Discussions between Europe and the United States over digital regulation continue to be marked by miscommunication and frustration, even as competitors observe from the sidelines. Europeans and Americans talk past each other while rivals watch. The European Union can set its own standards, but in an interconnected economy, decoupling fantasies and grandstanding won’t help.

The debate often centres on “free speech” concerns voiced by U.S. tech companies and policymakers in response to the EU’s legislative framework for digital platforms. In Europe, such narratives typically prompt defensive reactions. Some Europeans respond with a blunt message: “This is our land, our Union, our laws, follow them, or leave the EU—we’ll find alternative products to use!” Public awareness of American constitutional amendments is low across Europe, just as Americans pay little attention to European digital acts and regulations.

The transatlantic dialogue is further complicated by the global nature of social media platforms. Any EU legislation affecting user experience inevitably influences the functioning of these platforms worldwide, touching on what Americans see as free speech rights. The EU also seeks to extend its influence through the “Brussels effect,” ensuring that European rules shape global standards, while the U.S. maintains a large trade surplus in services and competes technologically with China. This mix of economic, political, and regulatory factors explains why U.S. attention is sharply focused on Europe’s digital policies.

Europeans argue that their 450-million-consumer market has the right to set rules that reflect local principles and values. Attempts to adjust or simplify regulations are difficult, with efforts often met with political resistance and scrutiny. The regulatory ecosystem in Europe supports industries of lawyers, consultants, and experts whose work depends on maintaining complex rules, making reform a sensitive topic.

On the American side, anti-EU rhetoric by public figures has sometimes compounded the problem, drowning out moderates and reinforcing defensive European responses. Analysts note that both regions have seen productive voices sidelined as grandstanding and negative statements dominate public discourse.

Observers argue that long-term thinking is necessary. By evaluating the EU-U.S. tech partnership in the broader context of global alliances, including China and Russia, policymakers can better assess priorities and avoid unnecessary disruption. Blank-slate decoupling between Europe and the United States is unrealistic, and delaying constructive dialogue risks broader economic consequences.

Experts warn that continued transatlantic infighting benefits other global powers and weakens the ability of both regions to set coherent standards in emerging technologies. The message from analysts is clear: cooperation, not confrontation, will determine whether the EU and U.S. can maintain leadership in digital regulation while safeguarding economic and technological interests.

Researchers in Spain have developed an AI system that allows robots to recover their position even after being moved, powered off, or displaced, offering a solution to the long-standing “kidnapped robot” problem. The system, designed at Miguel Hernández University of Elche, could enable autonomous machines to navigate safely in environments that change over time.

Autonomous robots, used in service operations, logistics, infrastructure inspection, environmental monitoring, and self-driving vehicles, often rely on satellite navigation systems such as GPS. These signals can be unreliable near tall buildings or completely unavailable indoors, making precise localisation a persistent challenge.

The new approach, called MCL-DLF (Monte Carlo Localisation – Deep Local Feature), uses 3D LiDAR technology to scan surroundings with laser pulses, creating a detailed map-like representation of the environment. By analysing both large structures and small distinguishing details, the system helps robots determine their exact location.

“This is similar to how people first recognise a general area and then rely on small distinguishing details to determine their precise location,” said Míriam Máximo, lead author of the study and a researcher at Miguel Hernández University of Elche.

MCL-DLF uses AI to identify which environmental features are most useful for localisation. The system maintains multiple possible location estimates simultaneously and continuously updates them as new sensor data becomes available. This allows robots to maintain reliable positioning even when environments look similar or have changed, such as when vegetation shifts or lighting conditions vary.

The research team tested the system over several months on the university campus under diverse conditions, including different seasons, lighting, and natural changes in vegetation. Results showed that MCL-DLF provided stronger positioning accuracy and more consistent performance compared with conventional localisation methods.

By enabling robots to navigate without constant reliance on external infrastructure, the system could increase operational independence in real-world environments, where conditions rarely remain static. Reliable localisation is particularly important for tasks where safety and precision are critical, such as autonomous deliveries, environmental monitoring, and industrial inspections.

The development of MCL-DLF represents a significant advance in robotics, providing a practical solution to the kidnapped robot problem. Researchers say the technology could help service and industrial robots operate more effectively in complex, dynamic settings, paving the way for wider adoption of autonomous systems in both indoor and outdoor environments.

With AI-driven localisation, robots may soon be able to recover from displacements quickly and continue tasks without human intervention, making them more resilient and adaptable in everyday operations.

A new report by German non-profit Beyond Fossil Fuels has raised concerns about the strength of evidence supporting claims that artificial intelligence can significantly reduce global carbon emissions.

The group reviewed more than 150 climate-related statements made by leading AI companies and organisations, including the International Energy Agency. It found that only 26 per cent of the claims cited published academic research, while 36 per cent did not reference any evidence at all. The remaining claims relied on corporate reports, media coverage, NGO publications or unpublished academic work.

According to the report, many corporate sources lack peer-reviewed data or primary research to substantiate their projections. “The evidence for massive climate benefits of AI is weak, whilst the evidence of substantial harm is strong,” the authors wrote.

Estimates of AI’s environmental footprint vary widely. A January study published in the journal Patterns suggested that data centres alone may have emitted between 32.6 million and 79.7 million tonnes of carbon dioxide in 2025, roughly comparable to the annual emissions of a small European country.

By contrast, the International Energy Agency has argued that AI could cut global emissions by up to 5 per cent by 2035 by accelerating innovation in the energy sector. The agency has pointed to applications such as testing new battery chemistries and materials for solar power as examples of how AI might support cleaner technologies.

Beyond Fossil Fuels examined high-profile industry claims, including a projection cited by Google that AI could reduce global greenhouse gas emissions by 5 to 10 per cent by 2030 if widely adopted. The report traced the estimate back to a 2021 blog post by consulting firm Boston Consulting Group, which based the figure on client experience rather than peer-reviewed global analysis. Researchers described the claim as an extrapolation built on limited evidence.

The report also reviewed assertions that smaller, narrowly trained AI models are more environmentally efficient. It concluded that there is insufficient peer-reviewed research demonstrating that such systems can deliver measurable emissions reductions at scale.

In addition, the analysis said it found no verified example of generative AI systems such as OpenAI’s ChatGPT, Google’s Gemini or Microsoft’s Copilot producing substantial, measurable emissions cuts. Even if certain efficiencies exist, the report argues that they may be outweighed by the rapid expansion in energy use linked to data centre growth.

The authors said their findings do not suggest AI lacks climate benefits altogether, but they contend there is limited evidence that current applications can offset the sector’s growing energy demands. Requests for comment were sent to major AI firms and the International Energy Agency.