Publications

09 Jan 2024
In Practice

Harnessing AI: What Businesses Need to Know in ChatGPT’s Second Year

includes addressing algorithmic biases, safeguarding privacy, ensuring security and copyright protection, as well as promoting transparency, fairness, and interpretability. Deploying mechanisms for responsible AI will be central to these... View Details

Keywords: by Rachel Layne; Information Technology

August 2020 (Revised March 2021)
Supplement

Migros Turkey: Scaling Online Operations (B)

By: Antonio Moreno and Gamze Yucaoglu

The case opens in February 2020 as Ozgur Tort and Mustafa Bartin, CEO and chief large-format and online retail officer of Migros Ticaret A.S. (Migros), Turkey’s oldest and one of its largest supermarket chains, are looking over the results of the fulfillment pilot the... View Details

Keywords: Grocery; Business Model; Strategy; Digital Platforms; Information Technology; Technology Adoption; Value Creation; Globalization; Competition; Expansion; Logistics; Profit; Resource Allocation; Corporate Strategy; Retail Industry; Turkey

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

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

Article

Counterfactual Explanations Can Be Manipulated

By: Dylan Slack, Sophie Hilgard, Himabindu Lakkaraju and Sameer Singh

Counterfactual explanations are useful for both generating recourse and auditing fairness between groups. We seek to understand whether adversaries can manipulate counterfactual explanations in an algorithmic recourse setting: if counterfactual explanations indicate... View Details

Keywords: Machine Learning Models; Counterfactual Explanations

Research Summary

Overview

By: Ayelet Israeli

Professor Israeli utilizes econometric methods and field experiments to study data driven decision making in marketing context. Her research focuses on data-driven marketing, with an emphasis on how businesses can leverage their own data, customer data, and market data... View Details

Keywords: Channel Management; Pricing; Pricing Policies; Online Marketing; E-commerce; Analytics; Econometrics; Field Experiments; Data Analytics; Artificial Intelligence; Value Of Data

26 Mar 2024
Research & Ideas

How Humans Outshine AI in Adapting to Change

the flexibility of AI versus humans in adjusting to new situations, the authors set up four video games, outlining certain tasks for humans and several popular game-playing AI algorithms to complete. The tasks tested the players’ ability... View Details

Keywords: by Rachel Layne; Technology; Information Technology

December 2019
Article

Communicating with Warmth in Distributive Negotiations Is Surprisingly Counterproductive

By: M. Jeong, J. Minson, M. Yeomans and F. Gino

When entering into a negotiation, individuals have the choice to enact a variety of communication styles. We test the differential impact of being “warm and friendly” versus “tough and firm” in a distributive negotiation, when first offers are held constant and... View Details

Keywords: Negotiation Style; Communication Strategy; Perception; Performance Effectiveness; Outcome or Result

Find at Harvard

October 2017 (Revised April 2018)
Case

Improving Worker Safety in the Era of Machine Learning (A)

By: Michael W. Toffel, Dan Levy, Jose Ramon Morales Arilla and Matthew S. Johnson

Managers make predictions all the time: How fast will my markets grow? How much inventory do I need? How intensively should I monitor my suppliers? Which potential customers will be most responsive to a particular marketing campaign? Which job candidates should I... View Details

Keywords: Machine Learning; Policy Implementation; Empirical Research; Inspection; Occupational Safety; Occupational Health; Regulation; Analysis; Forecasting and Prediction; Policy; Operations; Supply Chain Management; Safety; Manufacturing Industry; Construction Industry; United States

Educators

2020
Working Paper

Topic Preference Detection: A Novel Approach to Understand Perspective Taking in Conversation

By: Michael Yeomans and Alison Wood Brooks

Although most humans engage in conversations constantly throughout their lives, conversational mistakes are commonplace— interacting with others is difficult, and conversation re-quires quick, relentless perspective-taking and decision making. For example: during every... View Details

Keywords: Natural Language Processing; Interpersonal Communication; Perspective; Decision Making; Perception

2023
Working Paper

An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits

By: Biyonka Liang and Iavor I. Bojinov

Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the... View Details

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

June 2020
Article

Real-time Data from Mobile Platforms to Evaluate Sustainable Transportation Infrastructure

By: Omar Isaac Asensio, Kevin Alvarez, Arielle Dror, Emerson Wenzel, Catharina Hollauer and Sooji Ha

By displacing gasoline and diesel fuels, electric cars and fleets reduce emissions from the transportation sector, thus offering important public health benefits. However, public confidence in the reliability of charging infrastructure remains a fundamental barrier to... View Details

Keywords: Environmental Sustainability; Transportation; Infrastructure; Behavior; AI and Machine Learning; Demand and Consumers

Find at Harvard

2017
Working Paper

The Need for Speed: Effects of Uncertainty Reduction in Patenting

By: Mike Horia Teodorescu

Patents are essential in commerce to establish property rights for ideas and to give equal protection to firms that develop new technologies. Young firms especially depend on the protection of intellectual property to bring a product from concept to market. However,... View Details

Keywords: Startups; Natural Language Processing; Machine Learning; Patents; Business Startups; Risk and Uncertainty; Outcome or Result; Green Technology Industry

July 2011
Article

Kidney Paired Donation

By: C. Bradley Wallis, Kannan P. Samy, Alvin E. Roth and Michael A. Rees

Kidney paired donation (KPD) was first suggested in 1986, but it was not until 2000 when the first paired donation transplant was performed in the U.S. In the past decade, KPD has become the fastest growing source of transplantable kidneys, overcoming the barrier faced... View Details

Keywords: Philanthropy and Charitable Giving; Health Care and Treatment; Growth and Development Strategy; Success; Problems and Challenges; Programs; System; United States

Find at Harvard

29 Jun 2011
Working Paper Summaries

Better-reply Dynamics in Deferred Acceptance Games

Keywords: by Guillaume Haeringer & Hanna Halaburda

2024
Article

Learning Under Random Distributional Shifts

By: Kirk Bansak, Elisabeth Paulson and Dominik Rothenhäusler

Algorithmic assignment of refugees and asylum seekers to locations within host countries has gained attention in recent years, with implementations in the U.S. and Switzerland. These approaches use data on past arrivals to generate machine learning models that can... View Details

Keywords: AI and Machine Learning; Refugees; Employment

January 2024 (Revised February 2024)
Course Overview Note

Managing Customers for Growth: Course Overview for Students

By: Eva Ascarza

Managing Customers for Growth (MCG) is a 14-session elective course for second-year MBA students at Harvard Business School. It is designed for business professionals engaged in roles centered on customer-driven growth activities. The course explores the dynamics of... View Details

Keywords: Customer Relationship Management; Decision Making; Analytics and Data Science; Growth Management; Telecommunications Industry; Technology Industry; Financial Services Industry; Education Industry; Travel Industry