Addressing Bias

There are a variety of techniques that AI model developers use to address bias in AI models.

One key approach for reducing bias is Reinforcement Learning from Human Feedback (RLHF). During the training of models, humans rate the AI's responses and the model is adjusted to produce fairer answers over time.

Developers also use system prompts: hidden instructions that run before every conversation, telling the model to be balanced, safe, and avoid harmful responses. You can think of these as 'house rules' the AI must follow before it even reads your message. You never see them, but they're always there.

Even with these techniques, bias can't be fully eliminated, which is why thinking critically about AI responses matters.