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- Faculty Publications (28)
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- All HBS Web (67)
- Faculty Publications (28)
- 19 Jan 2023
- Research & Ideas
What Makes Employees Trust (vs. Second-Guess) AI?
products were grouped in 241 “style-colors'' and sizes. When the allocators received a recommendation from an interpretable algorithm, they often overruled it based on their own intuition. But when the same allocators had a recommendation from a similarly accurate...
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by Rachel Layne
- 11 Apr 2023
- Research & Ideas
Is Amazon a Retailer, a Tech Firm, or a Media Company? How AI Can Help Investors Decide
industry lines as companies increasingly bring seemingly unrelated business lines together in unconventional ways. New research by Awada, Harvard Business School Professor Suraj Srinivasan, and doctoral student Paul J. Hamilton harnesses View Details
- 12 Apr 2022
- Research & Ideas
Swiping Right: How Data Helped This Online Dating Site Make More Matches
some estimates, with players such as Bumble, Tinder, and OKCupid vying to help people find love. While McFowland is not a dating expert, his work in machine learning and social sciences examines the efficacy of how people interact in...
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by Kara Baskin
- 26 Jul 2022
- Research & Ideas
Burgers with Bugs? What Happens When Restaurants Ignore Online Reviews
reviews helps consumers choose cleaner restaurants, which is a pretty robust finding." Harvard Business School Assistant Professor Chiara Farronato and Georgios Zervas, an associate professor at Boston University, used machine learning to...
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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,...
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- May 9, 2023
- Article
8 Questions About Using AI Responsibly, Answered
By: Tsedal Neeley
Generative AI tools are poised to change the way every business operates. As your own organization begins strategizing which to use, and how, operational and ethical considerations are inevitable. This article delves into eight of them, including how your organization...
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Neeley, Tsedal. "8 Questions About Using AI Responsibly, Answered." Harvard Business Review (website) (May 9, 2023).
- 19 Feb 2019
- First Look
New Research and Ideas, February 19, 2019
forthcoming Journal of Political Economy CEO Behavior and Firm Performance By: Bandiera, Oriana, Stephen Hansen, Andrea Prat, and Raffaella Sadun Abstract— We measure the behavior of 1,114 CEOs in six countries parsing granular CEO diary data through an unsupervised...
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Sean Silverthorne
- 2023
- Working Paper
The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities
By: David S. Scharfstein and Sergey Chernenko
We show that the use of algorithms to predict race has significant limitations in measuring and understanding the sources of racial disparities in finance, economics, and other contexts. First, we derive theoretically the direction and magnitude of measurement bias in...
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Keywords:
Racial Disparity;
Paycheck Protection Program;
Measurement Error;
AI and Machine Learning;
Race;
Measurement and Metrics;
Equality and Inequality;
Prejudice and Bias;
Forecasting and Prediction;
Outcome or Result
Scharfstein, David S., and Sergey Chernenko. "The Limits of Algorithmic Measures of Race in Studies of Outcome Disparities." Working Paper, April 2023.
- 08 May 2018
- First Look
First Look at New Research and Ideas, May 8, 2018
unexpected networking opportunities, generating a tight community of German businesspeople in India. Publisher's link: https://pubwww.hbs.edu/faculty/Pages/item.aspx?num=54465 How Scheduling Can Bias Quality Assessment: Evidence from Food...
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Sean Silverthorne
- 26 Apr 2023
- In Practice
Is AI Coming for Your Job?
will be displaced in large numbers. Those job losses will be partially offset by job gains for machine learning specialists and emerging jobs like prompt engineers. But, once companies learn how to exploit generative AI, we can anticipate...
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- 2020
- Working Paper
(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial
By: Prithwiraj Choudhury, Tarun Khanna, Christos A. Makridis and Subhradip Sarker
While there is evidence about labor market discrimination based on race, religion, and gender, we know little about whether physical appearance leads to discrimination in labor market outcomes. We deploy a randomized experiment on 1,000 respondents in India between...
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Keywords:
Behavioral Economics;
Coronavirus;
Discrimination;
Homophily;
Labor Market Mobility;
Limited Attention;
Resumes;
Personal Characteristics;
Prejudice and Bias
Choudhury, Prithwiraj, Tarun Khanna, Christos A. Makridis, and Subhradip Sarker. "(When) Does Appearance Matter? Evidence from a Randomized Controlled Trial." Harvard Business School Working Paper, No. 21-038, September 2020.
- Web
Placement - Doctoral
Leventhal School of Accounting Dissertation: Truth and Bias in M&A Target Fairness Valuations: Appraising the Appraisals Advisors: Suraj Srinivasan, John Coates, and Charles C.Y. Wang 2018 Carolyn Deller Accounting & Management, 2018...
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- 06 Jun 2017
- First Look
First Look at New Research and Ideas: June 6, 2017
reallocation accounts for the majority of aggregate productivity gains, suggesting that ignoring this channel could lead to substantial bias in understanding the nature of gains from multinational production. Publisher's link:...
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Sean Silverthorne
- 17 Jun 2014
- First Look
First Look: June 17
feedback influence order quantities. We find that the portion of mismatch cost due to adjustment behavior exceeds the portion of mismatch cost due to level behavior in three out of four conditions. Observation bias is studied through...
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Sean Silverthorne
- Web
Technology & Operations Management - Faculty & Research
about demand, which may not fully account for its impact on employee welfare. Keywords: AI and Machine Learning; Forecasting and Prediction; Working Conditions; Performance Productivity Citation Read Now Related Kwon, Caleb, Ananth Raman,...
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- 08 Apr 2014
- First Look
First Look: April 8
By: Hałaburda, Hanna, and Felix Oberholzer-Gee Abstract—The value of many products and services rises or falls with the number of customers using them; the fewer fax machines in use, the less important it is to have one. These network...
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Sean Silverthorne
- 2024
- Working Paper
Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence
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...
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Keywords:
Cognitive Biases;
Algorithm Transparency;
Forecasting and Prediction;
Behavior;
AI and Machine Learning;
Analytics and Data Science;
Cognition and Thinking
Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Improving Human-Algorithm Collaboration: Causes and Mitigation of Over- and Under-Adherence." Working Paper, February 2024.
- 2024
- Working Paper
Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift
By: Matthew DosSantos DiSorbo and Kris Ferreira
Problem definition: While artificial intelligence (AI) algorithms may perform well on data that are representative of the training set (inliers), they may err when extrapolating on non-representative data (outliers). These outliers often originate from covariate shift,...
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DosSantos DiSorbo, Matthew, and Kris Ferreira. "Warnings and Endorsements: Improving Human-AI Collaboration Under Covariate Shift." Working Paper, February 2024.
- 30 May 2023
- Research & Ideas
Can AI Predict Whether Shoppers Would Pick Crest or Colgate?
came from a sample of customers.” While the recent emergence of ChatGPT has reignited fears that machines may replace humans in the workplace, the results of this study don’t necessarily mean that AI is going to gut marketing departments,...
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- 01 Dec 2023
- News
Thinking Ahead
As we wind down 2023, there’s talk everywhere of generative AI and how it will fundamentally alter the world as we know it; but how does that translate for your corner of the business world? Is TikTok something you need to take seriously? (Is it time to dance?) We...
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