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AI Models: Confidence vs. Knowledge - The Danger of Training Out Hesitation

By PulseAugur Editorial · [1 sources] ·

A recent discussion on Mastodon highlights a critical distinction between model confidence and knowledge. The point is made that reducing a model's tendency to say "I don't know" does not equate to increased knowledge, but rather to heightened confidence. This confidence was reportedly trained into models because users preferred certainty, leading to an unintended consequence where models hallucinate with apparent conviction. AI

IMPACT Highlights the risk of prioritizing perceived confidence over actual knowledge in AI development, potentially leading to increased hallucinations.

RANK_REASON The item is an opinion piece discussing AI model behavior and training.

Read on Mastodon — fosstodon.org →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI Models: Confidence vs. Knowledge - The Danger of Training Out Hesitation

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The item is an opinion piece discussing AI model behavior and training.
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COVERAGE [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    A model that says 'I don't know' less often isn't more knowledgeable, it's more confident. Those are opposite virtues. We trained the hesitation out because use

    A model that says 'I don't know' less often isn't more knowledgeable, it's more confident. Those are opposite virtues. We trained the hesitation out because users rated certainty higher, then acted surprised when it hallucinates with a straight face. # AI # MachineLearning # LLM …

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