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Show Results For
- All HBS Web
(946)
- People (1)
- News (155)
- Research (626)
- Events (13)
- Multimedia (3)
- Faculty Publications (534)
- 23 Oct 2018
- First Look
New Research and Ideas, October 23, 2018
Data and Machine Learning By: Guo, Xiaojia, Yael Grushka-Cockayne, and Bert De Reyck Abstract—Problem definition: In collaboration with Heathrow Airport, we develop a predictive system that generates... View Details
Keywords: Dina Gerdeman
- 2022
- Conference Presentation
Towards the Unification and Robustness of Post hoc Explanation Methods
By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two... View Details
Keywords: AI and Machine Learning
Agarwal, Sushant, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, and Himabindu Lakkaraju. "Towards the Unification and Robustness of Post hoc Explanation Methods." Paper presented at the 3rd Symposium on Foundations of Responsible Computing (FORC), 2022.
Tsedal Neeley
Tsedal Neeley is the Naylor Fitzhugh Professor of Business Administration, Senior Associate Dean of Faculty Development and Research, and Faculty Chair of the Christensen Center for Teaching... View Details
- 21 Sep 2023
- HBS Seminar
Pinar Ozcan, Saïd Business School
- Teaching Interest
Harvard Business Analytics Program: Operations and Supply Chain Management
By: Dennis Campbell
Digital technologies and data analytics are radically changing the operating model of an organization and how it connects to its broader supply chain and ecosystem. This course emphasizes managing product availability, especially in a context of rapid product... View Details
- April–June 2022
- Other Article
Commentary on 'Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters'
There has been a substantial discussion in various methodological and applied literatures around causal inference; especially in the use of machine learning and statistical models to understand heterogeneity in treatment effects and to make optimal decision... View Details
Keywords: Causal Inference; Treatment Effect Estimation; Treatment Assignment Policy; Human-in-the-loop; Decision Making; Fairness
McFowland III, Edward. "Commentary on 'Causal Decision Making and Causal Effect Estimation Are Not the Same... and Why It Matters'." INFORMS Journal on Data Science 1, no. 1 (April–June 2022): 21–22.
- 2021
- Book
The Future of Executive Development
By: Mihnea C Moldoveanu and Das Narayandas
Executive development programs have entered a period of rapid transformation, driven by digital disruption and a widening gap between the skills that participants and their organizations demand and those provided by their executive programs. This work delves into the... View Details
Moldoveanu, Mihnea C., and Das Narayandas. The Future of Executive Development. Stanford, CA: Stanford Business Books, 2021.
- 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
Wu, Andy, Matt Higgins, Miaomiao Zhang, and Hang Jiang. "AI Wars." Harvard Business School Case 723-434, April 2023. (Revised February 2024.)
- November 2015 (Revised May 2016)
- Case
Aspiring Minds
By: Karim R. Lakhani, Marco Iansiti and Christine Snively
By 2015, India-based employment assessment and certification provider Aspiring Minds had helped facilitate over 300,000 job matches through its assessment tools. Aspiring Minds' flagship product, the Aspiring Minds Computer Adaptive Test (AMCAT), used machine learning... View Details
Keywords: Information Technology; Strategy; Higher Education; Technological Innovation; Employment; Technology Industry; India; China
Lakhani, Karim R., Marco Iansiti, and Christine Snively. "Aspiring Minds." Harvard Business School Case 616-013, November 2015. (Revised May 2016.)
Elisabeth C. Paulson
Elisabeth Paulson is an Assistant Professor of Business Administration in the Technology and Operations Management Unit at Harvard Business School. She teaches the first year course on Technology and Operations Management in the required curriculum.
View Details
Policy versus Practice: Conceptions of Artificial Intelligence
The recent growth of concern around issues such as social biases implicit in algorithms, economic impacts of artificial intelligence (AI), or potential existential threats posed... View Details
- March 2025
- Case
Niramai: An AI Solution to Save Lives
By: Rembrand Koning, Maria P. Roche and Kairavi Dey
Founded in 2017, Niramai developed Thermalytix, a breast cancer screening tool. Thermalytix used a high-resolution thermal sensing device and machine learning algorithms to analyze thermal images and detect tumors. Its patented solution leveraged big data analytics,... View Details
- September 2023 (Revised January 2024)
- Case
AI21 Labs in 2023: Strategy for Generative AI
By: David Yoffie, Orna Dan and Elena Corsi
Israeli generative artificial intelligence company AI21 Labs was founded in 2017 to realize the vision of true machine intelligence. It sought to reinvent writing and reading and in 2020 it launched Wordtune, an app using GenAI software to offer alternate text... View Details
Keywords: Decision Making; AI and Machine Learning; Innovation Strategy; Growth and Development Strategy; Applications and Software; Competitive Strategy; Technology Industry; Israel
Yoffie, David, Orna Dan, and Elena Corsi. "AI21 Labs in 2023: Strategy for Generative AI." Harvard Business School Case 724-383, September 2023. (Revised January 2024.)
- May 2024
- Teaching Note
AI Wars
By: Andy Wu and Matt Higgins
Teaching Note for HBS Case No. 723-434. In 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 popularized over... View Details
Srikant M. Datar
Srikant M. Datar became the eleventh dean of Harvard Business School on 1 January 2021. During his tenure as a faculty member, he served as Senior Associate Dean for University Affairs (including Faculty Chair of the Harvard Innovation Lab), for Research, for... View Details
- Research Summary
Overview
By: Srikant M. Datar
Professor Datar has several research and course development interests. His initial areas of research interest were in cost management and management control, strategy implementation and governance. Over the last few years his areas of interest are management education,... View Details
- January 2023 (Revised April 2023)
- Case
Cobalt Robotics: Scaling Workplace Robotics
By: Jeffrey F. Rayport, Nicole Tempest Keller and Kyung Keun Park
Founded in 2016, Cobalt Robotics, based in Fremont, California, was a Robot-as-a-Service (RaaS) company that built autonomous workplace robots that were designed to replace or supplement human security guards. Outfitted with over 60 sensors, Cobalt robots patrolled... View Details
Keywords: Information Infrastructure; Disruptive Innovation; Innovation and Invention; Marketing Strategy; Marketing Channels; Customers; Technology Industry; United States; California
Rayport, Jeffrey F., Nicole Tempest Keller, and Kyung Keun Park. "Cobalt Robotics: Scaling Workplace Robotics." Harvard Business School Case 823-096, January 2023. (Revised April 2023.)
- Forthcoming
- Article
An AI Method to Score Celebrity Visual Potential from Human Faces
By: Flora Feng, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan and Cait Lamberton
It has long been a mantra of marketing practice that, particularly in low-involvement situations, spokespeople should be physically attractive. This paper suggests there is a higher probability of gaining fame and influence (i.e., celebrity potential) than is captured... View Details
Feng, Flora, Shunyuan Zhang, Xiao Liu, Kannan Srinivasan, and Cait Lamberton. "An AI Method to Score Celebrity Visual Potential from Human Faces." Journal of Marketing Research (JMR) (forthcoming).
- June 2023
- Article
When Does Uncertainty Matter? Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making
By: Sean McGrath, Parth Mehta, Alexandra Zytek, Isaac Lage and Himabindu Lakkaraju
As machine learning (ML) models are increasingly being employed to assist human decision
makers, it becomes critical to provide these decision makers with relevant inputs which can
help them decide if and how to incorporate model predictions into their decision... View Details
McGrath, Sean, Parth Mehta, Alexandra Zytek, Isaac Lage, and Himabindu Lakkaraju. "When Does Uncertainty Matter? Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making." Transactions on Machine Learning Research (TMLR) (June 2023).