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      • Faculty Publications  (126)

      Generative AiRemove Generative Ai →

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      • 2023
      • Article

      On the Impact of Actionable Explanations on Social Segregation

      By: Ruijiang Gao and Himabindu Lakkaraju
      As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research... View Details
      Keywords: Forecasting and Prediction; AI and Machine Learning; Outcome or Result
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      Gao, Ruijiang, and Himabindu Lakkaraju. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.
      • August 2023
      • Case

      Kariyer.net: Recruiting AI

      By: Shunyuan Zhang, Fares Khrais and Namrata Arora
      In 2017, Fatih Uysal (AMP 2021) became CEO of Kariyer.net. By then, the business was already the industry leading online job board in Turkey. However, faced with stalling growth, a turbulent macroenvironment, and growing competition from international players, Uysal... View Details
      Keywords: Online Technology; Marketing; Websites; Artificial Intelligence; Innovation; Two-sided Platforms; Internet and the Web; Product Launch; Product Positioning; Job Search; Employment; Transformation; Volatility; Innovation and Invention; Disruptive Innovation; Management Practices and Processes; Business Growth and Maturation; Competitive Strategy; Business Startups; Talent and Talent Management; Cost vs Benefits; Macroeconomics; Corporate Entrepreneurship; Emerging Markets; Digital Platforms; Employment Industry; Information Technology Industry; Technology Industry; Middle East; Turkey
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      Zhang, Shunyuan, Fares Khrais, and Namrata Arora. "Kariyer.net: Recruiting AI." Harvard Business School Case 524-014, August 2023.
      • 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
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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.)
      • 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
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      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.
      • 2023
      • Article

      Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten

      By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
      The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details
      Keywords: Analytics and Data Science; AI and Machine Learning; Decision Making; Governing Rules, Regulations, and Reforms
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      Lakkaraju, Himabindu, Satyapriya Krishna, and Jiaqi Ma. "Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 17808–17826.
      • July 2023
      • Supplement

      Honeycomb (B): Jumping on The Generative AI Bandwagon?

      By: Jeffrey J. Bussgang and Kumba Sennaar
      Honeycomb, an audio app enabling users to record stories and save family memories, considers pivoting to embrace generative AI. What should the co-founders business model look like if they pursued this new direction? View Details
      Keywords: Entrepreneurship; Venture Capital; Operations; Business Startups; Business Model; AI and Machine Learning; Technology Industry; United States
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      Bussgang, Jeffrey J., and Kumba Sennaar. "Honeycomb (B): Jumping on The Generative AI Bandwagon?" Harvard Business School Supplement 824-013, July 2023.
      • 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.)
      • June 2023 (Revised July 2023)
      • Case

      Social Media Background Screening at Fama Technologies

      By: Joseph Pacelli, Jillian Grennan and Alexis Lefort
      Fama Technologies is an online screening company that uses AI to analyze job applicants' publicly available online content for signs of risk and culture fit. The case opens with Ben Mones, founder and CEO, looking to secure funding from venture firms. He is running... View Details
      Keywords: Human Resources; Recruitment; Retention; Selection and Staffing; Organizational Culture; Talent and Talent Management; AI and Machine Learning; Social Media; Venture Capital; Entrepreneurship; United States
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      Pacelli, Joseph, Jillian Grennan, and Alexis Lefort. "Social Media Background Screening at Fama Technologies." Harvard Business School Case 123-010, June 2023. (Revised July 2023.)
      • June 2023
      • Supplement

      Social Media Background Screening at Fama Technologies (B)

      By: Joseph Pacelli, Jillian Grennan and Alexis Lefort
      Fama Technologies is an online screening company that uses AI to analyze job applicants' publicly available online content for signs of risk and culture fit. The case opens with Ben Mones, founder and CEO, looking to secure funding from venture firms. He is running... View Details
      Keywords: Human Resources; Recruitment; Retention; Selection and Staffing; Organizational Culture; Talent and Talent Management; United States
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      Pacelli, Joseph, Jillian Grennan, and Alexis Lefort. "Social Media Background Screening at Fama Technologies (B)." Harvard Business School Supplement 123-086, June 2023.
      • June 19, 2023
      • Article

      Should You Start a Generative AI Company?

      By: Julian De Freitas
      Many entrepreneurs are considering starting companies that leverage the latest generative AI technology, but they must ask themselves whether they have what it takes to compete on increasingly commoditized foundational models, or whether they should instead... View Details
      Keywords: Business Startups; Entrepreneurship; AI and Machine Learning; Applications and Software
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      De Freitas, Julian. "Should You Start a Generative AI Company?" Harvard Business Review (website) (June 19, 2023).
      • 2023
      • Article

      Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators

      By: Benjamin Jakubowski, Siram Somanchi, Edward McFowland III and Daniel B. Neill
      Regression discontinuity (RD) designs are widely used to estimate causal effects in the absence of a randomized experiment. However, standard approaches to RD analysis face two significant limitations. First, they require a priori knowledge of discontinuities in... View Details
      Keywords: Regression Discontinuity Design; Analytics and Data Science; AI and Machine Learning
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      Jakubowski, Benjamin, Siram Somanchi, Edward McFowland III, and Daniel B. Neill. "Exploiting Discovered Regression Discontinuities to Debias Conditioned-on-observable Estimators." Journal of Machine Learning Research 24, no. 133 (2023): 1–57.
      • May 9, 2023
      • Article

      8 Questions About Using AI Responsibly, Answered

      By: Tsedal Neeley
      Generative AI tools are poised to change the way every business operates. As your own organization begins strategizing which to use, and how, operational and ethical considerations are inevitable. This article delves into eight of them, including how your organization... View Details
      Keywords: AI and Machine Learning; Organizational Change and Adaptation; Prejudice and Bias; Ethics
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      Neeley, Tsedal. "8 Questions About Using AI Responsibly, Answered." Harvard Business Review (website) (May 9, 2023).
      • 2024
      • Working Paper

      Using LLMs for Market Research

      By: James Brand, Ayelet Israeli and Donald Ngwe
      Large language models (LLMs) have rapidly gained popularity as labor-augmenting tools for programming, writing, and many other processes that benefit from quick text generation. In this paper we explore the uses and benefits of LLMs for researchers and practitioners... View Details
      Keywords: Large Language Model; Research; AI and Machine Learning; Analysis; Customers; Consumer Behavior; Technology Industry; Information Technology Industry
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      Brand, James, Ayelet Israeli, and Donald Ngwe. "Using LLMs for Market Research." Harvard Business School Working Paper, No. 23-062, April 2023. (Revised July 2024.)
      • April 2023 (Revised February 2024)
      • Case

      AI Wars

      By: Andy Wu, Matt Higgins, Miaomiao Zhang and Hang Jiang
      In February 2024, the world was looking to Google to see what the search giant and long-time putative technical leader in artificial intelligence (AI) would do to compete in the massively hyped technology of generative AI. Over a year ago, OpenAI released ChatGPT, a... View Details
      Keywords: AI; Artificial Intelligence; AI and Machine Learning; Technology Adoption; Competitive Strategy; Technological Innovation
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      Wu, Andy, Matt Higgins, Miaomiao Zhang, and Hang Jiang. "AI Wars." Harvard Business School Case 723-434, April 2023. (Revised February 2024.)
      • March–April 2023
      • Article

      Pricing for Heterogeneous Products: Analytics for Ticket Reselling

      By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
      Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in... View Details
      Keywords: Price; Demand and Consumers; AI and Machine Learning; Investment Return; Entertainment and Recreation Industry; Sports Industry
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      Alley, Michael, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li, and Georgia Perakis. "Pricing for Heterogeneous Products: Analytics for Ticket Reselling." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 409–426.
      • 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.
      • 2023
      • Working Paper

      Sending Signals: Strategic Displays of Warmth and Competence

      By: Bushra S. Guenoun and Julian J. Zlatev
      Using a combination of exploratory and confirmatory approaches, this research examines how people signal important information about themselves to others. We first train machine learning models to assess the use of warmth and competence impression management... View Details
      Keywords: AI and Machine Learning; Personal Characteristics; Perception; Interpersonal Communication
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      Guenoun, Bushra S., and Julian J. Zlatev. "Sending Signals: Strategic Displays of Warmth and Competence." Harvard Business School Working Paper, No. 23-051, February 2023.
      • 8 Sep 2023
      • Conference Presentation

      Chatbots and Mental Health: Insights into the Safety of Generative AI

      By: Julian De Freitas, K. Uguralp, Z. Uguralp and Stefano Puntoni
      Keywords: AI and Machine Learning; Well-being
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      De Freitas, Julian, K. Uguralp, Z. Uguralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Paper presented at the Business & Generative AI Workshop, Wharton School, AI at Wharton, San Francisco, CA, United States, September 8, 2023.
      • 2023
      • Article

      Experimental Evaluation of Individualized Treatment Rules

      By: Kosuke Imai and Michael Lingzhi Li
      The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a... View Details
      Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning
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      Imai, Kosuke, and Michael Lingzhi Li. "Experimental Evaluation of Individualized Treatment Rules." Journal of the American Statistical Association 118, no. 541 (2023): 242–256.
      • December 2022 (Revised September 2024)
      • Case

      Sword Health

      By: Regina E. Herzlinger, Annelena Lobb and Carin-Isabel Knoop
      Virgilio “V” Bento, CEO of Sword Health—a startup that provided virtual physical therapy to patients in self-insured firms via AI and sensor technology with supervision by a physical therapist with a doctorate—considered how to increase its U.S. market share. To do so,... View Details
      Keywords: Business Growth and Maturation; Competitive Strategy; Health Industry; Technology Industry
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      Herzlinger, Regina E., Annelena Lobb, and Carin-Isabel Knoop. "Sword Health." Harvard Business School Case 323-022, December 2022. (Revised September 2024.)
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