Publications

01 Dec 2022
News

Future Vision

created by Professor Mitch Weiss for students in The Entrepreneurial Manager. In class, students negotiate terms for a pool of VC money. The simulation draws on PitchBook data from real pitches, and it uses View Details

Keywords: Brian Kenny; Educational Support Services; Educational Services

26 Jan 2024
Blog Post

Career Advice from the Guests of the HBS Climate Rising Podcast

be impacted by the effects of climate change, so it is critical to have people in many areas who want to find solutions and drive forward the climate agenda. Every role will need to take climate action and every organization will need... View Details

Web

Entrepreneurial Management Awards & Honors - Faculty & Research

one of 100 Black Board Members Making a Difference by Board Prospects in 2024. Archie L. Jones : Received the 2024 Dr. James I. Cash Advancing Pathways Award. Rembrand M. Koning : Winner of the 2024 Distinguished Paper Award from the... View Details

January 2018 (Revised March 2019)
Case

Autonomous Vehicles: The Rubber Hits the Road...but When?

By: William Kerr, Allison Ciechanover, Jeff Huizinga and James Palano

The rise of autonomous vehicles has enormous implications for business and society. Despite the many headlines and significant investment in the technology by early 2019, it was still unclear when truly autonomous vehicles would be a commercial reality. Students will... View Details

Keywords: Technology Management; Artificial Intelligence; General Management; Robotics; Technological Innovation; Transportation; Disruption; Information Technology; Decision Making; AI and Machine Learning; Auto Industry; Technology Industry

Educators

2019
Article

An Empirical Study of Rich Subgroup Fairness for Machine Learning

By: Michael J Kearns, Seth Neel, Aaron Leon Roth and Zhiwei Steven Wu

Kearns et al. [2018] recently proposed a notion of rich subgroup fairness intended to bridge the gap between statistical and individual notions of fairness. Rich subgroup fairness picks a statistical fairness constraint (say, equalizing false positive rates across... View Details

Keywords: Machine Learning; Fairness; AI and Machine Learning

October–December 2022
Article

Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem

By: Mochen Yang, Edward McFowland III, Gordon Burtch and Gediminas Adomavicius

Combining machine learning with econometric analysis is becoming increasingly prevalent in both research and practice. A common empirical strategy involves the application of predictive modeling techniques to "mine" variables of interest from available data, followed... View Details

Keywords: Machine Learning; Econometric Analysis; Instrumental Variable; Random Forest; Causal Inference; AI and Machine Learning; Forecasting and Prediction

Find at Harvard

Register to Read

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

SSRN

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

09 Jun 2024
Blog Post

The EC Formula: MBA Class of 2024 Looks Back

Professor Esty emphasized the importance of having a viewpoint backed up by data—I feel better equipped going into the working world having been forced to reckon with my values and how that applies to corporate policy issues. Why did you... View Details

29 Nov 2023
News

A Holiday Benefit Dinner in LA; Seattle Club Revival Underway

there.” When they met up at a Global Networking Night in 2019, the two agreed they could combine Ayengar’s experience with launching the Singapore club with Weintraub’s business development skills to reboot the Seattle club. After an initial push was delayed View Details

Keywords: Margie Kelley

January 2021
Article

Machine Learning for Pattern Discovery in Management Research

By: Prithwiraj Choudhury, Ryan Allen and Michael G. Endres

Supervised machine learning (ML) methods are a powerful toolkit for discovering robust patterns in quantitative data. The patterns identified by ML could be used for exploratory inductive or abductive research, or for post-hoc analysis of regression results to detect... View Details

Keywords: Machine Learning; Supervised Machine Learning; Induction; Abduction; Exploratory Data Analysis; Pattern Discovery; Decision Trees; Random Forests; Neural Networks; ROC Curve; Confusion Matrix; Partial Dependence Plots; AI and Machine Learning

Find at Harvard

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

Web

Organizational Behavior Awards & Honors - Faculty & Research

Approaches to Diversity Recruitment” (September 2023). Tsedal Neeley : Winner of the 2024 Axiom Business Book Award Gold Medal in the Emerging Trends/AI category for The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms and View Details

2023
Article

M4: A Unified XAI Benchmark for Faithfulness Evaluation of Feature Attribution Methods across Metrics, Modalities, and Models

By: Himabindu Lakkaraju, Xuhong Li, Mengnan Du, Jiamin Chen, Yekun Chai and Haoyi Xiong

While Explainable Artificial Intelligence (XAI) techniques have been widely studied to explain predictions made by deep neural networks, the way to evaluate the faithfulness of explanation results remains challenging, due to the heterogeneity of explanations for... View Details

Keywords: AI and Machine Learning

June 2021
Article

From Predictions to Prescriptions: A Data-driven Response to COVID-19

By: Dimitris Bertsimas, Léonard Boussioux, Ryan Cory-Wright, Arthur Delarue, Vassilis Digalakis Jr, Alexander Jacquillat, Driss Lahlou Kitane, Galit Lukin, Michael Lingzhi Li, Luca Mingardi, Omid Nohadani, Agni Orfanoudaki, Theodore Papalexopoulos, Ivan Paskov, Jean Pauphilet, Omar Skali Lami, Bartolomeo Stellato, Hamza Tazi Bouardi, Kimberly Villalobos Carballo, Holly Wiberg and Cynthia Zeng

The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers make difficult decisions on patient triage, treatment and care management on a daily basis. Policy makers have imposed social distancing measures to slow the disease, at... View Details

Keywords: COVID-19; Health Pandemics; AI and Machine Learning; Forecasting and Prediction; Analytics and Data Science

2023
Working Paper

Insufficiently Justified Disparate Impact: A New Criterion for Subgroup Fairness

By: Neil Menghani, Edward McFowland III and Daniel B. Neill

In this paper, we develop a new criterion, "insufficiently justified disparate impact" (IJDI), for assessing whether recommendations (binarized predictions) made by an algorithmic decision support tool are fair. Our novel, utility-based IJDI criterion evaluates false... View Details

Keywords: AI and Machine Learning; Forecasting and Prediction; Prejudice and Bias

December 2016 (Revised November 2017)
Teaching Plan

Olivia Lum: Wanting to Save the World

By: Geoffrey Jones and Ai Hisano

Teaching Plan for HBS No. 316-178. View Details

November 2016
Teaching Plan

Christian Dior: A New Look for Haute Couture

By: Geoffrey Jones and Ai Hisano

Teaching Note for HBS No. 809-159. View Details

2019
Working Paper

Soul and Machine (Learning)

By: Davide Proserpio, John R. Hauser, Xiao Liu, Tomomichi Amano, Alex Burnap, Tong Guo, Dokyun Lee, Randall Lewis, Kanishka Misra, Eric Schwarz, Artem Timoshenko, Lilei Xu and Hema Yoganarasimhan

Machine learning is bringing us self-driving cars, improved medical diagnostics, and machine translation, but can it improve marketing decisions? It can. Machine learning models predict extremely well, are scalable to “big data,” and are a natural fit to rich media... View Details

Keywords: Machine Learning; Technological Innovation; Marketing; AI and Machine Learning

SSRN