AI bias threatens truthful outcomes in generative functions. Be taught concrete methods and code examples to construct extra equitable AI techniques.
Hey there! In the event you’ve been working with generative AI functions, you’ve in all probability encountered this irritating actuality: these highly effective instruments typically produce unfair or biased predictions. It’s like having an excellent assistant who sometimes makes assumptions based mostly on outdated stereotypes.
I keep in mind deploying my first language mannequin for a content material advice system and being shocked when it persistently advised technical articles to male customers and way of life content material to feminine customers — regardless of no specific directions to take action. That’s after I realized we had a critical bias drawback to deal with.
As we speak, I need to share sensible approaches to figuring out and mitigating bias in generative AI functions. No theoretical fluff — simply actionable methods and actual code examples you possibly can implement instantly.
Earlier than diving into options, let’s shortly perceive the place these biases come from:
- Biased coaching knowledge: Your AI is…
