arXiv:2606.30652v1 Announce Type: cross Abstract: Transparency is increasingly mandated for public-sector AI systems, with organisations required to publish statements describing their AI use and oversight arrangements. However, the existence of such artefacts is often treated as equivalent to transparency itself, despite limited evidence that they proportionately serve relevant stakeholder groups. From a requirements engineering perspective, this raises a validation concern: compliance with mandated disclosure criteria does not necessarily ensure transparency adequacy for stakeholders with di
The proliferation of AI systems in the public sector is prompting increased scrutiny and attempts at regulation, making the effectiveness of transparency mandates a timely concern.
This highlights a critical disconnect between regulatory compliance and actual stakeholder needs for AI transparency, potentially leading to ineffective governance despite good intentions.
The focus is shifting from merely fulfilling mandated disclosure criteria to validating whether transparency efforts genuinely serve diverse stakeholder requirements.
- · AI governance experts
- · Public sector ethical AI teams
- · Citizen advocacy groups
- · Organizations prioritizing checklist compliance
- · Developers of opaque AI systems
- · Public entities with inadequate transparency frameworks
Public sector organizations will need to re-evaluate and potentially redesign their AI transparency mechanisms to be more stakeholder-centric.
This could lead to the development of new standards and auditing practices for 'effective' AI transparency, moving beyond mere disclosure.
Increased public trust (or distrust if not addressed) in government use of AI will directly correlate with the perceived adequacy of these transparency efforts.
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Read at arXiv cs.AI