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Publications

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  • All HBS Web  (1,194)
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  • All HBS Web  (1,194)
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    • News  (232)
    • Research  (675)
    • Events  (17)
    • Multimedia  (8)
  • Faculty Publications  (560)
← Page 4 of 1,194 Results →
  • 2018
  • Working Paper

Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning

By: Xiaojia Guo, Yael Grushka-Cockayne and Bert De Reyck
Problem definition: In collaboration with Heathrow Airport, we develop a predictive system that generates quantile forecasts of transfer passengers’ connection times. Sampling from the distribution of individual passengers’ connection times, the system also produces... View Details
Keywords: Quantile Forecasts; Regression Tree; Copula; Passenger Flow Management; Data-driven Operations; Forecasting and Prediction; Data and Data Sets
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Guo, Xiaojia, Yael Grushka-Cockayne, and Bert De Reyck. "Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning." Harvard Business School Working Paper, No. 19-040, October 2018.
  • 2021
  • Working Paper

Time and the Value of Data

By: Ehsan Valavi, Joel Hestness, Newsha Ardalani and Marco Iansiti

Managers often believe that collecting more data will continually improve the accuracy of their machine learning models. However, we argue in this paper that when data lose relevance over time, it may be optimal to collect a limited amount of recent data instead of... View Details

Keywords: Economics Of AI; Machine Learning; Non-stationarity; Perishability; Value Depreciation; Analytics and Data Science; Value
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Valavi, Ehsan, Joel Hestness, Newsha Ardalani, and Marco Iansiti. "Time and the Value of Data." Harvard Business School Working Paper, No. 21-016, August 2020. (Revised November 2021.)
  • July 2023 (Revised July 2023)
  • Background Note

Generative AI Value Chain

By: Andy Wu and Matt Higgins
Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details
Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value
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Wu, Andy, and Matt Higgins. "Generative AI Value Chain." Harvard Business School Background Note 724-355, July 2023. (Revised July 2023.)
  • Working Paper

Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application

By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely... View Details
Keywords: Peer-to-peer Markets; Marketplace Matching; AI and Machine Learning; Demand and Consumers; Digital Platforms; Marketing
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Feng, Flora, Charis Li, and Shunyuan Zhang. "Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application." SSRN Working Paper Series, No. 4665286, February 2024.
  • 2025
  • Working Paper

Generative AI and the Nature of Work

By: Manuel Hoffmann, Sam Boysel, Frank Nagle, Sida Peng and Kevin Xu
Recent advances in artificial intelligence (AI) technology demonstrate a considerable potential to complement human capital intensive activities. While an emerging literature documents wide-ranging productivity effects of AI, relatively little attention has been paid... View Details
Keywords: Generative Ai; Digital Work; Open Source Software; Knowledge Economy; AI and Machine Learning; Open Source Distribution; Organizational Structure; Performance Productivity; Labor
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Hoffmann, Manuel, Sam Boysel, Frank Nagle, Sida Peng, and Kevin Xu. "Generative AI and the Nature of Work." Harvard Business School Working Paper, No. 25-021, October 2024. (Revised April 2025.)
  • October 2018
  • Case

Shield AI

By: Mitchell Weiss and A.J. Steinlage
Shield AI’s quadcopter – with no pilot and no flight plan – could clear a building and outpace human warfighters by almost five minutes. This was not to say that it was better than the warfighters or would replace their jobs, but it was evidence that autonomous robots... View Details
Keywords: Public Entrepreneurship; Artificial Intelligence; AI; Entrepreneurial Sales; Government; Defense; Shield AI; Brandon Tseng; Ryan Tseng; Andrew Reiter; Robots; Robotics; UAV; UAVs; Government Sales; Entrepreneurship; Public Sector; Sales; Government Administration; National Security; Business and Government Relations; AI and Machine Learning; Technology Industry; United States
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Weiss, Mitchell, and A.J. Steinlage. "Shield AI." Harvard Business School Case 819-062, October 2018.
  • Article

Productivity and Selection of Human Capital with Machine Learning

By: Aaron Chalfin, Oren Danieli, Andrew Hillis, Zubin Jelveh, Michael Luca, Jens Ludwig and Sendhil Mullainathan
Keywords: Analytics and Data Science; Selection and Staffing; Performance Productivity; Mathematical Methods; Policy
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Chalfin, Aaron, Oren Danieli, Andrew Hillis, Zubin Jelveh, Michael Luca, Jens Ludwig, and Sendhil Mullainathan. "Productivity and Selection of Human Capital with Machine Learning." American Economic Review: Papers and Proceedings 106, no. 5 (May 2016): 124–127.
  • 2021
  • Working Paper

CRM and AI in Time of Crisis

By: Michelle Y. Lu and Navid Mojir
A crisis can affect the incentives of various players within a firm’s multi-layered sales and marketing organization (e.g., headquarters and branches of a bank). Such shifts can result in sales decisions against the firm’s best interests. Motivated by the backlash to... View Details
Keywords: CRM; Artificial Intelligence; AI; B2B Marketing; Decision Authority; Crisis Marketing; Intra-organizational Conflict; COVID-19 Pandemic; Customer Relationship Management; Technological Innovation; Decision Making; Strategy; Health Pandemics; Crisis Management; AI and Machine Learning
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Lu, Michelle Y., and Navid Mojir. "CRM and AI in Time of Crisis." Harvard Business School Working Paper, No. 22-035, November 2021.
  • 2024
  • Working Paper

Why Most Resist AI Companions

By: Julian De Freitas, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp and Stefano Puntoni
Chatbots are now able to form emotional relationships with people and alleviate loneliness—a growing public health concern. Behavioral research provides little insight into whether everyday people are likely to use these applications and why. We address this question... View Details
Keywords: Generative Ai; Chatbots; Artificial Intelligence; Algorithmic Aversion; Lonelines; Technology Adoption; AI and Machine Learning; Well-being; Emotions
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De Freitas, Julian, Zeliha Oğuz-Uğuralp, Ahmet Kaan Uğuralp, and Stefano Puntoni. "Why Most Resist AI Companions." Harvard Business School Working Paper, No. 25-030, December 2024. (Revised January 2025.)
  • February 2022 (Revised July 2022)
  • Supplement

InstaDeep: AI Innovation Born in Africa (B)

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
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Ghosh, Shikhar, and Esel Çekin. "InstaDeep: AI Innovation Born in Africa (B)." Harvard Business School Supplement 822-105, February 2022. (Revised July 2022.)
  • 2022
  • Working Paper

TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations

By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet they have become more complex and harder to understand. To address this issue, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use explainability... View Details
Keywords: Natural Language Conversations; Predictive Models; AI and Machine Learning
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Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations." Working Paper, 2022.
  • 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
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Ghosh, Shikhar, and Esel Çekin. "InstaDeep: AI Innovation Born in Africa (A)." Harvard Business School Case 822-104, February 2022. (Revised September 2022.)
  • 2024
  • Working Paper

Displacement or Complementarity? The Labor Market Impact of Generative AI

By: Wilbur Xinyuan Chen, Suraj Srinivasan and Saleh Zakerinia
Generative AI is poised to reshape the labor market, affecting cognitive and white-collar occupations in ways distinct from past technological revolutions. This study examines whether generative AI displaces workers or augments their jobs by analyzing labor demand and... View Details
Keywords: Generative Ai; Labor Market; Automation And Augmentation; Labor; AI and Machine Learning; Competency and Skills
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Chen, Wilbur Xinyuan, Suraj Srinivasan, and Saleh Zakerinia. "Displacement or Complementarity? The Labor Market Impact of Generative AI." Harvard Business School Working Paper, No. 25-039, December 2024.
  • February 2018 (Revised March 2018)
  • Case

Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP)

By: Lauren Cohen, Christopher Malloy and William Powley
This case examines the intersection of two firms (Cogent Labs—a machine learning software firm in Tokyo; and Google, the technology infrastructure giant) attempting to exploit the benefits of artificial intelligence and machine learning in the financial services... View Details
Keywords: Technological Innovation; Finance; Growth and Development Strategy; Business Model; Applications and Software; Infrastructure; Technology Industry; Financial Services Industry
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Cohen, Lauren, Christopher Malloy, and William Powley. "Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP)." Harvard Business School Case 218-080, February 2018. (Revised March 2018.)
  • September–October 2024
  • Article

The Crowdless Future? Generative AI and Creative Problem-Solving

By: Léonard Boussioux, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic and Karim R. Lakhani
The rapid advances in generative artificial intelligence (AI) open up attractive opportunities for creative problem-solving through human-guided AI partnerships. To explore this potential, we initiated a crowdsourcing challenge focused on sustainable, circular economy... View Details
Keywords: Large Language Models; Generative Ai; Crowdsourcing; AI and Machine Learning; Creativity; Technological Innovation
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Boussioux, Léonard, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim R. Lakhani. "The Crowdless Future? Generative AI and Creative Problem-Solving." Organization Science 35, no. 5 (September–October 2024): 1589–1607.

    The Experimentation Machine

    Leverage AI to be a 10x Founder

    Today’s most successful founders know that the startups that learn the fastest will win. In The Experimentation Machine, HBS professor, entrepreneur, and venture capitalist Jeffrey J. Bussgang reveals... View Details

    • August 2023
    • Article

    Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel

    By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
    Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use... View Details
    Keywords: AI and Machine Learning; Technological Innovation; Technology Adoption
    Citation
    Read Now
    Related
    Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel." Nature Machine Intelligence 5, no. 8 (August 2023): 873–883.
    • May 2022
    • Case

    AWS and Amazon SageMaker (A): The Commercialization of Machine Learning Services

    By: Karim R. Lakhani, Shane Greenstein and Kerry Herman
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    Lakhani, Karim R., Shane Greenstein, and Kerry Herman. "AWS and Amazon SageMaker (A): The Commercialization of Machine Learning Services." Harvard Business School Case 622-060, May 2022.
    • Forthcoming
    • Book

    The Experimentation Machine: Finding Product–Market Fit in the Age of AI

    By: Jeffrey J. Bussgang
    Leverage AI to be a 10x Founder

    Today’s most successful founders know that the startups that learn the fastest will win. In The Experimentation Machine, I reveal how AI is transforming the way startups find product-market fit and scale.... View Details
    Keywords: AI; Founder; Startup; AI and Machine Learning; Technology Adoption; Business Startups; Entrepreneurship; Market Entry and Exit
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    Bussgang, Jeffrey J. The Experimentation Machine: Finding Product–Market Fit in the Age of AI. Damn Gravity Media, forthcoming.
    • 2024
    • Working Paper

    The Crowdless Future? Generative AI and Creative Problem Solving

    By: Léonard Boussioux, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic and Karim R. Lakhani
    The rapid advances in generative artificial intelligence (AI) open up attractive opportunities for creative problem-solving through human-guided AI partnerships. To explore this potential, we initiated a crowdsourcing challenge focused on sustainable, circular economy... View Details
    Keywords: Large Language Models; Crowdsourcing; Generative Ai; Creative Problem-solving; Organizational Search; AI-in-the-loop; Prompt Engineering; AI and Machine Learning; Innovation and Invention
    Citation
    SSRN
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    Boussioux, Léonard, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim R. Lakhani. "The Crowdless Future? Generative AI and Creative Problem Solving." Harvard Business School Working Paper, No. 24-005, July 2023. (Revised July 2024.)
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