised January 2025)
Technical Note

A Guide to the Vocabulary, Evolution, and Impact of Artificial Intelligence (AI)

By: Shane Greenstein, Nathaniel Lovin, Scott Wallsten, Kerry Herman and Susan Pinckney

A note on the vocabulary, evolution, and impact of AI. View Details

Keywords: Artificial Intelligence; Software; AI and Machine Learning; Technology Adoption; Technological Innovation; Technology Industry

March 2024
Teaching Note

'Storrowed': A Generative AI Exercise

By: Mitchell Weiss

Teaching Note for HBS Exercise No. 824-188. “Storrowed” is an exercise to help participants raise their proficiency with generative AI. It begins by highlighting a problem: trucks getting wedged underneath bridges in Boston, Massachusetts on the city’s Storrow Drive.... View Details

Keywords: AI and Machine Learning; Entrepreneurship; Innovation and Invention; Government Administration; Transportation Industry; Public Administration Industry

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