Publications

21 Nov 2015
News

Machines Beat Humans at Hiring Best Employees

Keywords: machine learning; hiring practices; human resources

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

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

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

Article

Faithful and Customizable Explanations of Black Box Models

By: Himabindu Lakkaraju, Ece Kamar, Rich Caruana and Jure Leskovec

As predictive models increasingly assist human experts (e.g., doctors) in day-to-day decision making, it is crucial for experts to be able to explore and understand how such models behave in different feature subspaces in order to know if and when to trust them. To... View Details

Keywords: Interpretable Machine Learning; Black Box Models; Decision Making; Framework

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

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

9 Dec 2016
Conference Presentation

Learning Cost-Effective and Interpretable Regimes for Treatment Recommendation

By: Himabindu Lakkaraju and Cynthia Rudin

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

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

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

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

November 2023 (Revised June 2024)
Case

Zest AI: Machine Learning and Credit Access

By: David S. Scharfstein and Ryan Gilland

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

8 Dec 2016
Conference Presentation

Learning Cost-Effective and Interpretable Treatment Regimes for Judicial Bail Decisions

By: Himabindu Lakkaraju and Cynthia Rudin

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

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