arXiv:2607.01250v1 Announce Type: cross Abstract: Sociotechnical alignment concerns the social desirability of AI behavior and is thus inherently normative, not merely technical. While NLP research increasingly addresses its technical aspects, it often leaves underspecified what such "social desirability" entails. We argue that this reflects a fundamental gap: the absence of a systematic way to specify how sociotechnical alignment defines, justifies, and evaluates socially desirable AI behavior. To address this gap, we introduce a human-centered framework for specifying sociotechnical alignmen
The rapid deployment and increasing societal integration of AI systems necessitate a structured approach to defining and evaluating their social impact and ethical behavior.
A systematic framework for 'sociotechnical alignment' is critical for ensuring AI development aligns with human values, shaping future regulatory landscapes, and fostering public trust.
The publication provides a human-centered framework that moves beyond abstract discussions of 'social desirability' to offer a systematic way to specify, justify, and evaluate ethical AI behavior.
- · AI ethics researchers
- · Policymakers
- · AI developers focused on responsible AI
- · Society at large
- · AI developers ignoring ethical considerations
- · Unregulated AI deployments
This framework provides a common language for discussing and implementing AI alignment.
It could lead to the development of standardized metrics and audits for socially desirable AI behavior.
These standards might eventually influence AI investment, development priorities, and international AI governance frameworks.
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Read at arXiv cs.CL