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All HBS Web
(2,064)
- Faculty Publications (284)
- October 2023
- Teaching Note
Timnit Gebru: 'SILENCED No More' on AI Bias and The Harms of Large Language Models
By: Tsedal Neeley and Tim Englehart
Teaching Note for HBS Case No. 422-085. Dr. Timnit Gebru—a leading artificial intelligence (AI) computer scientist and co-lead of Google’s Ethical AI team—was messaging with one of her colleagues when she saw the words: “Did you resign?? Megan sent an email saying that...
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- October 2023
- Case
Fixie and Conversational AI Sidekicks
By: Jeffrey J. Bussgang and Carin-Isabel Knoop
In March 2023, Fixie Co-Founder and Chief Architect Matt Welsh and co-founders had the kind of meeting no founders want to have. The president of leading artificial intelligence (AI) research and deployment firm OpenAI, which had catapulted into fame with its ChatGPT...
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- October 2023
- Case
Driving Sustainability at AB InBev
By: Ethan Rouen and Antonio Manuel Oftelie
It was the height of the summer in 2022, and Michel Doukeris, the CEO of Anheuser-Busch InBev (AB InBev), and Peter Kraemer, the company’s Chief Supply Officer, gazed across the vast desert surrounding Zacatecas, Mexico. They were visiting their Grupo Modelo Brewery,...
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Rouen, Ethan, and Antonio Manuel Oftelie. "Driving Sustainability at AB InBev." Harvard Business School Case 124-037, October 2023.
- 2023
- Working Paper
Causal Interpretation of Structural IV Estimands
By: Isaiah Andrews, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan and Jesse M. Shapiro
We study the causal interpretation of instrumental variables (IV) estimands of nonlinear, multivariate structural models with respect to rich forms of model misspecification. We focus on guaranteeing that the researcher's estimator is sharp zero consistent, meaning...
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Keywords:
Mathematical Methods
Andrews, Isaiah, Nano Barahona, Matthew Gentzkow, Ashesh Rambachan, and Jesse M. Shapiro. "Causal Interpretation of Structural IV Estimands." NBER Working Paper Series, No. 31799, October 2023.
- 2023
- Working Paper
In-Context Unlearning: Language Models as Few Shot Unlearners
By: Martin Pawelczyk, Seth Neel and Himabindu Lakkaraju
Machine unlearning, the study of efficiently removing the impact of specific training points on the
trained model, has garnered increased attention of late, driven by the need to comply with privacy
regulations like the Right to be Forgotten. Although unlearning is...
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Pawelczyk, Martin, Seth Neel, and Himabindu Lakkaraju. "In-Context Unlearning: Language Models as Few Shot Unlearners." Working Paper, October 2023.
- 2023
- Working Paper
Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality
By: Fabrizio Dell'Acqua, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon and Karim R. Lakhani
The public release of Large Language Models (LLMs) has sparked tremendous interest in how humans will use Artificial Intelligence (AI) to accomplish a variety of tasks. In our study conducted with Boston Consulting Group, a global management consulting firm, we examine...
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Keywords:
Large Language Model;
AI and Machine Learning;
Performance Efficiency;
Performance Improvement
Dell'Acqua, Fabrizio, Edward McFowland III, Ethan Mollick, Hila Lifshitz-Assaf, Katherine C. Kellogg, Saran Rajendran, Lisa Krayer, François Candelon, and Karim R. Lakhani. "Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of AI on Knowledge Worker Productivity and Quality." Harvard Business School Working Paper, No. 24-013, September 2023.
- September 2023 (Revised January 2024)
- Case
AI21 Labs in 2023: Strategy for Generative AI
By: David Yoffie, Orna Dan and Elena Corsi
Israeli generative artificial intelligence company AI21 Labs was founded in 2017 to realize the vision of true machine intelligence. It sought to reinvent writing and reading and in 2020 it launched Wordtune, an app using GenAI software to offer alternate text...
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Keywords:
Decision Making;
AI and Machine Learning;
Innovation Strategy;
Growth and Development Strategy;
Applications and Software;
Competitive Strategy;
Technology Industry;
Israel
Yoffie, David, Orna Dan, and Elena Corsi. "AI21 Labs in 2023: Strategy for Generative AI." Harvard Business School Case 724-383, September 2023. (Revised January 2024.)
- 2023
- Article
On the Impact of Actionable Explanations on Social Segregation
By: Ruijiang Gao and Himabindu Lakkaraju
As predictive models seep into several real-world applications, it has become critical to ensure that individuals who are negatively impacted by the outcomes of these models are provided with a means for recourse. To this end, there has been a growing body of research...
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Gao, Ruijiang, and Himabindu Lakkaraju. "On the Impact of Actionable Explanations on Social Segregation." Proceedings of the International Conference on Machine Learning (ICML) 40th (2023): 10727–10743.
- 2024
- Working Paper
Generative AI and Creative Problem Solving
The rapid advances in generative artificial intelligence (AI) open up attractive opportunities for creative
problem-solving through human-guided AI partnerships. To explore this potential, we initiated a
crowdsourcing challenge focused on sustainable, circular...
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Boussioux, Léonard, Jacqueline N. Lane, Miaomiao Zhang, Vladimir Jacimovic, and Karim R. Lakhani. "Generative AI and Creative Problem Solving." Harvard Business School Working Paper, No. 24-005, July 2023. (Revised March 2024.)
- August 2023
- Article
Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel
By: Dylan Slack, Satyapriya Krishna, Himabindu Lakkaraju and Sameer Singh
Practitioners increasingly use machine learning (ML) models, yet models have become more complex and harder to understand. To understand complex models, researchers have proposed techniques to explain model predictions. However, practitioners struggle to use...
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Slack, Dylan, Satyapriya Krishna, Himabindu Lakkaraju, and Sameer Singh. "Explaining Machine Learning Models with Interactive Natural Language Conversations Using TalkToModel." Nature Machine Intelligence 5, no. 8 (August 2023): 873–883.
- August 2023
- Article
Financing the Litigation Arms Race
By: Samuel Antill and Steven R. Grenadier
Using a dynamic real-option model of litigation, we show that the increasingly popular practice of third-party litigation financing has ambiguous implications for total ex-post litigant surplus. A defendant and a plaintiff bargain over a settlement payment. The...
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Keywords:
Litigation Financing;
Dynamic Bargaining;
Real Options;
Lawsuits and Litigation;
Financing and Loans
Antill, Samuel, and Steven R. Grenadier. "Financing the Litigation Arms Race." Journal of Financial Economics 149, no. 2 (August 2023): 218–234.
- 2024
- Working Paper
Residential Battery Storage - Reshaping the Way We Do Electricity
By: Christian Kaps and Serguei Netessine
In this paper, we aim to understand when private households invest in behind-the-meter battery storage next to rooftop solar and how those batteries impact households, the electricity market, and emissions. We answer three main research questions: 1) When do customers...
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Keywords:
Solar Power;
Energy Storage;
Technology And Innovation Management;
Energy;
Energy Policy;
Renewable Energy;
Technological Innovation;
Innovation and Management;
Energy Industry
Kaps, Christian, and Serguei Netessine. "Residential Battery Storage - Reshaping the Way We Do Electricity." Working Paper, February 2024.
- August 29, 2023
- Article
The Fragility of Artists’ Reputations from 1795 to 2020
By: Letian Zhang, Mitali Banerjee, Shinan Wang and Zhuoqiao Hong
This study explores the longevity of artistic reputation. We empirically examine whether artists are more- or less-venerated after their death. We construct a massive historical corpus spanning 1795 to 2020 and build separate word-embedding models for each five-year...
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Zhang, Letian, Mitali Banerjee, Shinan Wang, and Zhuoqiao Hong. "The Fragility of Artists’ Reputations from 1795 to 2020." Proceedings of the National Academy of Sciences 120, no. 35 (August 29, 2023).
- July 2023
- Case
Vytal: Packaging-as-a-Service
By: George Serafeim, Michael W. Toffel, Lena Duchene and Daniela Beyersdorfer
The Germany-based startup Vytal operated the largest digital-native reusable packaging-as-a-service network globally, having raised nearly €15 million, established a large network of restaurant partners, and prevented the use of millions of single-use take-out food...
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Keywords:
Climate Risk;
Digital;
Platform Strategies;
Data;
Packaging;
Sustainability;
Start-up;
Startup;
Entrepreneur;
Impact;
Circular;
Growth Strategy;
Innovation;
Environmental Sustainability;
Innovation and Invention;
Business Growth and Maturation;
Growth and Development Strategy;
Business Startups;
Resource Allocation;
Risk Management;
Adoption;
Strategy;
Performance Productivity;
Service Delivery;
Service Operations;
Supply Chain;
Distribution;
Entrepreneurship;
Climate Change;
Green Technology Industry;
Service Industry;
Retail Industry;
Germany;
Europe
Serafeim, George, Michael W. Toffel, Lena Duchene, and Daniela Beyersdorfer. "Vytal: Packaging-as-a-Service." Harvard Business School Case 124-007, July 2023.
- 2023
- Working Paper
The Market for Sharing Interest Rate Risk: Quantities and Asset Prices
By: Umang Khetan, Jane Li, Ioana Neamtu and Ishita Sen
We study the extent of interest rate risk sharing across the financial system using granular positions and transactions data in interest rate swaps. We show that pension and insurance (PF&I) sector emerges as a natural counterparty to banks and corporations: overall,...
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Keywords:
Interest Rates;
Investment Funds;
Banks and Banking;
Insurance;
Investment Banking;
Risk and Uncertainty
Khetan, Umang, Jane Li, Ioana Neamtu, and Ishita Sen. "The Market for Sharing Interest Rate Risk: Quantities and Asset Prices." Harvard Business School Working Paper, No. 24-052, February 2024.
- 2023
- Working Paper
Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation
By: Dae Woong Ham, Michael Lindon, Martin Tingley and Iavor Bojinov
Randomized experiments have become the standard method for companies to evaluate the performance of new products or services. In addition to augmenting managers’ decision-making, experimentation mitigates risk by limiting the proportion of customers exposed to...
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Keywords:
Performance Evaluation;
Research and Development;
Analytics and Data Science;
Consumer Behavior
Ham, Dae Woong, Michael Lindon, Martin Tingley, and Iavor Bojinov. "Design-Based Confidence Sequences: A General Approach to Risk Mitigation in Online Experimentation." Harvard Business School Working Paper, No. 23-070, May 2023.
- April 12, 2023
- Article
Using AI to Adjust Your Marketing and Sales in a Volatile World
By: Das Narayandas and Arijit Sengupta
Why are some firms better and faster than others at adapting their use of customer data to respond to changing or uncertain marketing conditions? A common thread across faster-acting firms is the use of AI models to predict outcomes at various stages of the customer...
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Keywords:
Forecasting and Prediction;
AI and Machine Learning;
Consumer Behavior;
Technology Adoption;
Competitive Advantage
Narayandas, Das, and Arijit Sengupta. "Using AI to Adjust Your Marketing and Sales in a Volatile World." Harvard Business Review Digital Articles (April 12, 2023).
- 2023
- Working Paper
Using GPT for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have quickly become popular as labor-augmenting tools
for programming, writing, and many other processes that benefit from quick text generation.
In this paper we explore the uses and benefits of LLMs for researchers and...
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Keywords:
Large Language Model;
Research;
AI and Machine Learning;
Analysis;
Customers;
Consumer Behavior;
Technology Industry;
Information Technology Industry
Brand, James, Ayelet Israeli, and Donald Ngwe. "Using GPT for Market Research." Harvard Business School Working Paper, No. 23-062, April 2023. (Revised July 2023.)
- 2023
- Working Paper
Feature Importance Disparities for Data Bias Investigations
By: Peter W. Chang, Leor Fishman and Seth Neel
It is widely held that one cause of downstream bias in classifiers is bias present in the training data. Rectifying such biases may involve context-dependent interventions such as training separate models on subgroups, removing features with bias in the collection...
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Chang, Peter W., Leor Fishman, and Seth Neel. "Feature Importance Disparities for Data Bias Investigations." Working Paper, March 2023.
- April 2023
- Article
The Real Exchange Rate, Innovation and Productivity
By: Laura Alfaro, Alejandro Cuñat, Harald Fadinger and Yanping Liu
We evaluate manufacturing firms' responses to changes in the real exchange rate (RER) using detailed firm-level data for a large set of countries for the period 2001-2010. We uncover the following stylized facts about regional variation of manufacturing firms'...
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Keywords:
Real Exchange Rate;
Firm Level Data;
Innovation;
Productivity;
Exporting;
Importing;
Credit Constraints;
Currency Exchange Rate;
Innovation and Invention;
Performance Productivity
Alfaro, Laura, Alejandro Cuñat, Harald Fadinger, and Yanping Liu. "The Real Exchange Rate, Innovation and Productivity." Journal of the European Economic Association 21, no. 2 (April 2023): 637–689.