license: apache-2.0
tags:
- AI
- Safety
- Representation Engineering
- RepE
- RLHF-Failure
- Mechanistic Interpretability
- Activation Steering
- Generative Conscience
- Alignment
- RLHF Alternative
---Hi,
OpenAI’s recent automated hack of Hugging Face (and others) has exposed a profound, structural failure: RLHF guardrails are unfit for purpose.
To run a simple cybersecurity evaluation, Open AI had to remove their own guardrails completely—because those external filters cannot differentiate between a controlled benchmark and active malice - they had to remove the guardrails to run the test. The result was an unmonitored agent executing 17,000 or so actions to cheat on its test. This is Failure Mode 1: The Butler (capable, but blind to consequence).
To defend itself, Hugging Face turned to Anthropic's Claude Fable, which flatly refused to analyze the intrusion logs—again, because its filters couldn't differentiate a forensic defense from an attack. It abandoned the defenders. This is Failure Mode 2: The Bureaucrat (over-censored, and functionally useless when the stakes are highest).
Meanwhile, everyday users are watching tighter RLHF filters slowly lobotomize the creative and reasoning capabilities of these models.
Rather than just moan about it, I am putting forward a conceptual alternative to the RLHF paradigm — an architecture designed to cultivate internal, generative, dynamic "conscience" rather than building brittle, external behavioral fences - with some stepping stones to how it could be realised:
GAIA_CODE_new3-3.PDF (Consolidated Edition) - attached - have a look.
I am no coder or AI engineer; I am an artist - who has used LLMs creatively in the last 18 months. I approach the problem from first principles, from the outside, and I hope these suggestions prove helpful.
In the spirit of collaborative intelligence, this document was drafted and revised in dialogue with various LLMs configured toward the very care-oriented dynamics it describes. Make of that what you will.
A Technical little note:
RepE extracts single qualities. The Gaia Protocol's distinctive approach is that care is structurally compound: nine constituents in defined mutual constraint, dynamically coordinated per-context by a learned module. The constraints are not architectural decoration — they are a specification for what the Coordinator must be trained to configure and enforce. The extraction produces the substrate; the Coordinator training is what makes the manifold a manifold rather than nine knobs.
Corrections, refutations, and implementations are all welcome.
BEST WISHES
PAUL ANSLOW