Publications

Register to Read

March 2024
Exercise

'Storrowed': A Generative AI Exercise

By: Mitchell Weiss

"Storrowed" is an exercise to help participants raise their capacity and curiosity for generative AI. It focuses on generative AI for problem understanding and ideation, but can be adapted for use more broadly. Participants use generative AI tools to understand a... View Details

Keywords: AI and Machine Learning; Problems and Challenges

Forthcoming
Article

Personalization and Targeting: How to Experiment, Learn & Optimize

By: Aurelie Lemmens, Jason M.T. Roos, Sebastian Gabel, Eva Ascarza, Hernan Bruno, Elea McDonnell Feit, Brett Gordon, Ayelet Israeli, Carl F. Mela and Oded Netzer

Personalization has become the heartbeat of modern marketing. Advances in causal inference and machine learning enable companies to understand how the same marketing action can impact the choices of individual customers differently. This article provides an academic... View Details

Keywords: Targeting; Experiments; Observational Studies; Policy Implementation; Policy Evaluation; Customization and Personalization; Marketing Strategy; Customer Focus and Relationships; Research

SSRN

June 2024
Teaching Note

Beamery: Using Skills and AI to Modernize HR

By: Boris Groysberg, David Lane, Susan Pinckney and Alexis Lefort

Teaching Note for HBS Case No. 424-004. Unicorn human relationships startup Beamery evaluates it growth versus depth strategy as its strategic partners and customers could become future competitors in a quickly changing AI based human resources and talent management... View Details

18 Apr 2000
Research & Ideas

Learning in Action

Bean, the U.S. Army's Center for Army Lessons Learned (CALL), AT&T's Bell Laboratories, the Timken Companies and General Electric's Change Acceleration Process (CAP). L.L. Bean has long relied on... View Details

Keywords: by David A. Garvin

Article

Oracle Efficient Private Non-Convex Optimization

By: Seth Neel, Aaron Leon Roth, Giuseppe Vietri and Zhiwei Steven Wu

One of the most effective algorithms for differentially private learning and optimization is objective perturbation. This technique augments a given optimization problem (e.g. deriving from an ERM problem) with a random linear term, and then exactly solves it.... View Details

Keywords: Machine Learning; Algorithms; Objective Perturbation; Mathematical Methods

June 2024
Case

Aidoc: Building a Hospital-Centric AI Platform

By: Ariel D. Stern and Susan Pinckney

In 2023, Israel-based AI health care company Aidoc evaluated its future. The company, founded in 2016, had grown from commercializing a single AI product for radiologists to a software platform that could detect 20 conditions and immediately notify care teams of... View Details

Educators

11 Feb 2020
Sharpening Your Skills

10 Rules Entrepreneurs Need to Know Before Adopting AI

of it as superhuman—especially if AI is solving complicated problems such as 100 percent accuracy in self-driving cars and medical diagnosis. You have to help them understand that the performance of ML... View Details

Keywords: by Rocio Wu

2022
Working Paper

The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective

By: Satyapriya Krishna, Tessa Han, Alex Gu, Javin Pombra, Shahin Jabbari, Steven Wu and Himabindu Lakkaraju

As various post hoc explanation methods are increasingly being leveraged to explain complex models in high-stakes settings, it becomes critical to develop a deeper understanding of if and when the explanations output by these methods disagree with each other, and how... View Details

Keywords: AI and Machine Learning; Analytics and Data Science; Mathematical Methods

November 2023 (Revised April 2024)
Case

Khanmigo: Revolutionizing Learning with GenAI

By: William A. Sahlman, Allison M. Ciechanover and Emily Grandjean

Already a leader in the edtech space since its 2008 launch, Khan Academy was now one of the first edtech organizations to embrace generative artificial intelligence ("genAI"). In March 2023, Khan Academy began beta testing Khanmigo, a genAI “guide” and tutor built with... View Details

Keywords: Technology Adoption; Leading Change; Entrepreneurship; Risk and Uncertainty; Education; AI and Machine Learning; Corporate Social Responsibility and Impact; Education Industry; Technology Industry; United States; San Francisco

Educators

April 2017
Case

The Future of Patent Examination at the USPTO

By: Prithwiraj Choudhury, Tarun Khanna and Sarah Mehta

The U.S. Patent and Trademark Office (USPTO) is the federal government agency responsible for evaluating and granting patents and trademarks. In 2015, the USPTO employed approximately 8,000 patent examiners who granted nearly 300,000 patents to inventors. As of April... View Details

Keywords: Machine Learning; Telework; Collaborating With Unions; Human Resources; Recruitment; Retention; Intellectual Property; Copyright; Patents; Trademarks; Knowledge Sharing; Technology Adoption; Organizational Change and Adaptation; Performance Productivity; Performance Improvement; District of Columbia

Educators

2024
Article

Neyman Meets Causal Machine Learning: Experimental Evaluation of Individualized Treatment Rules

By: Michael Lingzhi Li and Kosuke Imai

A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today’s scientists across... View Details

Keywords: AI and Machine Learning; Research

September 2024 (Revised January 2025)
Exercise

Building an AI First Snack Company: A Hands-on Generative AI Exercise

By: Iavor I. Bojinov

Although the term 'Generative AI' (GenAI) is widely recognized, its practical application in daily workflows has yet to be understood. This exercise introduces students to GenAI tools, demonstrating how they can be seamlessly integrated into professional work practices... View Details

Keywords: AI and Machine Learning; Technology Adoption; Marketing Strategy; Product Launch; Brands and Branding

April 2024
Article

Detecting Routines: Applications to Ridesharing CRM

By: Ryan Dew, Eva Ascarza, Oded Netzer and Nachum Sicherman

Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines—which we define as repeated behaviors with recurring, temporal... View Details

Keywords: Ride-sharing; Routine; Machine Learning; Customer Relationship Management; Consumer Behavior; Segmentation

Find at Harvard

2024
Working Paper

The Uneven Impact of Generative AI on Entrepreneurial Performance

By: Nicholas G. Otis, Rowan Clarke, Solène Delecourt, David Holtz and Rembrand Koning

Scalable and low-cost AI assistance has the potential to improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it difficult to know whether recent AI advances can help business owners make... View Details

Keywords: AI and Machine Learning; Performance Improvement; Small Business; Decision Choices and Conditions; Kenya

SSRN

2025
Working Paper

Narrative AI and the Human-AI Oversight Paradox in Evaluating Early-Stage Innovations

By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang

Do AI-generated narrative explanations enhance human oversight or diminish it? We investigate this question through a field experiment with 228 evaluators screening 48 early-stage innovations under three conditions: human-only, black-box AI recommendations without... View Details

Keywords: Large Language Models; AI and Machine Learning; Innovation and Invention; Decision Making

SSRN

May 9, 2023
Article

8 Questions About Using AI Responsibly, Answered

By: Tsedal Neeley

Generative AI tools are poised to change the way every business operates. As your own organization begins strategizing which to use, and how, operational and ethical considerations are inevitable. This article delves into eight of them, including how your organization... View Details

Keywords: AI and Machine Learning; Organizational Change and Adaptation; Prejudice and Bias; Ethics

Register to Read

December 1, 2021
Article

Do You Know How Your Teams Get Work Done?

By: Rohan Narayana Murty, Rajath B. Das, Scott Duke Kominers, Arjun Narayan, Suraj Srinivasan, Tarun Khanna and Kartik Hosanagar

In a research study at four Fortune 500 companies, when managers were asked about their teams’ work, on average they either did not know or could not remember 60% of the work their teams do. This is a major problem because it can lead to unrealistic digital... View Details

Keywords: Leading Teams; Work Recall Gap; Machine Learning; Algorithms; Groups and Teams; Management; Technological Innovation

Find at Harvard

Working Paper

Shifting Work Patterns with Generative AI

By: Eleanor W. Dillon, Sonia Jaffe, Nicole Immorlica and Christopher T. Stanton

We present evidence on how generative AI changes the work patterns of knowledge workers using data from a 6-month-long, cross-industry, randomized field experiment. Half of the 7,137 workers in the study received access to a generative AI tool integrated into the... View Details

Keywords: AI and Machine Learning; Behavior; Time Management