AI can be unintentionally biased: Data cleaning and awareness can help prevent the problem

Most artificial intelligence systems strive for 95% accuracy of results when benchmarked against the traditional methods of determining outcomes. But how can organizations safeguard against systems so the AI doesn't inadvertently inject bias that affects the accuracy of results? Bias can be injected into AI by faulty algorithms, by lack of complete data on which the algorithms operate or even by machine learning that operates on certain biased assumptions. One example is an Amazon recruiting tool that began with an AI project in 2014. The intent of the AI application was to save recruiters time going through resumes.