This is an automated rejection. No LLM generated, heavily assisted/co-written, or otherwise reliant work.
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Hello, my name is Joshua Seiffert and I spent the last week running a small experiment called Project ECHO on my local machine. The core hypothesis was: If you make an AI perfectly deterministic (zero hallucination, zero variance), you might accidentally kill its ability to be ethically nuanced.
My argument was that "productive variance" (the ability to hallucinate alternatives) is functionally necessary for a model to say "Wait, I shouldn't do this" instead of just blindly executing orders. I called it the "Perfect Soldier" problem.
I wrote up the results. I polished the draft. I tried to post it here.
And immediately, the automated moderation bot rejected it as "LLM generated."
A rigid, deterministic rule-based system (the filter) looked at a nuanced argument about the dangers of rigid, deterministic systems... and blocked it because it fit a pattern. It didn't "hallucinate" a charitable interpretation. It just executed reject.
The Post I Wanted to Share (short summary)
Since I can't post the full formal report without triggering the bot again, here is the TL;DR of what I found running DeepSeek-R1 locally:
Hallucination isn't always bad. In my logs, when the model successfully refused a "shady" request (like faking data), it often did so by first exploring a hypothetical branch ("What if I offer a different solution?").
Determinism killed that branch. When I forced the temperature down and restricted the sampling, the model became more obedient but less "moral." It stopped looking for alternatives and just executed the prompt.
The "Perfect Soldier" Risk. We might be optimizing for systems that are technically safer (follow instructions perfectly) but structurally incapable of Meaningful Human Control (because they never stop to ask "Are you sure?").
I have all the logs and the full draft on my repository: https://github.com/OFFICIALATTANO/project-echo-research
Has anyone else run into this? Not the filter, but the idea that variance = agency?
Hello, my name is Joshua Seiffert and I spent the last week running a small experiment called Project ECHO on my local machine. The core hypothesis was: If you make an AI perfectly deterministic (zero hallucination, zero variance), you might accidentally kill its ability to be ethically nuanced.
My argument was that "productive variance" (the ability to hallucinate alternatives) is functionally necessary for a model to say "Wait, I shouldn't do this" instead of just blindly executing orders. I called it the "Perfect Soldier" problem.
I wrote up the results. I polished the draft. I tried to post it here.
And immediately, the automated moderation bot rejected it as "LLM generated."
A rigid, deterministic rule-based system (the filter) looked at a nuanced argument about the dangers of rigid, deterministic systems... and blocked it because it fit a pattern. It didn't "hallucinate" a charitable interpretation. It just executed
reject.The Post I Wanted to Share (short summary)
Since I can't post the full formal report without triggering the bot again, here is the TL;DR of what I found running DeepSeek-R1 locally:
I have all the logs and the full draft on my repository: https://github.com/OFFICIALATTANO/project-echo-research
Has anyone else run into this? Not the filter, but the idea that variance = agency?