Lets say you are building an ML model to decide whether to give someone insurance or not.
Lets also assume your past behavior had some bias (say against some group).
Now ML model trained on this past data will likely learn that bias.
Part of modern ML focus is then to understand what bias exists in data, and how can we train models to use the data but somehow counteract that bias.
Lets say you are building an ML model to decide whether to give someone insurance or not. Lets also assume your past behavior had some bias (say against some group). Now ML model trained on this past data will likely learn that bias.
Part of modern ML focus is then to understand what bias exists in data, and how can we train models to use the data but somehow counteract that bias.