Science and Society Policy Recommendations

Annex to the Davos Declaration on European AI Research and Innovation, based on the NGI Enrichers Program and the AI Horizon 25 conference in Davos

Executive Summary

Our analysis reveales Europe’s paradoxical position in AI development, characterized by a “risk-thinking mode” that contrasts with global optimism. Key paradoxes include collaboration versus competition tensions, fear versus excitement about AI adoption, skills divide implications, critical thinking challenges, trust and sovereignty issues, rights versus accountability dilemmas, and productivity versus employment concerns. Europe must urgently transition from regulatory leadership to industrial policy implementation, building a sovereign AI ecosystem based on EU values. Critical recommendations include investing in value-based AI infrastructure, comprehensive education integration, transparent governance frameworks, proactive environmental impact mitigation, and fostering collaboration with like-minded countries to achieve strategic autonomy and competitiveness.

Authors: Katalin Féher, Karolina Gyurovszka, Simon Gemperli, Paola Gortan, René Krikke, Marc Herren, Alberto Pasquale Ferrara, Johanna Füllmann.

Current State of the Field

Europe’s position is characterized by a prevailing “risk-thinking mode” with a core question: “What is or can be European AI? Just words or a geopolitical reality?” This reflects tension between global collaboration desires and regional autonomy drives. Despite being a leader in AI regulation, Europe is often perceived as a “loser” in the global AI landscape.

    Emerging Trends and Challenges (2025-2030)

    Anticipated Technological Advances

    • Continued rapid development of AI tools leading to AI developing empathy
    • Development of immersive AI environments and AI self-awareness
    • Emergence of AI Agents and potential for “co-intelligence/identity”

    Major Paradoxes of AI Integration

    • Collaboration vs. Competition: Tension between global cooperation and regional self-reliance
    • Fear vs. Excitement: Europe’s skepticism contrasts with global enthusiasm
    • Skills Divide: AI’s potential to exacerbate inequalities or equalize skills
    • Critical Thinking Paradox: Essential for proper AI use, but AI use may diminish critical thinking
    • Trust & Sovereignty: Building “trusted AI” complicated by external control over infrastructure
    • Rights vs. Accountability: Defining responsibility for AI actions and human rights protection
    • Productivity vs. Labour Market Structure: AI-driven productivity gains may eliminate junior-level jobs
    • Productivity vs. Unemployment: Need for social coherence as low-skill jobs disappear

    Areas of Uncertainty

    • Wild Cards: End of AI hype, job sector disappearance, school obsolescence, unprofitable AI
    • Black Swans: Societal collapse from “too much AI,” AI-powered despotism, infrastructure blackouts

    Strategic Recommendations

    Building Sovereign AI Ecosystem

    • Invest in building an AI ecosystem based on EU values and fundamental rights respect
    • Mandate Transparency & Interoperability: Require AI model transparency and API compatibility
    • Decentralize AI: Foster open, decentralized AI scaling through like-minded partnerships
    • Develop Technical Solutions: Support European values in AI development and governance

    Education / Human Capital

    • Integrate AI in Education Plans: Include basic AI skills starting with young generations
    • Upskilling & Reskilling: Implement personalized AI-driven programs and inclusivity initiatives
    • Labour Market Confidence: Ensure job security and societal benefit compensation
    • Transparency in AI Use: Require declaration of AI usage in work and research
    • Rights for Access: Ensure free AI providers and public citizen access

    AI Governance & Security

    • Define Accountability: Clearly establish responsibility levels for AI systems
    • Enforce Rights: Ensure human and fundamental rights application in EU AI ecosystem
    • Prevent Misuse: Leverage AI Act for empowerment and identity protection

    Societal & Environmental Impact

    • Energy Efficiency: Require built-in energy solutions for AI infrastructure
    • Reduce Fear & Increase Accessibility: Develop strategies to reduce societal AI fear
    • Strategic Foresight & Institutional Willingness: Transform regulation into robust industrial policy

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