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  • All HBS Web  (1,197)
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Show Results For

  • All HBS Web  (1,197)
    • People  (2)
    • News  (187)
    • Research  (797)
    • Events  (14)
    • Multimedia  (3)
  • Faculty Publications  (568)
← Page 4 of 1,197 Results →
  • Article

Productivity and Selection of Human Capital with Machine Learning

By: Aaron Chalfin, Oren Danieli, Andrew Hillis, Zubin Jelveh, Michael Luca, Jens Ludwig and Sendhil Mullainathan
Keywords: Analytics and Data Science; Selection and Staffing; Performance Productivity; Mathematical Methods; Policy
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Chalfin, Aaron, Oren Danieli, Andrew Hillis, Zubin Jelveh, Michael Luca, Jens Ludwig, and Sendhil Mullainathan. "Productivity and Selection of Human Capital with Machine Learning." American Economic Review: Papers and Proceedings 106, no. 5 (May 2016): 124–127.
  • 08 Dec 2016
  • News

A Guide to Solving Social Problems with Machine Learning

  • Research Summary

Overview

Jenny is broadly interested in interpretable machine learning (ML), identity and inequality, and improving existing methods used to answer social and policy-relevant questions. Her recent projects have focused on developing tools that explore how LLMs are reshaping... View Details
  • 04 Oct 2019
  • Working Paper Summaries

Soul and Machine (Learning)

Keywords: by Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano et al.
  • 2018
  • Working Paper

Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning

By: Xiaojia Guo, Yael Grushka-Cockayne and Bert De Reyck
Problem definition: In collaboration with Heathrow Airport, we develop a predictive system that generates quantile forecasts of transfer passengers’ connection times. Sampling from the distribution of individual passengers’ connection times, the system also produces... View Details
Keywords: Quantile Forecasts; Regression Tree; Copula; Passenger Flow Management; Data-driven Operations; Forecasting and Prediction; Data and Data Sets
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Guo, Xiaojia, Yael Grushka-Cockayne, and Bert De Reyck. "Forecasting Airport Transfer Passenger Flow Using Real-Time Data and Machine Learning." Harvard Business School Working Paper, No. 19-040, October 2018.
  • Article

When Dreaming Is Believing: The (Motivated) Interpretation of Dreams

By: Carey K. Morewedge and Michael I. Norton
This research investigated laypeople's interpretation of their dreams. Participants from both Eastern and Western cultures believed that dreams contain hidden truths (Study 1) and considered dreams to provide more meaningful information about the world than similar... View Details
Keywords: Anchoring; Attribution; Dreams; Motivated Reasoning; Unconscious Thought; Communication Intention and Meaning; Judgments; Values and Beliefs; Information; Behavior; Cognition and Thinking; Motivation and Incentives
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Morewedge, Carey K., and Michael I. Norton. "When Dreaming Is Believing: The (Motivated) Interpretation of Dreams." Journal of Personality and Social Psychology 96, no. 2 (February 2009): 249–264. (Winner of Society for Personality and Social Psychology. Theoretical Innovation Prize For an article or book chapter judged to provide the most innovative theoretical contribution to social/personality psychology within a given year presented by Society for Personality and Social Psychology​.)
  • 26 Feb 2018
  • Working Paper Summaries

Different Strokes for Different Folks: Experimental Evidence on Complementarities Between Human Capital and Machine Learning

Keywords: by Prithwiraj Choudhury, Evan Starr, and Rajshree Agarwal; Information Technology
  • 14 Mar 2023
  • News

Can AI and Machine Learning Help Park Rangers Prevent Poaching?

  • Link

Machine Learning Models for Prediction of Scope 3 Carbon Emissions

  • Web

Machine Learning frameworks (Tensorflow, PyTorch, Keras, OpenCV) - Research Computing Services

Software Tools Machine Learning frameworks (Tensorflow, PyTorch, Keras, OpenCV) 48ms The HBSGrid offers artificial intelligence(AI) and machine View Details
  • April 2018 (Revised February 2019)
  • Supplement

Improving Worker Safety in the Era of Machine Learning (B)

By: Michael W. Toffel, Dan Levy, Astrid Camille Pineda, Jose Ramon Morales Arilla and Matthew S. Johnson
Supplements the (A) case. View Details
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Toffel, Michael W., Dan Levy, Astrid Camille Pineda, Jose Ramon Morales Arilla, and Matthew S. Johnson. "Improving Worker Safety in the Era of Machine Learning (B)." Harvard Business School Supplement 618-064, April 2018. (Revised February 2019.)
  • January 2024 (Revised February 2024)
  • Case

Data-Driven Denim: Financial Forecasting at Levi Strauss

By: Mark Egan
The case examines Levi Strauss’ journey in implementing machine learning and AI into its financial forecasting process. The apparel company partnered with the IT company Wipro in 2017 to develop a machine learning algorithm that could help Levi Strauss forecast its... View Details
Keywords: Investor Relations; Forecasting; Machine Learning; Artificial Intelligence; Apparel; Corporate Finance; Forecasting and Prediction; AI and Machine Learning; Digital Transformation; Apparel and Accessories Industry; United States
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Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Case 224-029, January 2024. (Revised February 2024.)
  • February 2024
  • Teaching Note

Data-Driven Denim: Financial Forecasting at Levi Strauss

By: Mark Egan
Teaching Note for HBS Case No. 224-029. Levi Strauss & Co. (“Levi Strauss”) partnered with the IT services company Wipro to incorporate more sophisticated methods, such as machine learning, into their financial forecasting process starting in 2018. The decision to... View Details
Keywords: Forecasting; Regression; Machine Learning; Artificial Intelligence; Apparel; Corporate Finance; Forecasting and Prediction; AI and Machine Learning; Apparel and Accessories Industry; United States
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Egan, Mark. "Data-Driven Denim: Financial Forecasting at Levi Strauss." Harvard Business School Teaching Note 224-073, February 2024.
  • 2023
  • Chapter

Marketing Through the Machine’s Eyes: Image Analytics and Interpretability

By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details
Keywords: Transparency; Marketing Research; Algorithmic Bias; AI and Machine Learning; Marketing
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Zhang, Shunyuan, Flora Feng, and Kannan Srinivasan. "Marketing Through the Machine’s Eyes: Image Analytics and Interpretability." Chap. 8 in Artificial Intelligence in Marketing. 20, edited by Naresh K. Malhotra, K. Sudhir, and Olivier Toubia, 217–238. Review of Marketing Research. Emerald Publishing Limited, 2023.
  • February 2018 (Revised March 2018)
  • Case

Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP)

By: Lauren Cohen, Christopher Malloy and William Powley
This case examines the intersection of two firms (Cogent Labs—a machine learning software firm in Tokyo; and Google, the technology infrastructure giant) attempting to exploit the benefits of artificial intelligence and machine learning in the financial services... View Details
Keywords: Technological Innovation; Finance; Growth and Development Strategy; Business Model; Applications and Software; Infrastructure; Technology Industry; Financial Services Industry
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Cohen, Lauren, Christopher Malloy, and William Powley. "Artificial Intelligence and the Machine Learning Revolution in Finance: Cogent Labs and the Google Cloud Platform (GCP)." Harvard Business School Case 218-080, February 2018. (Revised March 2018.)
  • 2025
  • Article

Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments

By: Kosuke Imai and Michael Lingzhi Li
Researchers are increasingly turning to machine learning (ML) algorithms to investigate causal heterogeneity in randomized experiments. Despite their promise, ML algorithms may fail to accurately ascertain heterogeneous treatment effects under practical settings with... View Details
Keywords: AI and Machine Learning; Mathematical Methods; Analytics and Data Science
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Imai, Kosuke, and Michael Lingzhi Li. "Statistical Inference for Heterogeneous Treatment Effects Discovered by Generic Machine Learning in Randomized Experiments." Journal of Business & Economic Statistics 43, no. 1 (2025): 256–268.
  • May 2022
  • Case

AWS and Amazon SageMaker (A): The Commercialization of Machine Learning Services

By: Karim R. Lakhani, Shane Greenstein and Kerry Herman
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Lakhani, Karim R., Shane Greenstein, and Kerry Herman. "AWS and Amazon SageMaker (A): The Commercialization of Machine Learning Services." Harvard Business School Case 622-060, May 2022.
  • November 25, 2016
  • Article

How to Tell If Machine Learning Can Solve Your Business Problem

By: Anastassia Fedyk
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Fedyk, Anastassia. "How to Tell If Machine Learning Can Solve Your Business Problem." Harvard Business Review (website) (November 25, 2016).
  • May 2022 (Revised July 2022)
  • Supplement

AWS and Amazon SageMaker (C): The Commercialization of Machine Learning Services

By: Karim R. Lakhani, Shane Greenstein and Kerry Herman
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Lakhani, Karim R., Shane Greenstein, and Kerry Herman. "AWS and Amazon SageMaker (C): The Commercialization of Machine Learning Services." Harvard Business School Supplement 622-087, May 2022. (Revised July 2022.)
  • May 2022
  • Supplement

AWS and Amazon SageMaker (B): The Commercialization of Machine Learning Services

By: Karim R. Lakhani, Shane Greenstein and Kerry Herman
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Lakhani, Karim R., Shane Greenstein, and Kerry Herman. "AWS and Amazon SageMaker (B): The Commercialization of Machine Learning Services." Harvard Business School Supplement 622-086, May 2022.
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