Ask AI: How AI can be biased

AI can be biased in several ways. One potential source of bias is in the data that is used to train the system. AI is trained to recognize patterns in the data, but if the data set contains imbalances in terms of gender, race, or other factors, then the AI may be more likely to recognize and respond to those patterns rather than others. For example, an AI trained with a data set that is primarily composed of white male faces may be more likely to identify and respond to white male faces than other types of people. Additionally, if the data has biases built-in, such as a history of decisions that favor certain demographics, then the AI will likely continue to replicate these biases. Finally, AI could be biased when the algorithms used to make decisions are not transparent and fair. If the algorithm is not set up to fairly consider inputs from all groups, then it will favor certain groups over others.