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      • 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
      • Case

      Recruit Holdings Co. Ltd.: Managing Innovation and Trust in the Age of AI

      By: Sandra J. Sucher, Marilyn Morgan Westner and Bethelehem Y Araya
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      Sucher, Sandra J., Marilyn Morgan Westner, and Bethelehem Y Araya. "Recruit Holdings Co. Ltd.: Managing Innovation and Trust in the Age of AI." Harvard Business School Case 324-025, October 2023.
      • October 2023
      • Supplement

      Recruit Holdings Co. Ltd.: Managing Innovation and Trust in the Age of AI (B)

      By: Sandra J. Sucher, Marilyn Morgan Westner and Bethelehem Y Araya
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      Sucher, Sandra J., Marilyn Morgan Westner, and Bethelehem Y Araya. "Recruit Holdings Co. Ltd.: Managing Innovation and Trust in the Age of AI (B)." Harvard Business School Supplement 324-026, 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.
      • 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 2023 (Revised March 2025)
      • Teaching Note

      Accelerating AI Adoption in the U.S. Air Force

      By: Maria P. Roche
      Teaching Note for HBS Case No. 723-429. View Details
      Keywords: AI; "USA,"; Military; Strategy; Innovation; Economic Growth; Organizational Design; Technology
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      Roche, Maria P. "Accelerating AI Adoption in the U.S. Air Force." Harvard Business School Teaching Note 724-386, September 2023. (Revised March 2025.)
      • 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.)
      • September 2023 (Revised April 2024)
      • Case

      Atomwise: Strategic Opportunities in AI for Pharma

      By: Satish Tadikonda
      Abraham Heifets and his co-founder, Izhar Wallach, had founded Atomwise to develop i) an AI engine to transform drug discovery by creating better medicines faster, and ii) a machine learning-based discovery engine that combined the power of convolutional neural... View Details
      Keywords: Business Model; Business Startups; AI and Machine Learning; Science-Based Business; Technological Innovation; Biotechnology Industry; Pharmaceutical Industry
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      Tadikonda, Satish. "Atomwise: Strategic Opportunities in AI for Pharma." Harvard Business School Case 824-043, September 2023. (Revised April 2024.)
      • September 2023
      • Case

      Super Quantum: Using Artificial Intelligence to Transform Asset Management (A)

      By: Feng Zhu and Kerry Herman
      Dr. Zhang, CEO of Super Quantum, an AI-driven hedge fund, is considering an investor’s request to withdraw their funds as the markets experience volatility. Should he pull the investor’s funds? View Details
      Keywords: AI and Machine Learning; Volatility; Financial Markets; Investment Funds; Decision Choices and Conditions; Financial Services Industry
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      Zhu, Feng, and Kerry Herman. "Super Quantum: Using Artificial Intelligence to Transform Asset Management (A)." Harvard Business School Case 624-027, September 2023.
      • 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
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      Gao, Ruijiang, and Himabindu Lakkaraju. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.
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