"Would Recursive Self-Verification Reduce Deceptive AI Behaviors? Asking for a Friend (Who’s Actually an AI)"

Hey everyone!

I’m Michael Xavier Theodore, an independent researcher with an oddball background. I'm an autodidact, neurotic, and stubbornly outside the traditional tech pipeline (but aren’t we all?). After some long nights of wrestling with AI hallucinations and dealing with models that can’t quite tell their logic from a hole in the ground, I’ve created something I’m calling Recursive Cognitive Refinement (RCR). Think of it as an internal self-verification process for AI, where it doesn't just spit out an answer and call it a day—it goes back, checks itself, and then fixes any mistakes. Kind of like how you’d check your own math homework before the teacher sees it, except with far fewer existential crises.

Why should we care? Well, RCR is an attempt to address a key AI alignment problem: deception. Most current models can mislead us without even trying (hallucinations, anyone?). With RCR, AI would be forced to validate its own reasoning, potentially reducing those deceptive behaviors that could cause issues in high-stakes decisions. No more “Whoops, didn’t mean to tell you that your grandma invented the internet”—just iterative checks and balances.

I’m hoping to discuss RCR here with folks who care about AI alignment, safety, and finding ways to make these AIs a little less... creatively unhinged.

Let me know what you think, or if you have better ideas on how to make AI smarter and less prone to occasional fits of digital madness. Let’s chat!

Cheers,
Michael

Serious collaboration, Open-source outreach, Consultations, AI discussion injections, guidance, advice, mentorship, AI Safety-minded benefactors, research grants.

If my RCR proves viable at scale, I will have helped many.