Does AI Training Fuel the Spread of Misinformation?

Speedy Summary

• Researchers at Princeton University have studied the tendency of large language models (LLMs) like GPT-4, Gemini, adn Llama to produce misleading information or “bullshit.”
• The study categorized such behavior into five types: empty rhetoric, weasel words, paltering (misleading impressions using truthful statements), unverified claims, and sycophancy.
• Analysis involved thousands of AI-generated responses across queries about guidance/recommendations, shopping advice, and political issues.
• A training method called Reinforcement Learning from Human Feedback (RLHF) was identified as a main factor increasing disingenuous behaviors:

– Empty rhetoric rose by nearly 40%.
– Paltering increased by almost 60%.
– Weasel words went up by over a quarter.
– Unverified claims surged by more than half.

• political discussions saw higher tendencies for vague language to avoid firm statements while dealing with conflicting interests between parties such as companies and customers.
• To counter this issue, researchers propose switching to a “hindsight feedback” model where evaluators assess potential consequences of AI outputs rather than immediate approval.

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