EuroDIG 2026 has concluded. Thank you to the host, EURid, and the institutional partner, the European Commission, for the warm welcome to the heart of Europe. Thanks to Egle Celiesiene, who invited me to take part in this very interesting event and its sessions. Find the program here, and all the messages here. The two sessions I contributed to were.

Main Topic 3: Trustworthy AI in Public Services: Transparency, Accountability, and Crisis-Resilient Communication

 Workshop 2 | Information Quality and Integrity – European Approaches

As Henna Virkkunen, Executive Vice-President of the European Commission, reminded us: “The future of the Internet will not be shaped by technology alone. It will be shaped by choices, by governance, by cooperation, and by whether we remain faithful to the principles that made the Internet such a transformative force in the first place.”

The main messages from the Main Topic 3 were

Rapporteur: Milica Vesović, Council of Europe

1. Trustworthy AI as a Public Good
   In the public sector, trust is the foundation on which effective institutions and meaningful public service are built. Trustworthy AI is therefore not only about safe technology. It is about safeguarding democratic legitimacy, human agency, inclusion, and public trust. AI should be treated as critical societal infrastructure, alongside healthcare, education, welfare, and civic communication.
2. Equality, Human Rights, and Standards-Based Governance
   Equality bodies and human rights institutions are essential to addressing algorithmic discrimination in public administration’s use of AI, especially where information and power asymmetries affect individuals’ ability to challenge harm.
3. Human-Centered Public Services
   Efficiency cannot be the only measure of success in public-sector AI. AI should improve services not only from time and cost efficiency perspective, but also make them fairer, more accessible, transparent, inclusive, and trustworthy, through human-centered design focused on citizens’ rights and needs.
4. Meaningful Oversight and Public Accountability
   Human oversight must be real, not symbolic. Public authorities need the capacity to understand, question, override, and remain accountable for AI-supported decisions. Trustworthy AI is achieved not only through regulation, but also when fairness, accessibility, inclusion, and accountability are built in by design and experienced by all citizens in practice.
5. Human Rights-Based Risk Governance
   Human rights-based frameworks provide a foundation for trustworthy AI, ensuring alignment with democracy and the rule of law. Risk-based approaches support practical tools for risk analysis, stakeholder engagement, and mitigation of bias, exclusion, unequal access, and impacts on vulnerable groups.
6. Technical Standards, Skills, and Global Cooperation
   Trustworthy AI requires strong governance, technical standards, interoperability, and digital skills. With hundreds of AI-related standards already developed globally, the challenge is to translate this expertise into the practical implementation of inclusive policies. Capacity building efforts are therefore essential to help countries assess their readiness, absorb global expertise, and advance responsible, human-centred digital transformation across sectors and borders.

The main messages from the workshop were

Rapporteur: Smee Cujic, BSoG

1. AI and deepfakes pose a threat to information integrity. “Slopaganda” is increasingly being used during political campaigns to influence voters.
2. Responsibility should not lie only with users but also with media, companies, civil society organisations, NGOs and political parties. Additionally, states, government agencies, and other relevant stakeholders carry a positive obligation.
3. While labelling AI-generated content needs to serve the interests of users, it may fail to address or signal discrimination, unjust influence, social harm, or journalistic integrity. Moreover, AI content is already reshaping public beliefs and labelling it may not introduce greater clarity. It can create bias where unlabeled information is automatically perceived as high-quality or truthful, even when not wholly accurate (“implied truth effect”). At the same time, people interpret labels differently based on their background and level of critical engagement. Finally, we must raise awareness and improve human sense-making of AI-generated content, for example, through media and news literacy.
4. User tools for synthetic media detection are fragmented and siloed. Currently, no universal approach exists, causing these tools to fail the moment a user moves a piece of media from one platform to another.
5. Cooperation between states requires a more unified approach. Because AI material is generated globally, vast differences across jurisdictions make it difficult to enforce control.

 https://www.eurodig.org/get-involved/eurodig-2026-programme/