Science in the Age of AI: Knowledge, Data, and Trust


International Science Council & Committee on Data of the ISC

Session 216

Tuesday, 7 July 2026 17:00–17:45 (UTC+02:00) Physical (on-site) and Virtual (remote) participation Room A, ITU Tower Building Interactive Session
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Physical (on-site) and Virtual (remote) participation


Background
Artificial Intelligence is reshaping the scientific enterprise, but current governance discussions have paid insufficient attention to AI's systemic implications for science as a knowledge system. While social, economic, ethical, and technical dimensions of AI are being debated in multilateral forums, the impact on scientific knowledge production, validation, and sharing has been largely overlooked. This gap is particularly significant for science institutions and researchers in the Global South, who face distinct challenges: openly available scientific data generated in their regions is increasingly harvested to train commercial AI systems without reciprocal benefit or data governance frameworks that protect scientific sovereignty.

The International Science Council's Science Systems Futures programme and AI disclosure in research initiative, alongside CODATA's work on FAIR data and governance for AI, demonstrate that the international science community has begun to address these questions. However, these initiatives remain dispersed across institutional networks. The WSIS Forum provides a critical venue to surface this evidence base and connect it to broader digital governance conversations, ensuring that science's stakes in responsible AI development are visible to policymakers and multilateral processes.

Session themes
The session examines three interconnected dimensions: (1) AI and knowledge generation—how autonomous AI roles in research affect the scientific method and who counts as a knowledge producer; (2) Scientific data and AI models—the tension between open science principles and data sovereignty, especially for the Global South; and (3) Reliability and research integrity—what governance mechanisms are needed as AI-generated outputs enter the scientific record.

Relevant projects and practices
The session draws on evidence from multiple initiatives: ISC's work on a global AI disclosure standard for research (the Vancouver Standard); CODATA's Task Groups on data quality and governance for AI; and national examples of science systems navigating public-private partnerships around emerging technologies in the Global South. These initiatives provide practical grounding for discussions about what norms, standards, and frameworks are needed.

Vision for WSIS Beyond 2025
The WSIS commitment to science as a global public good (reflected in action line C7 on E-science) must evolve to address AI's role in determining what knowledge gets produced, who produces it, and who benefits from it. WSIS Beyond 2025 should position the science and research community as central stakeholders in AI governance, ensuring that discussions of data governance (GDC Objective 4) and responsible AI (GDC Objective 5) are grounded in the needs and equity concerns of the global scientific enterprise, particularly in the Global South.

Panellists
Prof. Vukosi Marivate ABSA UP Chair of Data Science University of Pretoria

Prof. Vukosi Marivate is Director of AfriDSAI and ABSA UP Chair of Data Science at the University of Pretoria. He leads Data Science for Social Impact and co-founded Lelapa AI, Masakhane, and Deep Learning Indaba, advancing AI for Africans by Africans.


Dr. Marion Mercier Science Anticipation Integration Manager Geneva Science and Diplomacy Anticipator (Switzerland)

Marion Mercier is Programme Manager for the GESDA Science Breakthrough Radar High-Level Review, where she oversees and facilitates the evaluation and strategic development of GESDA’s science anticipation work. Prior to this, she was a Research Manager at the Wellcome Trust, where she managed a broad and diverse research portfolio and led scoping work for emerging funding opportunities in discovery science.


Prof. David Castle Professor, Public Administration University of Victoria (Canada) Moderator

Dr. David Castle is a professor of science, technology and innovation policy in the School of Public Administration, University of Victoria. His research focuses socio-economic aspects of biodiversity, especially natural capital accounting and access and benefits sharing of genetic resources.

He is a researcher in residence at the Office of the Chief Science Advisor, Canada where he advises on science policy, open science, research security, major research infrastructure and biodiversity. He chairs the Scientific Committee of the International Science Council's World Data System (WDS).


Dr. Kamil Dziubek University Assistant University of Vienna (Austria)

I am studying effects of high pressure on matter, ranging from elements to proteins. My research aims to better understand chemistry at extreme conditions, which often goes beyond textbook knowledge and requires to revise the working models.
 


Dr. Moses Thiga Director of ICT Egerton University

Dr. Moses M. Thiga is a dynamic leader and researcher in ICT, currently serving as the Director of ICT at Egerton University and the Founder and Executive Director of the Savannah Digital Research Institute. With a Ph.D. in Information Systems, he possesses extensive experience in developing and implementing ICT strategies, overseeing projects, and formulating policies. Dr. Thiga is also an Adjunct Lecturer at the European Business Institute, teaching courses in deep learning, data science, and AI.


Mr. Alistair Nolan Senior Policy Analyst OECD (France)

Alistair Nolan is a Senior Policy Analyst in the OECD’s Directorate for Science, Technology and Innovation. Prior to the OECD, Mr. Nolan led a range of industry-related analytic and technical assistance projects with the United Nations. Over a number of years at the OECD Alistair has been involved in work on skills and education assessment, entrepreneurship, private sector development and policy evaluation. Alistair is currently coordinating various streams of OECD work on artificial intelligence, and is overseeing the work on AI diffusion under the AI-WIPS project. Mr. Nolan oversaw preparation of the 2017 publication The Next Production Revolution: Implications for Governments and Business, which examines a variety of emerging technologies, their impacts and policy implications, and which was referenced at the start of the 2017 G7 Taormina Action Plan. Mr. Nolan led work on 2020 publication The Digitalisation of Science, Technology and Innovation : Key Developments and Policies, which among other topics addresses the role of AI in advanced production.


Dr. Vanessa McBride Science Director International Science Council Moderator

Vanessa has a PhD in Astronomy from the University of Southampton. She has over fifteen years of experience, including various leadership roles, across university, research infrastructure and science-for-development settings in an international arena. She joins the ISC from the International Astronomical Union’s Office for Astronomy for Development, where she bridged the gap between the academic astronomy and development communities. Vanessa brings a passion for science and society, a perspective from the global south, and a connection with the member organizations of ISC.


Topics
Artificial Intelligence Digital Transformation Emerging Technologies
WSIS Action Lines
  • AL C2 logo C2. Information and communication infrastructure
  • AL C3 logo C3. Access to information and knowledge
  • AL C4 logo C4. Capacity building
  • AL C6 logo C6. Enabling environment
  • AL C7 E–SCI logo C7. ICT applications: benefits in all aspects of life — E-science
  • AL C10 logo C10. Ethical dimensions of the Information Society
  • AL C11 logo C11. International and regional cooperation

C2 (Information and communication infrastructure): AI governance requires understanding how data infrastructure—where it is stored, who controls it, how it flows—shapes scientific capacity in different regions.
C3 (Access to information and knowledge): Open science principles intersect with AI's use of scientific data; governance frameworks must balance openness with equitable control and benefit-sharing.
C4 (Capacity building): Science institutions require new skills and governance capacities to navigate AI's integration into research, particularly in the Global South.
C6 (Enabling environment): Policy frameworks are needed to support responsible AI use in research while protecting scientific integrity and data sovereignty.
C7 (ICT applications: E-science): This is the core action line; the session directly addresses how AI, as an emerging ICT, reshapes scientific discovery and research systems.
C10 (Ethical dimensions of the Information Society): AI in science raises fundamental questions about research ethics, accountability, and the public interest.
C11 (International and regional cooperation): Equitable AI governance for science requires multilateral cooperation and frameworks that serve all regions.

Sustainable Development Goals
  • Goal 4 logo Goal 4: Ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
  • Goal 9 logo Goal 9: Build resilient infrastructure, promote sustainable industrialization and foster innovation
  • Goal 16 logo Goal 16: Promote just, peaceful and inclusive societies
  • Goal 17 logo Goal 17: Revitalize the global partnership for sustainable development

SDG 4 (Quality education): AI's role in knowledge production affects how science education and research training evolve.
SDG 9 (Industry, innovation, infrastructure): Science and technology innovation increasingly depends on AI; governance of this intersection shapes innovation pathways globally.
SDG 16 (Peace, justice, and strong institutions): Research integrity and trustworthy knowledge are foundations for evidence-based policymaking.
SDG 17 (Partnerships for the goals): Equitable public-private partnerships in science-technology sectors depend on governance frameworks that protect public interest and Global South equity.

GDC Objectives
  • Objective 1: Close all digital divides and accelerate progress across the Sustainable Development Goals
  • Objective 4: Advance responsible, equitable and interoperable data governance approaches
  • Objective 5: Enhance international governance of artificial intelligence for the benefit of humanity
Links

https://council.science/events/wsis-forum-2026/

https://council.science/our-work/science-systems-futures/