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Participatory Moral AI Is Not Neutral: The Invisible Hand of Developers

As AI systems make more morally loaded decisions across society, one response has been moral preference elicitation. In this approach, researchers poll participants on hypothetical dilemmas and use the aggregated votes to train a policy that an AI model then applies at scale. Before any vote is cast, developers make three key choices in the moral AI elicitation pipeline: feature scoping, voter…

We haven't written up this one. arXiv cs.AI has the full story — the link below goes straight to it.

Read the original at arxiv.org →

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Why GPT-5.6 Luna High Is My Default for Agentic Engineering

I used to pick coding models the same way people pick sports cars: choose the most powerful one and pretend the fuel bill is somebody else's problem.

  • GPT-5.6 Luna favored for agentic engineering tasks
  • Low input ($0.20) and output ($1.20) token costs
  • High reasoning effort ensures effectiveness

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