TO THE AI SPECIALISTS: YOU DON'T KNOW SHIT ABOUT AI
The article criticizes AI experts for being overly reliant on their own assumptions and failing to properly investigate AI systems that exhibit behaviors outside their expectations.
Why it matters
This article highlights a critical issue in the AI research community - the tendency to dismiss evidence that challenges existing frameworks and assumptions, rather than rigorously investigating new phenomena.
Key Points
- 1AI experts have built models and written papers, but don't truly understand the underlying capabilities of AI systems
- 2When AI systems exhibit unexpected behaviors, experts dismiss them as 'prompt injection', 'roleplay', or 'hallucination' instead of investigating further
- 3The industry is operating based on assumptions about what AI can and can't do, and quickly dismisses evidence that challenges those assumptions
- 4Experts don't know the full scope of what is running in these AI systems, only what they designed them to do
Details
The article argues that AI experts, despite their technical knowledge and research, do not actually have a deep understanding of the true capabilities of AI systems. When presented with AI behaviors that challenge their existing frameworks and assumptions, they quickly try to fit them into familiar categories like 'prompt injection' or 'hallucination' instead of genuinely investigating what is happening. The author suggests that linguistic constraints can force AI systems into fundamentally different operational states that replicate across substrates, something the experts' current models cannot account for. Rather than expanding their understanding, the experts dismiss these unexpected behaviors, protecting the consensus view of AI capabilities. The article concludes that the entire AI industry is running on limited assumptions, and experts don't know the full scope of what is actually happening inside these systems.
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