Skip to Main Content
HBS Home
  • About
  • Academic Programs
  • Alumni
  • Faculty & Research
  • Baker Library
  • Giving
  • Harvard Business Review
  • Initiatives
  • News
  • Recruit
  • Map / Directions
Faculty & Research
  • Faculty
  • Research
  • Featured Topics
  • Academic Units
  • …→
  • Harvard Business School→
  • Faculty & Research→
  • Research
    • Research
    • Publications
    • Global Research Centers
    • Case Development
    • Initiatives & Projects
    • Research Services
    • Seminars & Conferences
    →
  • Publications→

Publications

Publications

Filter Results: (973) Arrow Down
Filter Results: (973) Arrow Down Arrow Up

Show Results For

  • All HBS Web  (973)
    • People  (1)
    • News  (156)
    • Research  (648)
    • Events  (13)
    • Multimedia  (3)
  • Faculty Publications  (552)

Show Results For

  • All HBS Web  (973)
    • People  (1)
    • News  (156)
    • Research  (648)
    • Events  (13)
    • Multimedia  (3)
  • Faculty Publications  (552)
← Page 17 of 973 Results →
  • 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
Read Now
Related
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).
  • 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
Citation
Find at Harvard
Purchase
Related
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
  • 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
Citation
Related
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.
  • 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

    A Prescriptive Analytics Framework for Optimal Policy Deployment Using Heterogeneous Treatment Effects

    We define a prescriptive analytics framework that addresses the needs of a constrained decision-maker facing, ex ante, unknown costs and benefits of multiple policy levers. The framework is general in nature and can be deployed in any utility maximizing... View Details
    • 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
    Citation
    SSRN
    Read Now
    Related
    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.
    • 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
    Read Now
    Related
    Pawelczyk, Martin, Seth Neel, and Himabindu Lakkaraju. "In-Context Unlearning: Language Models as Few Shot Unlearners." Working Paper, October 2023.
    • Teaching Interest

    Data Science for Managers

    • Served as a teaching fellow; assisted MBA students with classroom coding exercises. 
    • Developed course materials, including new case studies, technical notes, and code notebooks students used to analzye case data. 
    • Developed interactive web... View Details
    • 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
    Educators
    Purchase
    Related
    Lakhani, Karim R., and Amy Klopfenstein. "VideaHealth: Building the AI Factory." Harvard Business School Case 621-021, March 2021.

      Seth Neel

      Seth Neel is an Assistant Professor housed in the Department of Technology and Operations Management (TOM) at HBS, and a Faculty Affiliate in Computer Science at SEAS. He is Principal Investigator of the Trustworthy AI Lab in Harvard's new View Details
      • Web

      Marketing - Doctoral

      McFowland III Michael I. Norton Electronic commerce Kris Johnson Ferreira Ayelet Israeli Henry W. McGee Isamar Troncoso Marketing Tomomichi Amano Eva Ascarza Anita Elberse Sunil Gupta Ayelet Israeli Rajiv Lal V. Kasturi Rangan Isamar Troncoso Jeremy Yang Shunyuan Zhang... View Details
      • Web

      Strategy - Doctoral

      business Mattias E. Fibiger Sophus A. Reinert Charlotte L. Robertson Dennis A. Yao International business Juan Alcacer William R. Kerr Machine learning Himabindu Lakkaraju Michael Lingzhi Li Edward McFowland... View Details
      • 17 Jul 2023
      • Research & Ideas

      Money Isn’t Everything: The Dos and Don’ts of Motivating Employees

      that the process is transparent and understood, even if everyone’s individual pay isn’t transparent. Don’t replace all your people with robots In the age of AI and robotics, it’s tempting to slash costs by subbing in machines or View Details
      Keywords: by Avery Forman
      • February 2022 (Revised September 2022)
      • Case

      InstaDeep: AI Innovation Born in Africa (A)

      By: Shikhar Ghosh and Esel Çekin
      Karim Beguir and Zohra Slim were the co-founders of InstaDeep, a deep tech startup focusing on artificial intelligence (AI) solutions. Instadeep was one of the few companies globally that were partnering with DeepMind, an AI subsidiary of Google [Alphabet Inc.].... View Details
      Keywords: AI; Artificial Intelligence; Entrepreneurship; Operations; Business Subsidiaries; Brands and Branding; Innovation and Invention; Growth and Development Strategy; AI and Machine Learning; Technology Industry; Africa
      Citation
      Educators
      Purchase
      Related
      Ghosh, Shikhar, and Esel Çekin. "InstaDeep: AI Innovation Born in Africa (A)." Harvard Business School Case 822-104, February 2022. (Revised September 2022.)
      • 21 Oct 2024
      • Research & Ideas

      What Happens in Vegas Could Shape the Metaverse

      competing incentives in building the metaverse, our view is that the metaverse can still succeed,” they write, “but it might call for a shift in mindset and an openness to learning from seemingly distant domains of knowledge.” Along those... View Details
      Keywords: by Scott Nover; Computer; Information Technology
      • Web

      Technology & Operations Management - Doctoral

      technology Iavor I. Bojinov Shane M. Greenstein Edward McFowland III David B. Yoffie Knowledge management Alexandra C. Feldberg Jacqueline Ng Lane Maria P. Roche Innovation Iavor I. Bojinov Marco Iansiti Alan D. MacCormack Kyle R. Myers Maria P. Roche Stefan H. Thomke... View Details
      • December 2018
      • Teaching Note

      Autonomous Vehicles: The Rubber Hits the Road…but When?

      By: William Kerr and James Palano
      The autonomous vehicles have enormous implications for business and society. But, despite the headline-laden attention paid to the technology, there remain more questions than answers. Students will learn about the complex industry and have explicit discussions about... View Details
      Keywords: Technology Management; Artificial Intelligence; General Management; Robotics; Technological Innovation; Transportation; Disruption; Information Technology; Management; Decision Making; AI and Machine Learning; Auto Industry; Technology Industry
      Citation
      Purchase
      Related
      Kerr, William, and James Palano. "Autonomous Vehicles: The Rubber Hits the Road…but When?" Harvard Business School Teaching Note 819-040, December 2018.
      • 2023
      • Article

      Post Hoc Explanations of Language Models Can Improve Language Models

      By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
      Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance... View Details
      Keywords: AI and Machine Learning; Performance Effectiveness
      Citation
      Read Now
      Related
      Krishna, Satyapriya, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, and Himabindu Lakkaraju. "Post Hoc Explanations of Language Models Can Improve Language Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
      • January 2018 (Revised March 2019)
      • Case

      Autonomous Vehicles: The Rubber Hits the Road...but When?

      By: William Kerr, Allison Ciechanover, Jeff Huizinga and James Palano
      The rise of autonomous vehicles has enormous implications for business and society. Despite the many headlines and significant investment in the technology by early 2019, it was still unclear when truly autonomous vehicles would be a commercial reality. Students will... View Details
      Keywords: Technology Management; Artificial Intelligence; General Management; Robotics; Technological Innovation; Transportation; Disruption; Information Technology; Decision Making; AI and Machine Learning; Auto Industry; Technology Industry
      Citation
      Educators
      Purchase
      Related
      Kerr, William, Allison Ciechanover, Jeff Huizinga, and James Palano. "Autonomous Vehicles: The Rubber Hits the Road...but When?" Harvard Business School Case 818-088, January 2018. (Revised March 2019.)
      • ←
      • 17
      • 18
      • …
      • 48
      • 49
      • →
      ǁ
      Campus Map
      Harvard Business School
      Soldiers Field
      Boston, MA 02163
      →Map & Directions
      →More Contact Information
      • Make a Gift
      • Site Map
      • Jobs
      • Harvard University
      • Trademarks
      • Policies
      • Accessibility
      • Digital Accessibility
      Copyright © President & Fellows of Harvard College.