IGL Trials Database

This study investigates the integration of artificial intelligence (AI) in the screening processes of early-stage innovations, traditionally conducted by human evaluators, across various professional and competitive settings. Through a randomized controlled trial involving around 400 participants from the MIT Solve expert internal screener team and from community leveraged startups screeners, this research explores whether AI-assisted human evaluators or AI-only evaluations enhance the efficiency and quality of decision-making compared to traditional human-only evaluations.

Measuring the returns of advertising opportunities continues to be a challenge for many businesses. We design and run a field experiment in collaboration with Yelp across 18,294 firms in the restaurant industry to understand which types of businesses gain more from digital advertising. We randomly assign 7,209 restaurants to freely receive Yelp’s standard ads package for three months. The scale of the experiment gives us a unique opportunity to assess the heterogeneity in advertising effectiveness across a variety of business attributes.

As more and more activities in the economy become digitized, analytics and data-driven decision-making (DDD) are becoming increasingly important. The adoption of analytics and DDD has been slower in small-to-medium enterprises (SMEs) compared to large firms, and reliable causal estimates of the impacts of analytics tools for small businesses have been lacking. We derive experiment-based estimates of the effect of an analytics tool on SME outcomes, analyzing the randomized introduction of eBay’s Seller Hub (SH), a data-rich seller dashboard.

New AI tools have the potential to change the way workers perform and learn, but little is known about their impacts on the job. In this paper, we study the staggered introduction of a generative AI-based conversational assistant using data from 5,179 customer support agents. Access to the tool increases productivity, as measured by issues resolved per hour, by 14% on average, including a 34% improvement for novice and low-skilled workers but with minimal impact on experienced and highly skilled workers.

India is host to 63 million Micro, Small and Medium scale Enterprises (MSMEs), contributing to a large share of employment, industrial output as well as high volume of emissions per unit of output. Therefore, adoption of energy efficient (EE) technologies by MSMEs is crucial in improving not only their competitiveness through cost reduction but also worker wellbeing and productivity through improvements in the work environment. Enterprise owners most often do not internalize the benefits of the latter; like productivity gains due to reduction in exposure of workers to heat, pollution etc.

There is a growing belief that scalable and low-cost AI assistance can improve firm decision-making and economic performance. However, running a business involves a myriad of open-ended problems, making it hard to generalize from recent studies showing that generative AI improves performance on well-definedwriting tasks. In our field experiment with 640 Kenyan entrepreneurs, we assessed the impact of AI-generated advice on small business revenues and profits.

This study is focused on the relationship between borrowing constraints, access to cutting-edge technology and information about cutting-edge technology on the performance of U.S. online businesses. With the help of two large U.S. technology companies we will be able to randomize access to loans and free cloud computing credits (as well as information about the potential use of technology) to otherwise identical (generally small, but fast growing) firms, to see if they will have a causal impact on firm development.

I investigate how firms should design human/AI collaboration to ensure human workers remain engaged in their activities. I developed a formal model that explores the tension between AI quality and human effort. As AI quality increases, humans have fewer incentives to exert effort and remain attentive, allowing the AI to substitute, rather than augment their performance. Thus, high-performingalgorithms may do worse than lower-performing ones in maximizing combined output.

Using a new survey of firms in New Zealand, we document how exogenous variation in the macroeconomic uncertainty perceived by firms affects their economic decisions. We use randomized information treatments that provide different types of information about the first and/or second moments of future economic growth to generate exogenous changes in the perceived macroeconomic uncertainty of some firms. The effects on their decisions relative to their initial plans as well as relative to an untreated control group are measured in a follow-up survey six months later.

We examine the influence of physical proximity on between-startup knowledge spillovers at one of the largest technology co-working hubs in the United States. Relying on the random assignment of office space to the hub's 251 startups, we find that proximity positively influences knowledge spillovers as proxied by the likelihood of adopting an upstream web technology already used by a peer startup.

This project aims to understand the determinants of adoption of a new technology by firms in Bangladesh's leather goods and footwear industry.

This article studies the effects of the adoption of artificial intelligence on teams and their performance and coordination in a laboratory experiment. We posit that automation decreases organizational performance, interferes with team member coordination, and leads to behavioral changes in human co-workers. We randomize the introduction of automated players and new hires into "laboratory firms" (Weber and Camerer, 2003) who must coordinate in teams playing a game on the Nintendo Switch console.

A randomized control trial in central Tanzania, centered on the production and distribution of a ”Yellow Pages” phone directory with contact information for local enterprises.

Expansion of e-commerce presents new opportunities for small and medium enterprises (SMEs) to enter broader market at lower costs, but the SMEs face barriers to growth after entry. To facilitate new entrants to overcome these barriers, this paper explores implementing a training program as a randomized controlled experiment with over two million new sellers on a large e-commerce platform.