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Recent AI alignment work often frames alignment as a pre-deployment optimization problem: collect human feedback, learn preferences or principles, finetune the model, and deploy an aligned system. This framing has produced major progress, but it under-specifies what happens once AI systems act as agents on users'behalf...
As coding assistants become increasingly autonomous, developers run multiple sessions in parallel, shifting the challenge from code generation alone to coordinating and monitoring concurrent agent work. Through a formative study (N=14), we identified PILOT: five supervisory practices for Planning, Isolating, Logging, O...
DoubleAgents is presented, a system for human–agent alignment in coordination tasks, grounded in distributed cognition that introduces interactive simulation as a methodological testbed for rapid iteration and alignment testing of agentic systems.
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