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(645)
- News (145)
- Research (421)
- Events (15)
- Multimedia (11)
- Faculty Publications (295)
Show Results For
- All HBS Web
(645)
- News (145)
- Research (421)
- Events (15)
- Multimedia (11)
- Faculty Publications (295)
- Article
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses
By: Kaivalya Rawal and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision-making, there has been a lot of interest in developing algorithms which can provide recourses to affected individuals. While developing such tools is important, it is even more critical to... View Details
Rawal, Kaivalya, and Himabindu Lakkaraju. "Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses." Advances in Neural Information Processing Systems (NeurIPS) 33 (2020).
- March 2022
- Article
Where to Locate COVID-19 Mass Vaccination Facilities?
By: Dimitris Bertsimas, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li and Alessandro Previero
The outbreak of COVID-19 led to a record-breaking race to develop a vaccine. However, the limited vaccine capacity creates another massive challenge: how to distribute vaccines to mitigate the near-end impact of the pandemic? In the United States in particular, the new... View Details
Keywords: Vaccines; COVID-19; Health Care and Treatment; Health Pandemics; Performance Effectiveness; Analytics and Data Science; Mathematical Methods
Bertsimas, Dimitris, Vassilis Digalakis Jr, Alexander Jacquillat, Michael Lingzhi Li, and Alessandro Previero. "Where to Locate COVID-19 Mass Vaccination Facilities?" Naval Research Logistics Quarterly 69, no. 2 (March 2022): 179–200.
- 2022
- Article
Towards Robust Off-Policy Evaluation via Human Inputs
By: Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez and Himabindu Lakkaraju
Off-policy Evaluation (OPE) methods are crucial tools for evaluating policies in high-stakes domains such as healthcare, where direct deployment is often infeasible, unethical, or expensive. When deployment environments are expected to undergo changes (that is, dataset... View Details
Singh, Harvineet, Shalmali Joshi, Finale Doshi-Velez, and Himabindu Lakkaraju. "Towards Robust Off-Policy Evaluation via Human Inputs." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (2022): 686–699.
- 22 Feb 2024
- Research & Ideas
How to Make AI 'Forget' All the Private Data It Shouldn't Have
predictions about the world. And now, even though generative AI feels very different from making a simple prediction, at a technical level, that's really what it is. In order to train these predictive systems, you need lots of example data input and output pairs. The... View Details
- 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
Valenzuela, A., 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. "How Artificial Intelligence Constrains Human Experience." Journal of the Association for Consumer Research 9, no. 3 (July 2024): 241–256.
- December 2016
- Article
Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud
By: Michael Luca and Georgios Zervas
Consumer reviews are now part of everyday decision making. Yet, the credibility of these reviews is fundamentally undermined when businesses commit review fraud, creating fake reviews for themselves or their competitors. We investigate the economic incentives to commit... View Details
Luca, Michael, and Georgios Zervas. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud." Management Science 62, no. 12 (December 2016): 3412–3427.
- 2015
- Working Paper
Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud
By: Michael Luca and Georgios Zervas
Consumer reviews are now part of everyday decision-making. Yet, the credibility of these reviews is fundamentally undermined when businesses commit review fraud, creating fake reviews for themselves or their competitors. We investigate the economic incentives to commit... View Details
Keywords: Information; Competition; Internet and the Web; Ethics; Reputation; Social and Collaborative Networks; Retail Industry; Food and Beverage Industry
Luca, Michael, and Georgios Zervas. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud." Working Paper. (May 2015. Revise and resubmit, Management Science.)
- 2021
- Working Paper
Time Dependency, Data Flow, and Competitive Advantage
Data is fundamental to machine learning-based products and services and is considered strategic due to its externalities for businesses, governments, non-profits, and more generally for society. It is renowned that the value of organizations (businesses, government... View Details
Keywords: Economics Of AI; Value Of Data; Perishability; Time Dependency; Flow Of Data; Data Strategy; Analytics and Data Science; Value; Strategy; Competitive Advantage
Valavi, Ehsan, Joel Hestness, Marco Iansiti, Newsha Ardalani, Feng Zhu, and Karim R. Lakhani. "Time Dependency, Data Flow, and Competitive Advantage." Harvard Business School Working Paper, No. 21-099, March 2021.
- 22 May 2024
- HBS Case
Banned or Not, TikTok Is a Force Companies Can’t Afford to Ignore
Practice at HBS who authored the case study with HBS researcher Shweta Bagai. Businesses need to “understand how it is that they’re doing what they’re doing so that they can incorporate the power of algorithmic technologies into their... View Details
- 30 Nov 2010
- Working Paper Summaries
Sponsored Links’ or ’Advertisements’?: Measuring Labeling Alternatives in Internet Search Engines
- October–December 2022
- Article
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details
Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction
Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem." INFORMS Journal on Data Science 1, no. 2 (October–December 2022): 138–155.
- Web
Blavatnik Fellowship in Life Science Entrepreneurship - Health Care
Genomics, developing algorithms for groundbreaking single-cell and spatial transcriptomics products. Before that, he was a bioinformatics intern at Illumina. Narek holds an MEng and BSc in computer science and molecular biology from MIT.... View Details
- 28 Feb 2018
- HBS Seminar
Kartik Hosanagar, Wharton, University of Pennsylvania
- November 2024
- Case
AlphaGo (A): Birth of a New Intelligence
By: Shikhar Ghosh and Shweta Bagai
This case, the first of a three-part series, traces DeepMind's evolution from its 2010 founding through its acquisition by Google in 2014. Often referred to as the "Apollo project" of artificial intelligence, DeepMind used games as a testing ground to develop AI... View Details
- Web
Named Fellowship Funds - Alumni
companies. The firm is a pioneer in the innovative application of data science to the investment process. Its activities are supported by ContinuumLab.ai, a proprietary software platform that develops new investing algorithms by applying... View Details
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data,... View Details
- 07 Feb 2022
- Research & Ideas
Digital Transformation: A New Roadmap for Success
algorithms can lead to unintended bias that harms certain employees and customers, and the company’s reputation (a bias story can go viral on social media within minutes). 5. Design for inclusive and agile problem-solving As they become... View Details
- 29 Apr 2013
- Working Paper Summaries
Exclusive Preferential Placement as Search Diversion: Evidence from Flight Search
- 22 May 2019
- Blog Post
What is FIELD Global Immersion?
to travel based on where their home country is, and where they have extensive travel or professional experience. With these considerations in mind, country and team assignments (aka: Global Section assignments) are made via an algorithm... View Details
- 18 Feb 2025
- HBS Seminar