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Publications

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    • All HBS Web  (1,272)
      • Faculty Publications  (419)

      AI and Machine LearningRemove AI and Machine Learning →

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      • January 2017 (Revised March 2017)
      • Case

      IBM Transforming, 2012–2016: Ginni Rometty Steers Watson

      By: Rosabeth Moss Kanter and Jonathan Cohen
      To transform IBM for the next technology wave, Ginni Rometty, who became CEO in 2012, led divestment of declining businesses, made acquisitions in digital innovation and cloud computing, formed partnerships with former competitors such as Apple and tech startups, and... View Details
      Keywords: Digital; Technological Change; Artificial Intelligence; Data; IBM; Watson; Internet Of Things; Innovation and Invention; Management; Sales; Information Technology; Technological Innovation; Transformation; AI and Machine Learning
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      Kanter, Rosabeth Moss, and Jonathan Cohen. "IBM Transforming, 2012–2016: Ginni Rometty Steers Watson." Harvard Business School Case 317-046, January 2017. (Revised March 2017.)
      • 18 Nov 2016
      • Conference Presentation

      Rawlsian Fairness for Machine Learning

      By: Matthew Joseph, Michael J. Kearns, Jamie Morgenstern, Seth Neel and Aaron Leon Roth
      Motivated by concerns that automated decision-making procedures can unintentionally lead to discriminatory behavior, we study a technical definition of fairness modeled after John Rawls' notion of "fair equality of opportunity". In the context of a simple model of... View Details
      Keywords: Machine Learning; Algorithms; Fairness; Decision Making; Mathematical Methods
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      Joseph, Matthew, Michael J. Kearns, Jamie Morgenstern, Seth Neel, and Aaron Leon Roth. "Rawlsian Fairness for Machine Learning." Paper presented at the 3rd Workshop on Fairness, Accountability, and Transparency in Machine Learning, Special Interest Group on Knowledge Discovery and Data Mining (SIGKDD), November 18, 2016.
      • July 2016
      • Case

      Spotify

      By: Anita Elberse and Alexandre de Pfyffer
      In November 2014, Spotify's chief content officer Ken Parks learns that record label Big Machine Records has requested the immediate removal of superstar artist Taylor Swift's entire catalogue from Spotify's music streaming service. Is it time for Spotify to reconsider... View Details
      Keywords: Entertainment; Marketing; Superstar; Music; Entertainment Marketing; Media; Digital Technology; Creative Industries; Product Portfolio Management; General Management; Management; Strategy; Internet and the Web; Open Source Distribution; Creativity; Music Entertainment; Product Marketing; Music Industry
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      Elberse, Anita, and Alexandre de Pfyffer. "Spotify." Harvard Business School Case 516-046, July 2016.
      • June 2016 (Revised August 2019)
      • Case

      Numenta: Inventing and (or) Commercializing AI

      By: David B. Yoffie, Liz Kind and David Ben Shimol
      In March 2016, Donna Dubinsky (co-founder and CEO) and Jeff Hawkins (co-founder) were struggling with a key question: Could Numenta be successful in both creating fundamental technology and building a commercial business? Located in Redwood City, CA, Numenta was... View Details
      Keywords: Artificial Intelligence; Machine Intelligence; Machine Learning; Strategy; Business Model; Entrepreneurship; Information; Technological Innovation; Research; Research and Development; Information Technology; Applications and Software; Technology Adoption; Digital Platforms; Commercialization; AI and Machine Learning
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      Yoffie, David B., Liz Kind, and David Ben Shimol. "Numenta: Inventing and (or) Commercializing AI." Harvard Business School Case 716-469, June 2016. (Revised August 2019.)
      • Article

      Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy

      By: Edward Glaeser, Andrew Hillis, Scott Duke Kominers and Michael Luca
      The proliferation of big data makes it possible to better target city services like hygiene inspections, but city governments rarely have the in-house talent needed for developing prediction algorithms. Cities could hire consultants, but a cheaper alternative is to... View Details
      Keywords: User-generated Content; Operations; Tournaments; Policy-making; Machine Learning; Online Platforms; Analytics and Data Science; Mathematical Methods; City; Infrastructure; Business Processes; Government and Politics
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      Glaeser, Edward, Andrew Hillis, Scott Duke Kominers, and Michael Luca. "Crowdsourcing City Government: Using Tournaments to Improve Inspection Accuracy." American Economic Review: Papers and Proceedings 106, no. 5 (May 2016): 114–118.
      • Winter 2016
      • Article

      Analytics for an Online Retailer: Demand Forecasting and Price Optimization

      By: Kris J. Ferreira, Bin Hong Alex Lee and David Simchi-Levi
      We present our work with an online retailer, Rue La La, as an example of how a retailer can use its wealth of data to optimize pricing decisions on a daily basis. Rue La La is in the online fashion sample sales industry, where they offer extremely limited-time... View Details
      Keywords: Internet and the Web; Price; Forecasting and Prediction; Revenue; Sales; Retail Industry
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      Ferreira, Kris J., Bin Hong Alex Lee, and David Simchi-Levi. "Analytics for an Online Retailer: Demand Forecasting and Price Optimization." Manufacturing & Service Operations Management 18, no. 1 (Winter 2016): 69–88.
      • November 2015 (Revised May 2016)
      • Case

      Aspiring Minds

      By: Karim R. Lakhani, Marco Iansiti and Christine Snively
      By 2015, India-based employment assessment and certification provider Aspiring Minds had helped facilitate over 300,000 job matches through its assessment tools. Aspiring Minds' flagship product, the Aspiring Minds Computer Adaptive Test (AMCAT), used machine learning... View Details
      Keywords: Information Technology; Strategy; Higher Education; Technological Innovation; Employment; Technology Industry; India; China
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      Lakhani, Karim R., Marco Iansiti, and Christine Snively. "Aspiring Minds." Harvard Business School Case 616-013, November 2015. (Revised May 2016.)
      • October 2015 (Revised October 2016)
      • Case

      Building Watson: Not So Elementary, My Dear! (Abridged)

      By: Willy C. Shih
      This case is set inside IBM Research's efforts to build a computer that can successfully take on human challengers playing the game show Jeopardy! It opens with the machine named Watson offering the incorrect answer "Toronto" to a seemingly simple question during the... View Details
      Keywords: Analytics; Big Data; Business Analytics; Product Development Strategy; Machine Learning; Machine Intelligence; Artificial Intelligence; Product Development; AI and Machine Learning; Information Technology; Analytics and Data Science; Information Technology Industry; United States
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      Shih, Willy C. "Building Watson: Not So Elementary, My Dear! (Abridged)." Harvard Business School Case 616-025, October 2015. (Revised October 2016.)
      • 2015
      • Article

      A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes

      By: Himabindu Lakkaraju, Everaldo Aguiar, Carl Shan, David Miller, Nasir Bhanpuri, Rayid Ghani and Kecia Addison
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      Lakkaraju, Himabindu, Everaldo Aguiar, Carl Shan, David Miller, Nasir Bhanpuri, Rayid Ghani, and Kecia Addison. "A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes." Proceedings of the ACM SIGKDD Conference on Knowledge Discovery and Data Mining 21st (2015).
      • Article

      Who, When, and Why: A Machine Learning Approach to Prioritizing Students at Risk of Not Graduating High School on Time

      By: Everaldo Aguiar, Himabindu Lakkaraju, Nasir Bhanpuri, David Miller, Ben Yuhas, Kecia Addison and Rayid Ghani
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      Aguiar, Everaldo, Himabindu Lakkaraju, Nasir Bhanpuri, David Miller, Ben Yuhas, Kecia Addison, and Rayid Ghani. "Who, When, and Why: A Machine Learning Approach to Prioritizing Students at Risk of Not Graduating High School on Time." Proceedings of the International Learning Analytics and Knowledge Conference 5th (2015).
      • 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.
      • Forthcoming
      • Article

      An AI Method to Score Celebrity Visual Potential from Human Faces

      By: Flora Feng, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan and Cait Lamberton
      It has long been a mantra of marketing practice that, particularly in low-involvement situations, spokespeople should be physically attractive. This paper suggests there is a higher probability of gaining fame and influence (i.e., celebrity potential) than is captured... View Details
      Keywords: Personal Characteristics; AI and Machine Learning; Forecasting and Prediction; Marketing
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      Feng, Flora, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan, and Cait Lamberton. "An AI Method to Score Celebrity Visual Potential from Human Faces." Journal of Marketing Research (JMR) (forthcoming).
      • Forthcoming
      • Article

      Beefing IT Up for Your Investor? Engagement with Open Source Communities, Innovation, and Startup Funding: Evidence from GitHub

      By: Annamaria Conti, Christian Peukert and Maria P. Roche
      We study the engagement of nascent firms with open source communities and its implications for innovation and attracting funding. To do so, we link data on 160,065 U.S. startups from Crunchbase to their activities on the open source software development platform... View Details
      Keywords: Startups; Knowledge; Open Source Communities; GitHub; Machine Learning; Innovation; Business Startups; Venture Capital; Information Technology; Strategy
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      Conti, Annamaria, Christian Peukert, and Maria P. Roche. "Beefing IT Up for Your Investor? Engagement with Open Source Communities, Innovation, and Startup Funding: Evidence from GitHub." Organization Science (forthcoming). (Pre-published online March 7, 2025.)
      • Teaching Interest

      Data Science and AI for Leaders

      By: Dennis Campbell
      Modern business increasingly relies... View Details
      Keywords: Artificial Intelligence; Data Science
      • Teaching Interest

      Data Science and Artificial Intelligence for Leaders

      By: Chiara Farronato
      With artificial intelligence (AI)... View Details
      Keywords: Data Science; Data Science And Analytics Management; Data Analytics; Data Analysis; Artificial Intelligence; Generative Ai; Generative Models
      • Forthcoming
      • Article

      Digital Lending and Financial Well-Being: Through the Lens of Mobile Phone Data

      By: AJ Chen, Omri Even-Tov, Jung Koo Kang and Regina Wittenberg-Moerman
      To mitigate information asymmetry about borrowers in developing economies, digital lenders use machine-learning algorithms and nontraditional data from borrowers’ mobile devices. Consequently, digital lenders have managed to expand access to credit for millions of... View Details
      Keywords: Informal Economy; Digital Banking; Mobile Phones; Developing Countries and Economies; Mobile and Wireless Technology; AI and Machine Learning; Analytics and Data Science; Credit; Borrowing and Debt; Well-being; Banking Industry; Kenya
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      Chen, AJ, Omri Even-Tov, Jung Koo Kang, and Regina Wittenberg-Moerman. "Digital Lending and Financial Well-Being: Through the Lens of Mobile Phone Data." Accounting Review (forthcoming). (Pre-published online April 22, 2025.)
      • Article

      Don’t let an AI failure harm your brand

      By: Julian De Freitas
      How companies market their AI systems affects the repercussions they face when their products fail. Marketers must promote their AI products with potential failure in mind. To do that, they must first understand consumers’ unique attitudes toward AI. Marketers who... View Details
      Keywords: AI and Machine Learning; Brands and Branding; Product Marketing; Consumer Behavior; Attitudes
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      De Freitas, Julian. "Don’t let an AI failure harm your brand." Harvard Business Review (in press).
      • Teaching Interest

      Empirical Technology and Operations Management Course

      By: Himabindu Lakkaraju
      I taught a set of lectures on "Introduction to Machine Learning for Social Scientists" as part of this required course for first year PhD students. This module familiarizes students with all the basic concepts in machine learning, their implementations, as well as the... View Details
      • Forthcoming
      • Article

      Engaging Customers with AI in Online Chats: Evidence from a Randomized Field Experiment

      By: Shunyuan Zhang and Das Narayandas
      We examine how artificial intelligence (AI) affected the productivity of customer service agents and customer sentiment in online interactions. Collaborating with a meal delivery company, we conducted a randomized field experiment that exploited exogenous variation in... View Details
      Keywords: AI and Machine Learning; Customer Focus and Relationships; Performance Efficiency
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      Zhang, Shunyuan, and Das Narayandas. "Engaging Customers with AI in Online Chats: Evidence from a Randomized Field Experiment." Management Science (forthcoming).
      • Teaching Interest

      Harvard Business Analytics Program: Operations and Supply Chain Management

      By: Dennis Campbell
      Digital technologies and data analytics are radically changing the operating model of an organization and how it connects to its broader supply chain and ecosystem. This course emphasizes managing product availability, especially in a context of rapid product... View Details
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