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Publications

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  • All HBS Web  (955)
    • People  (1)
    • News  (156)
    • Research  (636)
    • Events  (13)
    • Multimedia  (3)
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Show Results For

  • All HBS Web  (955)
    • People  (1)
    • News  (156)
    • Research  (636)
    • Events  (13)
    • Multimedia  (3)
  • Faculty Publications  (542)
← Page 10 of 955 Results →

    Ta-Wei Huang

    Ta-Wei (David) Huang is a PhD candidate in Quantitative Marketing at Harvard Business School. His research integrates causal inference and machine learning to address methodological challenges and unintended consequences in targeting, personalization, and online... View Details
    • November 2024
    • Supplement

    AlphaGo (C): Birth of a New Intelligence

    By: Shikhar Ghosh and Shweta Bagai
    This case, the final of a three-part series, explores DeepMind's pivotal transition from mastering games to solving real-world scientific challenges. In December 2020, DeepMind's AI system AlphaFold 2 achieved a breakthrough by solving protein folding—a 50-year-old... View Details
    Keywords: Autonomy; Deep Learning; Drug Discovery; Healthcare Innovation; Neural Networks; Scientific Research; Technology Startup; AI and Machine Learning; Technological Innovation; Research and Development; Business Model; Business Strategy; Open Source Distribution; Technology Industry; United States
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    Ghosh, Shikhar, and Shweta Bagai. "AlphaGo (C): Birth of a New Intelligence." Harvard Business School Supplement 825-075, November 2024.
    • December 1984
    • Case

    Expense Tracking System at Tiger Creek

    By: Shoshana Zuboff
    Mill manager Carl Adelman learns that a group of senior managers is soon to visit the Tiger Creek mill to learn more about the success of the newly implemented Expense Tracking System. The System had been installed on two paper machines to give workers real time cost... View Details
    Keywords: Management Teams; Success; Cost Management; Technology; Pulp and Paper Industry
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    Zuboff, Shoshana. "Expense Tracking System at Tiger Creek." Harvard Business School Case 485-057, December 1984.
    • Research Summary

    Understanding the Limitations of Model Explanations

    By: Himabindu Lakkaraju
    The goal of this research is to understand how adversaries can exploit various algorithms used for explaining complex machine learning models with an intention to mislead end users. For instance, can adversaries trick these algorithms into masking their racial and... View Details
    • 20 Nov 2024
    • HBS Seminar

    Marc Rotenberg, Georgetown University Law

    • December 2018 (Revised March 2021)
    • Background Note

    Modern Automation (A): Artificial Intelligence

    By: William R. Kerr and James Palano
    This primer is meant to be a field guide to the late 2010s' surge in business use of "Artificial Intelligence" (AI), or enterprise software based in machine learning. First, it provides an overview of the key trends—digitization, connectivity, the continuation of... View Details
    Keywords: Artificial Intelligence; Digitization; Connectivity; Computing; Future Of Work; Automation; AI and Machine Learning
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    Kerr, William R., and James Palano. "Modern Automation (A): Artificial Intelligence." Harvard Business School Background Note 819-084, December 2018. (Revised March 2021.)
    • August 2021 (Revised November 2024)
    • Case

    Intenseye: Powering Workplace Health and Safety with AI (A)

    By: Michael W. Toffel and Youssef Abdel Aal
    Intenseye was a Turkey-based technology startup that deployed machine learning algorithms to workplace camera feeds in order to identify unsafe worker actions and unsafe working conditions, in order to help improve worker safety. The case describes how Intenseye’s... View Details
    Keywords: Privacy; Product Development; Operations; Technological Innovation; Value Creation; Production; Distribution; Safety; Risk and Uncertainty; Technology Industry; Manufacturing Industry; Distribution Industry; Turkey; Middle East; United States
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    Toffel, Michael W., and Youssef Abdel Aal. "Intenseye: Powering Workplace Health and Safety with AI (A)." Harvard Business School Case 622-037, August 2021. (Revised November 2024.)
    • February 2018
    • Case

    Vodafone: Managing Advanced Technologies and Artificial Intelligence

    By: William R. Kerr and Emer Moloney
    Vodafone was operating in the fast-moving telecommunications market where innovation and scale were key. Faced with an onslaught of technological advances—big data, automation, and artificial intelligence—CEO Vittorio Colao reflected on how he should change the... View Details
    Keywords: Technological Innovation; Management; Organizational Change and Adaptation; Corporate Social Responsibility and Impact; Opportunities; Telecommunications Industry
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    Kerr, William R., and Emer Moloney. "Vodafone: Managing Advanced Technologies and Artificial Intelligence." Harvard Business School Case 318-109, February 2018.
    • 28 Mar 2017
    • Working Paper Summaries

    CEO Behavior and Firm Performance

    Keywords: by Oriana Bandiera, Stephen Hansen, Andrea Pratt, and Raffaella Sadun

      Jeremy Yang

      Jeremy Yang is an Assistant Professor of Business Administration in the Marketing Unit at Harvard Business School. He teaches Marketing in the MBA required curriculum. He develops data products for... View Details
      Keywords: advertising; media; entertainment; information; consumer products
      • 13 Sep 2018
      • HBS Seminar

      Nitin Joglekar, Boston University

      • Research Summary

      Overview

      By: Isamar Troncoso
      Professor Troncoso's research explores problems related to digital marketplaces and AI applications in marketing, and combines toolkits from econometrics, causal inference, and machine learning. She has studied how different platform design choices can lead to... View Details
      • December 2020 (Revised April 2021)
      • Case

      IBM Watson at MD Anderson Cancer Center

      By: Shane Greenstein, Mel Martin and Sarkis Agaian
      After discovering that their cancer diagnostic tool, designed to leverage the cloud computing power of IBM Watson, needed greater integration into the clinical processes at the MD Anderson Cancer Center, the development team had difficult choices to make. The Oncology... View Details
      Keywords: Decision Making; Innovation Strategy; Knowledge Management; Knowledge Use and Leverage; Operations; Failure; Information Technology; Applications and Software; Health Care and Treatment; Product Development; Health Industry; Information Technology Industry; Technology Industry; United States; Houston; Texas
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      Greenstein, Shane, Mel Martin, and Sarkis Agaian. "IBM Watson at MD Anderson Cancer Center." Harvard Business School Case 621-022, December 2020. (Revised April 2021.)
      • 26 Mar 2025
      • News

      Behind the Research: Elisabeth Paulson

        Jenny Wang

        Jenny Shan Wang is a doctoral student in the Technology and Operations Management program at Harvard Business School (HBS). She is broadly interested in interpretable machine learning (ML), identity and inequality, and improving existing methods... View Details
        • January 2019 (Revised October 2019)
        • Case

        Liulishuo: AI English Teacher

        By: John J-H Kim and Shu Lin
        Educators and entrepreneurs alike are excited about the potential for artificial intelligence (AI) and machine learning to change the way learning will look like in the future. There is a confluence of factors such as the availability of large sources of rich,... View Details
        Keywords: AI; Artificial Intelligence; Education Technology; Information Technology; Education; Entrepreneurship; AI and Machine Learning; Education Industry; China
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        Kim, John J-H, and Shu Lin. "Liulishuo: AI English Teacher." Harvard Business School Case 319-090, January 2019. (Revised October 2019.)
        • 2022
        • Working Paper

        Rethinking Explainability as a Dialogue: A Practitioner's Perspective

        By: Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan and Sameer Singh
        As practitioners increasingly deploy machine learning models in critical domains such as healthcare, finance, and policy, it becomes vital to ensure that domain experts function effectively alongside these models. Explainability is one way to bridge the gap between... View Details
        Keywords: Natural Language Conversations; AI and Machine Learning; Experience and Expertise; Interactive Communication; Business and Stakeholder Relations
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        Lakkaraju, Himabindu, Dylan Slack, Yuxin Chen, Chenhao Tan, and Sameer Singh. "Rethinking Explainability as a Dialogue: A Practitioner's Perspective." Working Paper, 2022.
        • 19 Jan 2023
        • Research & Ideas

        What Makes Employees Trust (vs. Second-Guess) AI?

        products were grouped in 241 “style-colors'' and sizes. When the allocators received a recommendation from an interpretable algorithm, they often overruled it based on their own intuition. But when the same allocators had a recommendation from a similarly accurate... View Details
        Keywords: by Rachel Layne
        • 08 Mar 2017
        • HBS Seminar

        Fernanda Viégas and Martin Wattenberg, Google

        • 19 Oct 2021
        • HBS Seminar

        Cynthia Rudin, Duke University

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