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Show Results For
- All HBS Web
(1,483)
- People (1)
- News (274)
- Research (943)
- Events (19)
- Multimedia (6)
- Faculty Publications (771)
- Research Summary
Overview
Paul is primarily interested in studying explainable machine learning (ML), digital transformation, and data science operations. He works on research that explores how stakeholders within organizations can use machine learning to make better decisions. In particular,... View Details
- 2022
- Working Paper
The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives
By: Ariel Dora Stern
For those who follow health and technology news, it is difficult to go more than a few days without reading about a compelling new application of Artificial Intelligence (AI) to health care. AI has myriad applications in medicine and its adjacent industries, with... View Details
Keywords: AI and Machine Learning; Health Care and Treatment; Governing Rules, Regulations, and Reforms; Technological Innovation; Medical Devices and Supplies Industry
Stern, Ariel Dora. "The Regulation of Medical AI: Policy Approaches, Data, and Innovation Incentives." NBER Working Paper Series, No. 30639, December 2022.
Jingpeng Hong
Jingpeng is a Ph.D. student in Marketing at Harvard Business School. Previously, he received a B.A. in Economics from the National School of Development, Peking University and a M.A. in Social Sciences, Economics from the University of Chicago. His research interests... View Details
- 2024
- Working Paper
Learning to Cover: Online Learning and Optimization with Irreversible Decisions
By: Alexander Jacquillat and Michael Lingzhi Li
Keywords: Buildings and Facilities; AI and Machine Learning; Geographic Location; Strategic Planning
Jacquillat, Alexander, and Michael Lingzhi Li. "Learning to Cover: Online Learning and Optimization with Irreversible Decisions." Working Paper, June 2024.
- July 2024
- Article
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety... View Details
Keywords: Autonomy; Chatbots; New Technology; Brand Crises; Mental Health; Large Language Model; AI and Machine Learning; Behavior; Well-being; Technological Innovation; Ethics
De Freitas, Julian, Ahmet Kaan Uğuralp, Zeliha Uğuralp, and Stefano Puntoni. "Chatbots and Mental Health: Insights into the Safety of Generative AI." Journal of Consumer Psychology 34, no. 3 (July 2024): 481–491.
- 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).
- 01 Jun 1997
- News
Blockbuster Deals
inept or complacent management drew the attention of raiders. "I give credit to that 1980s movement as a whole for having created the profit machine that we see in the 1990s," Hayes says. "We now have an M&A; movement driven by strategic... View Details
Keywords: Garry Emmons and Nancy O. Perry
- January 2022
- Article
Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems
By: David R. Clough and Andy Wu
Gregory, Henfridsson, Kaganer, and Kyriakou (2020) highlight the important role of data and AI as strategic resources that platforms may use to enhance user value. However, their article overlooks a significant conceptual distinction: the installed base of... View Details
Keywords: Artificial Intelligence; Data Strategy; Ecosystem; Value Capture; Digital Platforms; Analytics and Data Science; Strategy; Learning; Value Creation; AI and Machine Learning; Technology Industry; Information Technology Industry; Video Game Industry; Advertising Industry
Clough, David R., and Andy Wu. "Artificial Intelligence, Data-Driven Learning, and the Decentralized Structure of Platform Ecosystems." Academy of Management Review 47, no. 1 (January 2022): 184–189.
- 01 May 2018
- First Look
First Look at New Research and Ideas, May 1, 2018
Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP) No abstract available. Purchase this case:... View Details
Keywords: Sean Silverthorne
- Fast Answer
Digital Innovation and Transformation: Resources useful for Course Assignments
DIT course assignment. To identify and analyze firms using company data and reports, you may begin with more than one of the following databases: View Details
- 22 Feb 2021
- Blog Post
I Found My Future at HBS and You Can Too
lenses, our place in the world appeared immutable. Fortunately for me, that was about to change. Two military aircraft suddenly flew low and fast over the field where I was riding. As they tore through the sky, I imagined the sensation of... View Details
- 2021
- Chapter
Towards a Unified Framework for Fair and Stable Graph Representation Learning
By: Chirag Agarwal, Himabindu Lakkaraju and Marinka Zitnik
As the representations output by Graph Neural Networks (GNNs) are increasingly employed in real-world applications, it becomes important to ensure that these representations are fair and stable. In this work, we establish a key connection between counterfactual... View Details
Agarwal, Chirag, Himabindu Lakkaraju, and Marinka Zitnik. "Towards a Unified Framework for Fair and Stable Graph Representation Learning." In Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence, edited by Cassio de Campos and Marloes H. Maathuis, 2114–2124. AUAI Press, 2021.
- December 1998 (Revised March 1999)
- Case
Disruptive Technology a Heartbeat Away: Ecton, Inc.
By: Clayton M. Christensen and Edward G Cape
Describes an innovating start-up company with a disruptive technology to the large, expensive echocardiography machines that leading cardiologists use to create images of heart functions for diagnostic purposes. Ecton's machine is small, cheap, portable, and can't... View Details
Keywords: Business Startups; Disruption; Machinery and Machining; Entrepreneurship; Innovation and Invention; Marketing; Product; Commercialization; Technology; Medical Devices and Supplies Industry
Christensen, Clayton M., and Edward G Cape. "Disruptive Technology a Heartbeat Away: Ecton, Inc." Harvard Business School Case 699-018, December 1998. (Revised March 1999.)
- 05 Dec 2017
- First Look
First Look at New Research and Ideas, December 5, 2017
methodologies such as machine learning. We highlight the importance of distinguishing between which customers are at risk and which should be targeted—as they are not necessarily the same customers. We... View Details
Keywords: Sean Silverthorne
- 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.
- 06 Feb 2018
- First Look
First Look at New Research and Ideas: February 6, 2018
and Machine Learning By: Choudhury, Prithwiraj, Evan Starr, and Rajshree Agarwal Abstract—The advent of artificial intelligence in the form of View Details
- 05 Nov 2024
- Book
Building the Road to 'Small Business Utopia' with AI and Fintech
assistant who knew all about the business, including the goals and preferences of the owner. What if this bot could respond to requests in plain English to perform daily tasks and improve sales View Details
- 28 Mar 2023
- Blog Post
Meet Professor Elisabeth Paulson: A Conversation on Life, Research, and Teaching
intervention and 2) decide how it should be deployed in order to be most effective. Rigorously accomplishing both steps requires many different tools from the fields of statistics, machine learning, View Details
Shunyuan Zhang
Shunyuan Zhang is an assistant professor in the Marketing unit at Harvard Business School. She teaches the first-year Marketing course in the MBA required curriculum.
Professor Zhang studies the sharing economy and the marketing problems that the dynamics of... View Details
- 20 Oct 2020
- Blog Post
Exploring Technology and Public Impact Through the HBS/HKS Joint Degree Program
Policy team. In that role, I developed and analyzed Lyft policy positions on future of work and emerging technology issues such as machine learning, data sharing, View Details