Digital cooperation Archives | Page 9 of 196

Quebec examines AI debt collection practices

Quebec’s financial regulator has opened a review into how AI tools are being used to collect consumer debt across the province. The Autorité des marchés financiers is examining whether automated systems comply with governance, privacy and fairness standards in Quebec.

Draft guidelines released in 2025 require institutions in Quebec to maintain registries of AI systems, conduct bias testing and ensure human oversight. Public consultations closed in November, with regulators stressing that automation must remain explainable and accountable.

Many debt collection platforms now rely on predictive analytics to tailor the timing, tone and frequency of messages sent to borrowers in Quebec. Regulators are assessing whether such personalisation risks undue pressure or opaque decision making.

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AI startup raises $100m to predict human behaviour

Artificial intelligence startup Simile has raised $100m to develop a model designed to predict human behaviour in commercial and corporate contexts. The funding round was led by Index Ventures with participation from Bain Capital Ventures and other investors.

The company is building a foundation model trained on interviews, transaction records and behavioural science research. Its AI simulations aim to forecast customer purchases and anticipate questions analysts may raise during earnings calls.

Simile says the technology could offer an alternative to traditional focus groups and market testing. Retail trials have included using the system to guide decisions on product placement and inventory.

Founded by Stanford-affiliated researchers, the startup recently emerged from stealth after months of development. Prominent AI figures, including Fei-Fei Li and Andrej Karpathy, joined the funding round as it seeks to scale predictive decision-making tools.

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Ethical governance at centre of Africa AI talks

Ghana is set to host the Pan African AI and Innovation Summit 2026 in Accra, reinforcing its ambition to shape Africa’s digital future. The gathering will centre on ethical artificial intelligence, youth empowerment and cross-sector partnerships.

Advocates argue that AI systems must be built on local data to reflect African realities. Many global models rely on datasets developed outside the continent, limiting contextual relevance. Prioritising indigenous data, they say, will improve outcomes across agriculture, healthcare, education and finance.

National institutions are central to that effort. The National Information Technology Agency and the Data Protection Commission have strengthened digital infrastructure and privacy oversight.

Leaders now call for a shift from foundational regulation to active enablement. Expanded cloud capacity, high-performance computing and clearer ethical AI guidelines are seen as critical next steps.

Supporters believe coordinated governance and infrastructure investment can generate skilled jobs and position Ghana as a continental hub for responsible AI innovation.

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Tokyo semiconductor profits surge amid AI boom

Major semiconductor companies in Tokyo have reported strong profit growth for the April to December period, buoyed by rising demand for AI related chips. Several firms also raised their full year forecasts as investment in AI infrastructure accelerates.

Kioxia expects net profit to climb sharply for the year ending in March, citing demand from data centres in Tokyo and devices equipped with on device AI. Advantest and Tokyo Electron also upgraded their outlooks, pointing to sustained orders linked to AI applications.

Industry data suggest the global chip market will continue expanding, with World Semiconductor Trade Statistics projecting record revenues in 2026. Growth is being driven largely by spending on AI servers and advanced semiconductor manufacturing.

In Tokyo, Rapidus has reportedly secured significant private investment as it prepares to develop next generation chips. However, not all companies in Japan share the optimism, with Screen Holdings forecasting lower profits due to upfront capacity investments.

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EU decision regulates researcher access to data under the DSA

A document released by the Republican-led House Judiciary Committee revived claims that the EU digital rules amount to censorship. The document concerns a €120 million fine against X under the Digital Services Act and was framed as a ‘secret censorship ruling’, despite publication requirements.

The document provides insight into how the European Commission interprets Article 40 of the DSA, which governs researcher access to platform data. The rule requires huge online platforms to grant qualified researchers access to publicly accessible data needed to study systemic risks in the EU.

Investigators found that X failed to comply with Article 40.12, in force since 2023 and covering public data access. The Commission said X applied restrictive eligibility rules, delayed reviews, imposed tight quotas, and blocked independent researcher access, including scraping.

The decision confirms platforms cannot price access to restrict research, deny access based on affiliation or location, or ban scraping by contract. The European Commission also rejected X’s narrow reading of ‘systemic risk’, allowing broader research contexts.

The ruling also highlights weak internal processes and limited staffing for handling access requests. X must submit an action plan by mid-April 2026, with the decision expected to shape future enforcement of researcher access across major platforms.

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AI anxiety strains the modern workforce

Mounting anxiety is reshaping the modern workplace as AI alters job expectations and career paths. Pew Research indicates more than a third of employees believe AI could harm their prospects, fuelling tension across teams.

Younger workers feel particular strain, with 92% of Gen Z saying it is vital to speak openly about mental health at work. Communicators and managers must now deliver reassurance while coping with their own pressure.

Leadership expert Anna Liotta points to generational intelligence as a practical way to reduce friction and improve trust. She highlights how tailored communication can reduce misunderstanding and conflict.

Her latest research connects neuroscience, including the role of the vagus nerve, with practical workplace strategies. By combining emotional regulation with thoughtful messaging, she suggests that organisations can calm anxiety and build more resilient teams.

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Hybrid AI could reshape robotics and defence

Investors and researchers are increasingly arguing that the future of AI lies beyond large language models. In London and across Europe, startups are developing so-called world models designed to simulate physical reality rather than simply predict text.

Unlike LLMs, which rely on static datasets, world models aim to build internal representations of cause and effect. Advocates say these systems are better suited to autonomous vehicles, robotics, defence and industrial simulation.

London based Stanhope AI is among companies pursuing this approach, claiming its systems learn by inference and continuously update their internal maps. The company is reportedly working with European governments and aerospace firms on AI drone applications.

Supporters argue that safety and explainability must be embedded from the outset, particularly under frameworks such as the EU AI Act. Investors suggest that hybrid systems combining LLMs with physics aware models could unlock large commercial markets across Europe.

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Researchers tackle LLM regression with on policy training

Researchers at MIT, the Improbable AI Lab and ETH Zurich have proposed a fine tuning method to address catastrophic forgetting in large language models. The issue often causes models to lose earlier skills when trained on new tasks.

The technique, called self distillation fine tuning, allows a model to act as both teacher and student during training. In Cambridge and Zurich experiments, the approach preserved prior capabilities while improving accuracy on new tasks.

Enterprise teams often manage separate model variants to prevent regression, increasing operational complexity. The researchers argue that their method could reduce fragmentation and support continual learning, useful for AI, within a single production model.

However, the method requires around 2.5 times more computing power than standard supervised fine tuning. Analysts note that real world deployment will depend on governance controls, training costs and suitability for regulated industries.

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Latam-GPT signals new AI ambition in Latin America

Chile has introduced Latam-GPT to strengthen Latin America’s presence in global AI.

The project, developed by the National Centre for Artificial Intelligence with support across South America, aims to correct long-standing biases by training systems on the region’s own data instead of material drawn mainly from the US or Europe.

President Gabriel Boric said the model will help maintain cultural identity and allow the region to take a more active role in technological development.

Latam-GPT is not designed as a conversational tool but rather as a vast dataset that serves as the foundation for future applications. More than eight terabytes of information have been collected, mainly in Spanish and Portuguese, with plans to add indigenous languages as the project expands.

The first version has been trained on Amazon Web Services. At the same time, future work will run on a new supercomputer at the University of Tarapacá, supported by millions of dollars in regional funding.

The model reflects growing interest among countries outside the major AI hubs of the US, China and Europe in developing their own technology instead of relying on foreign systems.

Researchers in Chile argue that global models often include Latin American data in tiny proportions, which can limit accurate representation. Despite questions about resources and scale, supporters believe Latam-GPT can deliver practical benefits tailored to local needs.

Early adoption is already underway, with the Chilean firm Digevo preparing customer service tools based on the model.

These systems will operate in regional languages and recognise local expressions, offering a more natural experience than products trained on data from other parts of the world.

Developers say the approach could reduce bias and promote more inclusive AI across the continent.

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Young voices seek critical approach to AI in classrooms

In Houston, more than 200 students from across the US gathered to discuss the future of AI in schools. The event, organised by the Close Up Foundation and Stanford University’s Deliberative Democracy Lab, brought together participants from 39 schools in 19 states.

Students debated whether AI tools such as ChatGPT and Gemini support or undermine learning. Many argued that schools are introducing powerful systems before pupils develop core critical thinking skills.

Participants did not call for a total ban or full embrace of AI. Instead, they urged schools to delay exposure for younger pupils and introduce clearer classroom policies that distinguish between support and substitution.

After returning to Honolulu, a student from ʻIolani School said Hawaiʻi schools should involve students directly in AI policy decisions. In Honolulu and beyond, he argued that structured dialogue can help schools balance innovation with cognitive development.

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