Implicit bias is an automatic association or assumption that can influence judgment without deliberate intent. In AI development, it can affect data collection, feature selection, labeling, testing, and system design, leading to skewed outcomes or unfair performance.
Automatically making an association or assumption based on one's mind models and memories. Implicit bias can affect the following: - How data is collected and classified. - How machine learning systems are designed and developed. For example, when building a classification model to identify wedding photos, an engineer may use the presence of a white dress in a photo as a feature. However, white dresses have been customary only during certain eras and in certain cultures. See also confirmation bias.