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      • Faculty Publications  (424)

      Machine LearningRemove Machine Learning →

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      • November 2023 (Revised April 2024)
      • Case

      Khanmigo: Revolutionizing Learning with GenAI

      By: William A. Sahlman, Allison M. Ciechanover and Emily Grandjean
      Already a leader in the edtech space since its 2008 launch, Khan Academy was now one of the first edtech organizations to embrace generative artificial intelligence ("genAI"). In March 2023, Khan Academy began beta testing Khanmigo, a genAI “guide” and tutor built with... View Details
      Keywords: Technology Adoption; Leading Change; Entrepreneurship; Risk and Uncertainty; Education; AI and Machine Learning; Corporate Social Responsibility and Impact; Education Industry; Technology Industry; United States; San Francisco
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      Sahlman, William A., Allison M. Ciechanover, and Emily Grandjean. "Khanmigo: Revolutionizing Learning with GenAI." Harvard Business School Case 824-059, November 2023. (Revised April 2024.)
      • November–December 2023
      • Article

      Keep Your AI Projects on Track

      By: Iavor Bojinov
      AI—and especially its newest star, generative AI—is today a central theme in corporate boardrooms, leadership discussions, and casual exchanges among employees eager to supercharge their productivity. Sadly, beneath the aspirational headlines and tantalizing potential... View Details
      Keywords: Generative Models; AI and Machine Learning; Success; Failure; Product Development; Technology Adoption
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      Bojinov, Iavor. "Keep Your AI Projects on Track." Harvard Business Review 101, no. 6 (November–December 2023): 53–59.
      • November 2023
      • Article

      Psychological Factors Underlying Attitudes toward AI Tools

      By: Julian De Freitas, Stuti Agarwal, B. Schmitt and N. Haslam
      What are the psychological factors driving attitudes toward AI tools, and how can resistance to AI systems be overcome when they are beneficial? In this perspective, we first organize the main sources of resistance into five main categories: opacity, emotionlessness,... View Details
      Keywords: Policy; Self; AI and Machine Learning; Attitudes; Technology Adoption
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      De Freitas, Julian, Stuti Agarwal, B. Schmitt, and N. Haslam. "Psychological Factors Underlying Attitudes toward AI Tools." Nature Human Behaviour 7, no. 11 (November 2023): 1845–1854.
      • 2023
      • Working Paper

      The Optimal Stock Valuation Ratio

      By: Sebastian Hillenbrand and Odhrain McCarthy
      Trailing price ratios, such as the price-dividend and the price-earnings ratio, scale prices by trailing cash flow measures. They theoretically contain expected returns, yet, their performance in predicting stock market returns is poor. This is because of an omitted... View Details
      Keywords: Price; Investment Return; AI and Machine Learning; Valuation; Cash Flow; Forecasting and Prediction
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      Hillenbrand, Sebastian, and Odhrain McCarthy. "The Optimal Stock Valuation Ratio." Working Paper, November 2023.
      • October 2023 (Revised January 2025)
      • Case

      Sydney Loves Kevin

      By: Ryan W. Buell and Himabindu Lakkaraju
      Kevin Roose was a columnist and podcast host for the New York Times, who focused on technology and its effects on society. When Microsoft launched the latest version of its search engine Bing in February 2023, the company invited Roose to its Redmond campus to... View Details
      Keywords: Newspapers; AI and Machine Learning; Technology Adoption; Technological Innovation; Perspective; Media and Broadcasting Industry; Technology Industry
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      Buell, Ryan W., and Himabindu Lakkaraju. "Sydney Loves Kevin." Harvard Business School Case 624-039, October 2023. (Revised January 2025.)
      • October 2023
      • Teaching Note

      Timnit Gebru: 'SILENCED No More' on AI Bias and The Harms of Large Language Models

      By: Tsedal Neeley and Tim Englehart
      Teaching Note for HBS Case No. 422-085. Dr. Timnit Gebru—a leading artificial intelligence (AI) computer scientist and co-lead of Google’s Ethical AI team—was messaging with one of her colleagues when she saw the words: “Did you resign?? Megan sent an email saying that... View Details
      Keywords: Ethics; Employment; Corporate Social Responsibility and Impact; Technological Innovation; AI and Machine Learning; Diversity; Prejudice and Bias; Technology Industry
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      Neeley, Tsedal, and Tim Englehart. "Timnit Gebru: 'SILENCED No More' on AI Bias and The Harms of Large Language Models." Harvard Business School Teaching Note 424-028, October 2023.
      • October 2023 (Revised June 2024)
      • Case

      ReUp Education: Can AI Help Learners Return to College?

      By: Kris Ferreira, Christopher Thomas Ryan and Sarah Mehta
      Founded in 2015, ReUp Education helps “stopped out students”—learners who have stopped making progress towards graduation—achieve their college completion goals. The company relies on a team of success coaches to engage with learners and help them reenroll. In 2019,... View Details
      Keywords: AI; Algorithms; Machine Learning; Edtech; Education Technology; Analysis; Higher Education; AI and Machine Learning; Customization and Personalization; Failure; Education Industry; Technology Industry; United States
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      Ferreira, Kris, Christopher Thomas Ryan, and Sarah Mehta. "ReUp Education: Can AI Help Learners Return to College?" Harvard Business School Case 624-007, October 2023. (Revised June 2024.)
      • October 2023
      • Case

      Fixie and Conversational AI Sidekicks

      By: Jeffrey J. Bussgang and Carin-Isabel Knoop
      In March 2023, Fixie Co-Founder and Chief Architect Matt Welsh and co-founders had the kind of meeting no founders want to have. The president of leading artificial intelligence (AI) research and deployment firm OpenAI, which had catapulted into fame with its ChatGPT... View Details
      Keywords: Large Language Model; Entrepreneurship; Decision Choices and Conditions; AI and Machine Learning; Technological Innovation; Competitive Strategy; Technology Industry; United States
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      Bussgang, Jeffrey J., and Carin-Isabel Knoop. "Fixie and Conversational AI Sidekicks." Harvard Business School Case 824-037, October 2023.
      • October 2023 (Revised February 2024)
      • Case

      Loris

      By: Shunyuan Zhang, Das Narayandas, Stacy Straaberg and David Lane
      In December 2022, Loris’s executive team considered their go-to-market strategy. Loris was an artificial intelligence (AI) software startup for the customer service industry with two products on the market: 1) Agent Assist which provided customer service agents (CSAs)... View Details
      Keywords: Decisions; Growth and Development Strategy; Product Launch; Product Positioning; Business Strategy; Competitive Strategy; Business Startups; AI and Machine Learning; Applications and Software; Marketing Strategy; Sales; Technology Industry; United States
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      Zhang, Shunyuan, Das Narayandas, Stacy Straaberg, and David Lane. "Loris." Harvard Business School Case 524-010, October 2023. (Revised February 2024.)
      • 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
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      Olagoke, Lukman, Salil Vadhan, and Seth Neel. "Black-box Training Data Identification in GANs via Detector Networks." Working Paper, October 2023.
      • October 2023
      • Article

      Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA

      By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
      We study how a regulator can best target inspections. Our case study is a U.S. Occupational Safety and Health Administration (OSHA) program that randomly allocated some inspections. On average, each inspection averted 2.4 serious injuries (9%) over the next five years.... View Details
      Keywords: Safety Regulations; Regulations; Regulatory Enforcement; Machine Learning Models; Safety; Operations; Service Operations; Production; Forecasting and Prediction; Decisions; United States
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      Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Improving Regulatory Effectiveness Through Better Targeting: Evidence from OSHA." American Economic Journal: Applied Economics 15, no. 4 (October 2023): 30–67. (Profiled in the Regulatory Review.)
      • 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.
      • 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
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      Padilla, Nicolas, Eva Ascarza, and Oded Netzer. "The Customer Journey as a Source of Information." Harvard Business School Working Paper, No. 24-035, October 2023. (Revised October 2023.)
      • 2025
      • Working Paper

      The Impact of Input Inaccuracy on Leveraging AI Tools: Evidence from Algorithmic Labor Scheduling

      By: Caleb Kwon, Antonio Moreno and Ananth Raman
      Problem Definition: Considerable academic and practitioner attention is placed on the value of ex-post interactions (i.e., overrides) in the human-AI interface. In contrast, relatively little attention has been paid to ex-ante human-AI interactions (e.g., the... View Details
      Keywords: AI and Machine Learning; Employees; Performance Effectiveness
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      Kwon, Caleb, Antonio Moreno, and Ananth Raman. "The Impact of Input Inaccuracy on Leveraging AI Tools: Evidence from Algorithmic Labor Scheduling." Working Paper, January 2025.
      • 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.
      • September 29, 2023
      • Article

      Eliminating Algorithmic Bias Is Just the Beginning of Equitable AI

      By: Simon Friis and James Riley
      When it comes to artificial intelligence and inequality, algorithmic bias rightly receives a lot of attention. But it’s just one way that AI can lead to inequitable outcomes. To truly create equitable AI, we need to consider three forces through which it might make... View Details
      Keywords: AI and Machine Learning; Prejudice and Bias; Equality and Inequality
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      Friis, Simon, and James Riley. "Eliminating Algorithmic Bias Is Just the Beginning of Equitable AI." Harvard Business Review (website) (September 29, 2023).
      • September 2023
      • Case

      Ada: Cultivating Investors

      By: Reza Satchu and Patrick Sanguineti
      Mike Murchison, co-founder and CEO of Ada, has an enviable dilemma. Launched in 2016 by Murchison and his co-founder David Hariri, Ada is an AI-native company that aims to revolutionize how businesses approach customer service. The company has already attracted a buzz,... View Details
      Keywords: Founder; Fundraising; Business Startups; Decisions; Entrepreneurship; Venture Capital; AI and Machine Learning; Technology Industry
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      Satchu, Reza, and Patrick Sanguineti. "Ada: Cultivating Investors." Harvard Business School Case 824-090, September 2023.
      • September 2023 (Revised December 2023)
      • Case

      TetraScience: Noise and Signal

      By: Thomas R. Eisenmann and Tom Quinn
      In 2019, TetraScience CEO “Spin” Wang needed advice. Five years earlier, he had cofounded a startup that saw early success with a hardware product designed to help laboratory scientists in the biotechnology and pharmaceutical spaces more easily collect data from... View Details
      Keywords: Entrepreneurship; Business Growth and Maturation; Business Organization; Restructuring; Forecasting and Prediction; Digital Platforms; Analytics and Data Science; AI and Machine Learning; Organizational Structure; Network Effects; Competitive Strategy; Biotechnology Industry; Pharmaceutical Industry; United States; Boston
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      Eisenmann, Thomas R., and Tom Quinn. "TetraScience: Noise and Signal." Harvard Business School Case 824-024, September 2023. (Revised December 2023.)
      • 2023
      • Working Paper

      Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality

      By: Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani
      The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine... View Details
      Keywords: Large Language Model; AI and Machine Learning; Performance Efficiency; Performance Improvement
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      Dell'Acqua, Fabrizio, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, and Karim R. Lakhani. "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality." Harvard Business School Working Paper, No. 24-013, September 2023.
      • September 2023 (Revised January 2024)
      • Case

      AI21 Labs in 2023: Strategy for Generative AI

      By: David Yoffie, Orna Dan and Elena Corsi
      Israeli generative artificial intelligence company AI21 Labs was founded in 2017 to realize the vision of true machine intelligence. It sought to reinvent writing and reading and in 2020 it launched Wordtune, an app using GenAI software to offer alternate text... View Details
      Keywords: Decision Making; AI and Machine Learning; Innovation Strategy; Growth and Development Strategy; Applications and Software; Competitive Strategy; Technology Industry; Israel
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      Yoffie, David, Orna Dan, and Elena Corsi. "AI21 Labs in 2023: Strategy for Generative AI." Harvard Business School Case 724-383, September 2023. (Revised January 2024.)
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