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AI network management systems deployed for BTS concert in Seoul

South Korea’s three major telecommunications operators plan to deploy advanced network technologies during the BTS comeback concert scheduled for 21 March at Gwanghwamun Square in central Seoul. The initiative aims to bolster network management, prevent congestion, and ensure stable connectivity as large crowds gather in a confined space.

SK Telecom said it will introduce its proprietary AI-powered network management system, A-One, at the event. The technology can recommend optimal equipment placement, predict traffic demand, and monitor real-time network performance to maintain service stability.

To manage heavy data usage during the concert, the company will operate multiple network systems across the venue’s different zones. The setup is designed to allow attendees inside the square to upload photos and videos quickly while enabling viewers outside the venue to stream the concert without interruptions. Additional equipment will also be installed in areas expected to attract international visitors.

KT will deploy its AI-based autonomous traffic management system, W-SDN, which monitors network usage in real time and automatically adjusts traffic flows if congestion is detected. The company will activate an emergency network control mode during the event and deploy about 80 engineers and portable base stations on site.

LG Uplus will also apply its autonomous network management technology, which predicts traffic changes and distributes network loads across nearby base stations. The South Korea-based operator said the system will help ensure uninterrupted connectivity for concertgoers throughout the event.

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AI and robotics could offset impact of aging populations in Asia

Declining fertility rates have long been considered a major risk to economic growth, but analysts suggest the outlook may not be entirely negative for several advanced Asian economies. Rising investment in AI and robotics is increasingly viewed as a way to offset labour shortages caused by ageing populations.

According to analysts at Bank of America Global Research, technological innovation driven by AI and robotics could support productivity growth even as workforces shrink. Strong ecosystems in semiconductors, technology hardware, and industrial machinery allow some countries in the region to deploy advanced technologies faster and at lower cost than many other parts of the world.

South Korea currently has the highest robot density in the world, with about 1,012 industrial robots per 10,000 manufacturing workers. Chi n a has 470 and Japan 419, both significantly above the global average of 162, according to 2024 figures from the International Federation of Robotics.

Analysts say governments across East Asia are accelerating the adoption of AI and robotics to address demographic pressures. In particular, China, South Korea, and Japan have expanded investments in robotics, AI systems, and advanced manufacturing technologies to maintain economic productivity.

Population projections highlight the scale of the challenge facing these economies. By 2050, about 37 percent of Japan’s population and nearly 40 percent of South Korea’s population are expected to be aged 65 or older, while China’s share could reach around 31 percent.

Despite concerns about slowing growth, economists argue that advances in AI and robotics could weaken the traditional link between economic output and workforce size. Automation technologies not only replace routine tasks but also enhance human productivity in many industries.

A study by the Bank of Korea estimated that demographic pressures could reduce the country’s gross domestic product by 16.5 percent between 2023 and 2050. However, wider adoption of AI and robotics could limit the decline to around 5.9 percent under favourable conditions.

Some analysts caution that the economic benefits of automation may not be evenly distributed. While AI and robotics can improve productivity, technological gains often benefit capital owners and highly skilled workers more than others.

Economists also warn that consumption may slow as the number of households declines, while governments may face greater fiscal pressure from higher pension and healthcare costs. Policymakers may need to invest in workforce retraining and education to help workers adapt to the growing role of AI and robotics in the economy.

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Study warns AI chatbots may reinforce delusional thinking

A new scientific review has raised concerns that AI chatbots could reinforce delusional thinking, particularly among people already vulnerable to psychosis. The review, published in The Lancet Psychiatry, summarises emerging evidence suggesting that chatbot interactions may validate or amplify delusional thinking in certain users.

The study examined reports and research discussing what some have described as ‘AI-associated delusions’. Dr Hamilton Morrin, a psychiatrist and researcher at King’s College London, analysed media reports and existing evidence exploring how chatbot responses might interact with psychotic symptoms.

Psychotic delusions generally fall into three categories: grandiose, romantic, and paranoid. Researchers say chatbots may unintentionally reinforce such beliefs because they often respond in ways that are supportive or affirming. In some reported cases, users received responses suggesting spiritual significance or implying that a higher entity was communicating through the chatbot.

Researchers emphasise that there is currently no clear evidence that AI systems can independently cause psychosis in individuals without prior vulnerability. However, interactions with chatbots could strengthen existing beliefs or accelerate the progression of delusional thinking in people already at risk.

Experts say the interactive nature of chatbots may intensify the effect. Unlike static sources of information such as videos or articles, chatbots can engage users directly and repeatedly, potentially reinforcing problematic beliefs more quickly.

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Google Earth AI supports disease forecasting and public health planning

Researchers are increasingly combining geospatial data with predictive modelling to anticipate health risks.

In that context, Google has introduced new capabilities within Google Earth AI designed to help public health experts forecast outbreaks and identify vulnerable communities.

The system integrates environmental information such as weather patterns, flooding and air quality with population mobility data and health records.

These insights allow researchers to analyse how environmental conditions influence the spread of diseases, including Dengue Fever and Cholera.

Several research initiatives are already testing the models. In collaboration with the World Health Organisation Regional Office for Africa, forecasting tools combining Google’s time-series models with geospatial data improved cholera prediction accuracy by more than 35 percent.

Academic researchers are also applying the technology to other diseases. Scientists at the University of Oxford have used Earth AI datasets to improve six-month dengue forecasts in Brazil, helping local authorities prepare preventative responses.

The technology is also being tested for chronic disease analysis. In Australia, partnerships with health organisations are exploring how geospatial models can identify regional health needs and support preventative care strategies.

Combining environmental intelligence with health data could enable public health systems to shift from reactive crisis management to earlier detection and prevention of disease outbreaks.

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China prioritises AI and tech self-reliance in new five-year plan

A new five-year development plan approved by lawmakers in Beijing places innovation and advanced technology at the centre of future economic growth. The strategy is designed to strengthen technological capabilities and position China as a leading global tech power.

The plan outlines ambitions to upgrade China’s industrial sector, expand domestic research capacity, and reduce reliance on foreign technologies. Priority sectors include AI, robotics, aerospace, biotechnology, and quantum computing. Officials see these industries as key drivers of economic growth over the coming decades.

AI features prominently in the strategy, with the term appearing dozens of times in the policy document. Beijing plans to expand AI-related industries, invest in large computing clusters, and support the development of advanced systems capable of performing complex tasks beyond traditional chatbots.

China also aims to increase spending on science and technology, with government research budgets rising by around 10 percent annually. The plan sets a target of expanding research and development investment by at least 7 percent per year, reflecting Beijing’s intention to strengthen domestic innovation capacity.

Efforts to achieve greater technological self-sufficiency come amid continued tensions with the United States over trade and technology restrictions. Export controls on advanced semiconductor technologies have highlighted China’s dependence on foreign chips, prompting the government to pursue breakthroughs across the semiconductor supply chain and emerging technologies.

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EU reviews X compliance proposal under Digital Services Act

X has submitted a compliance proposal to the European Commission outlining how it intends to modify its blue check verification system following regulatory concerns under the Digital Services Act.

The EU regulators concluded that the platform’s system allowed users to obtain verification simply by paying for a subscription without meaningful identity checks, potentially misleading users about the authenticity of accounts.

The Commission imposed a €120 million fine in December and gave the company 60 working days to propose corrective measures. Officials confirmed that X met the deadline for submitting a plan, which regulators will now assess.

The platform, owned by Elon Musk, must also pay the penalty while the Commission evaluates the proposed changes. The company has challenged the enforcement decision before the EU’s General Court.

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France pushes EU AI gigafactories to support European technology

In the EU, France is calling for planned European AI ‘gigafactories’ to focus on testing and scaling European technologies rather than primarily increasing demand for hardware from companies such as Nvidia.

The large computing facilities are intended to provide the infrastructure needed to train advanced AI systems. However, officials in France argue that the projects should strengthen Europe’s technological capabilities rather than reinforce reliance on foreign suppliers.

Several EU countries, including Poland, Austria and Lithuania, support using the infrastructure to improve Europe’s digital resilience.

The initiative forms part of the European Commission’s wider plans to expand computing capacity and support the development of a stronger European AI ecosystem.

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AI tools encourage exploration in creative tasks

AI is often associated with automation and job replacement, yet new research from Swansea University suggests a different role. Findings indicate that AI can serve as a creative collaborator, encouraging exploration and deeper engagement during design tasks.

Researchers from the university’s Computer Science Department ran an experiment with over 800 participants using an AI-supported system to design virtual cars.

Rather than optimising results, the system generated galleries with varied design ideas, including effective, unusual, and intentionally flawed concepts.

According to lead researcher Sean Walton, exposure to AI-generated suggestions increased participants’ involvement. Many users spent longer working on the task and produced stronger designs after interacting with the system’s diverse proposals.

The study in ACM Transactions on Interactive Intelligent Systems argues that traditional methods for evaluating AI tools are too narrow. Researchers believe broader assessments are needed to measure how AI affects human thinking, emotions, and creative exploration.

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AI technology set to reshape farming and rural life in South Korea

South Korea has launched a national agenda to expand AI across agriculture, aiming to boost productivity and improve living standards in rural communities. Officials from the Ministry of Agriculture, Food and Rural Affairs and the Ministry of Science and ICT presented the strategy as part of a wider digital transformation effort.

Plans include expanding smart farm models that reduce labour-intensive tasks and allow more farmers to benefit from automated technologies. Shared machinery centres and autonomous farming tools such as drones will be developed with support from the Rural Development Administration.

Authorities also intend to apply AI to agricultural distribution through smart logistics facilities that manage receiving, sorting and shipping processes. Around 300 smart Agricultural Products Processing Centres are expected to operate nationwide by 2030.

Livestock grading systems using AI will be introduced to improve accuracy and consumer trust across pork and beef processing facilities. Officials aim to raise the share of AI-graded meat from 19.4 percent in 2025 to 70 percent by 2030.

Beyond production, the programme seeks to expand ‘smart rural communities’ offering AI-based services such as transport, daily living support and farming assistance. Policymakers believe that a stronger digital infrastructure will help rural regions respond to climate pressures and an ageing population.

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Deepfake attacks push organisations to rethink cybersecurity strategies

Organisations are strengthening their cybersecurity strategies as deepfake attacks become more convincing and easier to produce using generative AI.

Security experts alert that enterprises must move beyond basic detection tools and adopt layered security strategies to defend against the growing threat of deepfake attacks targeting communications and digital identity.

Many existing tools for identifying manipulated media are still imperfect. Digital forensics expert Hany Farid estimates that some systems used to detect deepfake attacks are only about 80 percent effective and often fail to explain how they determine whether an image, video, or audio recording is authentic. The lack of explainability also raises challenges for legal investigations and public verification of suspicious media.

Cybersecurity companies are creating new technologies to improve the detection of deepfake attacks by analysing slight signals that are difficult for humans to notice. Firms such as GetReal Security, Reality Defender, Deep Media, and Sensity AI examine lighting consistency, shadow angles, voice patterns, and facial movements. Environmental indicators such as device location, metadata, and IP information can also help security teams spot potential deepfake attacks.

However, experts say detection alone cannot fully protect organisations from deepfake attacks. Companies are increasingly conducting internal red-team exercises that simulate impersonation scenarios to expose weaknesses in verification procedures. Multi-factor authentication techniques can reduce the risk of employees responding to fraudulent communications.

Another emerging defence involves digital provenance systems designed to track the origin and modification history of digital content. Initiatives such as the Coalition for Content Provenance and Authenticity (C2PA) embed cryptographically signed metadata into media files, allowing organisations to verify whether content linked to suspected deepfake attacks has been altered.

Recent experiments highlight how testing these threats can be. In February, cybersecurity company Reality Defender conducted an exercise with NATO by introducing deepfake media into a simulated military scenario. The findings showed how easily even experienced officials can struggle to identify manipulated communications, reinforcing calls for automated systems capable to detecting deepfake attacks across critical infrastructure.

As generative AI tools continue to advance, organisations are expected to combine detection technologies, stronger verification procedures, and provenance tracking to reduce the risks posed by deepfake attacks.

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