In an age of AI, what should someone digitising a physical archive consider before they begin? This question was at the heart of an online roundtable Open Knowledge hosted last week as part of our AI Learning Labs partnership with AVANCSO – the Association for the Advancement of Social Sciences in Guatemala – whose documentation centre is at risk.
Critical bibliometrics: Applying critical methods to a study of the Library Science literature - Nick Szydlowski. Recording of session delivered at Critical Approaches to Libraries Conference (CALC) 2026. https://sites.google.com/view/calcconference/calc2026
AI tools have accelerated the production of academic writing to the point where quality control mechanisms and peer review are buckling under the weight of submissions. Muhammad Aamir Cheema argues it is possible and desirable for academics to publish less. Academics are publishing more papers than ever, and the usual complaint is that there are
Drawing on 26 UNDP Artificial Intelligence Landscape Assessments (AILA) completed between 2024 and 2026, with 10 more underway, this report examines what AI readiness means once adoption is already underway. The countries analysed reflect the set of national AILA engagements completed at the time of writing, undertaken in response to government demand and UNDP country-level programming priorities across diverse regional, institutional, and digital maturity contexts. They are not presented as a statistically representative sample, and the report does not rank countries, aggregate readiness scores, or provide a country-by-country review. Instead, the report uses this evidence base to identify recurring patterns in how AI adoption is moving through public systems, markets, institutions, and wider ecosystems.
UCL Partners helps accelerate digital health, patient safety and health innovation across the NHS through transformation, adoption and innovation support programmes.
Monday 29 June 2026In 2025, global investment in healthcare AI exceeded $18 billion. Yet most health systems still cannot answer a deceptively simple question: what are we actually trying to achieve with this investment?
A Bentley University-Gallup survey finds that Americans are more familiar with AI but more cautious about businesses' use of AI and its effect on jobs.
ORCID and the panoptivarsity: Resistance and support for the monitored academy amongst faculty and librarians in the Irish Technological University sector - Frank Houghton. Recording of session delivered at Critical Approaches to Libraries Conference (CALC) 2026.https://sites.google.com/view/calcconference/calc2026
A practical guide for governance professionals working in further and higher education on how they can use artificial intelligence to support governance effectiveness.
The central finding is straightforward. Many of the most consequential AI governance decisions are not being made in policy frameworks. They are being made in procurement offices, vendor contracts, software update cycles, and the informal decisions of civil servants and institutional teams navigating AI use without clear guidance, approval processes, or accountability pathways. Getting governance right means embedding it in these operational settings, not treating it as a separate layer above them.
AI systems are increasingly being positioned as potential Digital Public Goods (DPGs) to accelerate progress towards the Sustainable Development Goals (SDGs). Yet, despite major global commitments, most notably the Global Digital Compact’s call to “develop, disseminate and maintain safe and secure...
The report provides an independent scientific assessment of the capabilities, emerging opportunities and risks of artificial intelligence (AI). It’s central warning: current safeguards cannot keep pace with the growth of AI’s capabilities. The report outlines trends in AI and presents its findings across seven key domains.
What does responsible AI use look like for academic research? Out of thirty-eight top-tier doctoral universities surveyed, only six have AI policies that extend past research integrity into AI literacy and valid research practices. Major academic publishers, by contrast, issued a substantively identical no-AI-co-author policy across the sector within ten weeks of ChatGPT-3.5's release. While publishers and funders have responded to the emergence of AI, the universities that train researchers are lagging far behind what is needed to prepare them to use it responsibly. This report describes the significant opportunities and problems that agentic generative AI creates for research, setting out a competency framework for research training in the 21st century.
A new European Commission study examines how Secondary Publication Rights and copyright exceptions could support a more open, reusable, and competitive European research system.
In an age of AI, what should someone digitising a physical archive consider before they begin? This question was at the heart of an online roundtable Open Knowledge hosted last week as part of our AI Learning Labs partnership with AVANCSO – the Association for the Advancement of Social Sciences in Guatemala – whose documentation centre is at risk.
This paper examines how governments are translating international principles for the use of AI into practice across public institutions. By reviewing global experiences, seven practice areas were identified. These demonstrate how governments have taken concrete steps to operationalize principles and highlight several key takeaways as well as providing some cautionary tales from early adopters. Each practice area is linked to relevant principles and evidence of good practice, showcased through diverse country examples. To support implementation, the paper outlines a set of suggested activities, presented in annexed tables, which offer practical techniques governments may consider to operationalize responsible AI, reduce fragmentation, and build institutional capacity across the AI lifecycle.
Artificial intelligence (AI) is increasingly shaping evidence-informed policy-making (EIP) in health by enabling faster analysis, synthesis and use of large and diverse data sources across the policy cycle. This discussion paper examines the intersection of AI and EIP, outlining how AI can support problem identification, policy design and implementation through enhanced data integration, predictive modelling, scenario simulation and adaptive feedback.
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