M

The extent to which the internal mechanics of a machine or deep learning model can be explained in human terms.

The process by which an AI model's performance degrades over time due to changes in the underlying data or environment.

Refers to an algorithmic model generating prejudiced results due to erroneous assumptions in the machine learning process.

A type of AI program with the ability to learn without explicit programming, and can change when exposed to new data; mainly comprising Supervised Learning, Unsupervised Learning, and Reinforcement Learning.