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- All HBS Web (15)
- Faculty Publications (5)
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- All HBS Web (15)
- Faculty Publications (5)
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- January–February 2022
- Article
Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion
By: Ryan Allen and Prithwiraj Choudhury
How does a knowledge worker’s level of domain experience affect their algorithm-augmented work performance? We propose and test theoretical predictions that domain experience has countervailing effects on algorithm-augmented performance: on one hand, domain experience... View Details
Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance
Allen, Ryan, and Prithwiraj Choudhury. "Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion." Organization Science 33, no. 1 (January–February 2022): 149–169. ("Best PhD Student Paper" at SMS conference 2020.)
- 2020
- Working Paper
Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion
By: Ryan Allen and Prithwiraj Choudhury
Past research offers mixed perspectives on whether domain experience helps or hurts algorithm-augmented work performance. To reconcile these perspectives, we theorize that domain experience affects algorithm-augmented performance via two distinct countervailing... View Details
Keywords: Automation; Domain Experience; Algorithmic Aversion; Experts; Algorithms; Machine Learning; Decision-making; Future Of Work; Employees; Experience and Expertise; Decision Making; Performance
Allen, Ryan, and Prithwiraj Choudhury. "Algorithm-Augmented Work and Domain Experience: The Countervailing Forces of Ability and Aversion." Harvard Business School Working Paper, No. 21-073, October 2020. (Revised September 2021.)
- April 2024
- Article
Decision Authority and the Returns to Algorithms
By: Hyunjin Kim, Edward L. Glaeser, Andrew Hillis, Scott Duke Kominers and Michael Luca
We evaluate a pilot in an Inspections Department to explore the returns to a pair of algorithms that varied in their sophistication. We find that both algorithms provided substantial prediction gains, suggesting that even simple data may be helpful. However, these... View Details
Keywords: Algorithmic Aversion; Algorithmic Decision Making; Algorithms; Public Entrepreneurship; Govenment; Local Government; Crowdsourcing; Crowdsourcing Contests; Inspection; Principal-agent Theory; Government Administration; Decision Making; Public Administration Industry; United States
Kim, Hyunjin, Edward L. Glaeser, Andrew Hillis, Scott Duke Kominers, and Michael Luca. "Decision Authority and the Returns to Algorithms." Strategic Management Journal 45, no. 4 (April 2024): 619–648.
- October 2019
- Article
Making Sense of Recommendations
By: Michael Yeomans, Anuj Shah, Sendhil Mullainathan and Jon Kleinberg
Computer algorithms are increasingly being used to predict people's preferences and make recommendations. Although people frequently encounter these algorithms because they are cheap to scale, we do not know how they compare to human judgment. Here, we compare computer... View Details
Keywords: Recommender Systems; Artificial Intelligence; Interpretability; Information Technology; Forecasting and Prediction; Decision Making; Attitudes
Yeomans, Michael, Anuj Shah, Sendhil Mullainathan, and Jon Kleinberg. "Making Sense of Recommendations." Journal of Behavioral Decision Making 32, no. 4 (October 2019): 403–414.
- 2021
- Article
Fair Influence Maximization: A Welfare Optimization Approach
By: Aida Rahmattalabi, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice and Milind Tambe
Several behavioral, social, and public health interventions, such as suicide/HIV prevention or community preparedness against natural disasters, leverage social network information to maximize outreach. Algorithmic influence maximization techniques have been proposed... View Details
Rahmattalabi, Aida, Shahin Jabbari, Himabindu Lakkaraju, Phebe Vayanos, Max Izenberg, Ryan Brown, Eric Rice, and Milind Tambe. "Fair Influence Maximization: A Welfare Optimization Approach." Proceedings of the AAAI Conference on Artificial Intelligence 35th (2021).
- 06 Oct 2015
- First Look
October 6, 2015
themselves and the charity, they respond very similarly to self risk and charity risk. By contrast, when their decisions force tradeoffs between money for themselves and the charity, participants act more averse to charity risk and less... View Details
Keywords: Sean Silverthorne
- 31 Jul 2023
- News
Striving for Imperfection
interaction of multiple AI models also with people. This has been used to great effect to guessing sports outcomes, but also to doing cancer diagnosis. It turns out that a swarm of AI algorithms with human doctors gives better outcomes... View Details
- 01 Dec 2015
- News
Case Study: Bionic Banking
(Thinkstock/Getty Images) Robo-advisors, like Betterment and Wealthfront, are built for millennials-automated asset management for those with lower account balances or an aversion to traditional financial advisors. Silicon Valley has... View Details
- 21 Nov 2017
- First Look
First Look at New Research and Ideas, November 21, 2017
reviews from Yelp.com, we construct an adjusted average rating and show that even a simple algorithm can lead to large information efficiency gains relative to the arithmetic average. Publisher's link:... View Details
Keywords: Sean Silverthorne
- 27 Jan 2016
- Research & Ideas
A Politician's Investment Portfolio Might Tip Off Corruption Potential
percent stocks for the scandal free. Split another way, politicians holding more than 50 percent stocks were almost twice as likely to be involved in a scandal compared to their more risk averse counterparts. Personal investments that... View Details
Keywords: by Roberta Holland
- 05 Nov 2024
- Research & Ideas
AI Can Help Leaders Communicate, But Can't Make Employees Listen
to replicate the unique characteristics of a specific person’s writing style, says Prithwiraj Choudhury, the Lumry Family Associate Professor of Business Administration at Harvard Business School. “We trained an algorithm to write using... View Details
- 02 Feb 2016
- First Look
February 2, 2016
Organization Tax Aversion in Labor Supply By: Kessler, Judd B., and Michael I. Norton Abstract—In a real-effort laboratory experiment, labor supply decreases more with the introduction of a tax than with a financially equivalent drop in... View Details
Keywords: Sean Silverthorne
- 01 Jun 2018
- News
Up by the Roots
bakery cranks out cookies—New York now holds a demonstrable lead over Silicon Valley in terms of fintech investment in the United States. According to CB Insights, a New York startup that uses algorithms to collect and analyze data on... View Details
- Web
Print View - Course Catalog
algorithms to shape consumer behavior (TikTok), the misuse of AI in social contexts such as in the justice system and the industrialization of misinformation and hacking of elections. How can business leaders create great companies that... View Details