Books shape how children learn about society and social norms, in part through the representation of different characters. To better understand the messages children encounter in books, we introduce new artificial intelligence methods for systematically converting images into data. We apply these image tools, along with established text analysis methods, to measure the representation of race, gender, and age in children’s books commonly found in US schools and homes over the last century. We find that more characters with darker skin color appear over time, but "mainstream" award-winning books, which are twice as likely to be checked out from libraries, persistently depict more lighter-skinned characters even after conditioning on perceived race. Across all books, children are depicted with lighter skin than adults. Over time, females are increasingly present but are more represented in images than in text, suggesting greater symbolic inclusion in pictures than substantive inclusion in stories. Relative to their growing share of the US population, Black and Latinx people are underrepresented in the mainstream collection; males, particularly White males, are persistently overrepresented. Our data provide a view into the "black box" of education through children’s books in US schools and homes, highlighting what has changed and what has endured.
Programs that provide lower-skill employment are a popular anti-poverty strategy in developing countries, with India's employment-guarantee program (MGNREGA) employing adults in 23% of Indian households. A potential concern is that guaranteeing lower-skill employment opportunities may discourage investment in human capital and long-run income growth. Using large-scale administrative data and household survey data, I estimate precise spillover impacts on education that reject substantive declines in children's education from the government's rollout of MGNREGA. I estimate that these small negative impacts are inexpensive to counteract, particularly compared to MGNREGA expenditures on rural employment and poverty alleviation.