The Biggest Risk of Embodied AI is Governance Lag

Fuente: arXiv
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Main Author: Liu, Shaoshan
Format: Preprint
Published: 2026
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author Liu, Shaoshan
author_facet Liu, Shaoshan
contents Embodied AI is widely discussed as a job-displacement problem. The deeper risk, however, is governance lag: the inability of public institutions to keep pace with how fast the technology spreads through the physical economy. As reusable robotic platforms are combined with increasingly general AI models, embodied AI may scale across manufacturing, logistics, care, and infrastructure faster than governance systems can observe, interpret, and respond. We argue that this lag appears in three connected forms: observational, institutional, and distributive. The central policy challenge, therefore, is not automation alone, but whether governance and compliance systems can adapt before disruption becomes entrenched.
format Preprint
id arxiv_https___arxiv_org_abs_2604_21938
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle The Biggest Risk of Embodied AI is Governance Lag
Liu, Shaoshan
Computers and Society
Artificial Intelligence
Embodied AI is widely discussed as a job-displacement problem. The deeper risk, however, is governance lag: the inability of public institutions to keep pace with how fast the technology spreads through the physical economy. As reusable robotic platforms are combined with increasingly general AI models, embodied AI may scale across manufacturing, logistics, care, and infrastructure faster than governance systems can observe, interpret, and respond. We argue that this lag appears in three connected forms: observational, institutional, and distributive. The central policy challenge, therefore, is not automation alone, but whether governance and compliance systems can adapt before disruption becomes entrenched.
title The Biggest Risk of Embodied AI is Governance Lag
topic Computers and Society
Artificial Intelligence
url https://arxiv.org/abs/2604.21938