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.
Moderators: Alicia Fátima Gómez (IE University, Madrid, LIBER Executive Board & Open Access Working Group) Raúl Aguilera (REBIUN & Universidad Carlos III de Madrid, LIBER Research Data Management Working Group)
Speakers: Olaf Siegert (Head of Publication Services, ZBW-Leibniz-Informationszentrum Wirtschaft, Germany). Co-chair of the Open Access Working Group Dr. Irene Nooren (Innovation Program Manager, SURF, The Netherlands)
Many universities still have no easily accessible AI policy. Two-in-five UK universities have no AI policy that a student, parent or regulator can easily find online, according to What UK University AI Policies Actually Do: A Study of 96 Institutions (HEPI Policy Note 71) by Professor Sam Illingworth. The paper also argues that most of the 96
This expert report examines how digital infrastructure, now central to essential services such as healthcare, finance, and emergency response, is creating new forms of systemic risk through increasing interdependence.
Public trust is the bedrock of legitimate, effective law enforcement. Its importance grows when law enforcement agencies adopt AI systems. Public attitudes towards AI in policing remain cautious, and trust in law enforcement agencies can strongly influence whether the public accepts new...
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?
Department forScience, Innovation& Technology Foreword by the Secretary of State for Science, Innovation and Technology Artificial intelligence will define the economic and security landscape of the coming decades. But AI does not exist in the abstract.
General guidelines8 May 2026Living guidelines on the responsible use of generative AI in researchAn ERA Forum stakeholders' document.English(739.17 KB - PDF)Download...
UNESCO and the Thomson Reuters Foundation launched this global report “Responsible AI in practice” on 31 March 2026 based on information gathered from 3,000 companies about the Artificial Intelligence-related adoption and strategies. It finds that, as AI development and adoption accelerates rapidly in the private sector, nearly half of the companies (44%) reported having an AI strategy. One in ten companies is also publicly committed to adhering to an AI governance framework.
This brief examines how workers’ exposure to artificial intelligence is measured and what current indicators suggest about the potential transformation of jobs. It clarifies the strengths and limitations of existing approaches and emphasizes that exposure estimates should be interpreted as signals of possible change rather than forecasts of employment outcomes.
Figure from correspondence to The Lancet by Maxim Topaz and colleagues. Fabricated citations in the biomedical literature have increased 12-fold in two years, according to an audit of nearly 2.5 million papers published as a letter to The Lancet today. The analysis of articles indexed in PubMed found that about one in 277 papers published…
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