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World Health Organization launches AI tool for reproductive health information

The World Health Organization and partners have launched ChatHRP, an AI-assisted tool designed to provide fast access to verified information on sexual and reproductive health and rights.

Developed under the HRP research programme, the system is aimed at supporting evidence-based decision-making in a field where misinformation remains a persistent challenge.

ChatHRP uses advanced natural language processing and retrieval-based AI to deliver referenced answers drawn exclusively from WHO and HRP materials.

The tool is designed for policy-makers, researchers, health workers and civil society organisations, helping them quickly navigate complex scientific and policy information without fragmented sources.

Built for global accessibility, the platform includes multilingual functionality and low-bandwidth optimisation to ensure usability in resource-limited settings. Its structure prioritises accuracy and transparency, with responses linked directly to validated research and guidance that is regularly updated.

The beta phase focuses on professional use cases, where users can query topics such as maternal health, contraception and disease management.

Why does it matter?

The initiative directly improves access to reliable, evidence-based health information in a field where misinformation can influence policy and health outcomes. By centralising verified sources and reducing reliance on fragmented or unverified material, it supports faster, more consistent decision-making across healthcare, research and policy environments globally.

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Wikipedia-based AI model identifies 100 emerging technologies to watch in 2026

A new analysis by Australian researchers reveals how AI is reshaping the way emerging technologies are identified and tracked.

Using a dataset derived from thousands of Wikipedia entries, the researchers mapped more than 23,000 technologies to produce the ‘Momentum 100’ list, highlighting the fastest-growing technologies across science and industry.

The findings place reinforcement learning at the top, followed closely by blockchain and other rapidly advancing fields such as 3D printing, soft robotics and augmented reality.

These technologies reflect a broader shift towards data-driven innovation, where systems capable of learning, adapting and scaling are becoming central to both research and commercial applications.

Unlike traditional forecasts, which often rely on expert judgement, the model uses large-scale data analysis to detect patterns of growth and interconnection between technologies.

The approach offers a more dynamic and repeatable method, capturing early signals that might otherwise be overlooked in manual assessments.

Despite its advantages, researchers caution that predicting real-world impact remains difficult at early stages.

While AI-driven mapping provides valuable insights, policymakers and industry leaders still rely on hybrid approaches that combine data analysis with expert evaluation, as seen in frameworks developed by organisations such as the World Economic Forum.

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ILO warns against treating AI exposure indicators as job-loss forecasts

A new brief from the International Labour Organisation argues that AI exposure indicators should not be treated as forecasts of job losses, even as they become a more common tool for assessing how artificial intelligence could reshape work.

According to the ILO, these indicators can help identify where jobs may be affected by AI. Still, they do not show whether workers will actually be displaced or how labour markets will adjust in practice.

The brief examines how different exposure measures are constructed and why they often produce different results. Earlier approaches to automation focused mainly on routine and lower-skilled work, while newer AI-related models point to greater exposure in higher-skilled cognitive occupations, including roles in finance, computing, business, and education. That shift reflects the growing capacity of AI systems to perform tasks once seen as less vulnerable to automation.

The ILO stresses that exposure does not necessarily lead to job loss. Most indicators rely on static task descriptions and estimate what may be technically feasible, rather than what employers will actually adopt or what makes economic sense. They do not capture whether automation is profitable, whether it improves productivity, or how firms, workers, and institutions may respond over time.

The brief also argues that AI-related disruption is unlikely to stay confined to a narrow set of occupations. Jobs are linked through shared skills, career mobility, and workplace structures, meaning that changes in one part of the labour market can influence broader employment patterns elsewhere. That makes simple occupation-by-occupation risk scores less useful on their own than they may appear.

For that reason, the ILO says exposure indicators should be used as early warning signals rather than stand-alone labour market forecasts. It recommends combining them with evidence on employment, wages, job transitions, and broader economic and institutional conditions to build a more realistic picture of how AI is affecting work.

The broader significance of the brief is that it pushes back against the simplest narratives about AI and employment. Rather than asking how many jobs AI will eliminate, the ILO is urging policymakers to focus on where work may change, how quickly adoption may happen, and what kinds of institutions, skills, and labour protections will shape the outcome.

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Study suggests AI reliance may weaken short-term problem-solving

A recent study by researchers from Carnegie Mellon University, the University of Oxford, MIT, and UCLA suggests that reliance on AI for basic tasks may temporarily weaken cognitive performance.

Participants who used AI tools to complete simple maths and reading exercises initially performed better than those working without assistance. However, once the technology was removed, their accuracy declined, and they were less likely to persist with the tasks.

The findings suggest that even brief exposure to AI support can reduce a person’s willingness to engage in sustained problem-solving, which remains essential to learning and skill development.

Researchers found that participants became more likely to abandon tasks and less able to complete them independently after relying on AI assistance.

The results add to wider concerns about how AI may be reshaping learning habits and intellectual development. Related research from MIT has described a phenomenon called ‘cognitive debt’, in which heavy reliance on AI tools may weaken retention, understanding, and independent reasoning over time.

Taken together, the studies point to a growing tension in AI design. While such tools can improve speed and convenience, they may also reduce the mental effort needed to build lasting cognitive skills. That suggests AI systems may need to be designed to support learning without replacing independent thought altogether.

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Canada launches hybrid AI weather model

Environment and Climate Change Canada has announced the launch of a hybrid AI weather forecasting model aimed at improving predictions of severe weather. The system combines AI with traditional physics-based forecasting methods.

According to Environment and Climate Change Canada, the model uses AI to analyse large datasets while relying on established models to account for local weather factors such as temperature, wind and precipitation. This combination is expected to improve forecast accuracy.

The department states the system will enhance performance across all forecast timeframes and provide earlier warnings of major weather events. In some cases, forecasts could identify large systems more than 24 hours earlier than current capabilities.

Environment and Climate Change Canada said the model has been extensively tested alongside existing systems and will support better preparedness and public safety as extreme weather events increase in Canada.

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EU approves Italian State aid to support graphene-based photonic chip development

The European Commission has approved a €211 million Italian State aid measure to support the development of photonic chips based on graphene technology.

A funding will be provided to the Italian SME CamGraPhIC, with project activities taking place in Pisa and Bergamo.

Such an initiative focuses on optical transceivers that transmit data using light rather than electrons. The use of graphene instead of silicon is expected to enhance performance and energy efficiency across sectors such as telecommunications, automotive, aerospace and defence.

The Commission assessed the measure under the EU State aid rules and concluded that the funding is necessary, proportionate and aligned with research and innovation objectives. It also found that the project would not proceed without public support, demonstrating an incentive effect.

A decision that reflects broader EU efforts to strengthen semiconductor capabilities and support advanced digital technologies through targeted public investment and regulatory oversight.

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EU universities could anchor AI strategy

Universities could play a central role in strengthening AI sovereignty across the European Union, it was said at a Brussels forum organised by Udice. Higher education institutions are positioned as key contributors to research, talent development and technological capability.

Universities already underpin much of Europe’s AI ecosystem through fundamental research and industry collaboration. Their role extends to training skilled workers needed to sustain long-term innovation.

However, challenges remain, including fragmented funding, competition for global talent and limited scaling of research into commercial applications. These barriers may constrain the European Union’s ability to capitalise on its academic strengths fully.

Yet, stronger coordination, investment and policy support could enable universities to act as a backbone for AI development and strategic autonomy in the European Union.

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Kazakhstan Machinery Forum examines technology policy, industrial development and energy strategy

Representatives from Samruk-Energy JSC took part in the 13th Kazakhstan Machinery Forum, according to the company. The event brought together government and business figures to discuss the future of the machinery and manufacturing sectors.

During a sector session, Managing Director Galymbek Autalipov outlined plans to adopt and localise clean coal technologies. These are described as a strategic priority to balance energy security with environmental commitments.

Company representatives also joined discussions on procurement and industrial policy under Samruk-Kazyna JSC. Talks focused on import substitution, technological modernisation and increasing domestic value in supply chains.

The forum serves as a platform for shaping long-term industrial strategy through cooperation between state bodies and businesses, including the development of manufacturing capacity and modern technologies in Kazakhstan.

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University of South Wales becomes the first in the UK to AI qualification as part of a degree

University of South Wales will become the first university in the UK to embed an AI qualification within a Business and Management degree. The programme was developed with the Institute of Enterprise and Entrepreneurs and will begin in September 2026.

Students will receive an IOEE award after their first year and may obtain a diploma upon graduation. The course is the first in the UK to combine both certifications within a single degree.

The qualification includes six units covering AI literacy, prompting, evaluation, application, ethics and reflective practice. These elements are assessed through existing coursework rather than separate examinations.

First-year students will take a module that includes weekly AI sessions linked to building a business. They will use AI for financial projections, marketing strategies, pitch materials and competitor analysis.

Final year students will create digital products using AI, including chatbots and business plans. Liam Newton, course leader for the BA Business and Management programme at the University of South Wales, said the programme aims to support employability and to develop informed use of AI tools.

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MIT develops AI framework to test ethics in autonomous systems

Researchers at MIT have introduced a new framework designed to evaluate the ethical impact of autonomous systems used in high-stakes environments. The approach aims to identify cases where AI-driven decisions may be technically efficient but fail to meet fairness expectations.

Growing reliance on AI in areas such as energy distribution and traffic management has raised concerns about unintended bias. Cost-optimised systems can still disadvantage communities, especially when ethical factors are hard to measure.

The framework, known as SEED-SET, separates objective performance metrics from subjective human values. A large language model is used to simulate stakeholder preferences, enabling the system to compare scenarios and detect where outcomes diverge from ethical expectations.

Testing shows the method generates more relevant scenarios while reducing manual analysis. Findings highlight its potential to improve transparency and support more balanced decision-making before AI systems are deployed.

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