These "Generally Good Practices" have their downsides.
We should be using more AI solutions by now. But there's this bias issue to consider!
We've seen AI models perform differently for underrepresented groups. These issues have been debated heavily in recent years. In search of why bias arises, we found that there are more ways than a human trainer's intention could cause bias.
Yet, when other people's lives and jobs are concerned, the innocence of a creator is not excused. Customer backlashes, public opinion, and badmouthing could harm your reputation, and it may be tough to recover from them.
Thus it's critical to understand AI bias. You can't manage something you don't understand.
Here are five situations where bias can sneak into your models.
Top comments (0)