artturipu 
Europe is best positioned to build an economy where AI works reliably in the benefit of everyone. To do this, however, the EU should strengthen its strategic self-determination, deploy substantive multistakeholderism, and integrate societal goals into AI standards and funding.
At a recent FORSEE seminar hosted by the American University of Armenia (AUA) Center for Ethics in Public Affairs, Professor Paul Boghossian examined whether large language models perform genuine reasoning
What counts as “AI success”? New FORSEE research suggests it depends on where you look.
To understand differing hopes and fears on AI, FORSEE researchers Charis Papaevangelou, Lucie Loubère, Nikos Smyrnaios, and Pierre Ratinaud (University of Toulouse) analysed how AI is discussed both in media and between citizens.
The American University of Armenia (AUA) Center for Ethics in Public Affairs officially launches its participation in the FORSEE project on 6 May. The event introduces the AUA research team and outlines the center’s role in our European research initiative redefining what success means for artificial intelligence.
This joint webinar by the ALFIE project, Transmedia Catalonia Access Talks, and FORSEE explores how the European Union’s Artificial Intelligence Act and the European Accessibility Act connect and impact technology and inclusion.
What counts as “AI success”? New FORSEE research suggests it depends on where you look.
To understand differing hopes and fears on AI, FORSEE researchers Charis Papaevangelou, Lucie Loubère, Nikos Smyrnaios, and Pierre Ratinaud (University of Toulouse) analysed how AI is discussed both in media and between citizens.
AI is often framed as a driver of growth and productivity, and economic analyses focus on productivity gains, potential for GDP growth, and job market impacts. Yet this perspective overlooks how AI is reshaping the social fabric of work: the organisation of workplaces, the distribution of power, and the conditions under which people participate in economic life.
Our collective understanding of what makes AI successful remains narrow and incomplete. Success in AI is often equated with technological sophistication or economic efficiency. How quickly can systems learn? How much productivity will they generate? How do they scale in specific contexts?
Project lead
Dr Elizabeth Farries
Director of the UCD Centre for Digital Policy
elizabeth.farries@ucd.ie
Lead of Communication and Impact
Johannes Mikkonen
Demos Helsinki
johannes.mikkonen@demoshelsinki.fi
Project Manager
Evangelos Papadamakis
UCD Centre for Digital Policy
vangelis.papadamakis@ucd.ie
Funded by the framework of the Horizon Europe Research and Innovation Programme under grant agreement Nº 101177579
