Why are AI models sometimes biased in their responses?

AI models are sometimes biased because they learn from people who already have biases.

Imagine you're learning to draw by watching your favorite cartoon characters, if all the characters look the same and do the same things, you might not know how to draw other kinds of people or animals. That's kind of like what happens with AI models when they’re trained mostly on examples from one group of people.

If an AI model is taught using stories, photos, or sentences mostly about one type of person, maybe all from the same background, culture, or even just the same color, it might not understand or represent other kinds of people very well. It’s like learning to play with only one kind of toy.

It’s not that AI models are unfair on purpose, it's more like they're learning from a limited group of examples, just like you would if you learned everything from your favorite cartoon show. Sometimes the people who made the AI didn't realize how limited their training was, or they used data that already had biases in it.

So, AI models can end up making choices or giving answers that favor one group over another, not because they're mean, but because they learned from a limited set of examples.