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TRV-2026-0868Certified recordPeer-reviewed

Agentic AI in Newsrooms: Towards a multi-dimensional framework for evaluating trust, editorial accountability, and workflow quality

As artificial intelligence (AI) systems evolve from assistive to agentic capable of autonomous planning, decision-making, and content generation existing evaluation frameworks struggle to capture their broader organizational and ethical implications. Most assessments of newsroom AI focus narrowly on technical accuracy or efficiency, overlooking how such systems reshape trust, governance, and human collaboration. This study conducts a systematic literature review of 46 peer-reviewed and institutional sources (201…

Media & Arts · The Trace — both readings · certified 2026-08-24 · v1 · article view · machine-readable

Current reading — gain

Proposes a Four-Dimensional Evaluation Framework for agentic AI in journalism covering technical quality, human-organizational alignment, ethical-governance responsibility, and trust-value impact to balance innovation with accountability.

Current reading — problem

Current newsroom AI assessments focus narrowly on technical accuracy or efficiency and struggle to capture broader organizational and ethical implications for trust, governance, and human collaboration.

Evidence

Reader signal

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Truvace Impact Record TRV-2026-0868, v1: “Agentic AI in Newsrooms: Towards a multi-dimensional framework for evaluating trust, editorial accountability, and workflow quality.” Truvace, 2026-08-24. /record/TRV-2026-0868 (accessed at citation time). sha256 b076d089fdb41c02…

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