Publications
Publications
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- 2023
- Working Paper
Words Can Hurt: How Political Communication Can Change the Pace of an Epidemic
By: Jessica Gagete-Miranda, Lucas Argentieri Mariani and Paula Rettl
While elite-cue effects on public opinion are well-documented, questions remain as
to when and why voters use elite cues to inform their opinions and behaviors. Using
experimental and observational data from Brazil during the COVID-19 pandemic, we
study how leader...
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Keywords:
Elites;
Public Engagement;
Politics;
Political Affiliation;
Political Campaigns;
Political Influence;
Political Leadership;
Political Economy;
Survey Research;
COVID-19;
COVID-19 Pandemic;
COVID;
Cognitive Psychology;
Cognitive Biases;
Political Elections;
Voting;
Power and Influence;
Identity;
Behavior;
Latin America;
Brazil
- 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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- September 2023
- Article
Addressing Vaccine Hesitancy: Experimental Evidence from Nine Countries during the COVID-19 Pandemic
By: Vincenzo Galasso, Vincent Pons, Paola Profeta, Martin McKee, David Stuckler, Michael Becher, Sylvain Brouard and Martial Foucault
We study the impact of public health messages on intentions to vaccinate and vaccination uptakes, especially among hesitant groups. We performed an experiment comparing the effects of egoistic and altruistic messages on COVID-19 vaccine intentions and behaviour. We...
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- Fall 2023
- Article
Infringing Use as a Path to Legal Consumption: Evidence from a Field Experiment
By: Hong Luo and Julie Holland Mortimer
Digitization has transformed how users find and use copyrighted goods, but many existing legal options remain difficult to access, possibly leading to infringement. In a field experiment, we contact firms that are caught infringing on expensive digital images. Emails...
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- 2023
- Article
On Minimizing the Impact of Dataset Shifts on Actionable Explanations
By: Anna P. Meyer, Dan Ley, Suraj Srinivas and Himabindu Lakkaraju
The Right to Explanation is an important regulatory principle that allows individuals to request actionable explanations for algorithmic decisions. However, several technical challenges arise when providing such actionable explanations in practice. For instance, models...
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- 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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- August 2023
- Case
Reimagining Hindustan Unilever (A)
By: Sunil Gupta and Rachna Tahilyani
In the fall of 2019, the CEO and MD of Hindustan Unilever (HUL), India’s largest fast-moving consumer goods (FMCG) firm, is wondering what to do about their experiments to digitize distribution. Despite three years of intense efforts, their apps to empower retailers...
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- August 2023
- Supplement
Reimagining Hindustan Unilever (B)
By: Sunil Gupta and Rachna Tahilyani
In April 2023, as the CEO and MD of Hindustan Unilever (HUL), India’s largest fast-moving consumer goods (FMCG) firm, prepared to hand over the firm’s reins to his successor, he proudly reflected on the last decade. His quest to digitally transform HUL into an...
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- 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...
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- 18 Jul 2023
- Interview
Jeffrey Rayport on Product Market Fit, Profit Market Fit and Whiplash, and More
By: Jeffrey F. Rayport and Doug Levin
This episode of "Lessons from Startup Life" podcast features Jeffrey Rayport, Senior Lecturer of Business Administration at the Harvard Business School. Jeffrey specializes in teaching and researching growth-stage technology ventures and their scalability. Prior to...
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- July 2023
- Article
Design and Analysis of Switchback Experiments
By: Iavor I Bojinov, David Simchi-Levi and Jinglong Zhao
In switchback experiments, a firm sequentially exposes an experimental unit to a random treatment, measures its response, and repeats the procedure for several periods to determine which treatment leads to the best outcome. Although practitioners have widely adopted...
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- July 2023
- Article
Impacts of Electricity Quality Improvements: Experimental Evidence on Infrastructure Investments
By: Robyn C. Meeks, Arstan Omuraliev, Ruslan Isaev and Zhenxuan Wang
Hundreds of millions of households depend on electricity grid connections providing low quality and unreliable services. Understanding the impacts of and consumer response to electricity quality improvements is important for development and the environment. We...
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- 2023
- Working Paper
The Nature, Sources, and Consequences of Citizens’ Anti-establishment Sentiments
By: Loreto Cox and Natalia Garbiras-Diaz
While recent studies examine anti-establishment parties and candidates, fewer focus
on citizens’ anti-establishment sentiments, which we define as an intense and angry
animosity toward political elites and distrust of political parties. What drives these
sentiments?...
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- June 2023
- Simulation
Artea Dashboard and Targeting Policy Evaluation
By: Ayelet Israeli and Eva Ascarza
Companies deploy A/B experiments to gain valuable insights about their customers in order to answer strategic business problems. In marketing, A/B tests are often used to evaluate marketing interventions intended to generate incremental outcomes for the firm. The Artea...
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Keywords:
Algorithm Bias;
Algorithmic Data;
Race And Ethnicity;
Experimentation;
Promotion;
Marketing And Society;
Big Data;
Privacy;
Data-driven Management;
Data Analysis;
Data Analytics;
E-Commerce Strategy;
Discrimination;
Targeted Advertising;
Targeted Policies;
Pricing Algorithms;
A/B Testing;
Ethical Decision Making;
Customer Base Analysis;
Customer Heterogeneity;
Coupons;
Marketing;
Race;
Gender;
Diversity;
Customer Relationship Management;
Marketing Communications;
Advertising;
Decision Making;
Ethics;
E-commerce;
Analytics and Data Science;
Retail Industry;
Apparel and Accessories Industry;
United States
- 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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- June 2023
- Article
Do Job Seekers Value Diversity Information? Evidence from a Field Experiment and Human Capital Disclosures
By: Jung Ho Choi, Joseph Pacelli, Kristina M. Rennekamp and Sorabh Tomar
We examine how information about the diversity of a potential employer's workforce affects individuals’ job-seeking behavior. We embed a field experiment in job recommendation emails from a leading career advice agency in the U.S. The experimental treatment involves...
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- 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...
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- April 2023 (Revised November 2023)
- Case
AI Wars
By: Andy Wu, Matt Higgins, Miaomiao Zhang and Hang Jiang
In November 2023, the world was looking to Google to see what the search giant and long-time putative technical leader in artificial intelligence (AI) would do to compete in the massively hyped technology of generative AI. Just a year ago, OpenAI released ChatGPT, a...
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- April 2023
- Article
Inattentive Inference
By: Thomas Graeber
This paper studies how people infer a state of the world from information structures that include additional, payoff-irrelevant states. For example, learning from a customer review about a product’s quality requires accounting for the reviewer’s otherwise irrelevant...
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- April 2023
- Article
On the Privacy Risks of Algorithmic Recourse
By: Martin Pawelczyk, Himabindu Lakkaraju and Seth Neel
As predictive models are increasingly being employed to make consequential decisions, there is a growing emphasis on developing techniques that can provide algorithmic recourse to affected individuals. While such recourses can be immensely beneficial to affected...
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