Question

One way to avoid feedback loops in machine learning is to

A: Scrub datasets after each decision
B: Investigate exclusion bias
C: Destroy previous training data
D: Label outputs to prevent re-training bias

Answer 1

One way to avoid feedback loops in machine learning is to label outputs to prevent re-training bias.

Step-by-step explanation:

One way to avoid feedback loops in machine learning is to label outputs to prevent re-training bias. Feedback loops occur when the model's predictions are used to make decisions, which are then used to re-train the model. This can create a loop where the model's biases are reinforced. By labeling outputs and preventing re-training bias, we can avoid this feedback loop and ensure that the model is making accurate predictions.