How IBM Is Working Toward a Fairer AI

Humans have many kinds of biases. To name just a few, we suffer from confirmation bias, which means that we tend to focus on information that confirms our preconceptions about a topic; from anchoring bias, where we make decisions mostly relying on the first piece of information we receive on that subject; and from gender bias, where we tend to associate women with certain traits, activities, or professions, and men with others. When we make decisions, these types of biases often creep in unconsciously, resulting in decisions that are ultimately unfair and unobjective. These same types of bias can show up in artificial intelligence (AI), especially when using machine learning techniques to program an AI system. A commonly-used technique called "supervised machine learning" requires that AI systems be trained with a large number of examples of problems and solutions.