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  • 2024
  • Working Paper

Climate Solutions, Transition Risk, and Stock Returns

By: Shirley Lu, Edward J. Riedl, Simon Xu and George Serafeim
Using large language models to measure firms' climate solution products and services, we find that high-climate solution firms exhibit lower stock returns and higher market valuation multiples. Their stock prices respond positively to events signaling increased demand... View Details
Keywords: Technology; Generative Ai; Large Language Models; Climate Finance; Climate Change; Innovation and Invention; Environmental Sustainability; AI and Machine Learning; Investment; Financial Markets
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  • October 2023 (Revised January 2025)
  • Case

Sydney Loves Kevin

By: Ryan W. Buell and Himabindu Lakkaraju
Kevin Roose was a columnist and podcast host for the New York Times, who focused on technology and its effects on society. When Microsoft launched the latest version of its search engine Bing in February 2023, the company invited Roose to its Redmond campus to... View Details
Keywords: Newspapers; AI and Machine Learning; Technology Adoption; Technological Innovation; Perspective; Media and Broadcasting Industry; Technology Industry
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  • 2025
  • Working Paper

Lessons from an App Update at Replika AI: Identity Discontinuity in Human-AI Relationships

By: Julian De Freitas, Noah Castelo, Ahmet K. Uğuralp and Zeliha O. Uğuralp
As consumers increasingly interact with AI applications specialized for social relationships, what is the nature and depth of these relationships among actual users, and can company actions influence these dynamics? We find that active users of the US-based AI... View Details
Keywords: AI and Machine Learning; Welfare; Loss; Well-being; Identity; Perception; Relationships
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  • Article

Unregulated Emotional Risks of AI Wellness Apps

By: Julian De Freitas and Glenn Cohen
We propose that AI-driven wellness apps powered by large language models can foster extreme emotional attachments and dependencies akin to human relationships—posing risks like ambiguous loss and dysfunctional dependence—that challenge current regulatory frameworks and... View Details
Keywords: AI and Machine Learning; Well-being; Emotions; Governing Rules, Regulations, and Reforms
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  • March 2025
  • Case

Xfund and Sam Altman: Finding Harvard’s Best Generative AI Founders

By: Suraj Srinivasan
On May 1, 2024, Xfund Managing Partners Patrick Chung and Brandon Farwell, hosted a high-stakes venture pitch session designed to select one startup for a minimum $100,000 investment. This “Xperiment Stake” competition, dedicated to startups in the Generative AI... View Details
Keywords: AI and Machine Learning; Venture Capital; Innovation Leadership; Technological Innovation; Technology Industry; United States
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  • Forthcoming
  • Article

Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation

By: Maya Balakrishnan, Kris Ferreira and Jordan Tong
Even if algorithms make better predictions than humans on average, humans may sometimes have private information which an algorithm does not have access to that can improve performance. How can we help humans effectively use and adjust recommendations made by... View Details
Keywords: AI and Machine Learning; Analytics and Data Science; Forecasting and Prediction; Digital Marketing
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  • July–August 2024
  • Article

Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals

By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response, which requires identifying differences in customer sensitivity, typically through the conditional average treatment effect (CATE) estimation. In theory, to... View Details
Keywords: Long-run Targeting; Heterogeneous Treatment Effect; Statistical Surrogacy; Customer Churn; Field Experiments; Consumer Behavior; Customer Focus and Relationships; AI and Machine Learning; Marketing Strategy
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  • June 2017
  • Teaching Note

IBM Transforming, 2012–2016: Ginni Rometty Steers Watson

By: Rosabeth Moss Kanter and Jonathan Cohen
Ginni Rometty, who became IBM CEO in 2012, led efforts to transform the company around cognitive computing and the AI platform Watson. This Teaching Note helps instructors understand and teach the Harvard Business School case “IBM Transforming, 2012–2016: Ginni Rometty... 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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  • 01 Dec 2020
  • News

AI Enhances Diagnostic Care

changing the field of medicine. In the past several decades, the growing use of artificial intelligence in the health care sector has made it possible for computer systems and diagnostic machines to learn... View Details
Keywords: Jennifer Gillespie
  • Web

Flatiron School: Reflections from Summer 2020 - Recruiting

analyzing its marketing and the sales data. NOTE: Full list of client partners included Calendly, Branch Furniture, Coconut Cartel, Halen Brands, OWYN, Birchbox, Young Invincibles, Color Camp, Women 2.0 and Casper. WHAT WERE YOUR GOALS FOR THE SUMMER? Rocio Wu (MBA... View Details
  • 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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  • July 2024
  • Article

How Artificial Intelligence Constrains Human Experience

By: A. Valenzuela, S. Puntoni, D. Hoffman, N. Castelo, J. De Freitas, B. Dietvorst, C. Hildebrand, Y.E. Huh, R. Meyer, M. Sweeney, S. Talaifar, G. Tomaino and K. Wertenbroch
Many consumption decisions and experiences are digitally mediated. As a consequence, consumer behavior is increasingly the joint product of human psychology and ubiquitous algorithms (Braun et al. 2024; cf. Melumad et al. 2020). The coming of age of Large Language... View Details
Keywords: Large Language Model; User Experience; AI and Machine Learning; Consumer Behavior; Technology Adoption; Risk and Uncertainty; Cost vs Benefits
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  • February 2022 (Revised November 2022)
  • Case

Nuritas

By: Mitchell Weiss, Satish Tadikonda, Vincent Dessain and Emer Moloney
Nora Khaldi had built a technology “to unlock the power of nature” in the service of extending human lifespan and improving health, and now in April 2020 was debating telling her Board of Directors she wanted to put on ice some of her discoveries. Nuritas, the company... View Details
Keywords: Cash Burn; Cash Flow Analysis; Pharmaceutical Companies; Founder; Artificial Intelligence; AI; Entrepreneurship; Health Testing and Trials; Health Care and Treatment; Decision Making; Market Entry and Exit; AI and Machine Learning; Pharmaceutical Industry
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  • September 2024 (Revised January 2025)
  • Exercise

Building an AI First Snack Company: A Hands-on Generative AI Exercise

By: Iavor I. Bojinov
Although the term 'Generative AI' (GenAI) is widely recognized, its practical application in daily workflows has yet to be understood. This exercise introduces students to GenAI tools, demonstrating how they can be seamlessly integrated into professional work practices... View Details
Keywords: AI and Machine Learning; Technology Adoption; Marketing Strategy; Product Launch; Brands and Branding
Related
  • March 2023
  • Teaching Note

VideaHealth: Building the AI Factory

By: Karim R. Lakhani
Teaching Note for HBS Case No. 621-021. The case “VideaHealth: Building the AI Factory” examines the creation of dental startup VideaHealth (Videa) and the development of its artificial intelligence (AI)-led business strategy through the eyes of founder and CEO Florian... View Details
Keywords: AI and Machine Learning; Applications and Software; Business Model; Marketing Strategy; Product Development; Health Industry; Technology Industry
Related
  • Student-Profile

Ta-Wei "David" Huang

management and using causal inference / machine learning tools to solve marketing problems.” It was this motivation that led him to pursue a Ph.D. Initially, David’s familiarity with HBS was limited to the... View Details
  • 01 Oct 1997
  • News

Expanded Elective Curriculum Offers Students A Wealth of Choices

finest." Field-Based Learning Expanded field-based learning opportunities now include more field studies, faculty-initiated research projects in which students may participate, and fieldwork within standard... View Details
  • 16 Nov 2020
  • Blog Post

Flatiron School: Reflections from Summer 2020

Birchbox, Young Invincibles, Color Camp, Women 2.0 and Casper. WHAT WERE YOUR GOALS FOR THE SUMMER? Rocio Wu (MBA 2020): Learning python and machine learning had always been on... View Details
Keywords: All Industries
  • 23 Oct 2019
  • News

Preparing Leaders to Leverage Artificial Intelligence

learning techniques to draw conclusions that weren’t possible with traditional methods, and creating new machine learning approaches and algorithms. They have published more... View Details
Keywords: Intellectual Ambition; Pathbreaking Research; Artificial Intelligence
  • 25 Mar 2014
  • Research & Ideas

Book Excerpt: ‘Can China Lead?’

leading universities in June 2012 to call for increased party supervision of higher education. Deans and presidents everywhere must make decisions and set priorities. In reality, however, many of the best ideas—those that deans and... View Details
Keywords: Re: William C. Kirby & F. Warren McFarlan; Education; Technology