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EU’s Data Union Strategy Seeks to Boost AI and Cross-Border Data Use, but GDPR Stays Untouched

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As the European Commission’s consultation on the European Data Union Strategy (EDUS) nears its July 18 deadline, the initiative has drawn a mix of support and criticism. Aimed at stimulating data-driven innovation—particularly for generative AI—the strategy promises to simplify the EU’s complex data governance landscape. But its deliberate omission of any review of the General Data Protection Regulation (GDPR) has raised eyebrows.

The EDUS is positioned as a framework to streamline and harmonize existing EU data laws, including the Open Data Directive, the Data Act, and the Data Governance Act. Its goals include promoting broader access to data, incentivizing voluntary data sharing, reducing administrative burdens, and strengthening international data flows.

However, experts argue that the strategy avoids addressing some of the key barriers currently hampering the European data economy—chief among them, the GDPR. The strategy makes only vague references to maintaining “privacy and security standards,” without directly naming the GDPR. Despite its role as a cornerstone of EU data policy, GDPR remains politically sensitive and, according to Commission officials, too controversial to revisit.

This approach has sparked concerns, especially as many EU member states interpret GDPR’s definition of “personal data” narrowly, creating legal and practical barriers to initiatives that rely on open or shared data. The lack of meaningful exemptions under Article 6(f), which allows for processing of personal data in the public interest, continues to constrain innovation, particularly in sectors like AI and public services.

Beyond the GDPR issue, stakeholders have also highlighted several unresolved structural problems:

  1. Unfair B2B Data Sharing
    While the Data Act is designed to ensure fair access to data for smaller companies, in practice, large corporations continue to dominate through restrictive and often exploitative contracts. Legal dispute mechanisms exist but are rarely used by startups wary of prolonged battles with industry giants.

  2. Lack of Compensation for Public Institutions
    State-owned entities that manage valuable datasets face financial disincentives when required to open data for free. Without clear government compensation—such as Latvia’s model of reimbursing public registries—many institutions have little motivation to provide high-value data.

  3. Gap in Business Feedback on Data Infrastructure
    While the EU measures progress through tools like the Open Data Maturity Index, there is limited insight into how businesses experience the system. Missing are evaluations on usability, dataset relevance, and responsiveness of public authorities—factors critical to real-world data utility.

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As the EU pushes forward with its Data Union Strategy, experts warn that meaningful transformation will require more than legislation—it demands addressing the entrenched structural issues and political sensitivities that continue to limit the full potential of Europe’s digital economy.

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Study Finds AI Use May Weaken Basic Problem-Solving Skills

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Meta Launches Muse Spark, Its First Major AI Model in Nine Months

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Meta has unveiled its first major AI model in nine months, following a $14.3 billion (€12.24 billion) investment spree and executive hiring push to rival OpenAI and Google. The American tech company introduced the model, called Muse Spark, on Wednesday, claiming it is faster and smarter than its previous technologies.

The company, founded by Mark Zuckerberg, invested $14.3 billion in Scale AI in June 2025 and recruited its CEO and co-founder, Alexandr Wang, to oversee Meta Superintelligence Labs, which houses teams working on foundational AI models. Zuckerberg also embarked on a hiring campaign, bringing in executives from competitors including OpenAI, Anthropic, and Google.

In a blog post, Meta said, “Over the last nine months, Meta Superintelligence Labs rebuilt our AI stack from the ground up, moving faster than any development cycle we have run before. This initial model is small and fast by design, yet capable enough to reason through complex questions in science, math, and health. It is a powerful foundation, and the next generation is already in development.”

Muse Spark is positioned as a significant upgrade over Meta’s last major release, Llama 4, launched in April 2025. The company highlighted that the model excels in advanced reasoning, particularly in scientific, mathematical, and medical queries. To improve its health advice capabilities, Meta worked with over 1,000 physicians to curate training data, aiming for more accurate and comprehensive responses.

The AI model will power the company’s digital assistant in the Meta AI app and website, with planned integration across Facebook, Instagram, WhatsApp, Messenger, and the Ray-Ban Meta AI glasses. A “contemplating mode” will gradually roll out, allowing multiple AI agents to reason in parallel on complex tasks. Meta’s technical blog noted this feature is designed to compete with high-level reasoning in models such as Gemini Deep Think and GPT Pro.

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Zuckerberg emphasized on social media that Meta aims to build AI products that “don’t just answer your questions but act as agents that do things for you.” Unlike conventional chatbots, these AI agents operate autonomously, gathering information based on user preferences to assist without direct human commands.

One notable shift for Meta is the move away from open-source AI models. Unlike earlier releases, Muse Spark is not available for public download, meaning access to the technology is currently restricted. The company said the model is initially available only in the United States.

Muse Spark underscores Meta’s aggressive push into the competitive AI market, combining extensive investment, executive recruitment, and technical innovation to challenge the dominance of established players like OpenAI and Google.

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OpenAI Urges Governments to Rethink Economy as AI Growth Accelerates

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OpenAI has called on governments to rethink the foundations of the economy, warning that artificial intelligence (AI) could soon surpass human intelligence and drastically change how people work, live, and pay taxes. The company outlined its initial policy ideas on Monday, aimed at mitigating the economic disruption caused by rapid AI adoption in the United States and worldwide.

One key proposal is the creation of a public wealth fund that would give citizens a direct stake in AI-driven economic growth. According to the policy document, the fund could invest in diversified, long-term assets, including AI companies and broader firms adopting AI technologies, with returns distributed to all citizens.

The company also suggested that governments encourage businesses to launch four-day workweek pilot programs without any reduction in pay. This approach aims to balance the productivity gains provided by AI with the well-being of workers. Lawmakers are also urged to modernize tax systems by increasing taxation on corporate income and capital gains instead of labor income, which could be affected by AI-related job losses. The report proposes additional measures, such as taxing companies that replace human labor with automation.

OpenAI recommends that social benefits, including retirement pensions and healthcare, be provided through portable accounts that follow individuals across different jobs, industries, and entrepreneurial ventures. This model would help ensure continuity of support in a labor market increasingly influenced by AI.

These recommendations echo broader discussions among AI leaders about the future of work. OpenAI CEO Sam Altman and xAI’s Elon Musk have previously highlighted universal basic income as a potential necessity as traditional employment declines. Other tech leaders, including Nvidia’s Jensen Huang and Zoom’s Eric Yuan, have advocated shorter workweeks to distribute productivity gains from AI more evenly.

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Concerns about AI’s long-term impact extend beyond economics. In January, Anthropic CEO Dario Amodei warned that superintelligent AI, capable of outpacing human decision-making, poses “existential danger.” He suggested tighter controls on the export of key technologies, such as semiconductor chips used to train large language models, as one way to manage the risk. Amodei also called for transparency laws requiring AI companies to disclose how they guide their models’ behavior.

OpenAI’s policy document represents an early step in urging governments to address the structural changes AI may bring. The proposals highlight the need to rethink traditional concepts of work, taxation, and social support as the technology continues to advance rapidly.

As AI continues to reshape global economies, policymakers and industry leaders face increasing pressure to develop strategies that protect citizens while fostering innovation and sustainable growth.

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