Summary of https://conference.nber.org/conf_papers/f210475.pdf This research paper examines the impact of an artificial intelligence (AI) tool on materials discovery in the R&D lab of a large U.S. firm. The AI tool, which leverages deep learning to partially automate the materials discovery process, was rolled out to scientists in three waves, allowing the researchers to analyze the effects of the technology. The study found that the AI tool significantly accelerated materials discovery, resulting in an increase in patent filings and product prototypes, particularly for scientists with strong initial productivity. However, the tool's effectiveness depended on the scientist's ability to evaluate the AI-generated compounds, highlighting the importance of human judgment in the scientific discovery process. The paper concludes by exploring the AI tool's impact on scientist job satisfaction and beliefs about artificial intelligence, revealing that while the tool enhances productivity, it also leads to changes in the types of tasks scientists perform, potentially affecting job satisfaction and prompting a need for reskilling.