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The backlog of the EU-wide digital regulatory facilities already includes over 50 various directives and regulations, united into the so-called “big digital acts”. The digital “regulatory burden” covers numerous socio-economic and corporate sectors; hence, it is both quite complicated and controversial for consumers and governance: e.g. to navigate in the “sea of digital rules”, and – at the same time – requiring a sort of simplification of the regulatory means.
Background
Although the European “digital initiatives” date back to the beginning of this century, the main regulatory efforts are taking place within the last two-three years.
The European continent stands at a civilizational crossroads; the digital transformation – and the artificial intelligence in particular – is no longer a question of technological progress alone. It represents a structural transformation of how knowledge is produced, decisions are made, the governance is exercised and the responsibilities understood.
Globally and in the EU’s context, almost every sphere of life is being reshaped: economies, governance systems, education, labor markets, cultural practices and the architecture of personal judgment itself. The benefits are substantial: i.e. the AIs can synthesize vast bodies of accumulated information within seconds, identify patterns beyond human perception, optimize industrial processes, accelerate scientific discovery and support complex administrative decisions.
The digital transition enhances analytical capacity and expands the reach of human capability. In this sense, AI is a powerful instrument of progress. Yet this expansion introduces a deeper tension: AI systems deliver outputs with the confidence of computation. The AI models do not hesitate, confess ignorance or experience moral uncertainty”; their logic appears neutral, objective and final. Increasingly, public and private decision-making relies on this algorithmic rationality, often without questioning its underlying assumptions.
The future of artificial intelligence is globally controlled, mainly, by the United States and China: the two countries employ 70 percent of the world’s top machine learning researchers, command 90 percent of global computing power, and attract the vast majority of AI investment—more than twice the combined total of every other state combined.
In past technological revolutions, powers that were not at the frontier could gradually adopt new capabilities and catch up; but the AI “revolution” is different by locking al other countries into a strategic trap that could consign much of the world to a sort of “technological vassalage”.
Source: https://www.foreignaffairs.com/united-states/ai-divide
EU’s “big digital acts”
There are, presently, at least eight the so-called “big digital acts” in the European digital regulatory framework – united, generally, into already over 50 EU-wide “digital rules”, including:
1. Data Governance Act (2023), 2. Cyber and Data Protection Act (2023), 3. Digital Market Act (DMA, 2023) and 4. Digital Services Act (DSA, from 2022); 5. Data Act (2023), 6. Digital Company Act (expected by 31 July 2027); 7. Digital Company Law Directive (adopted in 2024, to be transposed to the member states by July 2027), and 8. European Artificial Intelligence Act (EU AI Act, 2024 in 113 articles, delayed until December 2027, coped with the AI Liability Directive).
Two landmark EU-wide digital regulations – the DMA and the DSA – codify principles and create processes for digital services providers and ensure a wide choice of safe digital services and derivative products.
More on DMA/DSA in: https://eizpublishing.ch/artikel/euz/03-2024/digital-regulation-in-the-european-union/
Above all then, there is as the so-called “Common European Data Spaces”, an initiative (to be fully implemented by 2027), which is aimed at creating a “continental-common, and interoperable data spaces” in strategic sectors to overcome existing legal and technical barriers to data sharing. The rules for common European data spaces will cover areas like health, mobility, environment, energy and agriculture, to: a) make better use of publicly held data for research for the common good, b) support voluntary data sharing by individuals, and c) set up structures to enable key organisations to share data.
More in: https://www.freshfields.com/en/our-thinking/campaigns/tech-data-and-ai-the-digital-frontier/eu-digital-strategy/european-data-spaces
Vital European AI legislation: the EU AI Act
The EU is positioning itself as a global leader in trustworthy and human-centered artificial intelligence: i.e. the EU’s regulatory framework aims to balance innovation with safety, transparency and protection of fundamental rights. Thus, the European AI regulatory framework aims to create safe, ethical and trustworthy AI while supporting innovation.
The EU AI Act is becoming a global reference model, influencing regulatory discussions worldwide. European Union aims to lead in trustworthy, human-centered AI through strong regulations (often excessive); the ambition is clear: to balance innovation with citizens’ safety, data protection and fundamental rights. But — as with any ambitious regulation — there are debates, trade-offs and dissenting voices.
Main reference to: EU AI Act (Regulation 2024/1689), in https://ai-act-law.eu/
However, the EU is presently heavily dependent on the US digital services in many areas: the US tech giants often enjoy monopolistic power with a few alternatives, apart from Chinese providers. This dependency “represents” potential EU weakness, especially when it comes to critical digital infrastructure such as cloud services and satellites.
The European attempts to break these US monopolies and compete in digital services continue to be significant sources of friction in transatlantic relations, resulting in US threats of trade restrictions as a response to the enforcement of EU digital regulations.
The EU. therefore, prioritise reducing its reliance on US digital infrastructure and finding the most effective responses to US threats. As with critical raw materials dependencies, reducing dependencies linked to US digital or financial dominance requires a medium- to long-term strategy and a combination of different EU tools.
As to the EU’s digital dependency: in order to strengthen the digital resilience in the financial sector, the EU adopted the Digital Operational Resilience Act, DORA (it entered into force in January 2025) to ensure that banks, insurance companies, investment firms and other financial entities can withstand and recover from the ICTs disruptions, such as cyberattacks and/or system failures.
More in: https://www.integrin.dk/2024/05/23/digital-operational-resilience-act-dora-strengthening-european-financial-security/
European strategy in the digital economy
Since the EU’s first European economic security strategy in 2023, modern internal and external risks appeared to force the governing institutions in re-assessing (or, in moder EU-jargon, “re-calibrate”) the EU-wide political economy directions and general strategies. Initially the EU could rely on close cooperation with the US, the approach that was part of a coordinated transatlantic response to de-risk China’s economic dependence in several manufacturing sectors, particularly in the processing of critical raw materials,
The current geopolitical context implies that the EU needs another type of relationships with China and the US, while facing -at the same time- “major hard-security threat from other directions”. This contemporary challenge forces the EU leaders to develop broad alliances with countries that wish to maintain a rule-based cooperation. Theoretically, the practice of coercion is to pursue one side to actions through using force and/or threats; however, most EU issues/problems cannot be solved by any form of coercion – only by cooperation and agreements. Hence, the EU has to “distance” from Russian fossil-fuels’ resources, and reduce dependencies on China and the US “while maintaining a maximum of mutually beneficial economic engagement”. The extensive nature of dependencies implies the need for medium-term de-risking strategies, combined cooperation; at the same time, the EU must also be ready to respond to threats of coercion.
Presently, the main aspects of modern EU member states’ “resilient economic security measures” are preventive and long-term: i.e. they are both aimed at limiting risk of geopolitical tensions and safeguarding economic interests. In most instances economic security, essentially, is not about responding to security threats; generally, it is about forming institutional mechanisms in economics that would allow for the evaluation of trade-offs.
For example, trade-restrictive economic security measures need to be balanced against the economic benefits dealing with other essential EU objectives and political priorities, such as the green transition, reinforcement of the single market, support for research and innovation, as well as external free-trade agreements with developing countries. The EU “must combine a medium-term strategy to reduce dependencies on both China and the US in critical areas with the capacity to react in the short term to threats of coercion”; the approach requires the supply chain re-assessments, as identified by Commission research group.
More in the joint communication on “Strengthening EU economic security” (December 2025) in:
https://circabc.europa.eu/ui/group/7fc51410-46a1-4871-8979-20cce8df0896/library/777b1ecb-e7ce-4774-a92c-53f81e64ce76/details?open=true
Besides, the US strategy approaches the EU as “a second-order consideration”; i.e. attitudes on other global regions -mainly in the Indo-Pacific part- precede that of the Western Hemisphere. Hence, the strategy “establishes freedom of navigation and regional stability as priorities in the Indo-Pacific, positioning China as a competitor while underscoring the importance of avoiding direct conflict with a nuclear power that is a military behemoth”. Therefore, the Indo-Pacific “will continue to be among the next century’s key economic and geopolitical battlegrounds”; and the “geo-economic might of the Indo-Pacific makes it a place of infinite opportunity” for the modern US administration.
Source and citation from: https://www.foreignaffairs.com/trumps-power-paradox
Global digital competition
AI companies in China allegedly routed traffic through proxy addresses that managed a vast “hydra network,” a large group of fake accounts that spread their activity across platforms to get access to Anthropic, since it is banned in China.
Chinese AI companies are accused of stealing most valuable digital technologies from leading US companies: thus, DeepSeek, Moonshot AI and MiniMax secretly generated over 16 million conversations with Anthropic’s AI chatbot Claude, using more than 24,000 fake accounts, to harvest its intelligence and train their own competing models. OpenAI and Google have also warned about similar accusations at Chinese firms this month, raising fears that China is short-circuiting years of costly AI research.
Model extraction attacks (MEA), otherwise known as “distillation”, represent a digital-technique in which someone with access to a powerful AI model uses it to train a cheaper and faster rival.
The method feeds the larger model thousands of questions, collects its answers and uses those responses to teach a new model “to think in the same way”. The user can ask the larger model questions and use its responses to train the smaller model, which develops the smaller AI faster and “at a fraction of the cost,” than if the threat actor had done the original work themselves, Anthropic alleges.
This US company “theorizing” that those questions trained DeepSeek’s models “to steer conversations away from censored topics,” which could support a recent study that found Chinese AI models likely censor the same topics as their media. MiniMax AI and Moonshoot AI had larger distillation campaigns than DeepSeek, but Anthropic did not offer examples for the types of information that these two companies collected in their prompts.
Reference to: the Euro News. “The AI Cold War? US tech companies accuse China’s AI firms of stealing billions in research. 26.02.2026. In: https://www.euronews.com/next/2026/02/26/
China’s AI companies allegedly routed traffic through proxy addresses that managed a vast “hydra network,” a large group of fake accounts that spread their activity across platforms to get access to Anthropic, since it is banned in China. Once the companies were in, they generated large volumes of prompts either to collect high-quality responses for model training or to generate tens of thousands of tasks for reinforcement learning, how an agent learns to make decisions from feedback.
The DeepSeek accounts that hacked Claude asked the model to articulate how it rationalised an answer to a prompt and write it out step by step, which the company said was “generated chain-of-thought training data at scale”.
Claude was also used by the DeepSeek accounts to “generate censorship-safe alternatives to politically sensitive queries,” such as questions about opponents to the current China’s Communist Party, as the Anthropic alleged recently.
More in: https://www.anthropic.com/news/claude-opus-4-8