Summarizing books with human feedback
OpenAI Blog
Researchers developed methods to train AI systems to summarize books using human feedback, addressing the challenge of evaluating open-ended tasks where multiple correct answers exist. The approach involved collecting human preferences on summaries and training models to match those judgments, rather than relying on automated metrics. This technique demonstrates how human feedback can scale oversight of AI systems for complex tasks that resist simple automated evaluation.
Why it matters
Scaling human oversight of AI systems for tasks that are difficult to evaluate.
