Today’s guest post by Kate Murray introduces a white paper, 'Content Authenticity and Provenance in the Age of Artificial Intelligence: A Call-to-Action for the LAMs Community,' released in February 2026 by the C2PA for G+LAM Community of Practice. This paper urges libraries, archives, and museums (LAMs) to adopt proactive measures to ensure the authenticity, transparency, and verifiability of digital collections, especially when AI influences any part of their lifecycle. It addresses the increasing impact of AI-mediated workflows on traditional content authenticity and provenance (CAP) principles, leading to heightened expectations from researchers, donors, and the public for comprehensive documentation of AI’s effects. The article highlights this as a critical juncture, noting that while AI introduces novel ethical, legal, and privacy risks, it also transforms data creation and analysis at an unprecedented pace, challenging LAMs' conventional approaches to change. The white paper aims to address why LAMs and their users should prioritize CAP for AI-impacted materials and outlines essential actions for organizations to take, illustrating with examples such as verifying AI alteration in photojournalism, confirming capture device settings for artifacts, documenting chatbot transcripts, ensuring authenticity in recorded interviews, and distinguishing historical from AI-generated content in documentaries.
Research and Development
The LAMs community must invest in sustained research and development efforts to extend established content authenticity and provenance principles into the evolving landscape of AI. This R&D should specifically focus on ensuring that human oversight and involvement remain central across diverse workflows and institutional contexts, regardless of size, to maintain robust and trustworthy digital preservation practices in the age of artificial intelligence. This involves exploring new methodologies and tools that can effectively track and verify the origins and modifications of digital assets impacted by AI, thereby preserving public trust in cultural heritage institutions.
Partnerships and Collaboration
It is crucial for Libraries, Archives, and Museums (LAMs) to foster deeper collaborations, both across institutions and between different sectors, including technology developers and policy makers. This collective approach is essential to prevent redundant efforts, expedite learning processes, and collaboratively develop shared frameworks, tools, and standards. Such collaboration will ensure that new solutions effectively address the wide-ranging and evolving digital preservation needs within the LAMs community, creating a unified front against the challenges posed by AI-generated content.
Advocacy with Industry, Vendors and User Communities
LAMs are encouraged to proactively influence the development of standards, specifications, practice models, and technologies. By leveraging their established authority as long-standing custodians of public trust, they should clearly articulate their requirements for open, vendor-agnostic, and demonstrably trustworthy content authenticity and provenance (CAP) data. This advocacy will help shape future digital infrastructure to better serve their core mission of preserving and providing access to reliable information, ensuring that technological advancements align with archival ethics and principles.
Open Distribution of Results and Lessons Learned
Given the rapid and dynamic evolution of AI innovation, there is an urgent need for more transparent and collaborative methods of sharing experimental approaches and their outcomes. This open distribution of knowledge and experiences is vital to complement traditional scholarly communication channels, allowing the LAMs community to adapt quickly and collectively to new challenges and opportunities presented by AI. Sharing best practices and failures openly will accelerate the community's ability to develop robust strategies for managing content authenticity and provenance in an AI-driven world.
