Update as of 12 April:
The Call for Interest for the ASEFInnoLab7 White Paper Lab is now closed.
CALL FOR INTEREST
ASEFInnoLab7 White Paper Lab
Background
Established in 2021, the ASEF Higher Education Innovation Laboratory (ASEFInnoLab) creates opportunities for higher education stakeholders from Asia and Europe to expand their professional network, exchange knowledge, and collaboratively build their capacity to address common global challenges. Guided by its overarching theme of “Universities’ Role in AI Innovation Ecosystems,” ASEFInnoLab stands as a unique platform for higher education stakeholders to exchange good practices and co-create new ideas at the intersection of education, research, and innovation.
Read about the project series or explore the highlights of ASEFInnoLab6—our previous edition—to know more about the programme and its impact in enhancing dialogue on AI for the collective good.
In its seventh edition, the project will bring together outstanding experts, scholars, and changemakers to explore universities’ role in advancing AI for humanity’s benefit.
Topic Overview
Through this edition bearing the theme “The Role of Universities in Advancing AI for Good”, ASEFInnoLab7 will explore how AI is researched, governed, and applied at universities in service of the common good.
The ASEFInnoLab7 will deliver two main components: a white paper lab and a public webinar series. This call is only for the white paper lab component. These outputs will articulate strategic pathways for higher education institutions, providing insights to higher education leaders and education policymaker. The white papers will focus on following areas:
- #AI4GlobalGood: Universities harnessing AI to contribute to global social, environmental, or economic sustainability and the Sustainable Development Goals (SDGs)
- #AI4PublicInterest: Universities strengthening public understanding, inclusion, trust, and engagement through policymakers, legislators and the broader public
- #AI4InstitutionalExcellence: Universities seeking proper AI governance, policies, and infrastructure for enhanced excellence of the institution and its contribution to public good
Participants will collaborate in teams of 5-6 on the following white paper topics:
Coordinator: Prof Shen Yi (Fudan University)
Artificial intelligence technology poses a risk of widening the digital divide and further giving rise to a new unequal development trend—the Intelligence Divide. One possible future scenario is that due to the imperfect digital infrastructure and the lack of accessibility of digital elements in the Global South countries, the economic value created by artificial intelligence is concentrated in developed countries, while the Global South is facing a broader problem of exploitation. To bridge the digital divide and bridge the potential intelligence gap, extensive cooperation can be carried out among universities in Asia and Europe to promote talent exchange, capacity building and knowledge sharing. For this reason, this topic aims to explore a cooperation framework among universities affiliated with ASEF oriented towards equal development and promote it as part of a digital infrastructure globally.
Coordinators: Dr Yang Bong & Dr Neelima Sailaja (University of Nottingham)
In much of AI for Good discourse, what counts as “good” is too often determined externally rather than by the communities themselves, i.e. before local contexts are adequately understood. Universities, as institutions for public good, have both the opportunity and the obligation to address this by reorienting who AI is designed with and for. This paper proposes a capability-centred framework for university-led AI initiatives for sustainable development in marginalised contexts, with particular attention to underserved communities across Asia and Europe. Rather than asking what problems AI can solve, the paper calls for a bottom-up approach that starts with what communities value: the freedoms, aspirations, and futures they seek to realise. This also entails understanding which institutional and structural conditions enable or prevent these capabilities from being realised. This reframing shifts the emphasis from problem-solving to capacity expansion, from technological imposition to locally grounded innovation, and from community deficit to community agency.
Coordinator: Prof Dr Daniel Burgos (International University of La Rioja)
Generative Artificial Intelligence (GenAI) is becoming ubiquitous in many areas of society and the productive sector. In the higher education system, it is an instrument that is rapidly transforming the way we study, teach, and manage academically. In industry, the development and achievements of competencies and upskilling is a non-stop challenge that might be benefited by the use of AI, under a certain, personalised methodology. In society, in general, the combination of ethics, regulations, and social agreements and habits make the integration of AI a cross-cutting issue that might help shape society itself, along with people’s interaction and common goals, if properly implemented. In this context, this paper will investigate and present evidence, conclusions, and recommendations on the effective contribution of GenAI to various sectors and stakeholders (alone and combined as a whole) towards the ultimate goal of the common good in society.
Coordinator: Prof Lampros Stergioulas (The Hague University of Applied Sciences)
The aim of the paper is to analyse the needs of invisible, under-represented groups in Data and/or AI systems, as well as the rapidly growing AI-related multi-scale divides and inequalities from a global perspective, and explore how integrated AI approaches and digital platforms can improve coordination, data flow and AI operational performance. Frameworks and recommendations will be crafted towards harmonised cross-national data and AI infrastructures with built-in protection and privacy-by-design mechanisms and strategies, to augment representation, ensure interoperability across countries and cross-national comparability, preserve ethical principles and human rights, and enable equity for all. Alignment with international regulatory initiatives and standards around the world as well as appropriate roadmaps for key sectors of the economy will be included.
Coordinators: Prof Zainal Abidin Sanusi & Prof Mira Kartiwi (International Islamic University Malaysia)
As AI systems increasingly perform cognitive and productive tasks traditionally associated with students and academics alike, higher education faces a critical question: how can learning continue to cultivate critical thinking, intellectual agency, and human formation in an AI-mediated world? This white paper advances humanising learning as a strategic, evidence-informed, and policy-oriented framework for the AI era. Humanising learning that does not seek to restrict AI use, but reframes education around the capacities that remain distinctly human, such as judgement, ethical reasoning, creativity, and reflective understanding. Drawing on the authors’ combined expertise in faculty professional development, institutional capacity-building, and the technical foundations of machine learning and data analytics, the paper moves beyond theoretical framing to offer actionable pathways for universities, governments, and regional higher education networks.
Coordinator: Dr Shalinka Jayatilleke (La Trobe University)
Generative AI (GenAI) is rapidly transforming higher education, yet institutional responses remain fragmented across teaching and learning, assessment, research ethics, student support, staff capability, equity, data privacy, and public transparency. This white paper offers a comparative cross-regional analysis of GenAI-related policies across selected institutions in Asia, Europe, and Australia. Moving beyond policy inventories, it examines how universities can build coherent governance architectures that translate ethical principles into operational practice across diverse institutional and socio-cultural contexts. The paper will develop an inclusive, transferable framework to strengthen institutional readiness, support equitable access to AI, and foster sustainable public trust for all stakeholders.
Coordinators: Dr João Pita Costa, Dr Anja Polajnar, and Mr Davor Orlic (International Research Centre On Artificial Intelligence)
This initiative focuses on strengthening sustainability knowledge ecosystems and advancing education for the Sustainable Development Goals (SDGs). A small group of experts will work together with an SDG-informed AI agent capable of analysing global knowledge sources—including news media, scientific publications, public policy documents, and innovation ecosystem data—to identify emerging trends, narratives, and evidence related to sustainability and SDG progress. The project specifically addresses two key challenges in the current sustainability knowledge landscape: the spread of misinformation and fragmented narratives in sustainability discourse, and the limited accessibility of high-quality, multilingual educational resources on SDGs. By combining AI-driven knowledge synthesis with expert academic interpretation, the initiative will explore how universities can use AI tools to analyse sustainability narratives, identify evidence-based insights, and transform global knowledge into data-driven multilingual Open Educational Resources (OERs) that support inclusive sustainability education.
Coordinator: Dr Sharina Yunus (Universiti Teknologi Brunei)
Artificial Intelligence offers a powerful opportunity to accelerate progress toward the Sustainable Development Goals when technological innovation, sustainability priorities, and governance frameworks evolve together. Across Asia and Europe, universities are increasingly developing AI-driven solutions for challenges such as climate monitoring, renewable energy optimisation, sustainable agriculture, and inclusive digital services. Yet these innovations are often dispersed across research projects and pilot initiatives without strong pathways to inform national sustainability strategies. This white paper explores how universities can act as catalysts within national AI–SDG ecosystems, helping governments harness AI innovation in ways that advance environmental sustainability, social well-being, and responsible governance.
Coordinators: Dr Tejpavan Gandhok & Prof Spriha Bhandari (O.P. Jindal Global University)
In this white paper, we first seek to demonstrate the value-added of leading universities as key AI policy architects and advocates by articulating suitable framework(s) for various combinations of types of AI technologies (e.g. vision recognition , machine learning / general pattern recognition, generative AI & LLMs; agentic and autonomous AI, etc.) as embedded in a variety of use cases. Then for several of these key combinations, articulating the different policy stances to consider for their appropriate exploration/exploitation (ranging from full speed ahead, to sandboxed, to defining specific key guard rails, to go slow/regulate carefully, etc). We then seek to illustrate and inspire further the key role leading universities can play in several of these key stances as a bridge, a sandbox, accelerator, and a futures architect.
Who are we looking for?
We will select 50 academics, researchers, and experts from Asia and Europe based in ASEM Partner Countries who spearhead/work with AI-related teaching, learning, research, management initiatives. Technical background is welcome but not required, as there will be no technological exchanges in the programme.
Read more about the eligibility and selection criteria below:
What will our participants get out of ASEFInnoLab7?
Knowledge, ideas, connections, and a project.
Programme Design
The ASEFInnoLab7 programme will offer both online and onsite components. For applicants of this Call for Interest, the journey will begin in May after a thorough selection process.
- Online Introductory Sessions: Selected participants will be onboarded through three introductory webinar sessions for the whole ASEFInnoLab7 cohort, which will take place on 15, 22, and 29 May. They will familiarise themselves with the principles of project aim, white paper development and teamwork.
- Self-organised Team Collaboration: Between June to August, participants will collaborate with their assigned team of 5-6 to develop the first draft of their white paper under the leadership of their team coordinator. These sessions will be self-organised and online. The teams will be finalising their initial white paper drafts in a similar fashion between September and November.
- Onsite Event: The teams will be invited to present their draft at the ASEFInnoLab7 Conference to be hosted by University of Nottingham in the United Kingdom in August 2026. As an experiential, collaborative programme, the conference will welcome around 60 participating experts and will have an array of interactive sessions that will facilitate peer-to-peer learning to aid the finalisation of the white papers.
What commitment is needed?
Invited participants are required to commit to and attend the virtual onboarding phase and the in-person conference at University of Nottingham, United Kingdom.
Given the importance of rich intellectual exchanges in the white paper co-creation process, invited participants are also required to actively contribute to the drafting and finalisation periods.
Interested in this journey?
Read more on the stacked previous edition ASEFInnoLab6 here and check out our highlight video below to get a picture of our onsite events.
And what do our alumni say? You may read the testimonials of participants of past ASEFInnoLab editions and hear their reflections on the experience and connections gained through their involvement!
