Are we making AIs racist and sexist? Researchers warn machines are learning to have human biases

Machine learning is ubiquitous in our daily lives. Every time we talk to our smartphones, search for images or ask for restaurant recommendations, we are interacting with machine learning algorithms. They take as input large amounts of raw data, like the entire text of an encyclopedia, or the entire archives of a newspaper, and analyze the information to extract patterns that might not be visible to human analysts. But when these large data sets include social bias, the machines learn that too. If the source documents reflect gender bias – if they more often have the word'doctor' near the word'he' than near'she,' and the word'nurse' more commonly near'she' than'he' – then the algorithm learns those biases too, the researcher explains According to James Zou, Assistant Professor for Biomedical Data Science at Stanford University, machine systems are learning human biases when examples of such are included in the training set.