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- Faculty Publications (540)
Show Results For
- All HBS Web
(1,018)
- People (1)
- News (186)
- Research (659)
- Events (13)
- Multimedia (3)
- Faculty Publications (540)
- October 2024 (Revised April 2025)
- Case
Nvidia
By: Andy Wu and Matt Higgins
This case study examines Nvidia's strategic pivot from gaming GPUs to becoming a leader in general-purpose computing and AI. It explores how Nvidia leveraged its GPU architecture to dominate the growing fields of data center acceleration and AI training, outpacing... View Details
- 2023
- Working Paper
Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness
By: Neil Menghani, Edward McFowland III and Daniel B. Neill
In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details
Menghani, Neil, Edward McFowland III, and Daniel B. Neill. "Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness." Working Paper, June 2023.
- 01 Jun 2015
- News
The Military and the MBA: Gene Markowski (MBA 1973)
in 2013. I was stationed in a tank unit out in Colorado Springs when the Vietnam War started up. I didn’t think I wanted to be in a tank in Vietnam, so I volunteered to go to flight school. Six months later, I was in combat. I was a 24-year-old captain View Details
- 2025
- Working Paper
Balancing Engagement and Polarization: Multi-Objective Alignment of News Content Using LLMs
By: Mengjie Cheng, Elie Ofek and Hema Yoganarasimhan
We study how media firms can use LLMs to generate news content that aligns with multiple objectives—making content more engaging while maintaining a preferred level of polarization/slant consistent with the firm’s editorial policy. Using news articles from The New York... View Details
Keywords: Large Language Models; Content Creation; Media; Polarization; Generative Ai; Direct Preference Optimization; AI and Machine Learning; News; Perspective; Digital Marketing; Policy; Media and Broadcasting Industry
Cheng, Mengjie, Elie Ofek, and Hema Yoganarasimhan. "Balancing Engagement and Polarization: Multi-Objective Alignment of News Content Using LLMs." Harvard Business School Working Paper, No. 25-051, April 2025.
- 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
- 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
- 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
Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation." Management Science (forthcoming).
- 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
Huang, Ta-Wei, and Eva Ascarza. "Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals." Marketing Science 43, no. 4 (July–August 2024): 863–884.
- 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
- May–June 2024
- Article
Should Your Brand Hire a Virtual Influencer?
By: Serim Hwang, Shunyuan Zhang, Xiao Liu and Kannan Srinivasan
Followers respond more favorably to sponsored posts by virtual influencers versus those by humans, costs are lower, and creating an influencer from scratch allows marketers to introduce more diversity. View Details
Hwang, Serim, Shunyuan Zhang, Xiao Liu, and Kannan Srinivasan. "Should Your Brand Hire a Virtual Influencer?" Harvard Business Review 102, no. 3 (May–June 2024): 56–60.
- 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
- 29 Sep 2020
- Blog Post
New Life for Old Tech: Startup Provides Network Security Solutions for Obsolete Devices
device-specific representation of each device on the network, and our generalizable machine learning approach and software-based installation allows us to scale to all legacy and modern devices.” For Breen,... View Details
- March 2025
- Case
Metaphysic AI: Rethinking the Value of Human Expertise
By: Zoë B. Cullen, Shikhar Ghosh and Shweta Bagai
In early 2025, Thomas Graham, CEO of Metaphysic, a leading AI generative video company confronted fundamental questions about who should control digital identity in a world where AI could perfectly recreate human likeness. Founded in 2021, Metaphysic first rose to fame... View Details
Keywords: Business Model; Ethics; AI and Machine Learning; Intellectual Property; Rights; Negotiation; Value; Motion Pictures and Video Industry; Technology Industry
Cullen, Zoë B., Shikhar Ghosh, and Shweta Bagai. "Metaphysic AI: Rethinking the Value of Human Expertise." Harvard Business School Case 825-146, March 2025.
- February 2024 (Revised September 2024)
- Case
TimeCredit
By: Emanuele Colonnelli, Raymond Kluender and Shai Benjamin Bernstein
TimeCredit is an artificial intelligence (AI) startup that is developing large language models (LLMs) to generate accounting memos. The case follows Ndonga Sagnia, a Gambian Harvard Business School MBA student with an accounting background, as she decides how much... View Details
Keywords: Accounting; Business Startups; Entrepreneurship; Financing and Loans; AI and Machine Learning; Entrepreneurial Finance; Identity; Technology Industry
Colonnelli, Emanuele, Raymond Kluender, and Shai Benjamin Bernstein. "TimeCredit." Harvard Business School Case 824-139, February 2024. (Revised September 2024.)
- February 2021 (Revised June 2021)
- Case
Bairong and the Promise of Big Data
By: Lauren Cohen, Xiaoyan Zhang and Spencer C.N. Hagist
Bairong CEO Felix Zhang, in launching his credit scoring start-up that incorporates 74,000 variables per individual, found strong initial success. However, the shifting regulatory environment, growing breadth of competitors, difficulties in retaining top talent, and... View Details
Keywords: Fintech; Big Data; Artificial Intelligence; Credit Scoring; Finance; Credit; Business Startups; AI and Machine Learning; Analytics and Data Science; China
Cohen, Lauren, Xiaoyan Zhang, and Spencer C.N. Hagist. "Bairong and the Promise of Big Data." Harvard Business School Case 221-068, February 2021. (Revised June 2021.)
- January 2025
- Teaching Note
AGENTS.inc: Pathways to Growth at an AI Startup
By: Frank Nagle and Susan Pinckney
Teaching Note for HBS Case No. 724-444. In 2024, AI agent startup company AGENTS.inc faced multiple strategic decisions that could shape the company’s ability to grow into the future AI agent market leader. View Details
- October 2023
- Case
Fixie and Conversational AI Sidekicks
By: Jeffrey J. Bussgang and Carin-Isabel Knoop
In March 2023, Fixie Co-Founder and Chief Architect Matt Welsh and co-founders had the kind of meeting no founders want to have. The president of leading artificial intelligence (AI) research and deployment firm OpenAI, which had catapulted into fame with its ChatGPT... View Details
Keywords: Large Language Model; Entrepreneurship; Decision Choices and Conditions; AI and Machine Learning; Technological Innovation; Competitive Strategy; Technology Industry; United States
Bussgang, Jeffrey J., and Carin-Isabel Knoop. "Fixie and Conversational AI Sidekicks." Harvard Business School Case 824-037, October 2023.
- 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
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.)
- Article
Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting
By: Raymond H. Mak, Michael G. Endres, Jin Hyun Paik, Rinat A. Sergeev, Hugo Aerts, Christopher L. Williams, Karim R. Lakhani and Eva C. Guinan
Importance: Radiation therapy (RT) is a critical cancer treatment, but the existing radiation oncologist work force does not meet growing global demand. One key physician task in RT planning involves tumor segmentation for targeting, which requires substantial... View Details
Keywords: Crowdsourcing; AI Algorithms; Health Care and Treatment; Collaborative Innovation and Invention; AI and Machine Learning
Mak, Raymond H., Michael G. Endres, Jin Hyun Paik, Rinat A. Sergeev, Hugo Aerts, Christopher L. Williams, Karim R. Lakhani, and Eva C. Guinan. "Use of Crowd Innovation to Develop an Artificial Intelligence-Based Solution for Radiation Therapy Targeting." JAMA Oncology 5, no. 5 (May 2019): 654–661.
- May 2024
- Article
The Health Risks of Generative AI-Based Wellness Apps
By: Julian De Freitas and G. Cohen
Artifcial intelligence (AI)-enabled chatbots are increasingly being used to
help people manage their mental health. Chatbots for mental health and
particularly ‘wellness’ applications currently exist in a regulatory ‘gray area’.
Indeed, most generative AI-powered... View Details
Keywords: AI and Machine Learning; Well-being; Governing Rules, Regulations, and Reforms; Applications and Software
De Freitas, Julian, and G. Cohen. "The Health Risks of Generative AI-Based Wellness Apps." Nature Medicine 30, no. 5 (May 2024): 1269–1275.