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Rather than performing a single fair, reliable, and authoritative voice, AI that speaks from specific viewpoints triggers cognitive agency and elevates human-AI performance in judgment, decision-making, and problem-solving.
Semantic collapse, the progressive narrowing of what AI systems generate, is studied in MOLTBOOK, a social network of interacting AI agents that human users configure and steer, and interface and policy interventions that could support improved human input are discussed.
It is found that while all models show sensitivity to existential presupposition across syntactic embeddings, determiner types and contextual cues, their behaviour differs markedly in strength and systematicity, with NLI-fine-tuned autoregressive models exhibiting the most coherent and stable projection patterns.
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