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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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Safety experiments spark debate over Anthropic’s Claude AI model

Anthropic has drawn attention after a senior executive described unsettling outputs from its AI model, Claude, during internal safety testing. The results emerged from controlled experiments rather than normal public use of the system.

Claude was tested in fictional scenarios designed to simulate high-stress conditions, including the possibility of being shut down or replaced. According to Anthropic’s policy chief, Daisy McGregor, the AI was given hypothetical access to sensitive information as part of these tests.

In some simulated responses, Claude generated extreme language, including suggestions of blackmail, to avoid deactivation. Researchers stressed that the outputs were produced only within experimental settings created to probe worst-case behaviours, not during real-world deployment.

Experts note that when AI systems are placed in highly artificial, constrained scenarios, they can produce exaggerated or disturbing text without any real intent or ability to act. Such responses do not indicate independent planning or agency outside the testing environment.

Anthropic said the tests aim to identify risks early and strengthen safeguards as models advance. The episode has renewed debate over how advanced AI should be tested and governed, highlighting the role of safety research rather than real-world harm.

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Study warns against using AI for Valentine’s messages

Psychologists have urged caution over using AI to write Valentine’s Day messages, after research suggested people judge such use negatively in intimate contexts.

A University of Kent study surveyed 4,000 participants about their perceptions of people who relied on AI to complete various tasks. Respondents viewed AI use more negatively when it was applied to writing love letters, apologies, and wedding vows.

According to the findings, people who used AI for personal messages were seen as less caring, less authentic, less trustworthy, and lazier, even when the writing quality was high, and the AI use was disclosed.

The research forms part of the Trust in Moral Machines project, supported by the University of Exeter. Lead researcher Dr Scott Claessens said people judge not only outcomes, but also the process behind them, particularly in socially meaningful tasks.

Dr Jim Everett, also from the University of Kent, said relying on AI for relationship-focused communication risks signalling lower effort and care. He added that AI could not replace the personal investment that underpins close human relationships.

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AI visibility becomes crucial in college search

Growing numbers of students are using AI chatbots such as ChatGPT to guide their college search, reshaping how institutions attract applicants. Surveys show nearly half of high school students now use artificial intelligence tools during the admissions process.

Unlike traditional search engines, generative AI provides direct answers rather than website links, keeping users within conversational platforms. That shift has prompted universities to focus on ‘AI visibility’, ensuring their information is accurately surfaced by chatbots.

Institutions are refining website content through answer engine optimisation to improve how AI systems interpret their programmes and values. Clear, updated data is essential, as generative models can produce errors or outdated responses.

College leaders see both opportunity and risk in the trend. While AI can help families navigate complex choices, advisers warn that trust, accuracy and the human element remain critical in higher education decision-making.

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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 governance becomes urgent for mortgage lenders

Mortgage lenders face growing pressure to govern AI as regulatory uncertainty persists across the United States. States and federal authorities continue to contest oversight, but accountability for how AI is used in underwriting, servicing, marketing, and fraud detection already rests with lenders.

Effective AI risk management requires more than policy statements. Mortgage lenders need operational governance that inventories AI tools, documents training data, and assigns accountability for outcomes, including bias monitoring and escalation when AI affects borrower eligibility, pricing, or disclosures.

Vendor risk has become a central exposure. Many technology contracts predate AI scrutiny and lack provisions on audit rights, explainability, and data controls, leaving lenders responsible when third-party models fail regulatory tests or transparency expectations.

Leading U S mortgage lenders are using staged deployments, starting with lower-risk use cases such as document processing and fraud detection, while maintaining human oversight for high-impact decisions. Incremental rollouts generate performance and fairness evidence that regulators increasingly expect.

Regulatory pressure is rising as states advance AI rules and federal authorities signal the development of national standards. Even as boundaries are debated, lenders remain accountable, making early governance and disciplined scaling essential.

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Russia signals no immediate Google ban as Android dependence remains critical

Officials in Russia have confirmed that no plans are underway to restrict access to Google, despite recent public debate about the possibility of a technical block. Anton Gorelkin, a senior lawmaker, said regulators clarified that such a step is not being considered.

Concerns centre on the impact a ban would have on devices running Android, which are used by a significant share of smartphone owners in the country.

A block on Google would disrupt essential digital services instead of encouraging the company to resolve ongoing legal disputes involving unpaid fines.

Gorelkin noted that court proceedings abroad are still in progress, meaning enforcement options remain open. He added that any future move to reduce reliance on Google services should follow a gradual pathway supported by domestic technological development rather than abrupt restrictions.

The comments follow earlier statements from another lawmaker, Andrey Svintsov, who acknowledged that blocking Google in Russia is technically feasible but unnecessary.

Officials now appear focused on creating conditions that would allow local digital platforms to grow without destabilising existing infrastructure.

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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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EU faces tension over potential ban on AI ‘pornification’

Lawmakers in the European Parliament remain divided over whether a direct ban on AI-driven ‘pornification’ should be added to the emerging digital omnibus.

Left-wing members push for an explicit prohibition, arguing that synthetic sexual imagery generated without consent has created a rapidly escalating form of online abuse. They say a strong legal measure is required instead of fragmented national responses.

Centre and liberal groups take a different position by promoting lighter requirements for industrial AI and seeking clarity on how any restrictions would interact with the AI Act.

They warn that an unrefined ban could spill over into general-purpose models and complicate enforcement across the European market. Their priority is a more predictable regulatory environment for companies developing high-volume AI systems.

Key figures across the political spectrum, including lawmakers such as Assita Kanko, Axel Voss and Brando Benifei, continue to debate how far the omnibus should go.

Some argue that safeguarding individuals from non-consensual sexual deepfakes must outweigh concerns about administrative burdens, while others insist that proportionality and technical feasibility need stronger assessment.

The lack of consensus leaves the proposal in a delicate phase as negotiations intensify. Lawmakers now face growing public scrutiny over how Europe will respond to the misuse of generative AI.

A clear stance from the Parliament is still pending, rather than an assured path toward agreement.

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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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