As AI decouples cognition from biology, the binding constraint shifts from intelligence to human verification bandwidth. This structural asymmetry drives a measurability-biased technical change.
Why this matters: Researchers and innovators must focus on scaling verification capacity alongside execution to ensure AI preserves the humanity that initiated it.
cs.AI updates on arXiv.org
Empirical evidence reveals a substantial gap between expected and realized benefits of agentic AI systems, driven by workflow friction, verification burden, and uneven distribution of gains.
Why this matters: Researchers and practitioners must account for the expectation-realization gap to avoid overstating the benefits and mitigate the risks of deploying agentic AI.
cs.AI updates on arXiv.org