Interdisciplinary approaches Archives | Page 14 of 191

ECA Digital law raises pressure on Big Tech in Brazil

Brazil is set to enforce a new law aimed at strengthening protections for children online, marking a significant shift in how digital platforms are regulated in the country. The legislation, known as ECA Digital, introduces stricter rules for technology companies and will test whether stronger oversight can translate into real-world impact.

The law, which takes effect this week, allows authorities to impose warnings and fines of up to $10 million for violations. In severe cases, courts may order the suspension or banning of platforms operating in B razil. The measure was passed rapidly following public outrage over online content involving the sexualisation of minors.

ECA Digital builds on Brazil’s existing child protection framework and adapts it to the digital environment. It introduces obligations such as age verification, stricter content moderation, and mechanisms to remove harmful material involving minors without requiring a court order.

The law also targets platform design, requiring companies to limit features that may encourage compulsive use among children. This includes restrictions on excessive notifications, profiling for targeted advertising, and design elements that prolong user engagement.

Enforcement of ECA Digital will be led by Brazil’s data protection authority, ANPD, alongside a new screening centre within the Federal Police. However, implementation challenges remain, including limited regulatory capacity and the short timeline between the law’s approval and enforcement.

Experts say the law reflects a broader global trend, with dozens of countries considering similar measures. While technology companies have introduced tools such as age verification and parental controls, critics argue that bigger changes to platform design and content moderation are still needed.

Brazil’s experience may serve as a test case for how governments balance child protection, platform responsibility, and enforcement capacity. The effectiveness of ECA Digital will depend not only on its legal framework but also on how rigorously it is applied in practice.

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Google launches AI skills initiative to support Europe’s workforce transition

At the Future of Work Forum, Google introduced ‘AI Works for Europe’, a programme aimed at strengthening digital skills and supporting workforce adaptation to AI across the region.

Funding of $30 million will be directed through Google.org to expand training opportunities, alongside broader access to AI certification programmes designed to help individuals and businesses adopt new technologies in practical contexts.

A central focus involves preparing workers and students for labour market changes.

Partnerships with organisations such as INCO are supporting the development of targeted training programmes, particularly in sectors where demand for AI-related skills is increasing, including finance, logistics and marketing.

New educational pathways are also being introduced, including an expanded AI Professional Certificate available in multiple European languages. These initiatives aim to improve AI literacy and provide hands-on experience aligned with employer expectations.

Collaboration with local organisations and institutions remains a key element, reflecting a broader strategy to ensure access to training across different regions and communities.

Efforts to expand AI capabilities across Europe highlight the growing importance of skills development as AI becomes more integrated into economic activity.

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AI-powered MRI previews aim to reduce errors and rescans

Philips is creating AI-driven predictive MRI previews to improve scan planning and reduce operator variability. Using NVIDIA accelerated computing and foundation models, the system creates a pre-scan image to validate protocols, optimise positioning, and spot potential issues.

The technology is based on a dedicated MR foundation model trained on diverse datasets covering anatomies, field strengths, protocols, and artefacts.

When combined with NVIDIA’s NV‑Generate, NV‑Segment, and NV‑Reason models, the platform integrates image generation, segmentation, and interpretation. It creates a single intelligent workflow that supports consistent and efficient MRI procedures.

Predictive previews reduce rescans, enhance image quality, and increase technologist confidence, especially in complex exams or areas with limited expertise. Early guidance helps confirm protocols, optimise positioning, and flag issues that could affect diagnostic outcomes.

Philips envisions autonomous MRI, with AI monitoring image quality, guiding positioning, and assisting radiologists with actionable insights. Predictive imaging boosts consistency, efficiency, and access, improving patient experience and expanding MRI availability.

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NVIDIA expands physical AI ecosystem to accelerate real world robotics

Partnerships across the robotics sector are positioning NVIDIA at the centre of what is increasingly described as ‘physical AI’, a shift towards intelligent machines capable of perceiving, reasoning and acting in real environments.

A new generation of tools, including NVIDIA Cosmos world models and updated NVIDIA Isaac simulation frameworks, aims to support developers in training and validating robots before deployment.

These systems enable companies to simulate complex environments, reducing the risks and costs of real-world testing.

Industrial robotics leaders such as ABB Robotics, KUKA, and FANUC are integrating NVIDIA technologies into digital twin environments, enabling more accurate modelling of production lines and automation systems.

Advances are also extending into humanoid robotics, where companies are using AI models to develop machines capable of more flexible and adaptive behaviour.

New foundation models, including GR00T systems, are designed to give robots general-purpose capabilities instead of limiting them to specific tasks.

Healthcare and logistics represent additional areas of deployment, with robotics platforms being tested in surgical systems, warehouse automation and manufacturing environments. These applications highlight how physical AI could reshape industries requiring precision, safety and scalability.

Growing collaboration across cloud providers, manufacturers and AI developers suggests that robotics is moving toward a more integrated ecosystem, where simulation, data generation and deployment are increasingly interconnected.

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Why human remain the real advantage in the AI era?

AI is quickly becoming part of everyday business operations. Companies are already using it to analyse data, optimise campaigns and manage complex digital systems. Greater automation, however, is also revealing a simple reality: the human side of leadership is becoming even more important.

A I performs well when speed and scale are needed. Systems can process huge volumes of information and detect patterns far faster than people. Planning in many industries is already shifting from broad demographics toward signals based on behaviour and intent.

Operational complexity is another area where AI is proving useful. Modern digital ecosystems involve multiple platforms and formats, from programmatic advertising to retail media and connected television. Automation can handle forecasting, pacing and reporting, freeing teams to focus on strategy and interpretation.

Personalised communication is also becoming easier to achieve. AI tools can generate tailored messages for diverse audiences, adapting content based on context and behaviour. Human oversight still matters, especially in markets where culture, language and economic realities vary widely.

Growing reliance on AI also brings risks that leaders must address openly. Trust is one of the biggest concerns. Technologies capable of producing convincing text, images and video can also create misinformation at scale, threatening the credibility of media and digital platforms.

Workforce readiness presents another challenge. Technology alone cannot drive transformation without people who understand how to use it. Investment in reskilling and digital literacy is increasingly seen as essential for organisations adopting AI.

Dependence on large global platforms raises additional strategic questions. As automation expands, control over data, distribution and revenue can shift away from local players. Businesses may find themselves relying heavily on external technologies to reach their own markets.

Many leaders now argue that the role of management in the AI era is not simply to promote technology, but to protect trust and invest in people. AI can enhance productivity and support decision-making, yet responsibility for outcomes still rests with humans.

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AI tool could help detect domestic violence risk years earlier

Researchers in the United States have developed an AI system designed to help doctors identify patients who may be at risk of intimate partner violence. The tool analyses hospital data to detect patterns associated with abuse, potentially enabling healthcare professionals to intervene earlier.

Intimate partner violence refers to abuse from current or former partners and can lead to serious injuries, chronic pain, and long-term mental health problems. According to the European Commission, 18 percent of women who have had a partner reported experiencing physical or sexual violence from a partner in 2021.

The study, published in the journal Nature, examined hospital records from nearly 850 women who had experienced intimate partner violence and more than 5,200 similar patients in a control group. Researchers used the data to train three different machine learning systems to detect patterns associated with abuse.

One model analysed structured hospital data, such as age and medical history. A second model examined written clinical notes, including doctors’ observations and radiology reports. A third system combined both data types and achieved the strongest results, correctly identifying risk in 88 percent of cases.

Researchers found that the system could flag potential abuse more than three years before some patients later entered hospital-based intervention programmes. By analysing large datasets, the tool can detect patterns of physical trauma linked to abuse and alert clinicians so they can approach the issue carefully and offer support.

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Human made labels emerge as industries react to AI expansion

Organisations around the world are developing certification labels designed to show that products or creative work were made by humans rather than AI. New badges such as ‘Human made’, ‘AI free’ and ‘Proudly Human’ are appearing across books, films, marketing and websites as industries respond to the rapid spread of AI tools.

At least eight initiatives are now attempting to create a label that could achieve global recognition similar to the Fair Trade mark. Experts warn that competing definitions and inconsistent certification systems could confuse consumers unless a universal standard is agreed upon.

Some schemes allow creators to download AI-free badges with little or no verification, while others use paid auditing processes that rely on analysts and AI detection tools. Researchers note that defining ‘human-made’ is increasingly difficult because AI technologies are embedded in many everyday software tools.

Creative industries are at the centre of the debate as generative AI rapidly produces books, films and music at lower cost and higher speed. Advocates of certification argue that verified human-created content may gain greater value if consumers can clearly distinguish it from AI-generated work.

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Tinder tests AI matchmaking features for modern dating

Popular dating platform Tinder is testing a new AI-powered feature called ‘Chemistry’ designed to improve matchmaking. The tool analyses user profiles to identify more relevant connections while the app’s familiar swipe system remains central to the experience.

Developed by parent company Match Group, the feature uses AI to understand personality traits, interests and preferences through profile data. Future updates may allow users to answer questionnaires or share photo archives to refine recommendations.

Additional modes are also being introduced to further personalise matches. Music preferences and astrology signs can now influence suggested profiles, reflecting evolving trends among younger online daters.

The platform is also testing in-person events and virtual video speed dating to encourage real-world interaction. AI moderation tools are also being deployed, helping detect inappropriate messages and verify that profiles belong to real people.

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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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