The first meeting of this workstream was held on 29 April, 2026. It gathered representatives of signatory States of the Partnership as well as civil society experts and researchers. The meeting involved expounding the current economic challenges to the information ecosystem in the face of AI. It also considered the existential threats to media sustainability, and what a weakened media ecosystem does to public trust and knowledge. Finally, the meeting briefly touched upon global regulatory approaches, and started discussions on possible policy interventions.
Key Insights
This first meeting revealed the multitude of challenges faced in the realm of AI and the information space globally.
Power Dynamics, Copyright and Remuneration
The prevalent use by AI chatbots of journalistic content reveals a shift in power dynamics. This affects the remuneration of media houses for their work – either in the form of training data, in the form of data that is extracted and summarised, or in terms of their revenue from ad traffic reduced by AI summary tools. There is also a severe lack of transparency in terms of what data is used, and how credit for this content is attributed to the press. This is also related to the problem of fair compensation to all parties in the AI value chain, from frontline journalists, to editors and even to data workers.
The first question, then, is what kind of copyright or licensing regime is best placed to give power back in the hands of information gatekeepers – viz. Media houses. – for all these use cases. What kind of bargaining regime is best placed to do so? What would fostering transparency and provenance data look like, how do we ensure fair remuneration, and in what form must we consider digital levies and taxes?
Deepfakes and Epistemic Challenges
A second problem is the prevalence of hyperrealistic content – i.e. deepfakes and disinformation. Deepfakes are tied to large scale financial fraud, gendered violence, attacks on business ecosystems and public figures. Disinformation in sensitive contexts – such as war, elections and natural disasters – is especially worrying. These are further complicated by the use of agentic AI to scale up such information attacks – including, but not limited to Foreign Information Manipulation and Interference (FIMI).
The detection of deepfakes is increasingly difficult, and costs more than its generation. This is compounded by linguistic divides, regional variations, and a necessity to understand specific, local, contexts. This hampers detection, moderation and response – especially in the Global South – when AI tools are overwhelmingly developed and trained in the West.
The prevalence of deepfakes – especially in the form of ‘replica websites’ of established public service media – affects its visibility, trustworthiness and reputation. This consequently affects traffic and remuneration too. Sourcing errors and wrong answers from prevalent AI chatbots in summarizing the news – whether via a lack of context, mistaken attribution, lack of sourcing, editorialization or inaccuracy – also have these effects. This affects the perception of the media as a bulwark of truth and a reliable fourth pillar of democracies worldwide.
Where do we go from here?
Solving these issues would require fundamentally strengthening societal resilience via publication policies, but also risk-based governance, heightened safeguards, deployment of privacy law, data protection and targeted criminal law.
Taken together, these problems affect media pluralism – in the form of the media’s ability to report, especially from underserved and underreported regions, and in terms of visibility for the same. This affects access to reliable information for the general public.
What do we want to achieve?
At our next meeting, we hope to present policy interventions using a comparative, global and analytical research approach that we are working on currently. The next meeting is scheduled for the 18th of June. Civil society organizations are invited to share their work and policy interventions, while we also hope to learn from individual member states’ experiences.
