Bias in AI can have profound effects: while one biased person can affect many people, a biased AI system can affect many more. We have seen many prominent examples in recent years: cameras that don’t see dark skin, algorithms that discriminate against women in hiring, racist chatbots, sexist translation programs, etc. Contrasting the points of view of the optimist technologist and the pessimistic philosopher, this presentation will highlight the importance of thinking about bias when developing AI, the challenges that become evident in trying to identify those biases, and what we could do in the short and long-term to avoid those biases. In addition to broader long-term possible solutions, we discuss readily available tools and tactics that companies can use today to minimize bias in developing AI.