Mechanistic explanations—descriptions of a system through the causal interactions of its parts—play a key role in human cognition and scientific progress. Despite their importance, we lack systematic evidence on whether and how mechanistic explanations help lay decision-makers interpret information in complex economic environments. We evaluate the causal impact of including mechanistic explanations in an information intervention: public demonstrations of fertilizer use for smallholder tomato farmers in Eastern Uganda. In all demonstrations, extension officers showcased the impact of a recommended fertilizer recipe. In the treatment group, officers also explained the mechanisms underlying the recipe's effect—introducing the language of macronutrients and the causal processes linking nutrients, soil features, and plant growth. We collected detailed data on beliefs and behaviors from 797 farmers in a lab-in-the-field experiment conducted at the demonstration site and followed up with them over two growing seasons. In the lab-in-the-field, treated farmers generalized more effectively—making better substitution and arbitrage decisions among fertilizers and achieving 9% higher simulated profits in an incentivized fertilizer-application task. At endline, treated farmers' real fertilizer choices reflected improved nutrient timing and balance, and their yields were 14% higher.

Smallholder farmers in Sub-Saharan Africa face severe and persistent information barriers. A new wave of AI-assisted digital information technologies has the potential to overcome these barriers at scale, delivering personalized, hyperlocal agronomic advice at low cost. Yet little is known about the impacts of these technologies and how they diffuse. This pilot study investigates these questions in the context of a novel AI-assisted agricultural advisory tool called Virtual Agronomist. Farmers can use this technology to generate tailored nutrient management plans based on high-resolution soil maps, diagnose plant health and pest problems, and access weather advisories. We investigate the impacts of this tool on farmer practices and agricultural outcomes. We also use this context to study broader questions about how information technologies diffuse. We explore three potential mechanisms. First, because many such technologies deliver information as their primary output, peer adoption may generate information spillovers that permanently substitute for own adoption. Second, in contrast to canonical models where heterogeneity slows diffusion, agricultural heterogeneity may reduce the value of free-riding and accelerate adoption. Finally, information technologies constitute a new information source, changing incentives to form social network connections and potentially amplifying or dampening diffusion. We conduct a randomized experiment across 30 villages in Butaleja District, Eastern Uganda to explore these mechanisms. In 10 villages, farmers adopt the tool directly on their own phones. In a second set of 10 villages, usage is mediated by lead farmers who operate the tool on their behalf. The final 10 villages serve as a control, allowing us to compare adoption rates, feature usage, and agricultural outcomes across dissemination strategies.

Worldwide, pedagogical culture in schools is didactic, emphasizing one-way knowledge flows, limiting student learning. We study innovations at teacher training institutions in Uganda to reverse this towards a "culture of learning." Teachers are trained to apply scientific approaches to improve their practice. A coordination structure generates spillovers to transform system-level practice. Our research seeks to understand how effects of this intervention, dubbed the "Learning to Learn" (LTL) approach, spread and sustain change over time. We ask: What density of teachers must be trained for effects to spread? How do the extent and speed of spillovers depend on a "coordinator"? What conditions cause a culture of learning to emerge, with dynamically increasing effects on learning? Our design involves randomizing characteristics of the implementation process at three levels: clusters (groups of schools), schools, and teachers.

Improvements in health outcomes in the Global South are limited by underutilized and low-quality public health services. Under-utilization and low quality often stem from weak accountability structures, limited information flows between citizens, providers, and bureaucrats, and inadequate methods for gathering citizen feedback. This study evaluates a mobile citizen feedback system designed to improve service quality and accountability in Tanzanian public health facilities. The intervention enables patients to anonymously report healthcare experiences via SMS surveys, providing real-time, facility-specific insights on service quality across multiple domains. Feedback is aggregated and shared with facilities and government monitoring teams. Using a randomized controlled trial, we assess the intervention's impact on service quality, utilization, community satisfaction, and health outcomes.