Filter Results:
(418)
Show Results For
- All HBS Web
(670)
- News (145)
- Research (418)
- Events (16)
- Multimedia (11)
- Faculty Publications (295)
Show Results For
- All HBS Web
(670)
- News (145)
- Research (418)
- Events (16)
- Multimedia (11)
- Faculty Publications (295)
Sort by
- 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.
- 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).
- 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
- 19 Jan 2023
- Research & Ideas
What Makes Employees Trust (vs. Second-Guess) AI?
When an algorithm recommends ways to improve business outcomes, do employees trust it? Conventional wisdom suggests that understanding the inner workings of artificial intelligence (AI) can raise confidence in such programs. Yet, new... View Details
Keywords: by Rachel Layne
- 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.
- 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
- 10 Feb 2020
- In Practice
6 Ways That Emerging Technology Is Disrupting Business Strategy
Economic Research. 3. Algorithms are changing the pricing game “Firms are increasingly using pricing algorithms to set prices, especially in online markets. Pricing View Details
Keywords: by Danielle Kost
- 2021
- Article
To Thine Own Self Be True? Incentive Problems in Personalized Law
By: Jordan M. Barry, John William Hatfield and Scott Duke Kominers
Recent years have seen an explosion of scholarship on “personalized law.” Commentators foresee a world in which regulators armed with big data and machine learning techniques determine the optimal legal rule for every regulated party, then instantaneously disseminate... View Details
Keywords: Personalized Law; Regulation; Regulatory Avoidance; Regulatory Arbitrage; Law And Economics; Law And Technology; Law And Artificial Intelligence; Futurism; Moral Hazard; Elicitation; Signaling; Privacy; Law; Governing Rules, Regulations, and Reforms; Information Technology; AI and Machine Learning
Barry, Jordan M., John William Hatfield, and Scott Duke Kominers. "To Thine Own Self Be True? Incentive Problems in Personalized Law." Art. 2. William & Mary Law Review 62, no. 3 (2021).
- 29 Apr 2013
- Working Paper Summaries
Exclusive Preferential Placement as Search Diversion: Evidence from Flight Search
- 03 Jan 2017
- First Look
January 3, 2017
Winter 2017 MIT Sloan Management Review Why Big Data Isn't Enough By: Chai, Sen, and Willy C. Shih Abstract—There is a growing belief that sophisticated algorithms can explore huge databases and find relationships independent of any... View Details
Keywords: Carmen Nobel
- January 2021
- Case
Anodot: Autonomous Business Monitoring
By: Antonio Moreno and Danielle Golan
Autonomous business monitoring platform Anodot leveraged machine learning to provide real-time alerts regarding business anomalies. Anodot’s solution was used in various industries in order to primarily monitor business health, such as revenue and payments, product... View Details
Keywords: Digital Platforms; Internet and the Web; Knowledge Sharing; Information Management; Sales; Value Creation; Product Positioning; Israel
Moreno, Antonio, and Danielle Golan. "Anodot: Autonomous Business Monitoring." Harvard Business School Case 621-084, January 2021.
- 20 Aug 2013
- First Look
First Look: August 20
Lakhani, and Michael E. Menietti Abstract—Tournaments are widely used in the economy to organize production and innovation. We study individual contestant-level data from 2,796 contestants in 774 software algorithm design contests with... View Details
Keywords: Anna Secino
- 23 Jul 2013
- First Look
First Look: July 23
restaurant reviews with Yelp's algorithmic indicator of fake reviews. Using this imperfect indicator as a proxy, we develop an empirical methodology to identify the points in the life cycle of a business during which review fraud is most... View Details
Keywords: Anna Secino
- September 2011 (Revised July 2012)
- Case
Building Watson: Not So Elementary, My Dear!
By: Willy Shih
This case is set inside IBM Research's efforts to build a computer that can successfully take on human challengers playing the game show Jeopardy! It opens with the machine named Watson offering the incorrect answer "Toronto" to a seemingly simple question during the... View Details
Keywords: Technological Innovation; Standards; Product Development; Organizational Change and Adaptation; Mathematical Methods; Research and Development; Information Technology
Shih, Willy. "Building Watson: Not So Elementary, My Dear!" Harvard Business School Case 612-017, September 2011. (Revised July 2012.)
- 23 Aug 2012
- Working Paper Summaries
Field Evidence on Individual Behavior & Performance in Rank-Order Tournaments
- March–April 2023
- Article
Market Segmentation Trees
By: Ali Aouad, Adam Elmachtoub, Kris J. Ferreira and Ryan McNellis
Problem definition: We seek to provide an interpretable framework for segmenting users in a population for personalized decision making. Methodology/results: We propose a general methodology, market segmentation trees (MSTs), for learning market... View Details
Keywords: Decision Trees; Computational Advertising; Market Segmentation; Analytics and Data Science; E-commerce; Consumer Behavior; Marketplace Matching; Marketing Channels; Digital Marketing
Aouad, Ali, Adam Elmachtoub, Kris J. Ferreira, and Ryan McNellis. "Market Segmentation Trees." Manufacturing & Service Operations Management 25, no. 2 (March–April 2023): 648–667.
- 05 May 2022
- HBS Case
College Degrees: The Job Requirement Companies Seek, but Don't Really Need
than 70 percent of Black, Latinx, and rural workers from landing jobs, even though they may have the actual skills to do the required work. Many companies rely on machine learning algorithms that automatically weed out job applicants who... View Details
Keywords: by Jay Fitzgerald
- 12 Apr 2022
- Research & Ideas
Swiping Right: How Data Helped This Online Dating Site Make More Matches
we had no real idea what would prevail. So, this is where the scientific mystery lies,” he says. Applying dating algorithms to other industries, cautiously Platonic platforms could follow similar, industry-appropriate revelation models.... View Details
Keywords: by Kara Baskin