As machine learning has progressed, people have come to realize that these systems often adopt human biases due to the datasets they receive and their tendency to amplify existing processes and decisions. Researchers are now aware of these challenges and actively working to reduce biases in artificial intelligence. One recent model, for example, incorporates steps to detect, audit, and eliminate algorithmic biases.