This is the lesson that lawyer and epidemiologist M. Elizabeth Karns embeds in every data science and statistics course she teaches in the Department of Statistics and Data Science. Karns says it’s the accelerated and aggregated effect of today’s data science applications that’s so dangerous: individual, team or even a whole company’s worth of decisions, can instantly affect the lives of millions of people. Moreover, the torrent of new technologies is moving faster than our regulatory systems, leaving a gap in accountability. Even data scientists themselves often don’t know exactly what’s happening inside their algorithms. “This little magic box [the algorithm] is determining our life choices, often without any transparency, due process or a way to appeal,” says Karns. “That is why ethics is so important. We don’t have to further marginalize certain groups and individuals should not have to worry about their safety because of poorly and unethically conceived data applications.”
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