Question

Our goal in machine learning fairness is to minimize _______ as long as _______ is obtained

A: Accuracy issues, unfairness
B: Unfairness, equality
C: Error rates, parity
D: Equality, error rates

Answer 1

In machine learning fairness, the goal is to minimize unfairness as long as equality is obtained. option (B)

Step-by-step explanation:

In machine learning fairness, our goal is to minimize unfairness as long as equality is obtained. This means that we want to reduce any unfairness in the outcomes of a machine learning system while ensuring equal treatment for all individuals.

For example, let's say we are using a machine learning algorithm to make predictions about loan approvals. If the algorithm is biased and unfairly denies loans to certain groups of people, our goal would be to minimize this unfairness and ensure equal access to loans for all individuals.

So, the correct answer is option B: Unfairness, equality.