Publications
Publications
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- All HBS Web
(2,478)
- Faculty Publications (366)
- 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... View Details
- 2023
- Working Paper
Spatial Mobility, Economic Opportunity, and Crime
By: Gaurav Khanna, Carlos Medina, Anant Nyshadham, Daniel Ramos-Menchelli, Jorge Tamayo and Audrey Tiew
Neighborhoods are strong determinants of both economic opportunity and criminal activity. Does improving connectedness between segregated and unequal parts of a city predominantly import opportunity or export crime? We use a spatial general equilibrium framework to... View Details
- 2024
- Working Paper
The Crowdless Future? 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 economy... View Details
- 2023
- Working Paper
Channeled Attention and Stable Errors
By: Tristan Gagnon-Bartsch, Matthew Rabin and Joshua Schwartzstein
We develop a framework for assessing when somebody will eventually notice that she has
a misspecified model of the world, premised on the idea that she neglects information that
she deems—through the lens of her misconceptions—to be irrelevant. In doing so, we... View Details
- 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... View Details
- 2023
- Article
Towards Bridging the Gaps between the Right to Explanation and the Right to Be Forgotten
By: Himabindu Lakkaraju, Satyapriya Krishna and Jiaqi Ma
The Right to Explanation and the Right to be Forgotten are two important principles outlined to regulate algorithmic decision making and data usage in real-world applications. While the right to explanation allows individuals to request an actionable explanation for an... View Details
- July 2023
- Supplement
Honeycomb (B): Jumping on The Generative AI Bandwagon?
By: Jeffrey J. Bussgang and Kumba Sennaar
Honeycomb, an audio app enabling users to record stories and save family memories, considers pivoting to embrace generative AI. What should the co-founders business model look like if they pursued this new direction? View Details
- 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
- 2023
- Working Paper
The Complexity of Economic Decisions
By: Xavier Gabaix and Thomas Graeber
We propose a theory of the complexity of economic decisions. Leveraging a macroeconomic framework of production functions, we conceptualize the mind as a cognitive economy, where a task’s complexity is determined by its composition of cognitive operations. Complexity... View Details
- June 2023 (Revised November 2023)
- Case
Sober Sidekick
By: Jeffrey J. Bussgang and Kumba Sennaar
Case on the nascent business model of a mobile health IT startup. In particular, should they pivot away from their successful lead generation business model to charging health plans. View Details
- 2023
- Working Paper
Evaluation and Learning in R&D Investment
By: Alexander P. Frankel, Joshua L. Krieger, Danielle Li and Dimitris Papanikolaou
We examine the role of spillover learning in shaping the value of exploratory versus incremental
R&D. Using data from drug development, we show that novel drug candidates generate more
knowledge spillovers than incremental ones. Despite being less likely to reach... View Details
- 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... View Details
- 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
- April 2023 (Revised September 2023)
- Case
Apple's iPhone Revolution: Pioneering the Circular Economy
By: George Serafeim
When asked to identify an example of a circular economy business model that has generated billions in revenues for a company, ChatGPT, the famous chatbot that in 2022 rocked the world with its ability to perform a variety of tasks, immediately identified and... View Details
- 2024
- Working Paper
Using LLMs for Market Research
By: James Brand, Ayelet Israeli and Donald Ngwe
Large language models (LLMs) have rapidly gained popularity 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
practitioners... View Details
- April 2023 (Revised September 2023)
- Case
Levels: The Remote, Asynchronous, Deep Work Management System
By: Joseph B. Fuller and George Gonzalez
Levels is a highly innovative startup in the health care space. They intend to revolutionize health by linking behavior—eating, exercise, sleeping, etc.—to changes in metabolism. They believe metabolic health can be managed through careful monitoring of changes in... View Details
- 2023
- Article
Estimating Causal Peer Influence in Homophilous Social Networks by Inferring Latent Locations.
By: Edward McFowland III and Cosma Rohilla Shalizi
Social influence cannot be identified from purely observational data on social networks, because such influence is generically confounded with latent homophily, that is, with a node’s network partners being informative about the node’s attributes and therefore its... View Details
- March–April 2023
- Article
Pricing for Heterogeneous Products: Analytics for Ticket Reselling
By: Michael Alley, Max Biggs, Rim Hariss, Charles Herrmann, Michael Lingzhi Li and Georgia Perakis
Problem definition: We present a data-driven study of the secondary ticket market. In particular, we are primarily concerned with accurately estimating price sensitivity for listed tickets. In this setting, there are many issues including endogeneity, heterogeneity in... View Details
- March 2023 (Revised March 2025)
- Case
Close Concerns: Diabetes Research and Advocacy
By: Regina Herzlinger and Brian L. Walker
Diagnosed with diabetes at the age of 18, Kelly Close understood the importance of balancing consistency and iteration. This principle had also informed her professional work, which started with a rapid promotion from financial analyst at Goldman Sachs to an analyst... View Details
- 2023
- Chapter
Marketing Through the Machine’s Eyes: Image Analytics and Interpretability
By: Shunyuan Zhang, Flora Feng and Kannan Srinivasan
he growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility—if only the... View Details