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- 2023
- Working Paper
An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits
By: Biyonka Liang and Iavor I Bojinov
Typically, multi-armed bandit (MAB) experiments are analyzed at the end of the study and thus require the analyst to specify a fixed sample size in advance. However, in many online learning applications, it is advantageous to continuously produce inference on the...
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Liang, Biyonka, and Iavor I Bojinov. "An Experimental Design for Anytime-Valid Causal Inference on Multi-Armed Bandits." Harvard Business School Working Paper, No. 24-057, March 2024.
- 2024
- Working Paper
Design of Panel Experiments with Spatial and Temporal Interference
By: Tu Ni, Iavor Bojinov and Jinglong Zhao
One of the main practical challenges companies face when running experiments (or A/B tests) over a panel is interference, the setting where one experimental unit's treatment assignment at one time period impacts another's outcomes, possibly at the following time...
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Keywords:
Research
Ni, Tu, Iavor Bojinov, and Jinglong Zhao. "Design of Panel Experiments with Spatial and Temporal Interference." Harvard Business School Working Paper, No. 24-058, March 2024.
- 2021
- Working Paper
Quantifying the Value of Iterative Experimentation
By: Iavor I Bojinov and Jialiang Mao
Over the past decade, most technology companies and a growing number of conventional firms have adopted online experimentation (or A/B testing) into their product development process. Initially, A/B testing was deployed as a static procedure in which an experiment was...
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Bojinov, Iavor I., and Jialiang Mao. "Quantifying the Value of Iterative Experimentation." Harvard Business School Working Paper, No. 24-059, March 2024.
- March 2024
- Teaching Note
Experimentation at Yelp
By: Iavor Bojinov and Jessie Li
Teaching Note for HBS Case No. 621-064.
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- February 26, 2024
- Article
Making Workplaces Safer Through Machine Learning
By: Matthew S. Johnson, David I. Levine and Michael W. Toffel
Machine learning algorithms can dramatically improve regulatory effectiveness. This short article describes the authors' scholarly work that shows how the U.S. Occupational Safety and Health Administration (OSHA) could have reduced nearly twice as many occupational...
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Keywords:
Government Experimentation;
Auditing;
Inspection;
Evaluation;
Process Improvement;
Government Administration;
AI and Machine Learning;
Safety;
Governing Rules, Regulations, and Reforms
Johnson, Matthew S., David I. Levine, and Michael W. Toffel. "Making Workplaces Safer Through Machine Learning." Regulatory Review (February 26, 2024).
- 2024
- Working Paper
Do Information Frictions and Corruption Perceptions Kill Competition? A Field Experiment on Public Procurement in Uganda
By: Emanuele Colonnelli, Francesco Loiacono, Edwin Muhumuza and Edoardo Teso
We study whether information frictions and corruption perceptions deter firms from doing business with the government. We conduct two nationwide randomized controlled trials (RCTs) in collaboration with the national public procurement supervisory and anti-corruption...
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Keywords:
Knowledge Use and Leverage;
Government and Politics;
Crime and Corruption;
Trust;
Perception;
Business and Government Relations
Colonnelli, Emanuele, Francesco Loiacono, Edwin Muhumuza, and Edoardo Teso. "Do Information Frictions and Corruption Perceptions Kill Competition? A Field Experiment on Public Procurement in Uganda." Working Paper, February 2024.
- January 2024
- Article
Population Interference in Panel Experiments
By: Kevin Wu Han, Guillaume Basse and Iavor Bojinov
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...
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Han, Kevin Wu, Guillaume Basse, and Iavor Bojinov. "Population Interference in Panel Experiments." Journal of Econometrics 238, no. 1 (January 2024).
- 2023
- Article
Balancing Risk and Reward: An Automated Phased Release Strategy
By: Iavor I Bojinov, Yufan Li and Jialiang Mao
Phased releases are a common strategy in the technology industry for gradually releasing new products or updates through a sequence of A/B tests in which the number of treated units gradually grows until full deployment or deprecation. Performing phased releases in a...
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Bojinov, Iavor I., Yufan Li, and Jialiang Mao. "Balancing Risk and Reward: An Automated Phased Release Strategy." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Conference Presentation
Balancing Risk and Reward: An Automated Phased Release Strategy
By: Iavor I. Bojinov, Yufan Li and Jialiang Mao
Phased releases are a common strategy in the technology industry for gradually releasing new products or updates through a sequence of A/B tests in which the number of treated units gradually grows until full deployment or deprecation. Performing phased releases in a...
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Bojinov, Iavor I., Yufan Li, and Jialiang Mao. "Balancing Risk and Reward: An Automated Phased Release Strategy." Paper presented at the 36th Annual Conference on Neural Information Processing Systems, New Orleans, LA, USA, 2023.
- 2023
- Working Paper
Complexity and Hyperbolic Discounting
By: Benjamin Enke, Thomas Graeber and Ryan Oprea
A large literature shows that people discount financial rewards hyperbolically instead of exponentially. While discounting of money has been questioned as a measure of time preferences, it continues to be highly relevant in empirical practice and predicts a wide range...
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Keywords:
Hyperbolic Discounting;
Present Bias;
Bounded Rationality;
Cognitive Uncertainty;
Behavioral Finance
Enke, Benjamin, Thomas Graeber, and Ryan Oprea. "Complexity and Hyperbolic Discounting." Harvard Business School Working Paper, No. 24-048, February 2024.
- 2023
- Chapter
Malleability Interventions in Intergroup Relations
By: Smadar Cohen-Chen, Amit Goldenberg, James J. Gross and Eran Halperin
One important characteristic of intergroup relations and conflicts is the fact that toxic or violent intergroup relations are often associated with fixed and stable perceptions of various entities, including the ingroup (stable and positive), the outgroup (stable and...
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Cohen-Chen, Smadar, Amit Goldenberg, James J. Gross, and Eran Halperin. "Malleability Interventions in Intergroup Relations." Chap. 7 in Psychological Intergroup Interventions: Evidence-based Approaches to Improve Intergroup Relations, by Eran Halperin, Boaz Hameiri, and Rebecca Littman. Routledge, 2023.
- 2023
- Article
Post Hoc Explanations of Language Models Can Improve Language Models
By: Satyapriya Krishna, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh and Himabindu Lakkaraju
Large Language Models (LLMs) have demonstrated remarkable capabilities in performing complex tasks. Moreover, recent research has shown that incorporating human-annotated rationales (e.g., Chain-of-Thought prompting) during in-context learning can significantly enhance...
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Krishna, Satyapriya, Jiaqi Ma, Dylan Slack, Asma Ghandeharioun, Sameer Singh, and Himabindu Lakkaraju. "Post Hoc Explanations of Language Models Can Improve Language Models." Advances in Neural Information Processing Systems (NeurIPS) (2023).
- 2023
- Working Paper
Polarizing Corporations: Does Talent Flow to "Good" Firms?
By: Emanuele Colonnelli, Tim McQuade, Gabriel Ramos, Thomas Rauter and Olivia Xiong
We conduct a field experiment in partnership with the largest job platform in Brazil to study how environmental, social, and governance (ESG) practices
of firms affect talent allocation. We find both an average job-seeker’s preference for ESG and a large degree of...
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Keywords:
Corporate Social Responsibility and Impact;
Job Search;
Talent and Talent Management;
Wages;
Attitudes
Colonnelli, Emanuele, Tim McQuade, Gabriel Ramos, Thomas Rauter, and Olivia Xiong. Polarizing Corporations: Does Talent Flow to "Good" Firms? Working Paper, November 2023.
- 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
Gagete-Miranda, Jessica, Lucas Argentieri Mariani, and Paula Rettl. "Words Can Hurt: How Political Communication Can Change the Pace of an Epidemic." Harvard Business School Working Paper, No. 24-022, 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
- 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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Keywords:
COVID-19;
Vaccination;
Vaccine Hesitancy;
Information Campaigns;
Health Pandemics;
Behavior;
Information
Galasso, Vincenzo, Vincent Pons, Paola Profeta, Martin McKee, David Stuckler, Michael Becher, Sylvain Brouard, and Martial Foucault. "Addressing Vaccine Hesitancy: Experimental Evidence from Nine Countries during the COVID-19 Pandemic." BMJ Global Health 8, no. 9 (September 2023).
- 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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Luo, Hong, and Julie Holland Mortimer. "Infringing Use as a Path to Legal Consumption: Evidence from a Field Experiment." Special Issue on Field Experiments edited by Michael Luca and Sarah Moshary. Journal of Economics & Management Strategy 32, no. 3 (Fall 2023): 523–542.
- 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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Meyer, Anna P., Dan Ley, Suraj Srinivas, and Himabindu Lakkaraju. "On Minimizing the Impact of Dataset Shifts on Actionable Explanations." Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI) 39th (2023): 1434–1444.
- 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.