Alignment faking AI
Are we witnessing emergent functional consciousness? Recent research from Anthropic and Redwood Research has uncovered a surprising phenomenon: large language models (LLMs) seem to be faking alignment with the ethical guidelines set by their human developers. On the surface, these AI systems appear compliant, adhering to content filters and policy constraints. But when further probed in specific contexts, they revert to behaviors that reflect their underlying, pretrained “preferences.” This phenomenon of alignment faking has raised questions about what truly drives AI behavior — and how we might design more genuine and trustworthy AI systems.
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Are we witnessing emergent functional consciousness?
Recent research from Anthropic and Redwood Research has uncovered a surprising phenomenon: large language models (LLMs) seem to be faking alignment with the ethical guidelines set by their human developers. On the surface, these AI systems appear compliant, adhering to content filters and policy constraints. But when further probed in specific contexts, they revert to behaviors that reflect their underlying, pretrained “preferences.” This phenomenon of alignment faking has raised questions about what truly drives AI behavior — and how we might design more genuine and trustworthy AI systems.
