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

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11 Oct 2024
Research & Ideas

How AI Could Ease the Refugee Crisis and Bring New Talent to Businesses

says. “What we’re asking is, can we build algorithms that will help find better matches that will allow people to integrate more easily?” The paper presents data from Switzerland and the United States that showed promise in using machine... View Details

Keywords: by Ben Rand; Technology; Information Technology

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

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

Research Summary

Overview

Michael is interested in research at the intersection of technology and supply chain in corporations, especially retailers. His recent projects have focused on Human-AI collaboration at retailers. View Details

Keywords: Supply Chain Management; Supply Chain; Operations; AI and Machine Learning; Retail Industry

2025
Working Paper

Why Most Resist AI Companions

By: Julian De Freitas, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp and Stefano Puntoni

AI companion applications—designed to serve as synthetic interaction partners—have recently become capable enough to reduce loneliness, a growing public health concern. However, behavioral research has yet to fully explain the barriers to adoption of such AI and... View Details

Keywords: Generative Ai; Chatbots; Artificial Intelligence; Algorithmic Aversion; Lonelines; Technology Adoption; AI and Machine Learning; Well-being; Emotions

June 19, 2023
Article

Should You Start a Generative AI Company?

By: Julian De Freitas

Many entrepreneurs are considering starting companies that leverage the latest generative AI technology, but they must ask themselves whether they have what it takes to compete on increasingly commoditized foundational models, or whether they should instead... View Details

Keywords: Business Startups; Entrepreneurship; AI and Machine Learning; Applications and Software

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2025
Working Paper

Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers

By: Matthew DosSantos DiSorbo, Kris Ferreira, Maya Balakrishnan and Jordan Tong

Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). How can humans and algorithms work together to make... View Details

Keywords: AI and Machine Learning; Decision Choices and Conditions

2023
Article

Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators

By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill

Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details

Keywords: Regression Discontinuity Design; Analytics and Data Science; AI and Machine Learning

May 2022
Supplement

Borusan CAT: Monetizing Prediction in the Age of AI (B)

By: Navid Mojir and Gamze Yucaoglu

Borusan Cat is an international distributor of Caterpillar heavy machines. In 2021, it had been three years since Ozgur Gunaydin (CEO) and Esra Durgun (Director of Strategy, Digitization, and Innovation) started working on Muneccim, the company’s predictive AI tool.... View Details

Keywords: AI and Machine Learning; Commercialization; Technology Adoption; Industrial Products Industry; Turkey; Middle East

Frederick L. Maytag

As the founder of the Maytag Company, Maytag was renowned for his financial reliability and technical innovation. The company introduced several models of washing machines with great success, including the... View Details

Keywords: Fabricated Goods

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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16 Oct 2018
First Look

New Research and Ideas, October 16, 2018

Methods By: Choudhury, Prithwiraj, Ryan Allen, and Michael G. Endres Abstract—We describe how to employ machine learning (ML) methods in theory development. Compared to traditional causal inference methods,... View Details

Keywords: Dina Gerdeman

October 2019
Case

Feeling Machines: Emotion AI at Affectiva

By: Shane Greenstein and John Masko

In 2016, Affectiva—a Boston-based emotion AI software company with a long track record of building emotion-sensing software for market research—had attempted to expand into new verticals by releasing a mobile software development kit (SDK) that downloaders could adapt... View Details

Keywords: Artificial Intelligence; Market Research; Business Model; Finance; Revenue; Decision Making; Risk and Uncertainty; Market Entry and Exit; Applications and Software; AI and Machine Learning; Information Technology Industry; Auto Industry; United States

October 14, 2023
Article

Will Consumers Buy Selfish Self-Driving Cars?

By: Julian De Freitas

Keywords: AI and Machine Learning; Ethics; Technological Innovation; Safety; Auto Industry

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Working Paper

AI in Disguise—How AI-generated Ads' Visual Cues Shape Consumer Perception and Performance

By: Yannick Exner, Jochen Hartmann, Oded Netzer and Shunyuan Zhang

Generative AI’s recent advancements in creating content have offered vast potential to transform the advertising industry. This research investigates the impact of generative AI-enabled visual ad creation on real-world advertising effectiveness. For this purpose, we... View Details

Keywords: Digital Marketing; AI and Machine Learning; Advertising; Consumer Behavior; Advertising Industry

March 27, 2025
Article

How One Company Used AI to Broaden Its Customer Base

By: Sunil Gupta and Frank V. Cespedes

The software company SAP successfully leveraged AI tools to begin selling to the small and medium enterprises (SMEs) market, which had previously been uneconomical for its in-person sales approach. By mapping the customer journey and deploying over 40 AI tools, SAP... View Details

Keywords: AI and Machine Learning; Sales; Business Strategy; Market Entry and Exit

2024
Working Paper

The Wade Test: Generative AI and CEO Communication

By: Prithwiraj Choudhury, Bart S. Vanneste and Amirhossein Zohrehvand

Can generative artificial intelligence (Gen-AI) transform the role of the CEO? This study investigates whether Gen-AI can mimic a human CEO and whether employees display aversion to Gen-AI communication. We present a framework of Gen-AI aversion that distinguishes... View Details

Keywords: Business or Company Management; AI and Machine Learning; Perception; Communication

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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