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- All HBS Web (70)
- Faculty Publications (30)
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- All HBS Web (70)
- Faculty Publications (30)
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- 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
- Teaching Interest
Overview
Paul is primarily interested in teaching data science to management students through the case method. This includes technical topics (programming and statistics) as well as higher-level management issues (digital transformation, data governance, etc.) As a research... View Details
Keywords: A/B Testing; AI; AI Algorithms; AI Creativity; Algorithm; Algorithm Bias; Algorithmic Bias; Algorithmic Fairness; Algorithms; Analytics; Application Program Interface; Artificial Intelligence; Causality; Causal Inference; Computing; Computers; Data Analysis; Data Analytics; Data Architecture; Data As A Service; Data Centers; Data Governance; Data Labeling; Data Management; Data Manipulation; Data Mining; Data Ownership; Data Privacy; Data Protection; Data Science; Data Science And Analytics Management; Data Scientists; Data Security; Data Sharing; Data Strategy; Data Visualization; Database; Data-driven Decision-making; Data-driven Management; Data-driven Operations; Datathon; Economics Of AI; Economics Of Innovation; Economics Of Information System; Economics Of Science; Forecast; Forecast Accuracy; Forecasting; Forecasting And Prediction; Information Technology; Machine Learning; Machine Learning Models; Prediction; Prediction Error; Predictive Analytics; Predictive Models; Analysis; AI and Machine Learning; Analytics and Data Science; Applications and Software; Digital Transformation; Information Management; Digital Strategy; Technology Adoption
- 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... View Details
Keywords: by Rachel Layne
- 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... View Details
- 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... View Details
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... View Details
Keywords: 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... View Details
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://www.hbs.edu/faculty/Pages/item.aspx?num=54465 How Scheduling Can Bias Quality Assessment: Evidence from Food... View Details
Keywords: Sean Silverthorne
- 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... View Details
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.
- 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... View Details
- Forthcoming
- Article
Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation
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... View Details
Keywords: AI and Machine Learning; Analytics and Data Science; Forecasting and Prediction; Digital Marketing
Balakrishnan, Maya, Kris Ferreira, and Jordan Tong. "Human-Algorithm Collaboration with Private Information: Naïve Advice Weighting Behavior and Mitigation." Management Science (forthcoming).
- 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... View Details
Keywords: Sean Silverthorne
- 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:... View Details
Keywords: 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... View Details
Keywords: Sean Silverthorne
- 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,... View Details
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,... View Details
Keywords: by Kristen Senz
- 07 Jan 2019
- Research & Ideas
The Better Way to Forecast the Future
for prediction and for forecasting something that is unknown.” The rise of big data and machine learning offers infinitely more fuel to churn out probability forecasts, which can serve as an entry point for businesses looking to harness... View Details
- 07 Aug 2013
- What Do You Think?
Is There Still a Role for Judgment in Decision-Making?
'gut check' on big decisions is always prudent. I realize that is the sort of bias these authors warn about, but the application of their methods shouldn't reduce decision-making to a formula " Phil Clark had a more encompassing view... View Details
Keywords: by James Heskett
- 26 Mar 2018
- Research & Ideas
To Motivate Employees, Give an Unexpected Bonus (or Penalty)
employees make or how many units they produce. “The objective performance measures don’t take into consideration whether the machine broke down or whether someone is still learning the job,” Gallani explains. To compensate, managers often... View Details
- May 2022 (Revised June 2024)
- Case
LOOP: Driving Change in Auto Insurance Pricing
By: Elie Ofek and Alicia Dadlani
John Henry and Carey Anne Nadeau, co-founders and co-CEOs of LOOP, an insurtech startup based in Austin, Texas, were on a mission to modernize the archaic $250 billion automobile insurance market. They sought to create equitably priced insurance by eliminating pricing... View Details
Keywords: AI and Machine Learning; Technological Innovation; Equality and Inequality; Prejudice and Bias; Growth and Development Strategy; Customer Relationship Management; Price; Insurance Industry; Financial Services Industry
Ofek, Elie, and Alicia Dadlani. "LOOP: Driving Change in Auto Insurance Pricing." Harvard Business School Case 522-073, May 2022. (Revised June 2024.)