Asia-Europe for Artificial Intelligence (AE4AI) Network

 THE ASIA AND EUROPE FOR AI (AE4AI) NETWORK

The Asia-Europe for Artificial Intelligence (AE4AI) Network was established by the participants of the ASEF Higher Education Innovation Laboratory project series in October 2023, in Shanghai, China. Founding members are 20 academics and managers of higher education institutions, and Alumni of the ASEFInnoLab project. All subsequent Alumni of the project series is invited to join.

The network was launched by releasing a Joint Statement of Founding Members, to highlight areas of importance to the network and to address these areas through a peer-to-peer collaboration.

Thematic areas of the Network 

AI Governance

The difficulty of regulating AI due to its complex nature and rapid development leads to having various fragmented efforts in place but with no coherent legislation to govern and guide them. The current absence of regulations has led national, regional, and global institutions to come up with diverse guidelines to encourage responsible design and deployment of AI. Legislative efforts generally aim at striking a balance between security and development but remain fragmented. Regulation may lead to short-term economic losses; but long-term benefits from AI that is trustworthy, ethical, secure, humane, and standardised are foreseen to outweigh these.

We call for the collective task of fostering a global initiative for knowledge exchange and building consensus on key AI concepts, priorities, security and standards as a first step towards meaningful governance of AI. Current guidelines stand as sources of key values that should be integrated in AI efforts moving forward, such as security, openness and transparency, ethical deployment, the use of AI for sustainable development, instilling human-centred values into AI, and establishing co-accountability and shared responsibility.

Thus AE4AI Network puts an emphasis on:

On AI governance, we encourage states to seek balance between data protection and data openness which is crucial for the successful development of AI. Efforts to regulate AI must not only be for risk management, but also for sustainable development. Global standards must be developed for both data and algorithms to help more equitable distribution of data, tools, technologies, and benefits for all societies.

On building an AI ecosystem, there is a need to define and shape societies’ understanding of equitable AI implementation for individuals and organisations in recognition of the importance of knowledge- and awareness-building in empowering collective action for AI.

On approaching AI regulations, we encourage the use of scenario-thinking and foresight-informed methods that could help identify the key drivers for short-term and long-term developments. By analysing these scenarios, we aim to establish frameworks, build partnerships, create common regulations, and cultivate common values.

Action Lines: 

Set up the Asia-Europe Policy Centre for AI Governance to:

• Organise a periodic exchange and report of state-of-the-art AI safety techniques;
• Perform analyses on the job tasks in which AI is likely to replace humans; 
• Publish policy briefs on insights and recommendations directed to regulators, focused on key insights: in AI safety, to determine the needs for our workforce capability development, curricula adaptation and higher education reinvention, as well as the specific needs for AI regulation, that our new reality will bring; 
• Organise awareness-building events that disseminate the policy briefs and facilitate the necessary multi-stakeholder discourse. 

AI Governance Coordinators:

• Prof Raphael WEUTS (Belgium), Visiting Professor of Artificial Intelligence, UC Leuven 
• Prof Robert BILLONES (The Philippines),  Full Professor and CEO, Intelligent Systems Innovation, De La Salle University Manila 

AI in Education

With the emergence of AI and its prolific use in education and research, universities are urged to cultivate an environment conducive to the nurturing of a high-demand skill set among learners effectively addressing the changing demands of the job market. Institutions of higher education play a pivotal role in realising the transformative potential of AI in education.

We aspire to equip the forthcoming generation with the competencies and outlook needed for propelling technological innovation, nurturing economic growth, and equitable societal development through the exploration of pioneering pedagogical methodologies, robust industry alliances, and the facilitation of entrepreneurship. Building and sustaining intellectual curiosity, encouraging the use of AI to adapt to the future, developing an AI literacy framework, and investing in innovative AI curriculum are some priorities we must bear in mind as educators.

Thus AE4AI Network puts an emphasis:

On developing AI skills and content, AI in education should promote an equitable access to AI learning and skills development and relevant competencies that would benefit learners across different disciplines. AI-embedded learning should provide opportunities to include low-level coding or no-code programming at all levels of education in Asia and Europe. In the pursuit of talent development in AI, higher education institutions have both the responsibility and capability to ensure that AI education is inclusive, ethical, and transformative.

On increasing social awareness on AI, we believe universities should take an active role in the open and accessible reskilling and upskilling of the public on the basics of AI, emphasising its risks, opportunities, as well as responsible, and ethical use.

On formulating learning and teaching methodologies, creation of self-paced learning opportunities, partnerships for shared accountability for learning processes, and provision of opportunities for meaningful interactions should be priorities. Concepts such as enabling spaces, outcomes-based education (OBE), nonviolent communication (NVC), reverse mentoring, the corporate perspective, and affirmative inquiry should inform methodologies to teaching and learning.

On building institutional capacity to conduct policy dialogue and strengthen educational capabilities, resilience, and develop reliability, there is a need to first address the lack of full engagement from stakeholders (policymakers, universities, etc.). Furthermore, international collaboration in addressing the challenges of adapting AI is key. It is also important to pinpoint where to catalyse change in universities and promote AI-friendly culture in higher education and provide incentives, especially in developing countries.

Action Lines: 

• Create a self-paced course covering AI literacy empowered by Generative AI technologies. Consider the train-the-trainer approach targeting academics and local community members, in their local language. Consider segmenting the content along “learning about AI” and “learning with AI” categories, customized to the target group, and providing certification (e.g. micro credentials).  

• Build a platform to incentivize open collaboration, by featuring information and partnership opportunities from various sources (e.g. EU funded projects, Leadership in Innovation Fellowship, etc.). The key goal of the platform is to incentivize forming consortiums to work on AI in Education initiatives.  

AI in Education Coordinators:

• Dr Monika SONTA (Poland), Adjunct, Researcher, Head of The Bachelor in Management & Artificial Intelligence Program, Kozminski University
• Dr Rahul BHANDARI (India), Joint Director and Asst Professor, School of Management and The Office of International Study Abroad Program, O.P. Jindal Global University
• Dr Vicente PITOGO (The Philippines), Dean of the College of Computing and Information Sciences, Caraga State University

AI for Sustainable Development

Due to the cross-cutting, encompassing nature of the Sustainable Development Goals (SDGs), the role of AI in their achievement has become an important topic of discussion as the world races to meet global sustainability targets. We recognise the enormous potential of AI to accelerate efforts to achieve the SDGs, specifically in the promotion of economic growth, environmental conservation, and improving the quality of life of our peoples. Thus, AI development should be guided by the objectives of addressing pressing global problems of poverty, inequality in access, climate change, environmental degradation, food security, economic productivity, quality education, access to healthcare, energy security, gender and racial discrimination, and sustainable cities and communities.

Universities have a unique position to become leaders in AI for sustainable development. It is paramount that they foster multi-lateral collaboration and partnerships between different stakeholders (including public, private, and non-governmental) to conduct multi-disciplinary research which includes STEM and social sciences and address real-world multi-faceted issues.

Thus AE4AI Network puts an emphasis:

On raising awareness on AI potential, there is a need to increase knowledge on the full potential of ethical AI adoption for sustainable development to ensure intergenerational justice that promotes diversity and inclusivity, protects human rights, and enrich human agency through its capability to inform, guide, and direct.

On promoting environmentally responsible AI, sustainable AI designs and best practices for the development of AI should be used to balance carbon emissions generated in deployment. To make its responsibleness tangible, AI should carry the bill for its carbon footprint.

On contributing to socio-cultural dynamics of sustainable development, focus should be given on addressing real and specific societal issues in increasing social capabilities and cultivating social cohesion through AI deployment and development. AI for sustainable development should generate feasible, trustworthy solutions that make humans more aware of interdependencies in their reality.

Action Lines: 

Create a virtual AI4SDG Asia-Europe open platform to facilitate awareness, showcase activities, highlight projects, and research that aligns with the 17 SDGs through:

• Creating exposure and mobilising private-public partnership and funding;
• Showcasing courses and train-the-trainor programmes across Asia and Europe focusing on the implementation of AI to achieve the SDGs; 
• Promoting and encouraging data-sharing and data sets used in the activities on the open platform; 
• Organising periodic forums to compare and exchange best practices with a view to foster open collaboration. 

AI for Sustainable Development Coordinators:

• Dr Sharina YUNUS (Brunei Darussalam), Director of Enterprise Office, Assistant Professor, Faculty of Engineering, Universiti Teknologi Brunei 
• Dr Yang BONG (United Kingdom), N/Lab, Centre for AI Research for Social Good, Nottingham University Business School, United Kingdom 

Contact

The website of the AE4AI Network is under development. In the meantime feel free to contact ASEF at E: innolab [at] asef.org email address for further information.

Founding Members include (in alphabetical order of country): Dr Akhtar Ali JALBANI, Senior Lecturer, Holmesglen, Australia; Prof Raphaël WEUTS, Visiting professor of Artificial Intelligence, UC Leuven, Belgium; Dr Sharina YUNUS, Deputy Director of the Enterprise Office, Universiti Teknologi Brunei, Brunei Darussalam; Prof SHEN Yi, Professor, Department of International Politics, Director of International Institution of Global Cyberspace Governance, Fudan University, China; Mr Fan Weiei, Founder, Google Developer Startup incubator, China; Mr Andres PEÑA ARCHILA, Project Manager, Nexus Incubator, University of Helsinki, Finland; Dr Rahul BHANDARI, Joint Director and Asst Professor, O.P. Jindal Global University, India; Mr Iwan ADHICANDRA, Head of Informatics Department, Bakrie University, Indonesia; Dr Edi Triono NURYATNO, Head of Aerospace Health Informatics Research Group and Health Informatician. Adisutjipto Institute of Aerospace Technology, Indonesia; Ms Katerina CERNAVSKA, Lecturer, Riga Business School, Riga Technical University, Latvia; Dr Claudio RIVERA, Dean, Riga Business School, Riga Technical University, Latvia; Dr Paula ELKSNE, Director, Education Innovation Lab, Riga Business School, Riga Technical University, Latvia; Dr Lampros STERGIOLAS, UNESCO Chair on Artificial Intelligence and Data Science for Society, The Hague University of Applied Sciences, Netherlands; Dr Robert Kerwin BILLONES, Full Professor and Research Fellow, De La Salle University Manila; Philippines; Dr Vicente PITOGO, Dean, College of Computing and Information Science, Caraga State University, Philippines; Mr Orland TUBOLA, Director of Research Institute for Strategic Foresight and Innovation, Polytechnic University of the Philippines, Philippines; Ms Monika SOŃTA, Adjunct Professor, Researcher, Head of The Bachelor in Management & Artificial Intelligence Program, Kozminski University, Poland; Ms Renata BACAROVA, Head of Technology Transfer Office in Technology and Innovation Park, Pavol Jozef Safarik University in Kosice, Slovakia; Mr Yang BONG, Teaching Affiliate, N/Lab, a Centre for AI Research for Social Good, University of Nottingham, United Kingdom; Dr Minjia CHEN, Assistant Professor in Finance, University of Nottingham, United Kingdom; Ms Ha Le THu HOAI, Deputy Director of Project Design Education Center, Ho Chi Minh City University of Economics and Finance, Viet Nam; Ms Reka TOZSA, Director, Education Department, Asia-Europe Foundation (ASEF); Ms Cleo CACHAPERO, Senior Project Executive, Higher Education Policy Programme Asia-Europe Foundation (ASEF); Mr Miguel PANGALANGAN, Project Executive, Higher Education Policy Programme, Asia-Europe Foundation (ASEF).