Publications

July 2023 (Revised July 2023)
Background Note

Generative AI Value Chain

By: Andy Wu and Matt Higgins

Generative AI refers to a type of artificial intelligence (AI) that can create new content (e.g., text, image, or audio) in response to a prompt from a user. ChatGPT, Bard, and Claude are examples of text generating AIs, and DALL-E, Midjourney, and Stable Diffusion are... View Details

Keywords: AI; Artificial Intelligence; Model; Hardware; Data Centers; AI and Machine Learning; Applications and Software; Analytics and Data Science; Value

Educators

Research Summary

Overview

By: Shunyuan Zhang

Professor Zhang uses machine learning to address marketing problems that have arisen within the nascent sharing economy. She conducts rigorous analyses of structured and unstructured data generated by new sharing economy platforms to address important issues emerging... View Details

September 15, 2021
Article

Improving Deconvolution Methods in Biology Through Open Innovation Competitions: An Application to the Connectivity Map

By: Andrea Blasco, Ted Natoli, Michael G. Endres, Rinat A. Sergeev, Steven Randazzo, Jin Hyun Paik, N.J. Maximilian Macaluso, Rajiv Narayan, Xiaodong Lu, David Peck, Karim R. Lakhani and Aravind Subramanian

A recurring problem in biomedical research is how to isolate signals of distinct populations (cell types, tissues, and genes) from composite measures obtained by a single analyte or sensor. Existing computational deconvolution approaches work well in many specific... View Details

Keywords: Deconvolution; Methods; Open Innovation Competition; Genomics; Research; Innovation and Invention

Research Summary

Overview

Ms. Fedyk's main research interests lie at the intersection of asset pricing and behavioral finance, with a particular focus on information and belief formation. Her job market paper is part of a broader research agenda on the way in which information is incorporated... View Details

2018
Working Paper

Some Facts of High-Tech Patenting

By: Michael Webb, Nick Short, Nicholas Bloom and Josh Lerner

Patenting in software, cloud computing, and artificial intelligence has grown rapidly in recent years. Such patents are acquired primarily by large U.S. technology firms such as IBM, Microsoft, Google, and HP, as well as by Japanese multinationals such as Sony, Canon,... View Details

Keywords: Patents; Applications and Software; Technological Innovation; United States

SSRN

May 2024
Article

Financial Innovation in the 21st Century: Evidence from U.S. Patents

By: Josh Lerner, Amit Seru, Nick Short and Yuan Sun

We develop a unique dataset of 24 thousand U.S. finance patents granted over the last two decades to explore the evolution and production of financial innovation. We use machine learning to identify the financial patents and extensively audit the results to ensure... View Details

Keywords: Banking; Investment Banks; Information Technology; Regulation; Patents; Innovation and Invention; Trends

April 2021
Article

Work-From-Anywhere: The Productivity Effects of Geographical Flexibility

By: Prithwiraj Choudhury, Cirrus Foroughi and Barbara Larson

An emerging form of remote work allows employees to work-from-anywhere, so that the worker can choose to live in a preferred geographic location. While traditional work-from-home (WFH) programs offer the worker temporal flexibility, work-from-anywhere (WFA) programs... View Details

Keywords: Geographic Flexibility; Work-from-anywhere; Remote Work; Telecommuting; Geographic Mobility; USPTO; Employees; Geographic Location; Performance Productivity

Predictive model development is understudied despite its importance to modern businesses. Although prior discussions highlight advances in methods (along the dimensions of data, computing power, and algorithms) as the primary driver of model quality, the value of... View Details

May 2021 (Revised February 2024)
Teaching Note

THE YES: Reimagining the Future of E-Commerce with Artificial Intelligence (AI)

By: Ayelet Israeli and Jill Avery

THE YES, a multi-brand shopping app launched in May 2020 offered a new type of buying experience for women’s fashion, driven by a sophisticated algorithm that used data science and machine learning to create and deliver a personalized store for every shopper, based on... View Details

Keywords: Data; Data Analytics; Artificial Intelligence; AI; AI Algorithms; AI Creativity; Fashion; Retail; Retail Analytics; E-Commerce Strategy; Platform; Platforms; Big Data; Preference Elicitation; Predictive Analytics; App Development; ＂Marketing Analytics＂; Advertising; Mobile App; Mobile Marketing; Apparel; Online Advertising; Referral Rewards; Referrals; Female Ceo; Female Entrepreneur; Female Protagonist; Analytics and Data Science; Analysis; Creativity; Marketing Strategy; Brands and Branding; Consumer Behavior; Demand and Consumers; Forecasting and Prediction; Marketing Channels; Digital Marketing; Internet and the Web; Mobile and Wireless Technology; AI and Machine Learning; E-commerce; Digital Platforms; Fashion Industry; Retail Industry; Apparel and Accessories Industry; Consumer Products Industry; United States

March 1, 2022
Article

Widespread Use of National Academies Consensus Reports by the American Public

By: Diana Hicks, Matteo Zullo, Ameet Doshi and Omar Isaac Asensio

In seeking to understand how to protect the public information sphere from corruption, researchers understandably focus on dysfunction. However, parts of the public information ecosystem function very well, and understanding this as well will help in protecting and... View Details

Keywords: Reports; Surveys; AI and Machine Learning; Knowledge Dissemination; Knowledge Use and Leverage

January 2021
Case

Anodot: Autonomous Business Monitoring

By: Antonio Moreno and Danielle Golan

Autonomous business monitoring platform Anodot leveraged machine learning to provide real-time alerts regarding business anomalies. Anodot’s solution was used in various industries in order to primarily monitor business health, such as revenue and payments, product... View Details

Keywords: Digital Platforms; Internet and the Web; Knowledge Sharing; Information Management; Sales; Value Creation; Product Positioning; Israel

Educators

Linda A. Hill is the Wallace Brett Donham Professor of Business Administration at the Harvard Business School and Faculty Chair of the Leadership Initiative. Hill is regarded as one of the top experts on leadership and innovation. Hill is... View Details

27 Oct 2016
HBS Seminar

Andrea Pratt, Richard Paul Richman Professor of Business and Professor of Economics, Columbia University

July 2024
Technical Note

What Is AI?

By: Michael Parzen and Jo Ellery

This note discusses definitions of artificial intelligence and covers the broad types of learning used in training AI, as well as explaining in detail how neural networks are built, trained, and used. View Details

Keywords: AI and Machine Learning

Educators

2023
Article

Verifiable Feature Attributions: A Bridge between Post Hoc Explainability and Inherent Interpretability

By: Usha Bhalla, Suraj Srinivas and Himabindu Lakkaraju

With the increased deployment of machine learning models in various real-world applications, researchers and practitioners alike have emphasized the need for explanations of model behaviour. To this end, two broad strategies have been outlined in prior literature to... View Details

Keywords: AI and Machine Learning; Mathematical Methods

2021
Article

ThreeDWorld: A Platform for Interactive Multi-Modal Physical Simulation

By: Chuang Gan, Jeremy Schwartz, Seth Alter, Damian Mrowca, Martin Schrimpf, James Traer, Julian De Freitas, Jonas Kubilius, Abhishek Bhandwaldar, Nick Haber, Megumi Sano, Kuno Kim, Elias Wang, Michael Lingelbach, Aidan Curtis, Kevin Feigelis, Daniel M. Bear, Dan Gutfreund, David Cox, Antonio Torralba, James J. DiCarlo, Joshua B. Tenenbaum, Josh H. McDermott and Daniel L.K. Yamins

We introduce ThreeDWorld (TDW), a platform for interactive multi-modal physical simulation. TDW enables simulation of high-fidelity sensory data and physical interactions between mobile agents and objects in rich 3D environments. Unique properties include: real-time... View Details

Keywords: Artificial Intelligence; Platform; Interactive Physical Simulation; Virtual Environment; Multi-modal; AI and Machine Learning

2023
Article

Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse

By: Martin Pawelczyk, Teresa Datta, Johannes van-den-Heuvel, Gjergji Kasneci and Himabindu Lakkaraju

As machine learning models are increasingly being employed to make consequential decisions in real-world settings, it becomes critical to ensure that individuals who are adversely impacted (e.g., loan denied) by the predictions of these models are provided with a means... View Details

Keywords: AI and Machine Learning; Decision Choices and Conditions; Mathematical Methods

15 Oct 2001
Op-Ed

Lessons from the Rubble

Pundits and investors spoke giddily of the end of national borders, of markets that spanned the globe and replaced the hefty weight of machines and plants with ephemeral bits of information. This may be true. We do have global markets and... View Details

Keywords: by Debora L. Spar

2023
Article

Experimental Evaluation of Individualized Treatment Rules

By: Kosuke Imai and Michael Lingzhi Li

The increasing availability of individual-level data has led to numerous applications of individualized (or personalized) treatment rules (ITRs). Policy makers often wish to empirically evaluate ITRs and compare their relative performance before implementing them in a... View Details

Keywords: Causal Inference; Heterogeneous Treatment Effects; Precision Medicine; Uplift Modeling; Analytics and Data Science; AI and Machine Learning