Digital identities Archives | Page 19 of 185

xAI faces lawsuit over alleged misuse of AI image generation

Legal action has been filed against xAI in a US federal court, with plaintiffs alleging that its AI system Grok was used to generate harmful and explicitly manipulated images of minors.

The lawsuit claims that xAI failed to implement adequate safeguards to prevent the creation of such content, despite similar protections adopted by other AI developers.

According to the filing, the technology enabled the transformation of real images into explicit material without sufficient restrictions.

Plaintiffs seek to establish a class action, arguing that the company should be held accountable for both direct and third-party uses of its models. Legal arguments focus on whether responsibility extends to external applications built using the same underlying AI systems.

The case also highlights broader regulatory challenges surrounding AI-generated content, particularly the difficulty of preventing misuse when systems can modify real images. Questions around platform liability, safety standards, and enforcement are likely to shape future policy discussions.

Growing scrutiny of AI developers reflects increasing concern over how generative systems are deployed, especially in contexts involving sensitive or harmful content.

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New licensing rules for crypto platforms in Australia

Australia is advancing plans to regulate digital asset platforms under its financial services framework. The Senate committee recommended passing the Digital Assets Framework Bill 2025, bringing Australia closer to licensing crypto exchanges and tokenisation platforms.

Industry groups have raised concerns about definitions such as ‘digital token’ and ‘factual control.’ Broad wording could inadvertently cover infrastructure providers, including multi-party wallet systems, potentially classifying them as financial service operators.

Ripple Labs emphasised the need for precise language to avoid unintended regulation.

The committee supported the Treasury’s approach while planning to refine technical details through future regulations. Coinbase welcomed the progress but noted ongoing banking challenges for crypto firms.

The bill now proceeds to the Senate for debate and a final vote, which could reshape digital asset operations in Australia.

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Britain targets quantum leadership with £1bn investment

UK Secretary of State for Science, Innovation and Technology Liz Kendall has announced a £1bn funding package to boost UK quantum computing and retain domestic talent.

The initiative reflects growing concern over the country’s ability to compete globally, particularly after the US established dominance in AI.

Officials emphasised the need to retain British startups, engineers, and researchers who often relocate abroad in search of better funding and scaling opportunities. The UK produces top talent, but Google and OpenAI own many leading firms.

The investment will support the development of large-scale quantum computers for use across science, industry, and the public sector. Another £1bn will fund real-world use in finance, pharmaceuticals, and energy.

The government aims to build a fully operational domestic quantum system by the early 2030s.

Quantum computing uses qubits that can exist in multiple states simultaneously, enabling far greater computational power than classical systems. Fully fault-tolerant machines are still in development, but the technology could drive advances in drug discovery, materials science, and complex modelling.

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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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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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Seoul deepens ties with global AI developers

South Korea is pursuing a partnership with AI company Anthropic as part of a national strategy to strengthen technological capabilities. Officials are working toward a memorandum of understanding with the developer of the Claude AI system.

The initiative follows discussions between South Korea’s science minister and Anthropic’s chief executive, Dario Amodei, during an AI summit in New Delhi. Authorities are also preparing for the company’s planned office opening in the city in 2026.

Government leaders in South Korea have already expanded cooperation with OpenAI. Policymakers say the strategy aims to build ties with leading global AI developers while supporting domestic innovation.

Officials are also developing a homegrown AI foundation model with local companies. The programme forms part of a national plan to position the country among the world’s leading AI powers.

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Meta removes encrypted messaging from Instagram DMs

Meta will discontinue end-to-end encryption for Instagram direct messages starting in May 2026. The company said the feature saw limited use among Instagram users.

Users with encrypted chats will receive instructions on how to download messages or media before the feature ends. Meta confirmed the change through updates to its support pages and in-app notifications.

The decision comes amid ongoing debate about encryption and online safety on major social platforms. Critics argue that encrypted messaging can make it harder to detect harmful activity involving minors.

Meta said users seeking encrypted communication can continue using WhatsApp or Messenger. The company maintains end-to-end encryption for messaging services outside Instagram.

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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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