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  • 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... View Details
Keywords: by Kara Baskin
  • 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
Keywords: by Danielle Kost; Consumer Products; Real Estate; Financial Services; Retail
  • 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
Keywords: by Kara Baskin; Entertainment & Recreation; Food & Beverage; Retail
  • 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
Keywords: AI and Machine Learning; Organizational Change and Adaptation; Prejudice and Bias; Ethics
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  • 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
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  • 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
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  • 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
  • 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
  • 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
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  • 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
Keywords: by Kristen Senz; Technology
  • 2025
  • Working Paper

Warnings and Endorsements: Improving Human-AI Collaboration in the Presence of Outliers

By: Matthew DosSantos DiSorbo, Kris Ferreira, Maya Balakrishnan and Jordan Tong
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). How can humans and algorithms work together to make... View Details
Keywords: AI and Machine Learning; Decision Choices and Conditions
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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:... 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
  • 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
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  • 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
Keywords: by Roberta Holland; Air Transportation; Transportation
  • 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
Keywords: by Michael Blanding; Manufacturing

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