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Jonathan Hersh, Chapman University Disruptive transformations are all the rage in Silicon Valley, and even traditional organizations are starting to discuss machine learning and artificial intelligence. However, new methods from data science can create internal frictions within organizations that alter power dynamics. The extent to which any project scales can often be determined by institutional support, even if the project is successful. Moreover, 'move fast and break things' isn't a reliable model in organizations where the cost to failure are high or catastrophic. Discussing his experience within institutions such as the World Bank and Inter-American Development Bank, this talk will discuss strategies to help data scientists respectfully advocate for data science solutions at more traditional institutions. In the process, we will learn about research on using satellites to estimate bombing damage in Syria, and how 3G cell phones are caused thousands of accidents per year. Visit rstats.ai to learn more about the R Conference series.