By 2030 AI will measurably influence and impact more than 8.5 billion people, across all sectors, and human & earth diverse ecosystems on an unprecedented scale. According to a study published in Nature, AI could help achieve 79 % of the Sustainable Development Goals (SDGs), more specifically it can enable the accomplishment of 134 targets across all the goals, but it may also inhibit 59 targets.

Since sustainable development problems affect all countries in different ways on macro and micro levels, that means each country is developing its own scientific AI expertise on a given set of development problems. Some of these overlap across different continents and regions, some are location-specific. Therefore, there is an opportunity to connect the research groups working on this topic and tap into different solutions, case studies, skills and competences in the domain of development as well as AI.

IRCAI including its partners at Data-Pop Alliance, and its personnel have an existing portfolio of setting up such research networks as early as 2004 with NeuroColt, NeuroColt2, PASCAL, PASCAL2, AI4D, ELISE and HumaneAI in 2020 which have empowered an enormous number of researchers and made possible innovation for the transition of AI from a research topic into a worldwide technological phenomenon. At the same time the cumulative basis of all the networks provided funding in the range of 50 million EUR across Europe and beyond.

During the first few networks important lessons were learned that will be applied in NAIXUS. For example, the remarkable success of empowering and trusting people. Therefore, the whole premise of NAIXUS is to encourage people to collaborate and think outside of their particular research interests and help take machine learning into the field of sustainable development.

In order to understand and take advantage of these opportunities Slovenia is launching NAIXUS, a multi-stakeholder initiative which aims to bridge the gap between AI and Sustainable Development by supporting cutting-edge research and applied activities on SDGs-related priorities via a Network of connected research centers and companies around the world.

The Network is focused on R&D and is complementary to all existing international initiatives currently in place, including the UN framework and its initiatives. Additional encouragement for this step also comes from the UN General Assembly A/RES/76/213 “Science, technology and innovation for sustainable development”.

Adopted on 17 December 2021, among others encouraging all stakeholders in an effort to prepare for existing and future opportunities and challenges presented by technological change, including the fourth industrial revolution, among others, to explore ways and means of conducting inclusive national, regional and international technology assessment and foresight exercises on existing, new and emerging technologies to help to evaluate their development potential and mitigate possible negative effects and risks.

The network is expected to mobilise researchers to collaborate on key AI methods and Sustainable Development domain topics, to reach critical mass on these topics and to collaborate across cultural and language barriers and focus on the science that is much needed to push the efforts. Since its launch in March 2021, IRCAI has been having extensive conversations with already 15 core partners across 5 UN regions and plans to launch the network in its current form during the STI 2022 forum.

The initial partners are coming from Slovenia, Australia, Andorra, Brazil, Chile, Ghana, Iceland, Italy, Kenya, Mexico, Netherlands Nigeria, Pakistan, South Africa, Spain, Sweden, Tanzania, UK and USA.

• International Research Centre in Artificial Intelligence under the auspices of UNESCO
• Advanced International Center for Smart Decision Science Applications based on Blockchain And Artificial Intelligence (BAIA Center)
• African Institute for Mathematical Sciences (AIMS)
• Andorra Research + Innovation
• Bio-Robotics Laboratory, National Autonomous University of Mexico
• Data-Pop Alliance
• Data Scientists Network Foundation
• ELLIS Unit Alicante Foundation
• Icelandic Institute for Intelligence Machines
• Knowledge 4 All Foundation 
• Laboratory at the University of the Witwatersrand (RAIL)
• Masakhane Foundation
• Northeastern University, Northeastern Civic A.I.
• Regional Center for Studies on the Development of the Information Society (CETIC)
• Tanzania AI Lab & Community
• The Alan Turing Institute
• TU Delft, Digital Ethics Centre
• Queensland University of Technology
• UNICEF headquarters
• University College London, Centre for Artificial Intelligence
• University Islamabad of the Islamic Republic of Pakistan (COMSATS)
• University of Cape Coast 
• University of Essex 
• University of Gothenburg 
• University of Leeds
• University of Pretoria
• University of Tuscia 

• Make the topic of Sustainable Development relevant for AI;
• Increase the visibility of Sustainable Development topics being solved with the power of AI for scientists, so that it notably becomes relevant for future generations of scientists and breakthroughs in AI;
• Ensure UNESCO’s policy recommendations are ingrained in the key strategic research topics;
• Strengthen the various available platforms with Sustainable Development related data with algorithms, tools, solutions developed by the actions funded by the network;
• Foster mobilization and commitment from the community, including high level experts to contributing to the topic, making it the reference resource for Global researchers, developers, integrators and users;
• Reinforce Global South’s research capacity in AI;
• Pave the way to enrich the education offer in order to equip a broad range of non-ICT professionals and sustainable development experts with the necessary AI skills, to make the best of this technology;
•  Foster exchanges of knowledge and perspectives between and within GS and GN research institutions on key building blocks of AI for SD – access to data, insights, inclusion, governance
• Tackle “blind spots” in AI including Tier 3 SDG indicators, ethical aspects, empowerment issues
• Foster and develop multi-lingual research and products
• Inspire and create opportunities for young researchers and future researchers to grow in and join the field, including to create internal demand and retain talents

• Focus on scientific or technological major challenges, with the primary goal to reinforce capacity and progress in critical technologies;
• Building on existing efforts of already existing platforms, networks and projects, the network will develop mechanisms to spread the latest and most advanced knowledge to all the AI-labs in the United Nations five geographical regions: Africa, Americas, Asia and the Pacific, Europe and Central Asia, and the Middle East and prepare the next generation of talent in AI. Such mechanisms will be defined with all network partners;
• Another objective is also to develop synergies and cross-fertilization between industry and investors in the network of excellence centres, in particular through internships of academic staff (at all levels) in industry, or PhD programmes with industry;
• The network will form a common resource and will become a shared facility, as a virtual laboratory offering access to knowledge and expertise and attracting scientists, investors, policymakers and new talents. It should become a reference, creating an easy entry point to AI excellence across the Global South as well and should also be instrumental for its visibility;
• Creating a data driven benchmark system for the measurement of SDGs to further create a social impact investment ecosystem for AI research and companies.

• The network is spread across all continents, and driven by leading figures in AI from major excellent research centers, bringing the best scientists distributed all over the UNESCO Regions. They will bring on board the necessary level of expertise and variety of disciplines and profiles to achieve their objectives;
• However, it wants to empower those researchers, thinkers, entrepreneurs and specifically projects using AI that otherwise could not reach visibility in global markets, have a meaningful impact or have a voice
• Industrial participation will be ensured through the IRCAI partners network in industry and across incubators and accelerators, and also in bringing expertise to identify important technological limitations hampering deployment in industrial context. Such industrial involvement will thus help defining the research priorities of the network and will raise new research questions.
• Each partner will have to demonstrate access to resources and infrastructure to support R&D, such as data, HPC (central, GPUs, edge computing), storage, robotics equipment, IoT infrastructure, support staff and engineers to develop experiments, etc. All available data sources, including United Nations data where relevant, should be made use of.

• In order to structure the activities, the network will focus on relevant scientific or technological challenges with industrial relevance and investment potential in segments where it can make a difference, either in building on strengths, or strengthening knowledge to fill gaps critical for AI and sustainability;
• Based on these challenges, the network will develop and implement common research agendas;
• Progress will be demonstrated in the context of use-cases, also helping to foster industry-academia collaboration;
• Strong links will be developed among the members of the network, notably through collaborative projects, exchange programmes, or other mechanisms to be defined by the consortia;
• Mechanisms will be designed to foster excellence, to increase efficiency of collaboration, and to develop a vibrant AI network across the world;
• The network will disseminate the latest and most advanced knowledge to all the academic and industrial AI laboratories, and involve them in collaborative projects/exchange programmes;
• The network will develop interactions with the industry (inside the consortium and beyond), and international policymaking organisations in view of triggering new scientific questions and fostering take-up of scientific advances;
• Overall, the network will become a virtual center of excellence, offering access to knowledge and serve as a reference in their chosen specific field, including activities to ensure visibility.

Collaborative projects carried out in network should focus on one or several of the following topics and would involve the necessary competencies available in the network to address these:

• Projects and solutions across all UN regions: Africa, Asia, Europe, Latin America and the Caribbean, Northern America, and Oceania;
• With a strong Machine Learning, Artificial Intelligence or Data Science component, in any discipline of science;
• With a strong emphasis on producing solutions in one or more than one Sustainable Development Goals.

Membership in NAIXUS is free and open to profit and not-for-profit institutions (not individuals). Institutions must be knowledge-generating, i.e. they must conduct research, analyses, and/or data collection, and can be universities, research institutions, foundations, or civil society groups. Members have to be involved in research and/or education to participate in the global network. Member institutions should have deep expertise in one or more areas related to atificial intelligence and sustainable development and commit a substantial amount of their own work towards finding and/or implementing solutions in AI for the SDGs.