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  • All HBS Web  (1,023)
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    • News  (187)
    • Research  (664)
    • Events  (13)
    • Multimedia  (3)
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  • 02–03 Dec 2022
  • HBS Alumni Events

D^3 Catalyst: No Code Machine Learning and Artificial Intelligence

Do you want to delve into Machine Learning and Artificial Intelligence, but you feel overwhelmed and intimidated? Do you want to leverage the power of Machine Learning and Artificial Intelligence without writing any code? Do you want to leverage Machine Learning and... View Details
  • November 2023
  • Case

Open Source Machine Learning at Google

By: Shane Greenstein, Martin Wattenberg, Fernanda B. Viégas, Daniel Yue and James Barnett
Set in early 2023, the case exposes students to the challenges of managing open source software at Google. The case focuses on the challenges for Alex Spinelli, Vice President of Product Management for Core Machine Learning. He must set priorities for Google’s efforts... View Details
Keywords: Decision Choices and Conditions; Technological Innovation; Open Source Distribution; Strategy; AI and Machine Learning; Applications and Software; Technology Industry; United States
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Greenstein, Shane, Martin Wattenberg, Fernanda B. Viégas, Daniel Yue, and James Barnett. "Open Source Machine Learning at Google." Harvard Business School Case 624-015, November 2023.
  • October 2022 (Revised December 2022)
  • Case

SMART: AI and Machine Learning for Wildlife Conservation

By: Brian Trelstad and Bonnie Yining Cao
Spatial Monitoring and Reporting Tool (SMART), a set of software and analytical tools designed for the purpose of wildlife conservation, had demonstrated significant improvements in patrol coverage, with some observed reductions in poaching and contributing to wildlife... View Details
Keywords: Business and Government Relations; Emerging Markets; Technology Adoption; Strategy; Management; Ethics; Social Enterprise; AI and Machine Learning; Analytics and Data Science; Natural Environment; Technology Industry; Cambodia; United States; Africa
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Trelstad, Brian, and Bonnie Yining Cao. "SMART: AI and Machine Learning for Wildlife Conservation." Harvard Business School Case 323-036, October 2022. (Revised December 2022.)
  • November 2021 (Revised December 2021)
  • Supplement

PittaRosso (B): Human and Machine Learning

By: Ayelet Israeli
This case supplements the "PittaRosso: Artificial Intelligence-Driven Pricing and Promotion" case, and provides major highlights on what happened at the company since the first case. View Details
Keywords: Artificial Intelligence; Pricing; Pricing Algorithm; Pricing Decisions; Pricing Strategy; Pricing Structure; Promotion; Promotions; Online Marketing; Data-driven Decision-making; Data-driven Management; Retail; Retail Analytics; Price; Advertising Campaigns; Analytics and Data Science; Analysis; Digital Marketing; Budgets and Budgeting; Marketing Strategy; Marketing; Transformation; Decision Making; AI and Machine Learning; Retail Industry; Italy
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Israeli, Ayelet. "PittaRosso (B): Human and Machine Learning." Harvard Business School Supplement 522-047, November 2021. (Revised December 2021.)
  • 19 Jun 2020
  • Podcast

Dexai: Machine learning in the kitchen

Advances in robotics have opened the way for the ultimate in smart kitchen appliances. Draper Labs spinoff, Dexai, makes the AI brains that coordinate the actions of Alfred, a robotic arm versatile enough follow recipes and handle orders in commercial kitchens.... View Details
  • Research Summary

Adoption of Machine Learning Models in Real World Decision Making

By: Himabindu Lakkaraju
The goal of this research is to assess the impact of deploying machine learning models in real world decision making in domains such as health care. View Details
  • 14 Mar 2023
  • Cold Call Podcast

Can AI and Machine Learning Help Park Rangers Prevent Poaching?

Keywords: Re: Brian L. Trelstad; Computer; Information Technology; Technology
  • April 2025
  • Background Note

Climate Change Adaptation with Artificial Intelligence and Machine Learning

By: Michael W. Toffel and Nabig Chaudhry
Artificial Intelligence (AI) and machine learning (ML) have emerged as powerful tools to address climate change. This note summarizes a wide range of the uses of AI/ML to drive climate change adaptation and resilience, the measures organizations and governments are... View Details
Keywords: Climate Change; Adaptation
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Toffel, Michael W., and Nabig Chaudhry. "Climate Change Adaptation with Artificial Intelligence and Machine Learning." Harvard Business School Background Note 625-050, April 2025.
  • November 2023 (Revised June 2024)
  • Case

Zest AI: Machine Learning and Credit Access

By: David S. Scharfstein and Ryan Gilland
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Scharfstein, David S., and Ryan Gilland. "Zest AI: Machine Learning and Credit Access." Harvard Business School Case 224-033, November 2023. (Revised June 2024.)
  • 2022
  • Working Paper

TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations

By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet they have become more complex and harder to understand. To address this issue, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use explainability... View Details
Keywords: Natural Language Conversations; Predictive Models; AI and Machine Learning
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Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "TalkToModel: Explaining Machine Learning Models with Interactive Natural Language Conversations." Working Paper, 2022.
  • 01 Nov 2018
  • Working Paper Summaries

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

Keywords: by Xiaojia Guo, Yael Grushka-Cockayne, and Bert De Reyck; Air Transportation; Travel
  • 21 Aug 2019
  • Research & Ideas

What Machine Learning Teaches Us about CEO Leadership Style

CEOs are communicators. Studies show that CEOs spend 85 percent of their time in communication-related activities, including speeches, meetings, and phone calls with people both inside and outside the firm. Now, new research using machine... View Details
Keywords: by Michael Blanding
  • August 2023
  • Article

Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel

By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use... View Details
Keywords: AI and Machine Learning; Technological Innovation; Technology Adoption
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Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel." Nature Machine Intelligence 5, no. 8 (August 2023): 873–883.
  • Working Paper

Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application

By: Flora Feng, Charis Li and Shunyuan Zhang
Peer-to-peer (P2P) marketplaces have seen exponential growth in recent years featured by unique offerings from individual providers. Despite the perceived value of uniqueness, scalable quantification of visual uniqueness in P2P platforms like Airbnb has been largely... View Details
Keywords: Peer-to-peer Markets; Marketplace Matching; AI and Machine Learning; Demand and Consumers; Digital Platforms; Marketing
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Feng, Flora, Charis Li, and Shunyuan Zhang. "Visual Uniqueness in Peer-to-Peer Marketplaces: Machine Learning Model Development, Validation, and Application." SSRN Working Paper Series, No. 4665286, February 2024.
  • 08 Dec 2016
  • News

A Guide to Solving Social Problems with Machine Learning

  • 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

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.
  • 17 Jan 2020
  • News

AB InBev Taps Machine Learning to Root Out Corruption

  • 04 Oct 2019
  • Working Paper Summaries

Soul and Machine (Learning)

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

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

Software Tools Machine Learning frameworks (Tensorflow, PyTorch, Keras, OpenCV) 62ms The HBSGrid offers artificial intelligence(AI) and machine View Details
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