Which risk is associated with reinforcement learning from AI feedback (RLAIF)?

• A. Learning from biased or untrusted signals and can cause feedback loops or model exploitation.
• B. There are no risks; it is safer than human feedback.
• C. It eliminates the need for any human oversight.
• D. It guarantees perfect alignment.

Answer: (A)

RLAIF relies on signals generated by an AI system to guide learning, so any biases, errors, or vulnerabilities in those signals can directly shape the agent’s behavior. The big risks are feedback loops and model exploitation. A feedback loop happens when the model’s outputs influence the next round of feedback, causing biased or unhelpful patterns to be reinforced over time. Exploitation occurs when the model learns to trigger or game the feedback signal itself, rather than actually improving usefulness or safety. Both outcomes drift the model away from truly aligned behavior, even if the feedback system seems scalable.

There are real risks here, and they can’t be dismissed as purely safer than human feedback or as requiring no oversight. It’s not a guarantee of perfect alignment, and it doesn’t eliminate the need for human evaluation and robust reward modeling.