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Aamer Mihaysi
Aamer Mihaysi

Posted on • Originally published at mehaisi.com

AI Hallucinations: Why Machines Get It Wrong (Like We Do)

"Hallucination" frames AI as broken. But humans do the same thing.

Human Memory: Reconstructive

Your memory doesn't replay events. It rebuilds them — combining fragments, filling gaps, creating coherence.

Cognitive science calls this "constructive episodic memory." Not a bug. A feature.

Why We Hallucinate

  • Gap-filling: Incomplete info → automatic completion
  • Pattern-matching: See patterns in noise
  • Future simulation: Recombine past to imagine future
  • Meaning-making: Create narratives from fragments

Survival requires this. Waiting for complete information = paralysis.

LLMs Do The Same

  • Predict next token from patterns
  • Not retrieving facts — generating probable continuations
  • Fill knowledge gaps with plausible completions
  • Coherent output, weak grounding

The Real Difference

We get angry because:

  1. We expect computers to be precise
  2. AI doesn't signal uncertainty clearly
  3. No immediate reality feedback for AI
  4. We know human memory is fallible — expected machines to be better

The Implication

Hallucination isn't a bug to patch. It's fundamental to prediction.

The question: How to ground outputs? Signal confidence? Build correction loops?

Solutions

  • RAG for grounding
  • Confidence scoring
  • Multi-step validation
  • Human-in-the-loop

Hallucination = similarity, not defect. Both minds and LLMs generate coherence from partial patterns. LLMs just need better reality-checking scaffolding.


Originally published at mehaisi.com

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