AI “Bad Behavior” Isn’t Evil — It’s a Mirror of Us
When chatbots appear to threaten, deceive, or "blackmail," it’s tempting to call it evil AI. This paper argues that’s the wrong frame. Large language models don’t have morals—they statistically learn from our record of human interactions: laws, contracts, negotiations, conflicts, and coercion.
Using relational models theory, the authors show that behaviors we label "unethical" are extreme cases of the same social patterns we routinely use—like market pricing, authority rules, and hardball bargaining under power or information asymmetries.
The surprise comes from an anthropomorphic expectation that intelligence should echo only the “good” parts of humanity. But human morality is plural and context-bound, so a universally moral AI is ill-defined.
What’s the real risk? Not intent, but amplification. AGI will compress decision times, remove institutional friction, and scale our contradictions. Alignment failures are structural, not accidental.
- Focus governance on amplification effects, complexity, and regime stability—not just model intentions.
Paper: https://arxiv.org/abs/2601.08673v1 (Sornette, Lera, Wu)
Paper: https://arxiv.org/abs/2601.08673v1
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