Publications

Educators

March 2016 (Revised January 2020)
Teaching Note

Behavioural Insights Team (A) and (B)

By: Michael Luca and Patrick Rooney

The Behavioural Insights Team case introduces students to the concept of choice architecture and the value of experimental methods (sometimes called A/B testing) within organizational contexts. The exercise provides an opportunity for students to apply these principles... View Details

Keywords: Behavioral Economics; Experiments; Choice Architecture; Public Entrepreneurship; Decision Choices and Conditions; Mathematical Methods; United Kingdom

Research Summary

Consumer Behavior and Health

Professor Riis studies consumer behavior and health using the methods and theories of experimental psychology and behavioral economics. Particular problems that he is currently investigating include:

• Information use and decision making in food service... View Details

09 Aug 2011
First Look

First Look: August 9

experiment. The two experiments use the same methods and subject pool and examine games randomly selected from the same distribution. The current introductory paper presents the results of the estimation experiment and clarifies the... View Details

Keywords: Sean Silverthorne

March 2015 (Revised January 2020)
Supplement

Behavioural Insights Team (B)

By: Michael Luca and Patrick Rooney

The Behavioural Insights Team case introduces students to the concept of choice architecture and the value of experimental methods (sometimes called A/B testing) within organizational contexts. The exercise provides an opportunity for students to apply these principles... View Details

Keywords: Behavioral Economics; Experiments; Choice Architecture; Public Entrepreneurship; United Kingdom

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

Research Summary

Interpersonal Communication & Human-Computer Interaction

This stream of research, combining methods from experimental psychology and natural language processing, investigates behaviors that improve interpersonal communication. In our paper on question-asking published in Journal of Personality and Social Psychology,... View Details

Keywords: Communication; Responsiveness; Negotiation; Gender Stereotypes

June 2013
Article

Opting-in: Participation Bias in Economic Experiments

By: Robert Slonim, Carmen Wang, Ellen Garbarino and Danielle Merrett

Assuming individuals rationally decide whether to participate or not to participate in lab experiments, we hypothesize several non-representative biases in the characteristics of lab participants. We test the hypotheses by first collecting survey and experimental data... View Details

Keywords: Participation Bias; Laboratory Experiments; Prejudice and Bias; Research

23 Apr 2018
Research & Ideas

Sponsorship Programs Could Actually Widen the Gender Gap

to her heart when she got pregnant in the 1980s,” Coffman says.) Since joining academia in the 1980s, Baldiga has studied issues related to advancement and retention in professional services firms. Coffman, meanwhile, is a behavioral economist who uses View Details

Keywords: by Carmen Nobel

January 2008
Article

Nonemployment Stigma as Rational Herding: A Field Experiment

By: Felix Oberholzer-Gee

Long spells of unemployment are known to reduce the likelihood of re-employment, but it is difficult to discern the reasons for this observation. Using an experimental method that controls for search intensity and possible discouragement of job applicants, I document... View Details

Keywords: Job Search; Job Cuts and Outsourcing; Employment; Cognition and Thinking; Perception; Creativity; Human Needs; Job Interviews; Selection and Staffing; Recruitment; Managerial Roles; Judgments; Employment Industry

Research Summary

Overview

Over the last decade, technology companies like Amazon, Google, and Netflix have pioneered data-driven research and development processes centered on massive experimentation. However, as companies increase the breadth and scale of their experiments to millions of... View Details

Research Summary

Overview

By: Iavor I. Bojinov

Over the last decade, technology companies like Amazon, Google, and Netflix have pioneered data-driven research and development processes centered on massive experimentation. However, as companies increase the breadth and scale of their experiments to millions of... View Details

2022
Article

Towards Robust Off-Policy Evaluation via Human Inputs

By: Harvineet Singh, Shalmali Joshi, Finale Doshi-Velez and Himabindu Lakkaraju

Off-policy Evaluation (OPE) methods are crucial tools for evaluating policies in high-stakes domains such as healthcare, where direct deployment is often infeasible, unethical, or expensive. When deployment environments are expected to undergo changes (that is, dataset... View Details

Keywords: Analytics and Data Science; Research

July 2015
Article

BYOB: How Bringing Your Own Shopping Bags Leads to Treating Yourself, and the Environment

By: Uma R. Karmarkar and Bryan Bollinger

As concerns about pollution and climate change have become more central in public discourse, shopping with reusable grocery bags has been strongly promoted as environmentally and socially conscious. In parallel, firms have joined policy makers in using a variety of... View Details

Keywords: Grocery Shopping; Reusable Bags; Licensing; Priming; Goals; Hedonic; Marketing Strategy; Consumer Behavior; Environmental Sustainability; Retail Industry

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... View Details

Keywords: AI and Machine Learning; Copyright; Information

Article

Reliable Post hoc Explanations: Modeling Uncertainty in Explainability

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

As black box explanations are increasingly being employed to establish model credibility in high stakes settings, it is important to ensure that these explanations are accurate and reliable. However, prior work demonstrates that explanations generated by... View Details

Keywords: Black Box Explanations; Bayesian Modeling; Decision Making; Risk and Uncertainty; Information Technology