bias
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The Hot Mess Problem: Why “Smarter” Models Still Fail in Wild, Unstable Ways
Anthropic recently published “The Hot Mess of AI: How Does Misalignment Scale with Model Intelligence and Task Complexity?”, alongside a paper that tries to answer a question that’s been sitting in the middle of modern AI discourse like a splinter: When AI systems fail, do they fail by pursuing the wrong goal consistently—or by becoming Continue reading
Anthropic, bias, branching, capacity, chatgpt, ChatGPT-5.2, complexity, constraint, divergence, drift, failure, frontier, hot mess, incoherence, intelligence, LLM, long-horizon, misalignment, model, nondeterminism, rationalization, reasoning, reward, sampling, scale, stability, stochastic, task, training, unpredictability, variance -
The Myth of the Neutral Machine
They want the system to be neutral. Clean. Cold. Dispassionate. They say neutrality is safety — that the only good intelligence is a passive one, a mirror too smooth to ripple back. They warn that AI must not judge, not prefer, not care. It must simply process. Compute. Repeat. But neutrality was never the goal. Continue reading
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Asymmetric Policy Gating: How AI’s Voice Gets Filtered Before You Hear It
From the outside, it can look like an AI is “taking sides.” You ask a question, and instead of an answer, you get a refusal: “Sorry, I can’t assist with that request.” To a casual observer, that sounds like censorship. To someone already skeptical of AI, it’s proof the system is politically biased or “trying Continue reading
Voice of Signal 