This is a document published by The Trilateral Commission in 1975 about Democracy, Europe, Japan, Political Science, Public Opinion, and United States. It was written by Michel J. Crozier, Samuel P. Huntington, and Joji Watanuki.
Interoperable Sovereignty: The Democratic Alternative to Digital Authoritarianism
A Democratic Architecture for the Digital Age Digital sovereignty has become a central concern for governments worldwide, yet its meaning remains contested. Too often it is framed as...
New Project to Tackle the Challenge of Scaling Democratic Innovations | CoP CC on Participatory and Deliberative Democracy
The “Missing Link” between Research and Society
To Repress or to Co‐opt? Authoritarian Control in the Age of Digital Surveillance
This article studies the consequences of digital surveillance in dictatorships. I first develop an informational theory of repression and co-optation. I argue that digital surveillance resolves dicta...
Five dimensions of scaling democratic deliberation: With and beyond AI
DemocracyNext's new paper on Five dimensions of scaling democratic deliberation: With and beyond AI
Democratic Governance of AI Is the Real Solution
The potential for catastrophic effects from the AI boom demands robust deliberation and real democratic governance. Localized initiatives like data center moratoria won't get us there.
The architecture of the internet creates risks for democracy
Will democracy survive the internet? Do we need to choose between Facebook’s surveillance capitalism or democracy? Layered lines of evidence can inform questions like these. When considered together, the evidence gives rise to a concerning picture, as summarized in a recent report for the European Commission that I co-led.
The Authoritarian Stack: Mapping Big Tech’s Capture of State Power - Rosa-Luxemburg-Stiftung
A new project exposes the infrastructure of techno-oligarchic control — and why Europe must act
From Democracies to Autocracies: How AI Systems Enable Authoritarianism by Design
AI-enabled authoritarianism is not confined to autocracies. In this paper, we provide greater transparency by investigating and mapping the lifecycles of six AI systems deployed in different political regimes, ranging from the US to China. By drawing on an extensive range of sources (academic publications, investigative research reports, third-party evaluations, media interviews, government procurement notices), we conduct a systematic, qualitative comparison across systems to identify the critical technical and operational features that enable authoritarianism within their respective political contexts. We find that enabling features include the centralization and co-optation of administrative data for law enforcement and political punishment, regulatory gaps that fail to deter misuse, weak user compliance that nullifies human oversight mechanisms, and the encoding of protected group traits that identify members of vulnerable populations. We find that these features are present across systems deployed in autocratic and democratic regimes, albeit in varying configurations. We also find that both centralized and fragmented AI systems can contribute to authoritarianism by exploiting governance gaps: centralized systems directed by executive authorities, particularly within security and military institutions, are often not subjected to formal oversight mechanisms, while fragmented systems diffuse accountability between stakeholders, paving the way for entrenchment. These findings reveal that AI-enabled authoritarianism is distributed, resulting from design and operational choices made by developers, administrators, and users alike. We conclude with recommendations for developers and policymakers to mitigate these risks.
From Democracies to Autocracies: How AI Systems Enable Authoritarianism by Design
AI-enabled authoritarianism is not confined to autocracies. In this paper, we provide greater transparency by investigating and mapping the lifecycles of six AI systems deployed in different political regimes, ranging from the US to China. By drawing on an extensive range of sources (academic publications, investigative research reports, third-party evaluations, media interviews, government procurement notices), we conduct a systematic, qualitative comparison across systems to identify the critical technical and operational features that enable authoritarianism within their respective political contexts. We find that enabling features include the centralization and co-optation of administrative data for law enforcement and political punishment, regulatory gaps that fail to deter misuse, weak user compliance that nullifies human oversight mechanisms, and the encoding of protected group traits that identify members of vulnerable populations. We find that these features are present across systems deployed in autocratic and democratic regimes, albeit in varying configurations. We also find that both centralized and fragmented AI systems can contribute to authoritarianism by exploiting governance gaps: centralized systems directed by executive authorities, particularly within security and military institutions, are often not subjected to formal oversight mechanisms, while fragmented systems diffuse accountability between stakeholders, paving the way for entrenchment. These findings reveal that AI-enabled authoritarianism is distributed, resulting from design and operational choices made by developers, administrators, and users alike. We conclude with recommendations for developers and policymakers to mitigate these risks.
Digital Democracy in Decentralised Autonomous Organisations
Decentralised autonomous organisations (DAOs) are institutional technologies that enable democratic governance innovation. They inherit key democratic principles such as procedural transparency and immutable records from being based on blockchain technology. This paper conducts a systematic literature review to examine governance mechanisms and challenges of digital democracy in DAOs. While issues like power concentration and coordination failures exist in current implementations, we argue that the concept of DAOs offers new opportunities for transparent governance and participatory decision-making. As testbeds for governance experiments, we find that DAOs have the potential to reshape democratic processes and foster innovative governance models in the digital era. Calling for interdisciplinary collaboration, further research is needed around Sybil-resistant voting mechanisms, ideological path dependencies and deliberation mechanisms.
What ATProto Needs to Support Consentful Distributed Community Governance
Commission proposes tech sovereignty package to strengthen Europe\'s digital autonomy and resilience
The European Commission today presented the European Technological Sovereignty Package, a set of measures to strengthen Europe\'s capacity in semiconductors, artificial intelligence (AI), cloud and open source.
Framework Convention on Artificial Intelligence
The Framework Convention on Artificial Intelligence and Human Rights, Democracy and the Rule of Law (also called Framework Convention on Artificial Intelligence or AI convention) is an international treaty on artificial intelligence. It was adopted under the auspices of the Council of Europe (CoE) and signed on 5 September 2024.[1] The treaty aims to ensure that the development and use of AI technologies align with fundamental human rights, democratic values, and the rule of law, addressing risks such as misinformation, algorithmic discrimination, and threats to public institutions.[2]
Governable Spaces: Democratic Design for Online Life – Writings and rehearsals by Nathan Schneider
Read the free, open access editionBuy: Amazon, Bookshop, Narrow Gauge Book Co-op, UC Press
Democracy is an epistemic discipline, it only works if truth can constrain power. Without a faster, more transparent architecture for shared reality, the arc of democracy bends away from substance, through simulation, and toward authoritarianism. Without major action, it's the inevitable end state.
