Development Archives | Digital Watch Observatory

Greece launches public AI literacy guide for citizens

Greece’s Ministry of Digital Governance and Artificial Intelligence has launched ‘Artificial Intelligence for All’, a public guide designed to improve understanding and use of AI tools.

The guide was developed through cooperation between leading AI scientists, the Ministry of Digital Governance and Artificial Intelligence, the National Council for Research, Technology and Innovation, and the Special Secretariat for Long-Term Planning. The guide is available free of charge through the digital platform of the Special Secretariat for Artificial Intelligence and Data Governance.

According to the ministry, the initiative aims to support digital education, responsible AI use, and a broader understanding of AI systems.

The material introduces basic concepts related to AI and large language models through practical examples and simplified explanations. The guide explains how AI systems can process different forms of data and generate outputs, including recommendations, summaries, and digital content.

The project forms part of Greece’s broader digital strategy focused on digital skills development and public familiarity with emerging technologies.

Officials also highlighted collaboration with the members of the Greek scientific community in Greece and abroad, with the objective of making advanced technological tools more accessible to the wider population.

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Environmental group raises concerns over AI data centre emissions in Scotland

Environmental charity APRS has criticised the Scottish Government over how greenhouse gas emissions linked to hyperscale AI data centres are assessed within existing planning and climate frameworks.

According to APRS, earlier lifecycle emissions assessments focused primarily on broadband and smaller-scale digital infrastructure before the recent expansion of generative AI-related facilities.

The concerns are linked to a proposed 212MW AI data centre project in Edinburgh, currently involved in a planning appeal process.

APRS argued that the term ‘green data centre’ lacks a clear policy definition in relation to large-scale AI infrastructure projects. The organisation said Scotland does not yet have a dedicated policy framework addressing hyperscale AI data centres.

APRS stated that multiple large-scale data centre proposals are currently under consideration across Scotland. The group warned that growing electricity demand linked to data centre expansion could have implications for energy planning and climate objectives.

APRS also called for updated lifecycle emissions assessments and revised planning guidance for hyperscale AI infrastructure projects.

Why does it matter?

The debate highlights a widening policy gap between the rapid expansion of AI infrastructure and existing environmental planning frameworks. Many national climate assessments were created before the emergence of hyperscale generative AI systems, meaning governments may be underestimating the energy, emissions, and resource demands associated with large-scale AI deployment.

It also demonstrates how AI is no longer only a digital or technological policy challenge, but increasingly an environmental, infrastructure, and energy governance issue.

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Singapore pushes trusted AI governance with KPMG AI centre

Singapore’s Ministry of Digital Development and Information has highlighted trust and accountability as key factors in AI adoption during the launch of KPMG’s new Trusted AI Centre of Excellence. Minister of State Jasmin Lau said governments and businesses should ensure AI adoption benefits workers, citizens, and smaller enterprises alongside larger organisations.

The new centre will focus on AI governance, monitoring systems, and AI-related assurance processes as organisations deploy increasingly advanced AI models. KPMG said it is using AI tools internally across audit, tax, and advisory services before broader deployment to clients.

Singapore also reiterated its goal of strengthening its role in regional AI governance and standards development. Officials highlighted efforts involving ASEAN cooperation, AI testing capabilities, and governance initiatives such as AI Verify. According to officials, transparency, explainability, and accountability will remain important factors influencing public confidence in AI systems.

The discussions also reflected broader concerns about AI-related economic disruption, governance challenges, and public trust. Officials noted that businesses and workers continue to face uncertainty regarding AI governance, compliance, and the economic effects of AI adoption.

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Kazakhstan launches UNESCO AI readiness assessment initiative

The United Nations Educational, Scientific and Cultural Organization has announced the launch of its AI Readiness Assessment Methodology in Kazakhstan to evaluate the country’s preparedness for AI governance and development.

The framework is intended to help countries align AI governance approaches with UNESCO Recommendation on the Ethics of AI. Representatives from government, academia, business, civil society, and expert organisations participated in the launch discussions.

Participants discussed Kazakhstan’s digital transformation priorities and plans related to AI ecosystem development. According to UNESCO representatives, the assessment process will address issues including human rights, inclusion, gender equality, and transparency in AI governance.

A national stakeholder group involving ministries, universities, business associations, and civil society organisations will support implementation and policy recommendations. The launch event was held at Astana Hub in Kazakhstan.

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Canada backs AI adoption across Toronto businesses

Canada has announced nearly C$16.5 million in funding for 13 businesses and organisations in the Greater Toronto Area to support AI adoption and help bring new AI technologies to market.

The investment was announced by Evan Solomon, Minister of Artificial Intelligence and Digital Innovation and Minister responsible for the Federal Economic Development Agency for Southern Ontario. The funding will support projects in healthcare, energy management, legal services, construction, finance, transportation, sensitive data infrastructure, and enterprise software.

Several projects focus on healthcare and life sciences. Cosm Medical will accelerate the clinical and commercial rollout of an AI-driven platform for patient-specific gynaecological devices, while Future Fertility will commercialise AI-powered technology for assessing endometrial receptivity. MarkiTech will advance an AI healthcare solution for clinical workflows, and ProteinQure will bring to market an AI-powered targeted drug delivery solution.

Other recipients will use AI to improve business operations and sector-specific workflows. DMD Building Systems will integrate robotics, automation, and AI software for engineering workflows, while Edgecom Energy will commercialise its AI Energy Co-Pilot platform for energy management. Trax will develop an AI-assisted platform for building permit compliance checks, and VisFuture will deliver a natural-language AI tool for small and medium-sized enterprises.

The funding also includes C$2 million for Private AI, operating as Limina, to scale a sensitive data infrastructure platform for regulated sectors such as healthcare, financial services, and insurance. MinuteBox will add advanced AI capabilities to its legal services platform, while Stratosphere Technology, operating as Fiscal.ai, will develop an AI-powered platform for structuring corporate filing data.

The Vector Institute will receive C$4 million to launch and deliver a programme helping start-ups improve data readiness, develop models, and deploy AI products. The Government of Canada said the investment is intended to support AI adoption, commercialisation, productivity, competitiveness, and Ontario’s wider AI ecosystem.

Why does it matter?

The funding shows how Canada is using regional development programmes to push AI from research and experimentation into sector-specific commercial deployment. The mix of recipients also points to a broader policy priority: supporting domestic AI capacity while encouraging adoption in regulated and productivity-sensitive sectors such as healthcare, finance, construction, energy, and legal services.

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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.

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Canada launches AI learning initiative for federal public servants

Canada’s School of Public Service is organising the Learning Week on Artificial Intelligence, an initiative aimed at strengthening AI understanding across the federal public service.

The programme is linked to the Government of Canada’s AI Strategy for the Federal Public Service 2025–2027.

The AI learning programme is open to public servants at all levels and across the country. The initiative includes live events, virtual sessions, self-paced learning tools, and practical demonstrations related to AI technologies.

According to organisers, the programme aims to improve awareness of AI-related opportunities, challenges, and skills within the public service.

The initiative also aligns with broader public service priorities involving digital transformation, productivity, and process modernisation.

Sessions will examine potential applications of AI in areas including policy development, service delivery, and internal administrative functions.

The programme is intended to support responsible AI adoption and prepare public servants in Canada for organisational and operational changes linked to AI technologies.

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UN DESA launches AI governance workshop for Africa and Asia-Pacific officials

The United Nations Department of Economic and Social Affairs (UN DESA) is organising a capacity-building workshop in Hangzhou, China, focused on AI governance and digital transformation for senior government officials from Africa and the Asia-Pacific region.

The activity is part of the project ‘Strengthening AI Capabilities and Governance for Sustainable Digital Transformation in Africa and Asia-Pacific’, implemented in partnership with the Government of China. The programme includes a five-day study tour examining policy, institutional, and technical approaches to AI governance and adoption.

According to the concept note, the initiative responds to gaps in national AI governance frameworks and implementation capacity in many countries. The programme references findings from the UN E-Government Survey 2024 and OECD data concerning AI regulation and national AI strategies.

The programme will draw on the UN E-Government Survey 2024 and its AI Addendum, as well as China’s experience in using AI to support micro, small, and medium-sized enterprises, poverty reduction, and inclusive growth.

Participants are expected to review AI governance structures, regulatory frameworks, and institutional coordination mechanisms. The agenda also includes briefings with relevant ministries or AI bodies, as well as visits to AI coordination or digital transformation institutions.

The agenda includes discussions on international cooperation, regulatory interoperability, public-private collaboration, and AI-related opportunities for small businesses.

According to the concept note, the workshop aims to strengthen institutional understanding of AI governance and support integration of digital policies into national development strategies. Participation is by invitation only and limited to around 20 attendees.

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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.

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International Labour Organization warns AI could reshape labour markets across the Arab region

The International Labour Organization (ILO) and the United Nations Economic and Social Commission for Western Asia (ESCWA) have examined how AI may reshape labour markets and employment patterns across the Arab region.

The organisations released a report exploring how AI adoption may transform jobs, productivity, and workforce dynamics by 2035. According to the report, outcomes will depend on policy choices related to skills development, labour protections, and social support systems.

The report outlines three possible scenarios ranging from inclusive AI-driven growth to increased inequality linked to insufficient labour protections and workforce adaptation measures.

One projected strong AI-driven economic growth, combined with large-scale investment in workforce transition and retraining programmes.

Another warned that rapid technological adoption without sufficient social safeguards could deepen inequality and displace large numbers of lower- and middle-skilled workers.

A third scenario envisaged a more gradual AI integration, supported by coordinated policy reforms and inclusive labour-market strategies.

The report identifies sectors such as healthcare, education, logistics, tourism, and digital services as areas where AI-related employment opportunities may emerge. At the same time, the organisations noted that automation could reduce demand for some routine and clerical occupations.

ILO Regional Director for Arab States Ruba Jaradat said AI technologies are already affecting workplaces across public administration and service sectors in the region. She added that nearly one-quarter of occupations may experience either displacement or technological augmentation linked to generative AI systems.

The analysis also highlighted widening skills mismatches between education systems and labour market demands, with some countries facing gaps ranging from 40% to 70%. The report also highlights the importance of investment in lifelong learning, labour market institutions, social protection, and AI governance frameworks.

The discussions took place during a preparatory session linked to the Arab Forum for Sustainable Development, where policymakers, labour organisations, and international experts examined how AI may affect youth employment, women workers, and lower-skilled populations across the region.

Why does it matter?

ILO highlights how developing and emerging economies may experience AI transitions differently depending on infrastructure, education systems, governance capacity, and investment levels. Policymakers across the Arab region are now under increasing pressure to modernise labour systems while ensuring that AI adoption supports inclusive growth instead of deepening social inequality.

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