Sustainable development Archives | Page 2 of 304

UNESCO highlights ethical AI integration in South Asian higher education

AI is transforming higher education systems across South Asia, creating opportunities to improve teaching, learning, research, and institutional management, while also exposing challenges around policy readiness, educator capacity, digital infrastructure, and equitable access.

A regional policy dialogue held in Kathmandu on 20 May 2026, jointly organised by UNESCO Kathmandu, Tribhuvan University, the Asian Development Bank, and UNESCO-ICHEI, highlighted the need for coordinated strategies to guide AI integration in higher education.

Key priorities include strengthening policies and strategies for AI use, investing in teacher professional development, improving collaboration between universities and industry, and better understanding the implications of generative AI for higher education and technical and vocational education and training.

The discussions also focused on inclusion, particularly the gender divide in AI. UNESCO said one of the most significant forms of AI bias in South Asia affects girls and women, underscoring the need for their participation in AI-related education and workplaces to build an inclusive AI ecosystem.

The launch of the IIOE Nepal National Centre at Tribhuvan University reflects the growing need for sustained national capacity-building mechanisms to support higher education institutions in adapting to digital transformation.

The dialogue also reinforced the importance of evidence-based policymaking, following the release of the Report on Digital Transformation in Higher Education in South Asia. UNESCO said such knowledge can help governments and universities move beyond experimentation towards more coherent and future-oriented strategies for AI integration.

Why does it matter?

AI integration in higher education is becoming a structural policy issue, not only a classroom technology question. UNESCO’s regional dialogue points to the risk that unequal digital infrastructure, weak institutional capacity, limited AI literacy, and gender gaps could deepen existing inequalities if clear policies, ethical safeguards, and investment in educators do not guide AI adoption.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our chatbot!

EU consultation closes on AI energy measurement

The European Commission has moved forward with work on measuring the energy consumption and emissions of AI models and systems, as part of preparations for a possible AI energy measurement framework under the EU AI Act.

The targeted consultation forms part of a Commission-procured study on measuring and promoting energy-efficient and low-emission AI in the European Union. Responses will help refine the study, contribute to a measurement framework for the AI Act’s energy-related objectives and support the design of a potential AI energy and emissions label.

The process focuses on how to measure energy use across the AI lifecycle, including development and training, as well as operational use and inference. The Commission says a comprehensive picture of AI’s energy efficiency and carbon footprint requires data on computational resources, electricity consumption and hardware details.

Under Annex XI of the AI Act, providers of general-purpose AI models must document known or estimated energy consumption as part of their technical documentation obligations. The consultation, therefore, targets developers and deployers of general-purpose AI models and AI systems, as well as component and service suppliers.

Stakeholders were asked about the accessibility of data needed to assess AI energy consumption and emissions, as well as the suitability of different AI performance indicators. The Commission said the aim is to develop a robust and practical industry-informed framework for measuring AI energy consumption and efficiency.

The AI Office will publish a summary of the consultation results based on aggregated data, with respondents not directly quoted.

Why does it matter?

AI’s growing energy demand is becoming a regulatory and environmental policy concern, especially as general-purpose AI models require substantial computing resources for training and inference. A common EU framework for measuring AI energy use and emissions could make environmental impacts more visible, support future transparency obligations and help compare systems more consistently. A possible AI energy and emissions label would also push sustainability into AI governance alongside safety, transparency and accountability.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!

World Bank highlights ‘Small AI’ for farmers and rural communities

According to Hindustan Times, World Bank President Ajay Banga highlighted the potential of ‘Small AI’ systems to support farmers and rural communities through locally deployed and lower-cost technologies.

Examples discussed included farmers in India using mobile phones to share images of diseased crops and receive agricultural advice remotely. Banga also referred to healthcare workers in Indonesia using basic internet connections to access local diagnostic support systems in remote areas.

At the summit, entrepreneur Saurav Mukherjee said AI adoption was expanding into sectors including agriculture and food production. Mukherjee said AI tools may support agricultural decision-making through analysis of seed quality and environmental conditions such as soil, weather, and water availability.

He also noted that wider internet connectivity and 5G access could support wider AI adoption in underserved regions. However, he cautioned that shortages of skilled workers could limit implementation capacity in some regions.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

EU lawmakers challenge confidentiality rules on data centre emissions data

A group of 35 Members of the European Parliament has called on the European Commission to review confidentiality rules affecting public access to environmental data from data centres. The request focused on the disclosure of information related to emissions, energy use, and water consumption.

According to reporting by Investigate Europe, the disputed wording was linked to proposals submitted during consultations by Microsoft and DIGITALEUROPE. The clause was later incorporated into the EU Energy Efficiency Directive and limits disclosure of certain information related to individual data centres.

Critics argue that the measure may reduce transparency regarding the environmental impact of expanding digital infrastructure. Some lawmakers and advocacy groups have also raised questions about compatibility with transparency principles under the Aarhus Convention. Reports said critics believe the rules reduce scrutiny of the environmental impact linked to expanding AI and cloud infrastructure.

The lawmakers called on the European Commission to reconsider the provision and publish more detailed environmental reporting data. The issue has contributed to broader discussions in the EU regarding environmental accountability and oversight of digital infrastructure.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

NASA develops AI system to track harmful algal blooms using satellite data

NASA researchers have developed an AI system designed to combine satellite datasets to improve monitoring of harmful algal blooms.

The system uses self-supervised machine learning to analyse patterns across five satellite missions and instruments, helping researchers identify blooms in regions including western Florida and Southern California. According to researchers, the approach could support environmental monitoring and earlier identification of marine health risks.

Harmful algal blooms can affect ecosystems, wildlife, coastal environments, and public health. In parts of Florida, blooms caused by Karenia brevis have disrupted coastal communities for decades, while toxic blooms along the US West Coast have harmed dolphins, sea lions, and other marine species.

NASA researchers said the system combines information from multiple satellite observation technologies. Instruments such as the PACE satellite and the TROPOMI monitoring instrument help identify algae characteristics, including pigment, fluorescence, and biological activity across ocean surfaces.

The researchers said the self-supervised AI model identifies relationships between datasets without relying heavily on manually labelled data. The system was trained using satellite observations collected during 2018 and 2019 before being tested on later bloom events.

Michelle Gierach of NASA’s Jet Propulsion Laboratory said the system could help environmental agencies identify areas for water sampling earlier during bloom development. Researchers said combining satellite observations with field data may improve coordination between scientific and public health teams.

The project team said the system is being expanded using additional coastal and freshwater datasets.

Why does it matter?

NASA’s development highlights growing use of AI and satellite intelligence for environmental monitoring and climate-related risk management. Harmful algal blooms are becoming an increasing concern for coastal economies, fisheries, tourism, biodiversity, and public health systems worldwide.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

Study examines local warming effects linked to data centre expansion

New research suggests that expanding data centre infrastructure may contribute to localised warming effects similar to urban heat islands.

The study, published in the Journal of Engineering for Sustainable Buildings and Cities, examined several data centres in the Phoenix metropolitan area and found measurable increases in surrounding air temperatures. Researchers reported temperature increases ranging from approximately 1.5 to 4 degrees Fahrenheit within areas located downwind from facilities.

Data centres generate waste heat through cooling systems used to support high-performance computing operations.

According to the researchers, large data centre campuses can generate concentrated thermal output associated with high energy consumption.

The findings come as global demand for AI, cloud computing, and digital services continues to drive the construction of new facilities across the US and other regions. Northern Virginia, Phoenix, and several European locations have become major hubs for hyperscale infrastructure development.

The researchers said the observed effects differ from traditional urban heat islands because of continuous cooling activity and continuous energy consumption. The study noted that clusters of facilities may produce cumulative effects that require further investigation.

The researchers discussed potential implications for energy demand, infrastructure planning, and surrounding communities. The study said elevated local temperatures could influence cooling demand and related environmental conditions.

Furthermore, scientists stressed that additional peer-reviewed research remains necessary to determine the long-term climatic significance of large-scale data centre expansion.

Why does it matter?

The findings reflect growing scrutiny surrounding the environmental footprint of AI infrastructure. Data centres already face criticism over electricity consumption, water usage, and grid pressure. The possibility that concentrated AI infrastructure may also influence local temperatures introduces another dimension to debates surrounding sustainable digital expansion.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

ITU Radiocommunication Bureau outlines key aspects future connectivity

ITU Radiocommunication Bureau has highlighted the critical role of radio-frequency spectrum in ensuring digital resilience, emphasising that reliable connectivity underpins essential services such as healthcare, transport and emergency communications.

According to the Bureau, resilience begins before disruption through coordinated spectrum management, international standards and regulatory frameworks. These systems enable wireless networks and satellite services to operate reliably and avoid harmful interference.

The organisation stressed that growing demand for connectivity, including 5G, satellite broadband and AI-enabled systems, increases pressure on spectrum resources. Technical standards and global coordination are therefore essential to maintain interoperability and support innovation.

ITU also pointed to the importance of satellite systems and early warning technologies in responding to climate risks and disasters. Future decisions at the World Radiocommunication Conference 2027 in China will further shape how resilient digital infrastructure develops globally.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

UN calls for AI-driven transformation of future cities

UN organisations and urban experts have called on governments, city leaders, and the private sector to accelerate the use of AI and digital technologies to shape the future of urban life. The appeal was made during the 3rd UN Virtual Worlds Day held in Geneva.

With 70 percent of the global population expected to live in urban areas by 2050, discussions focused on the emergence of an ‘AI-enabled citiverse’ combining AI, digital twins and spatial intelligence to improve planning, infrastructure management and quality of life in cities.

Participants outlined five strategic priorities, including strengthening inclusive AI systems, improving data-driven decision-making, and ensuring responsible economic and social development. Emphasis was also placed on global cooperation and the need for common standards to guide digital urban transformation.

The conference also highlighted key risks, including governance gaps, trust and safety concerns, and widening digital divides. A joint briefing warned that the benefits of AI-driven urban systems must be distributed fairly, including to developing economies and underserved communities.

Why does it matter?

The integration of AI into urban systems signals a structural shift in how cities are designed, managed and experienced. As urbanisation accelerates globally, AI-enabled infrastructure could significantly improve efficiency, resilience and sustainability, but also risks deepening inequality if governance and access remain uneven across regions.

United Nations organisations and urban experts have called on governments, city leaders and the private sector to accelerate the use of AI and digital technologies in shaping the future of urban life. The appeal was made during the 3rd UN Virtual Worlds Day held in Geneva.

The conference also highlighted key risks such as governance gaps, trust and safety concerns, and widening digital divides. A joint briefing warned that the benefits of AI-driven urban systems must be distributed fairly, including to developing economies and underserved communities.

Why does it matter?

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our chatbot!

Australian Senate opens inquiry into AI data centres

The Australian Greens announced that the Senate has established a parliamentary inquiry into AI data centres, according to its official statement. The move follows growing concern over the rapid expansion of energy-intensive AI infrastructure and limited federal oversight.

The inquiry will examine environmental, economic and social impacts, including energy and water use, effects on communities, and the regulatory framework governing AI. It aims to better understand how these facilities influence resources and infrastructure.

Greens Senator Sarah Hanson-Young said communities have raised concerns about pressure on energy supply, water availability and environmental protection. She also called for greater transparency and parliamentary scrutiny of agreements involving global technology companies.

The party warned against repeating past regulatory failures and stressed the need for accountability as AI infrastructure expands. The inquiry is expected to gather input from affected communities and stakeholders across Australia.

Would you like to learn more about AI, tech and digital diplomacy? If so, ask our Diplo chatbot!

China AI ethics draft translated by Georgetown’s CSET

The Center for Security and Emerging Technology (CSET), a policy research organisation within Georgetown University’s Walsh School of Foreign Service, has published an English translation of China’s draft trial measures on ethics reviews for AI technology.

The translated draft says the measures would apply to AI-related scientific and technological activities conducted within China that may pose ethical risks to human health, human dignity, the ecological environment, public order, or sustainable development. It covers universities, research institutions, medical and health institutions, enterprises, and other organisations involved in AI research and development.

Under the draft, organisations with the necessary conditions would be expected to establish AI technology ethics committees, while others could commission specialised ethics service centres to conduct reviews. Review applications would need to include details on the AI activity, algorithms, data sources, data cleaning methods, testing and evaluation, expected applications, user groups, risk assessments, and risk prevention plans.

The review process would focus on fairness and impartiality; controllability and trustworthiness; transparency and explainability; accountability and traceability; and whether the activity has scientific and social value. Committees or service centres would generally have 30 days to approve, reject, or request revisions to an application.

Higher-risk activities would require expert reconsideration. The draft list includes human-computer fusion systems that strongly affect behaviour, psychological or emotional states, or health; AI models and systems able to mobilise public opinion or channel social consciousness; and highly autonomous automated decision-making systems used in safety or personal health-risk scenarios.

Approved AI activities would also be subject to follow-up reviews, generally at intervals of no more than 12 months, while activities requiring expert reconsideration would be subject to follow-up reviews at least every 6 months. Emergency ethics reviews would normally have to be completed within 72 hours.

CSET notes that China released a final trial version of the regulation in April 2026, which it is now translating. The newly published draft translation therefore provides insight into the regulatory structure that preceded the final version, including committee-based ethics review, external service centres, expert reconsideration, and oversight roles for the Ministry of Science and Technology, the Ministry of Industry and Information Technology, and other departments.

Would you like to learn more about AI, tech, and digital diplomacy? If so, ask our Diplo chatbot!