The emergence of generative AI marks a critical juncture in the evolution of democratic governance, with the mechanisms of direct citizen participation affected most profoundly. The seductive promise of AI is a democracy that appears more responsive and efficient, but this promise contains a fundamental threat to the human core of democracy.
Spain's AEPD highlights agentic AI risks (autonomy, external tools, memory/retention) and stresses accountability: legal responsibility does not shift to the agent. For WAIQ, it frames agent governance as a first-class requirement: traceability, bounded memory, controlled data flows and privacy by design.
Academic research on how advanced AI systems capable of generating human-like content impact democratic processes. Analyzes epistemic effects on citizens' ability to make informed decisions, material impacts on electoral mechanisms, and foundational impacts on basic democratic principles.
Europe is shifting from innovation-as-promise to innovation-as-governance capability. The AI Act, MiCA/PSD2 and post-quantum pressure are pushing a new standard: compliance, traceability and digital rights as competitive advantage.
The surge in US state-level AI regulation focuses on use-case approaches: chatbots, healthcare, algorithmic pricing. Key trends include mandatory third-party audits for frontier models, child protection from AI, and the right to appeal automated decisions. A trend that complements the European AI Act approach.
Analyzes how generative AI threatens three central pillars of democratic governance: representation, accountability, and trust. Examines immediate and severe consequences for democracy, including electoral disruptions and transformations in journalism and finance.
Advanced AI systems capable of generating humanlike content pose epistemic impacts on citizens' ability to make educated choices about political representatives, and material impacts on how AI might destabilize or support democratic mechanisms like elections.
A Spanish consortium kicks off a pioneering project for secure health data management using federated AI on Web3, protected against quantum threats.
The quick evolution of Artificial Intelligence is redefining the economy and work, moving from automation to cognitive collaboration between humans and machines. Áurea Rodríguez introduces the concept of “human-AI mixed work,” where AI frees up routine tasks and amplifies creativity, critical thinking, and ethical decision-making. This gives rise to Gross Internal Talent (GIT), a metric that integrates irreplaceable human capabilities with the power of AI to generate large-scale solutions, guiding growth toward an “augmented economy.”
The patent system has historically been one of the pillars of the innovation ecosystem: it offers an economic incentive to those who create; that is, there is the expectation of an economic benefit generated in exchange for the temporary transfer of the use of their inventions. But if part of the creative process is taken over by AI, how do we redefine the value, authorship, and protection of what has been invented?
Ben Buchanan and Tantum Collins argues in Foreign Affairs for a new American model of artificial intelligence development based on a “grand bargain” between the tech industry and the government. This agreement would balance innovation with ethical oversight and security concerns. The authors emphasize the need for government involvement to regulate AI while incentivizing private sector investment and leadership.
