Tech
AI Tools Boost Paper Production but Raise Quality Concerns in Scientific Research
Large language models such as ChatGPT are increasing research output, particularly for scientists who are not native English speakers, but a new study warns that many AI-assisted papers are less likely to pass peer review.
Researchers at Cornell University, United States, analysed more than two million research papers posted between 2018 and 2024 on three major preprint servers, which host early versions of scientific work prior to formal review. Their findings, published in the journal Science, show that AI tools are reshaping how scientific papers are written and disseminated.
To identify AI-assisted papers, the team trained an AI system to detect text likely generated by large language models. Comparing papers posted before 2023 with those written after tools like ChatGPT became widely available, the researchers measured publication output and subsequent acceptance rates in scientific journals.
The analysis revealed a significant productivity boost for AI users. On a major preprint server for physics and computer science, researchers using AI produced about one-third more papers than those who did not. In biology and the social sciences, the increase exceeded 50 percent. The largest gains were seen among scientists whose first language is not English. In some Asian institutions, researchers published between 40 percent and nearly 90 percent more papers after adopting AI writing tools, depending on the discipline.
AI tools also appear to aid in literature review. Researchers using AI were more likely to identify newer studies and relevant books rather than relying on older, frequently cited works. “People using LLMs are connecting to more diverse knowledge, which might be driving more creative ideas,” said Keigo Kusumegi, a doctoral student and first author of the study.
Despite the productivity gains, the study highlights quality concerns. Many AI-written papers, while linguistically polished, were less likely to be accepted by journals. Papers written by humans that scored high on writing complexity were more likely to be accepted, whereas AI-generated papers with similar scores often failed to meet scientific standards.
“Already now, the question is not, ‘Have you used AI?’ The question is, ‘How exactly have you used AI and whether it’s helpful or not,’” said Yian Yin, assistant professor at Cornell and corresponding author of the study. Yin added that the widespread adoption of AI tools across disciplines—including physical sciences, computer science, biology, and social sciences—requires careful consideration by reviewers, funders, and policymakers.
The researchers stress that AI-assisted tools are reshaping the academic ecosystem, offering opportunities to improve productivity and access to scientific knowledge, but they also call for guidelines to ensure that the technology is used responsibly and that scientific contributions maintain their integrity.
As AI becomes increasingly integrated into research practices, the challenge for the scientific community will be balancing efficiency and innovation with rigorous evaluation standards to maintain the quality and credibility of published science.
Tech
Mobile World Congress Opens in Barcelona With Focus on AI and 5G Concerns
Tech
Transatlantic Tensions on Digital Rules Highlight Need for Cooperation
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.
Tech
New AI System Helps “Kidnapped” Robots Find Their Way in Changing Environments
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.
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