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- 2025
- Working Paper
Narrative AI and the Human-AI Oversight Paradox in Evaluating Early-Stage Innovations
By: Jacqueline N. Lane, Léonard Boussioux, Charles Ayoubi, Ying Hao Chen, Camila Lin, Rebecca Spens, Pooja Wagh and Pei-Hsin Wang
Do AI-generated narrative explanations enhance human oversight or diminish it? We investigate this question through a field experiment with 228 evaluators screening 48 early-stage innovations under three conditions: human-only, black-box AI recommendations without... View Details
- 2024
- Working Paper
Pitch Perfect: Investing in Transportable Presentation Skills to Support Poly-vocal Personae
By: James Riley and Susan S. Silbey
For organizations requiring independent and creative thinking skills for complex problem-solving, especially within a multi-disciplinary pool of collaborators, conventional socialization practices flattening individuality for the sake of uniformity is not necessarily... View Details
- August 20, 2024
- Article
Sexual Assault Victims Face a Penalty for Adjacent Consent
By: Jillian J. Jordan and Roseanna Sommers
Across 11 experimental studies (n = 12,257), we show that female victims of sexual assault are blamed more and seen as less morally virtuous if their assault follows voluntary sexual intimacy, a factor we term “adjacent consent”. Moreover, we illuminate a... View Details
- Working Paper
The Returns to Skills During the Pandemic: Experimental Evidence from Uganda
By: Livia Alfonsi, Vittorio Bassi, Imran Rasul and Elena Spadini
The Covid-19 pandemic represents one of the most significant labor market shocks to the world economy in recent times. We present evidence from a field experiment to understand whether and why skilled and unskilled workers were differentially impacted by the shock, in... View Details
- July 2024
- Article
Chatbots and Mental Health: Insights into the Safety of Generative AI
By: Julian De Freitas, Ahmet Kaan Uğuralp, Zeliha Uğuralp and Stefano Puntoni
Chatbots are now able to engage in sophisticated conversations with consumers. Due to the ‘black box’ nature of the algorithms, it is impossible to predict in advance how these conversations will unfold. Behavioral research provides little insight into potential safety... View Details
- July–August 2024
- Article
Doing More with Less: Overcoming Ineffective Long-Term Targeting Using Short-Term Signals
By: Ta-Wei Huang and Eva Ascarza
Firms are increasingly interested in developing targeted interventions for customers with the best response,
which requires identifying differences in customer sensitivity, typically through the conditional average treatment
effect (CATE) estimation. In theory, to... View Details
- July 2024 (Revised July 2024)
- Case
Gates Ventures: Making Alzheimer's a Forgotten Past
By: Satish Tadikonda, William Marks, Shardule Shah and Calvin Marambo
After a personal journey and interest in Alzheimer's Disease (AD) by Bill Gates, Gates Ventures set out to find the best way to accelerate innovation in the field of AD. In partnership with the Alzheimer's Drug Discovery Foundation, Gates Ventures created the... View Details
- July 2024
- Article
Whether to Apply
By: Katherine B. Coffman, Manuela Collis and Leena Kulkarni
Labor market outcomes depend, in part, upon an individual’s willingness to put herself forward for different opportunities. We use a series of experiments to explore gender differences in willingness to apply for higher return, more challenging work. We find that, in... View Details
- June 2024 (Revised September 2024)
- Case
Major League Baseball: Changing the Rules of America's Pastime
By: Stephen A. Greyser, Mac Levin and Brent Schwarz
This case describes the efforts of Major League Baseball (MLB) to make meaningful changes in the rules affecting the ways the game is played. These changes are intended to speed the pace of the game and make it more appealing to younger fans. The principal changes... View Details
- 2024
- Working Paper
Incrementality Representation Learning: Synergizing Past Experiments for Intervention Personalization
This paper introduces Incrementality Representation Learning (IRL), a novel multitask representation learning framework that predicts heterogeneous causal effects of marketing interventions. By leveraging past experiments, IRL efficiently designs and targets... View Details
- 2025
- Working Paper
Evaluations Amid Measurement Error: Determining the Optimal Timing for Workplace Interventions
By: Matthew DosSantos DiSorbo, Iavor I. Bojinov and Fiammetta Menchetti
Researchers have embraced factorial experiments to simultaneously evaluate multiple treatments, each with different levels. Typically, in large-scale factorial experiments, the primary objective is identifying the treatment with the largest causal effect, especially... View Details
- 2024
- Working Paper
Immigrant Entrepreneurship: New Estimates and a Research Agenda
By: Saheel Chodavadia, Sari Pekkala Kerr, William R. Kerr and Louis Maiden
Immigrants contribute disproportionately to entrepreneurship in many countries, accounting for a quarter of new employer businesses in the US. We review recent research on the measurement of immigrant entrepreneurship, the traits of immigrant founders, their economic... View Details
- 2024
- Working Paper
Old Moats for New Models: Openness, Control, and Competition in Generative AI
By: Pierre Azoulay, Joshua L. Krieger and Abhishek Nagaraj
Drawing insights from the field of innovation economics, we discuss the likely competitive environment shaping generative AI advances. Central to our analysis are the concepts of appropriability—whether firms in the industry are able to control the knowledge generated... View Details
- May–June 2024
- Article
Setting Gendered Expectations? Recruiter Outreach Bias in Online Tech Training Programs
By: Jacqueline N. Lane, Karim R. Lakhani and Roberto Fernandez
Competence development in digital technologies, analytics, and artificial intelligence is increasingly important to all types of organizations and their workforce. Universities and corporations are investing heavily in developing training programs, at all tenure... View Details
- 2025
- Working Paper
Greenlighting Innovative Projects: How Evaluation Format Shapes the Perceived Feasibility of Early-Stage Ideas
By: Jacqueline N. Lane, Simon Friis, Tianxi Cai, Michael Menietti, Griffin Weber and Eva C. Guinan
The evaluation of innovative early-stage projects is essential for allocating limited resources. We
investigate how the evaluation format affects the identification of feasibility issues through a
field experiment at a leading research university. Experts were... View Details
- 2024
- Working Paper
Platform Information Provision and Consumer Search: A Field Experiment
By: Lu Fang, Yanyou Chen, Chiara Farronato, Zhe Yuan and Yitong Wang
Despite substantial efforts to help consumers search in more intuitive ways, text search remains the predominant tool for product discovery online. In this paper, we explore the effects of visual and textual cues for search refinement on consumer search and purchasing... View Details
- 2023
- Working Paper
New Facts and Data about Professors and Their Research
By: Kyle Myers, Wei Yang Tham, Jerry Thursby, Marie Thursby, Nina Cohodes, Karim R. Lakhani, Rachel Mural and Yilun Xu
We introduce a new survey of professors at roughly 150 of the most research-intensive institutions of higher education in the US. We document seven new features of how research-active professors are compensated, how they spend their time, and how they perceive their... View Details
- December 2023 (Revised August 2024)
- Case
Monsters in the Machine? Tackling the Challenge of Responsible AI
By: Paul M. Healy and Debora L. Spar
In November of 2022, the small tech company OpenAI released ChatGPT, an artificial intelligence chatbot which quickly captured the public’s imagination—becoming the world’s fastest-growing consumer application within months of its release. Though observers from across... View Details
- 2023
- Article
Benchmarking Large Language Models on CMExam—A Comprehensive Chinese Medical Exam Dataset
By: Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu and Michael Lingzhi Li
Recent advancements in large language models (LLMs) have transformed the field of question answering (QA). However, evaluating LLMs in the medical field is challenging due to the lack of standardized and comprehensive datasets. To address this gap, we introduce CMExam,... View Details
- December 2023
- Article
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work
By: Mijeong Kwon, Julia Lee Cunningham and Jon M. Jachimowicz
Intrinsic motivation has received widespread attention as a predictor of positive work outcomes, including employees’ prosocial behavior. In the current research, we offer a more nuanced view by proposing that intrinsic motivation does not uniformly increase prosocial... View Details