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  • All HBS Web  (1,658)
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    • Multimedia  (84)
  • Faculty Publications  (583)
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  • 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
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Greenstein, Shane, Nathaniel Lovin, Scott Wallsten, Kerry Herman, and Susan Pinckney. "A Guide to the Vocabulary, Evolution, and Impact of Artificial Intelligence (AI)." Harvard Business School Technical Note 625-039, December 2024. (Revised January 2025.)
  • 2023
  • Working Paper

In-Context Unlearning: Language Models as Few Shot Unlearners

By: Martin Pawelczyk, Seth Neel and Himabindu Lakkaraju
Machine unlearning, the study of efficiently removing the impact of specific training points on the trained model, has garnered increased attention of late, driven by the need to comply with privacy regulations like the Right to be Forgotten. Although unlearning is... View Details
Keywords: AI and Machine Learning; Copyright; Information
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Pawelczyk, Martin, Seth Neel, and Himabindu Lakkaraju. "In-Context Unlearning: Language Models as Few Shot Unlearners." Working Paper, October 2023.
  • 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
  • 2023
  • Working Paper

Sending Signals: Strategic Displays of Warmth and Competence

By: Bushra S. Guenoun and Julian J. Zlatev
Using a combination of exploratory and confirmatory approaches, this research examines how people signal important information about themselves to others. We first train machine learning models to assess the use of warmth and competence impression management... View Details
Keywords: AI and Machine Learning; Personal Characteristics; Perception; Interpersonal Communication
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Guenoun, Bushra S., and Julian J. Zlatev. "Sending Signals: Strategic Displays of Warmth and Competence." Harvard Business School Working Paper, No. 23-051, February 2023.
  • 16 Jul 2024
  • Research & Ideas

Weighing Digital Tradeoffs in Private Equity

answer that question, the researchers compared the performance of companies that had undergone some level of digital transformation with those that didn’t. They found that: Expanding IT budgets increased hiring by 11 percent and sales by 9 percent. Adding View Details
Keywords: by Michael Blanding; Financial Services
  • December 2020
  • Supplement

VIA Science (B)

By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details
Keywords: Data Analytics; Machine Learning; Artificial Intelligence; Strategy; Business Startups; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan
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Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (B)." Harvard Business School Supplement 721-368, December 2020.
  • March 2022 (Revised January 2025)
  • Technical Note

Prediction & Machine Learning

By: Iavor I. Bojinov, Michael Parzen and Paul Hamilton
This note provides an introduction to machine learning for an introductory data science course. The note begins with a description of supervised, unsupervised, and reinforcement learning. Then, the note provides a brief explanation of the difference between traditional... View Details
Keywords: Machine Learning; Data Science; Learning; Analytics and Data Science; Performance Evaluation; AI and Machine Learning
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Bojinov, Iavor I., Michael Parzen, and Paul Hamilton. "Prediction & Machine Learning." Harvard Business School Technical Note 622-101, March 2022. (Revised January 2025.)
  • 2024
  • Article

Learning Under Random Distributional Shifts

By: Kirk Bansak, Elisabeth Paulson and Dominik Rothenhäusler
Algorithmic assignment of refugees and asylum seekers to locations within host countries has gained attention in recent years, with implementations in the U.S. and Switzerland. These approaches use data on past arrivals to generate machine learning models that can... View Details
Keywords: AI and Machine Learning; Refugees; Employment
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Bansak, Kirk, Elisabeth Paulson, and Dominik Rothenhäusler. "Learning Under Random Distributional Shifts." Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) 27th (2024).
  • October–December 2022
  • Article

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
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Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
  • 2021
  • Chapter

Towards a Unified Framework for Fair and Stable Graph Representation Learning

By: Chirag Agarwal, Himabindu Lakkaraju and Marinka Zitnik
As the representations output by Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes important to ensure that these representations are fair and stable. In this work, we establish a key connection between counterfactual... View Details
Keywords: Graph Neural Networks; AI and Machine Learning; Prejudice and Bias
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Agarwal, Chirag, Himabindu Lakkaraju, and Marinka Zitnik. "Towards a Unified Framework for Fair and Stable Graph Representation Learning." In Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence, edited by Cassio de Campos and Marloes H. Maathuis, 2114–2124. AUAI Press, 2021.
  • May–June 2024
  • Article

Should Your Brand Hire a Virtual Influencer?

By: Serim Hwang, Shunyuan Zhang, Xiao Liu and Kannan Srinivasan
Followers respond more favorably to sponsored posts by virtual influencers versus those by humans, costs are lower, and creating an influencer from scratch allows marketers to introduce more diversity. View Details
Keywords: Social Media; AI and Machine Learning; Brands and Branding; Power and Influence
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Hwang, Serim, Shunyuan Zhang, Xiao Liu, and Kannan Srinivasan. "Should Your Brand Hire a Virtual Influencer?" Harvard Business Review 102, no. 3 (May–June 2024): 56–60.
  • August 2024
  • Background Note

Mitigating Climate Change with Machine Learning

By: Michael W. Toffel, Kelsey Carter, Amy Chambers, Avery Park and Susan Pinckney
This note highlights how machine learning is being used to decarbonize (reduce GHG emissions) several key sectors including electricity, transportation, building, industrial processes, and agriculture -- and how machine learning is being used to accelerate efforts to... View Details
Keywords: Climate; Artificial Intelligence; Adaptation; Climate Change; AI and Machine Learning; Innovation and Invention
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Toffel, Michael W., Kelsey Carter, Amy Chambers, Avery Park, and Susan Pinckney. "Mitigating Climate Change with Machine Learning." Harvard Business School Background Note 625-014, August 2024.
  • November–December 2024
  • Article

Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing

By: Kirk Bansak and Elisabeth Paulson
This study proposes two new dynamic assignment algorithms to match refugees and asylum seekers to geographic localities within a host country. The first, currently implemented in a multi-year pilot in Switzerland, seeks to maximize the average predicted employment... View Details
Keywords: AI and Machine Learning; Refugees; Geographic Location; Employment
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Bansak, Kirk, and Elisabeth Paulson. "Outcome-Driven Dynamic Refugee Assignment with Allocation Balancing." Operations Research 72, no. 6 (November–December 2024): 2375–2390.
  • December 2018
  • Teaching Note

Autonomous Vehicles: The Rubber Hits the Road…but When?

By: William Kerr and James Palano
The autonomous vehicles have enormous implications for business and society. But, despite the headline-laden attention paid to the technology, there remain more questions than answers. Students will learn about the complex industry and have explicit discussions about... View Details
Keywords: Technology Management; Artificial Intelligence; General Management; Robotics; Technological Innovation; Transportation; Disruption; Information Technology; Management; Decision Making; AI and Machine Learning; Auto Industry; Technology Industry
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Kerr, William, and James Palano. "Autonomous Vehicles: The Rubber Hits the Road…but When?" Harvard Business School Teaching Note 819-040, December 2018.
  • 2023
  • Article

Experimental Evaluation of Individualized Treatment Rules

By: Kosuke Imai and Michael Lingzhi Li
The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a... View Details
Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning
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Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
  • December 2020
  • Case

VIA Science (A)

By: Juan Alcácer, Rembrand Koning, Annelena Lobb and Kerry Herman
Via (a) captures the early days of the data analytics startup as founders Gounden and Ravanis considered which markets offer the right opportunities for their firm and what kinds of experiments will help them narrow their choice. Supplement Via (b) reveals the... View Details
Keywords: Data Analytics; Machine Learning; Artificial Intelligence; Strategy; Business Startups; Markets; AI and Machine Learning; Telecommunications Industry; Utilities Industry; United States; Japan
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Alcácer, Juan, Rembrand Koning, Annelena Lobb, and Kerry Herman. "VIA Science (A)." Harvard Business School Case 721-367, December 2020.
  • March 16, 2021
  • Article

From Driverless Dilemmas to More Practical Commonsense Tests for Automated Vehicles

By: Julian De Freitas, Andrea Censi, Bryant Walker Smith, Luigi Di Lillo, Sam E. Anthony and Emilio Frazzoli
For the first time in history, automated vehicles (AVs) are being deployed in populated environments. This unprecedented transformation of our everyday lives demands a significant undertaking: endowing complex autonomous systems with ethically acceptable behavior. We... View Details
Keywords: Automated Driving; Public Health; Artificial Intelligence; Transportation; Health; Ethics; Policy; AI and Machine Learning
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De Freitas, Julian, Andrea Censi, Bryant Walker Smith, Luigi Di Lillo, Sam E. Anthony, and Emilio Frazzoli. "From Driverless Dilemmas to More Practical Commonsense Tests for Automated Vehicles." Proceedings of the National Academy of Sciences 118, no. 11 (March 16, 2021).
  • February 2024
  • Teaching Note

Data-Driven Denim: Financial Forecasting at Levi Strauss

By: Mark Egan
Teaching Note for HBS Case No. 224-029. Levi Strauss & Co. (“Levi Strauss”) partnered with the IT services company Wipro to incorporate more sophisticated methods, such as machine learning, into their financial forecasting process starting in 2018. The decision to... View Details
Keywords: Forecasting; Regression; Machine Learning; Artificial Intelligence; Apparel; Corporate Finance; Forecasting and Prediction; AI and Machine Learning; Apparel and Accessories Industry; United States
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Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Teaching Note 224-073, February 2024.
  • May 2022
  • Article

Coins for Bombs: The Predictive Ability of On-Chain Transfers for Terrorist Attacks

By: Dan Amiram, Evgeny Lyandres and Daniel Rabetti
This study examines whether we can learn from the behavior of blockchain-based transfers to predict the financing of terrorist attacks. We exploit blockchain transaction transparency to map millions of transfers for hundreds of large on-chain service providers. The... View Details
Keywords: Blockchain; Bitcoin; Accounting; AI and Machine Learning; National Security; Governing Rules, Regulations, and Reforms
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Amiram, Dan, Evgeny Lyandres, and Daniel Rabetti. "Coins for Bombs: The Predictive Ability of On-Chain Transfers for Terrorist Attacks." Journal of Accounting Research 60, no. 2 (May 2022): 427–466.
  • 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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De Freitas, Julian. "Will Consumers Buy Selfish Self-Driving Cars?" Wall Street Journal (October 14, 2023), C5.
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