Publications

December 1984
Case

Expense Tracking System at Tiger Creek

By: Shoshana Zuboff

Mill manager Carl Adelman learns that a group of senior managers is soon to visit the Tiger Creek mill to learn more about the success of the newly implemented Expense Tracking System. The System had been installed on two paper machines to give workers real time cost... View Details

Keywords: Management Teams; Success; Cost Management; Technology; Pulp and Paper Industry

Research Summary

Understanding the Limitations of Model Explanations

By: Himabindu Lakkaraju

The goal of this research is to understand how adversaries can exploit various algorithms used for explaining complex machine learning models with an intention to mislead end users. For instance, can adversaries trick these algorithms into masking their racial and... View Details

20 Nov 2024
HBS Seminar

Marc Rotenberg, Georgetown University Law

Jeremy Yang

Jeremy Yang is an Assistant Professor of Business Administration in the Marketing Unit at Harvard Business School. He teaches Marketing in the MBA required curriculum. He develops data products for... View Details

Keywords: advertising; media; entertainment; information; consumer products

13 Sep 2018
HBS Seminar

Nitin Joglekar, Boston University

December 2018 (Revised March 2021)
Background Note

Modern Automation (A): Artificial Intelligence

By: William R. Kerr and James Palano

This primer is meant to be a field guide to the late 2010s' surge in business use of "Artificial Intelligence" (AI), or enterprise software based in machine learning. First, it provides an overview of the key trends—digitization, connectivity, the continuation of... View Details

Keywords: Artificial Intelligence; Digitization; Connectivity; Computing; Future Of Work; Automation; AI and Machine Learning

Research Summary

Overview

By: Isamar Troncoso

Professor Troncoso's research explores problems related to digital marketplaces and AI applications in marketing, and combines toolkits from econometrics, causal inference, and machine learning. She has studied how different platform design choices can lead to... View Details

August 2021 (Revised November 2024)
Case

Intenseye: Powering Workplace Health and Safety with AI (A)

By: Michael W. Toffel and Youssef Abdel Aal

Intenseye was a Turkey-based technology startup that deployed machine learning algorithms to workplace camera feeds in order to identify unsafe worker actions and unsafe working conditions, in order to help improve worker safety. The case describes how Intenseye’s... View Details

Keywords: Privacy; Product Development; Operations; Technological Innovation; Value Creation; Production; Distribution; Safety; Risk and Uncertainty; Technology Industry; Manufacturing Industry; Distribution Industry; Turkey; Middle East; United States

February 2018
Case

Vodafone: Managing Advanced Technologies and Artificial Intelligence

By: William R. Kerr and Emer Moloney

Vodafone was operating in the fast-moving telecommunications market where innovation and scale were key. Faced with an onslaught of technological advances—big data, automation, and artificial intelligence—CEO Vittorio Colao reflected on how he should change the... View Details

Keywords: Technological Innovation; Management; Organizational Change and Adaptation; Corporate Social Responsibility and Impact; Opportunities; Telecommunications Industry

28 Mar 2017
Working Paper Summaries

CEO Behavior and Firm Performance

Keywords: by Oriana Bandiera, Stephen Hansen, Andrea Pratt, and Raffaella Sadun

26 Mar 2025
News

Behind the Research: Elisabeth Paulson

December 2020 (Revised April 2021)
Case

IBM Watson at MD Anderson Cancer Center

By: Shane Greenstein, Mel Martin and Sarkis Agaian

After discovering that their cancer diagnostic tool, designed to leverage the cloud computing power of IBM Watson, needed greater integration into the clinical processes at the MD Anderson Cancer Center, the development team had difficult choices to make. The Oncology... View Details

Keywords: Decision Making; Innovation Strategy; Knowledge Management; Knowledge Use and Leverage; Operations; Failure; Information Technology; Applications and Software; Health Care and Treatment; Product Development; Health Industry; Information Technology Industry; Technology Industry; United States; Houston; Texas

17 Jun 2021
News

Too Few Women Get to Invent – That’s a Problem for Women’s Health

Jenny Wang

Jenny Shan Wang is a doctoral student in the Technology and Operations Management program at Harvard Business School (HBS). She is broadly interested in interpretable machine learning (ML), identity and inequality, and improving existing methods... View Details

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

January 2019 (Revised October 2019)
Case

Liulishuo: AI English Teacher

By: John J-H Kim and Shu Lin

Educators and entrepreneurs alike are excited about the potential for artificial intelligence (AI) and machine learning to change the way learning will look like in the future. There is a confluence of factors such as the availability of large sources of rich,... View Details

Keywords: AI; Artificial Intelligence; Education Technology; Information Technology; Education; Entrepreneurship; AI and Machine Learning; Education Industry; China

20 Sep 2014
News

Making Big Data Think Bigger

2022
Working Paper

Rethinking Explainability as a Dialogue: A Practitioner's Perspective

By: Himabindu Lakkaraju, Dylan Slack, Yuxin Chen, Chenhao Tan and Sameer Singh

As practitioners increasingly deploy machine learning models in critical domains such as healthcare, finance, and policy, it becomes vital to ensure that domain experts function effectively alongside these models. Explainability is one way to bridge the gap between... View Details

Keywords: Natural Language Conversations; AI and Machine Learning; Experience and Expertise; Interactive Communication; Business and Stakeholder Relations