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  • All HBS Web  (1,039)
    • People  (1)
    • News  (187)
    • Research  (673)
    • Events  (13)
    • Multimedia  (3)
  • Faculty Publications  (552)
← Page 17 of 1,039 Results →
  • 2020
  • Book

Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World

By: Marco Iansiti and Karim R. Lakhani
In industry after industry, data, analytics, and AI-driven processes are transforming the nature of work. While we often still treat AI as the domain of a specific skill, business function, or sector, we have entered a new era in which AI is challenging the very... View Details
Keywords: Artificial Intelligence; Technological Innovation; Change; Competition; Strategy; Leadership; Business Processes; Organizational Change and Adaptation; AI and Machine Learning
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Iansiti, Marco, and Karim R. Lakhani. Competing in the Age of AI: Strategy and Leadership When Algorithms and Networks Run the World. Boston: Harvard Business Review Press, 2020.
  • 2020
  • Working Paper

Design in the Age of Artificial Intelligence

By: Roberto Verganti, Luca Vendraminelli and Marco Iansiti
Artificial Intelligence (AI) is affecting the scenario in which innovation takes place. What are the implications for our understanding of design? Is AI just another digital technology that, akin to many others, will not significantly question what we know about... View Details
Keywords: Artificial Intelligence; Design Thinking; Technological Innovation; Design; Change; Theory; AI and Machine Learning
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Verganti, Roberto, Luca Vendraminelli, and Marco Iansiti. "Design in the Age of Artificial Intelligence." Harvard Business School Working Paper, No. 20-091, February 2020.
  • Web

Publications - Faculty & Research

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 View Details

    Eliminating unintended bias in personalized policies using Bias Eliminating Adapted Trees (BEAT) - PNAS

    An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those... View Details

      Robert J. Dolan

      Robert J. Dolan is the Baker Foundation Professor at Harvard Business School. He received his Ph.D. from the University of Rochester and began his academic career in 1976 as a faculty member at the Graduate School of Business of the University of Chicago. He joined... View Details

      • 09 Mar 2016
      • Lessons from the Classroom

      In This Classroom, Beer Can Improve Your Grade

      simulations, but Strategic Brew stands alone in scope. All 940 first-year students play the game simultaneously as part of the required Strategy course. Roughly 40 faculty and project members manage and supervise the events. “It’s a... View Details
      Keywords: by Roberta Holland; Education; Food & Beverage
      • 2023
      • Chapter

      Marketing Through the Machine’s Eyes: Image Analytics and Interpretability

      By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
      he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
      Keywords: Transparency; Marketing Research; Algorithmic Bias; AI and Machine Learning; Marketing
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      Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.
      • 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.)
      • 2019
      • Book

      Fintech, Small Business & the American Dream: How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity

      By: Karen G. Mills
      Fintech, Small Business & the American Dream describes the needs of small businesses for capital and demonstrates how technology—novel data sources, artificial intelligence, machine learning—will transform the small business lending market. This market has been... View Details
      Keywords: Fintech; Big Data; Data; Technology; Artificial Intelligence; Great Recession; Regulation; Innovation; Banks; Lending; Loans; Access To Capital; American Dream; Community Banking; Small Business Administration; Entrepreneur; Government; Public Policy; API; Policy Making; Small Business; Financing and Loans; Technological Innovation; Financial Crisis; Banks and Banking; Governing Rules, Regulations, and Reforms; Policy; AI and Machine Learning; Analytics and Data Science; United States
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      Mills, Karen G. Fintech, Small Business & the American Dream: How Technology Is Transforming Lending and Shaping a New Era of Small Business Opportunity. Palgrave Macmillan, 2019.
      • 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.
      • Web

      HBS Working Knowledge – Harvard Business School Faculty Research

      could other businesses learn from his ascent? What Will It Take to Confront the Invisible Mental Health Crisis in Business? by Kara Baskin 09 NOV 2023 | HBS Case The pressure to do more, to be more, is fueling its own silent epidemic.... View Details
      • 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.
      • 08 Mar 2011
      • First Look

      First Look: March 8

      relocate to Japan and compete with other world-class international business schools. Purchase this case:http://cb.hbsp.harvard.edu/cb/product/811061-PDF-ENG The Wright Brothers and Their Flying Machines Tom Nicholas and David ChenHarvard... View Details
      Keywords: Sean Silverthorne
      • Article

      Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)

      By: Eva Ascarza and Ayelet Israeli

      An inherent risk of algorithmic personalization is disproportionate targeting of individuals from certain groups (or demographic characteristics such as gender or race), even when the decision maker does not intend to discriminate based on those “protected”... View Details

      Keywords: Algorithm Bias; Personalization; Targeting; Generalized Random Forests (GRF); Discrimination; Customization and Personalization; Decision Making; Fairness; Mathematical Methods
      Citation
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      Ascarza, Eva, and Ayelet Israeli. "Eliminating Unintended Bias in Personalized Policies Using Bias-Eliminating Adapted Trees (BEAT)." e2115126119. Proceedings of the National Academy of Sciences 119, no. 11 (March 8, 2022).
      • 03 Apr 2025
      • HBS Seminar

      Ziad Obermeyer, UC Berkeley School of Public Health

      • 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
      Citation
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      Pawelczyk, Martin, Seth Neel, and Himabindu Lakkaraju. "In-Context Unlearning: Language Models as Few Shot Unlearners." Working Paper, October 2023.
      • March 2021
      • Case

      VideaHealth: Building the AI Factory

      By: Karim R. Lakhani and Amy Klopfenstein
      Florian Hillen, co-founder and CEO of VideaHealth, a startup that used artificial intelligence (AI) to detect dental conditions on x-rays, spent the early years of his company laying the groundwork for an AI factory. A process for quickly building and iterating on new... View Details
      Keywords: Artificial Intelligence; Innovation and Invention; Disruptive Innovation; Technological Innovation; Information Technology; Applications and Software; Technology Adoption; Digital Platforms; Entrepreneurship; AI and Machine Learning; Technology Industry; Medical Devices and Supplies Industry; North and Central America; United States; Massachusetts; Cambridge
      Citation
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      Lakhani, Karim R., and Amy Klopfenstein. "VideaHealth: Building the AI Factory." Harvard Business School Case 621-021, March 2021.

        Graphic Packaging: Project Cowboy

        In July 2019, Graphic Packaging CEO Michael Doss was proposing a $600 million investment in a new machine to produce coated recycled board (CRB), a type of paper packaging used for consumer products (cups, cereal boxes, beverage boxes, etc.) that utilized recycled... View Details
        • 06 Jun 2017
        • First Look

        First Look at New Research and Ideas: June 6, 2017

        recent years, a number of new and exciting tools enabled by advances in telework, machine learning, and other approaches had emerged. Hirshfeld hoped to maximize these tools’ utility in order to enhance patent examiners’ work and... View Details
        Keywords: Sean Silverthorne
        • 05 Feb 2024
        • Research & Ideas

        The Middle Manager of the Future: More Coaching, Less Commanding

        driven economy, suggests new research from Harvard Business School, and managers who can collaborate—not just supervise and discipline—are reaping the rewards. To support more autonomous, creative workers, organizations want managers to... View Details
        Keywords: by Ben Rand
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