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- Article
Learning Models for Actionable Recourse
By: Alexis Ross, Himabindu Lakkaraju and Osbert Bastani
As machine learning models are increasingly deployed in high-stakes domains such as legal and financial decision-making, there has been growing interest in post-hoc methods for generating counterfactual explanations. Such explanations provide individuals adversely... View Details
Ross, Alexis, Himabindu Lakkaraju, and Osbert Bastani. "Learning Models for Actionable Recourse." Advances in Neural Information Processing Systems (NeurIPS) 34 (2021).
- 2021
- Article
Nudging the Commute: Using Behaviorally-Informed Interventions to Promote Sustainable Transportation
By: Ashley Whillans, Joseph Sherlock, Jessica Roberts, Shibeal O'Flaherty, Lyndsay Gavin, Holly Dykstra and Michael Daly
Dramatic reductions in carbon emissions must take place immediately. A human-centric method of reducing environmental impacts is to “nudge” employees away from single-occupancy vehicles (SOVs) toward more sustainable commuting options. While an abundance of research... View Details
Keywords: Behavioral Science; Transportation Demand Management; Commuting; Single-occupancy Vehicle Commutes; Transportation; Behavior; Change; Environmental Sustainability
Whillans, Ashley, Joseph Sherlock, Jessica Roberts, Shibeal O'Flaherty, Lyndsay Gavin, Holly Dykstra, and Michael Daly. "Nudging the Commute: Using Behaviorally-Informed Interventions to Promote Sustainable Transportation." Behavioral Science & Policy 7, no. 2 (2021): 27–49.
- Article
Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
By: Sushant Agarwal, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu and Himabindu Lakkaraju
As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a post hoc manner. In this work, we analyze two... View Details
Keywords: Machine Learning; Black Box Explanations; Decision Making; Forecasting and Prediction; Information Technology
Agarwal, Sushant, Shahin Jabbari, Chirag Agarwal, Sohini Upadhyay, Steven Wu, and Himabindu Lakkaraju. "Towards the Unification and Robustness of Perturbation and Gradient Based Explanations." Proceedings of the International Conference on Machine Learning (ICML) 38th (2021).
- 2021
- Working Paper
Population Interference in Panel Experiments
By: Iavor I Bojinov, Kevin Wu Han and Guillaume Basse
The phenomenon of population interference, where a treatment assigned to one experimental unit affects another experimental unit's outcome, has received considerable attention in standard randomized experiments. The complications produced by population interference in... View Details
Bojinov, Iavor I., Kevin Wu Han, and Guillaume Basse. "Population Interference in Panel Experiments." Harvard Business School Working Paper, No. 21-100, March 2021.
- Mar 2021
- Conference Presentation
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning
By: Seth Neel, Aaron Leon Roth and Saeed Sharifi-Malvajerdi
We study the data deletion problem for convex models. By leveraging techniques from convex optimization and reservoir sampling, we give the first data deletion algorithms that are able to handle an arbitrarily long sequence of adversarial updates while promising both... View Details
Neel, Seth, Aaron Leon Roth, and Saeed Sharifi-Malvajerdi. "Descent-to-Delete: Gradient-Based Methods for Machine Unlearning." Paper presented at the 32nd Algorithmic Learning Theory Conference, March 2021.
- 2021
- Working Paper
How Much Should We Trust Staggered Difference-In-Differences Estimates?
By: Andrew C. Baker, David F. Larcker and Charles C.Y. Wang
Difference-in-differences analysis with staggered treatment timing is frequently used to assess the impact of policy changes on corporate outcomes in academic research. However, recent advances in econometric theory show that such designs are likely to be biased in the... View Details
Keywords: Difference In Differences; Staggered Difference-in-differences Designs; Generalized Difference-in-differences; Dynamic Treatment Effects; Mathematical Methods
Baker, Andrew C., David F. Larcker, and Charles C.Y. Wang. "How Much Should We Trust Staggered Difference-In-Differences Estimates?" European Corporate Governance Institute Finance Working Paper, No. 736/2021, February 2021. (Harvard Business School Working Paper, No. 21-112, April 2021.)
- Article
Manage the Suppliers That Could Harm Your Brand: Know When to Avoid, Engage, or Drop Them
By: Jodi L Short and Michael W. Toffel
The pandemic has placed a new spotlight on working conditions in factories that supply global companies. To avert problems, firms often impose codes of conduct on their suppliers and perform audits to assess compliance. Do these measures help identify unethical... View Details
Keywords: Auditing; Agency Cost; Quality And Safety; Quality Management System; Quality Management; Unions; Environmental Management; Globalization; Goods and Commodities; Governance; Labor; Labor Unions; Wages; Working Conditions; Operations; Supply Chain; Safety; Quality; China; Bangladesh; Asia; Pakistan
Short, Jodi L., and Michael W. Toffel. "Manage the Suppliers That Could Harm Your Brand: Know When to Avoid, Engage, or Drop Them." Harvard Business Review 99, no. 2 (March–April 2021).
- February 2021 (Revised April 2021)
- Case
Board Director Dilemmas—Back the SPAC?
By: Suraj Srinivasan, David G. Fubini and Amram Migdal
This case focuses on a board director of a diversified holding company. The firm’s longtime CEO had always exhibited a cautious, methodical approach to growth. Now, the CEO is raising the idea of joining with a special purpose acquisition company (SPAC) to spin off... View Details
Srinivasan, Suraj, David G. Fubini, and Amram Migdal. "Board Director Dilemmas—Back the SPAC?" Harvard Business School Case 121-042, February 2021. (Revised April 2021.)
- February 2021
- Tutorial
What is AI?
By: Tsedal Neeley
This video explores the elements that constitute artificial intelligence (AI). From its mathematical basis to current advances in AI, this video introduces students to data, tools, and statistical models that make a computer 'intelligent.' Through an explanation of... View Details
- February 2021
- Article
A Dynamic Theory of Multiple Borrowing
By: Daniel Green and Ernest Liu
Multiple borrowing—a borrower obtains overlapping loans from multiple lenders—is a common phenomenon in many credit markets. We build a highly tractable, dynamic model of multiple borrowing and show that, because overlapping creditors may impose default externalities... View Details
Keywords: Commitment; Multiple Borrowing; Common Agency; Misallocation; Microfinance; Investment; Mathematical Methods
Green, Daniel, and Ernest Liu. "A Dynamic Theory of Multiple Borrowing." Journal of Financial Economics 139, no. 2 (February 2021): 389–404.
- 2021
- Article
Prisoners, Rooms, and Lightswitches
By: Daniel M. Kane and Scott Duke Kominers
We examine a new variant of the classic prisoners and lightswitches puzzle: A warden leads his n prisoners in and out of r rooms, one at a time, in some order, with each prisoner eventually visiting every room an arbitrarily large number of times. The... View Details
Keywords: Mathematical Methods
Kane, Daniel M., and Scott Duke Kominers. "Prisoners, Rooms, and Lightswitches." Electronic Journal of Combinatorics 28, no. 1 (2021).
- 2021
- Article
Fair Algorithms for Infinite and Contextual Bandits
By: Matthew Joseph, Michael J Kearns, Jamie Morgenstern, Seth Neel and Aaron Leon Roth
We study fairness in linear bandit problems. Starting from the notion of meritocratic fairness introduced in Joseph et al. [2016], we carry out a more refined analysis of a more general problem, achieving better performance guarantees with fewer modelling assumptions... View Details
Joseph, Matthew, Michael J Kearns, Jamie Morgenstern, Seth Neel, and Aaron Leon Roth. "Fair Algorithms for Infinite and Contextual Bandits." Proceedings of the AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society 4th (2021).
- 2021
- Book
Harvard Business Review Family Business Handbook: How to Build and Sustain a Successful, Enduring Enterprise
By: Josh Baron and Rob Lachenauer
Navigate the complex decisions and critical relationships necessary to create and sustain a healthy family business--and business family. Though "family business" may sound like it refers only to mom-and-pop shops, businesses owned by families are among the most... View Details
Keywords: Family Business; Entrepreneurship; Family and Family Relationships; Outcome or Result; Business Model; Conflict and Resolution; Organizational Culture
Baron, Josh, and Rob Lachenauer. Harvard Business Review Family Business Handbook: How to Build and Sustain a Successful, Enduring Enterprise. Harvard Business Review Press, 2021.
- Article
Resilience vs. Vulnerability: Psychological Safety and Reporting of Near Misses with Varying Proximity to Harm in Radiation Oncology
By: Palak Kundu, Olivia Jung, Amy C. Edmondson, Nzhde Agazaryan, John Hegde, Michael Steinberg and Ann Raldow
Background
Psychological safety, a shared belief that interpersonal risk taking is safe, is an important determinant of incident reporting. However, how psychological safety affects near-miss reporting is unclear, as near misses contain contrasting cues that... View Details
Psychological safety, a shared belief that interpersonal risk taking is safe, is an important determinant of incident reporting. However, how psychological safety affects near-miss reporting is unclear, as near misses contain contrasting cues that... View Details
Kundu, Palak, Olivia Jung, Amy C. Edmondson, Nzhde Agazaryan, John Hegde, Michael Steinberg, and Ann Raldow. "Resilience vs. Vulnerability: Psychological Safety and Reporting of Near Misses with Varying Proximity to Harm in Radiation Oncology." Joint Commission Journal on Quality and Patient Safety 47, no. 1 (January 2021): 15–22.
- January 2021
- Article
Using Models to Persuade
By: Joshua Schwartzstein and Adi Sunderam
We present a framework where "model persuaders" influence receivers’ beliefs by proposing models that organize past data to make predictions. Receivers are assumed to find models more compelling when they better explain the data, fixing receivers’ prior beliefs. Model... View Details
Keywords: Model Persuasion; Analytics and Data Science; Forecasting and Prediction; Mathematical Methods; Framework
Schwartzstein, Joshua, and Adi Sunderam. "Using Models to Persuade." American Economic Review 111, no. 1 (January 2021): 276–323.
- Article
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses
By: Kaivalya Rawal and Himabindu Lakkaraju
As predictive models are increasingly being deployed in high-stakes decision-making, there has been a lot of interest in developing algorithms which can provide recourses to affected individuals. While developing such tools is important, it is even more critical to... View Details
Rawal, Kaivalya, and Himabindu Lakkaraju. "Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses." Advances in Neural Information Processing Systems (NeurIPS) 33 (2020).
- Article
The Unprecedented Stock Market Reaction to COVID-19
By: Scott Baker, Nicholas Bloom, Steven J. Davis, Kyle Kost, Marco Sammon and Tasaneeya Viratyosin
No previous infectious disease outbreak, including the Spanish Flu, has impacted the stock market as forcefully as the COVID-19 pandemic. In fact, previous pandemics left only mild traces on the U.S. stock market. We use text-based methods to develop these points with... View Details
Baker, Scott, Nicholas Bloom, Steven J. Davis, Kyle Kost, Marco Sammon, and Tasaneeya Viratyosin. "The Unprecedented Stock Market Reaction to COVID-19." Review of Asset Pricing Studies 10, no. 4 (December 2020): 742–758.
- 2021
- Working Paper
The Value of Descriptive Analytics: Evidence from Online Retailers
By: Ron Berman and Ayelet Israeli
Does the adoption of descriptive analytics impact online retailer performance, and if so, how? We use the synthetic difference-in-differences method to analyze the staggered adoption of a retail analytics dashboard by more than 1,500 e-commerce websites, and we find an... View Details
Keywords: Descriptive Analytics; Big Data; Synthetic Control; E-commerce; Online Retail; Difference-in-differences; Martech; Internet and the Web; Analytics and Data Science; Performance; Retail Industry
Berman, Ron, and Ayelet Israeli. "The Value of Descriptive Analytics: Evidence from Online Retailers." Harvard Business School Working Paper, No. 21-067, November 2020. (Revised December 2021. Accepted at Marketing Science.)
- 2020
- Other Teaching and Training Material
Encouraging Student Participation Online—and Assessing It Fairly: Techniques and Methods to Involve More Voices in Virtual Classes
By: Ayelet Israeli
This article is about encouraging student participation online—and assessing it fairly. It includes techniques and methods to involve more voices in virtual classes, and evaluate them equitably and fairly. View Details
Israeli, Ayelet. "Encouraging Student Participation Online—and Assessing It Fairly: Techniques and Methods to Involve More Voices in Virtual Classes." Harvard Business Publishing, 2020. Electronic.
- November 2020 (Revised March 2022)
- Teaching Note
Social Salary Setting at Spiber
By: Ashley Whillans and John Beshears
Teaching Note for HBS Case No. 920-050. The case tells the story of Spiber, a Japanese technology start-up company. To reflect the company’s values, the leadership team implemented a new and unique salary-setting process: each employee had the authority to choose their... View Details