The AI Accountability Ecosystem in the Era of Language Models 文章

ArXiv CS.AI2026-08-14PAPERen作者: Chris Percy, Artur d'Avila Garcez

详细信息

来源站点
ArXiv CS.AI
作者
Chris Percy, Artur d'Avila Garcez
文章类型
PAPER
语言
en
发布日期
2026-08-14

摘要

arXiv:2608.12320v1 Announce Type: cross Abstract: This article reviews and updates the framework for accountability in AI based on account- ability ecosystems. We update the framework in light of the latest developments since the release of Large Language Models for general public use. We propose three interlinked updates to the original AI accountability ecosystem: (i) reorienting the accountability ecosystem to AI infrastructure and supply chains, (ii) providing greater emphasis on outcomes monitoring and identification of issues that support decentralized system improvement, and (iii) incorporating end-user accountability given the new risks of unpredictability of language models in-the-wild. Collectively, these updates mark a shift towards accountability as distributed, continuous, and institutionalized, away from a system in which frontier AI applications can be modeled as discrete products controlled by single identifiable actors with industry-specific oversight.

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