The mission of IRCAI is to advance AI research in sustainable development to improve the human condition. With this in mind, we are inviting the AI in SDGs research community, policymakers, and companies to join us and to “self-organize” with us small online workshops to explore research themes in areas related to various aspects of our common vision. We will help our colleagues in their interdisciplinary collaborations with our infrastructure and to the best of our abilities.



Location: Taiwan
Date: 26 October 2021
Registration: Zoom link

There is a strong consensus that artificial intelligence (AI) will bring forth changes that will be much more profound than any other technological revolution in human history. Depending on the course that this revolution takes, AI will either empower our ability to make more informed choices or reduce human autonomy; expand the human experience or replace it; create new forms of human activity or make existing jobs redundant; help distribute well-being for many or increase the concentration of power and wealth in the hands of a few; expand democracy in our societies or put it in danger. The choices we face today are related to fundamental ethical issues about the impact of AI on society, in particular, how it affects labor, social interactions, healthcare, privacy, fairness and security. The ability to make the right choices requires new solutions to fundamental scientific questions in AI and human-computer interaction (HCI). There is a need of shaping the AI revolution in a direction that is beneficial to humans both individually and societally, and that adheres to ethical values and social, cultural, legal, and political norms.

Human-Centered AI (HCAI) is an emerging discipline that aims to create AI systems that amplify and augment human abilities and preserve human control in order to make AI partnerships more productive, enjoyable, and fair. Our workshop aims to bring together researchers and practitioners from the IRCAI and NTU communities and others with convergent interests in HCAI. With an emphasis on internationality, diversity and discussion, we will explore research questions that stem from the increasingly wide-spread usage of machine learning algorithms across all areas of society, with a specific focus on understanding both technical and design requirements for HCAI systems, as well as how to evaluate the efficacy and effects of HCAI systems. This workshop is intended to be a working group to co-construct new and combined perspectives and potentially bring forward the idea of introducing HCAI into the new IRCAI Network of Centers of Excellence in AI. We will therefore allocate much of the time for short presentations.


  • Help build trust in AI as a technology
  • Promote transparency in AI
  • Create positive/enthusiasm for AI
  • Create a report to be uploaded into the IRCAI library


9:05 – 9:15 CET – Introduction and Welcome
Opening and Introduction
• Jane Yung-jen Hsu
• John Shawe-Taylor

Overview of the field and current topics in Human-Centered AI (HCAI)
• Background
• Over-Arching Challenges
• Areas of Action

9:15 – 10:15 CET – Panel 1
Roundtable on Technology towards Human-Centered AI moderated by Lenart Kucic, independent journalist
There is a strong consensus that AI will beget changes far more profound than any other technological revolution in human history. Depending on the course that this revolution takes, AI will either empower our ability to make more informed choices or reduce human autonomy; expand the human experience or replace it; create new forms of human activity or make existing jobs redundant; help distribute well-being for many or increase the concentration of power and wealth in the hands of a few; expand or endanger democracy in our societies.

Key topics to be discussed:
• Key advances in AI technology
• Impacts on humans/society
• Data-driven vs. human-centered
• Improved technology?

Presentations on Technical Perspectives:
• Min Sun
• Hung-yi Lee
• Nuria Oliver
• Jan Hajic

10:30 – 11:30 CET – Panel 2
Roundtable on Human-Centered AI Interaction moderated by Lenart Kucic, independent journalist
A key challenge is that HCAI solutions cannot be found by working within the traditional AI silos, but instead require breakthroughs at the interfaces of various areas of AI, HCI, cognitive science, social science, complex systems, etc. Thus, we need to bring together a unique community which has the expertise both within these silos and at the interfaces between them and can address those challenges.

Key topics to be discussed:
• Social interactions
• Ethical Issues of AI
• Impacts on society, e.g. information bubbles
• AI governance
• AI for Society 5.0

Presentations on Sociological Perspectives:
• Yueh-Hsuan Weng
• Su-Ling Yeh
• Yvonne Rogers
• Marija Slavkovik


  •  Min Sun received his M.S. from Stanford University and Ph.D. from the University of Michigan at Ann Arbor in 2007 and 2012, respectively. He is an expert in Computer Vision and Machine Learning (especially Deep Learning). his research interests include 3D object recognition, human pose estimation, scene understanding, video understanding, text summarization, reinforcement learning, and neural architecture search. Through research breakthroughs, his ultimate goal is to build game-changing applications to be used in our daily life. Dr. Sun also holds 4 U.S. patents and has published 50+ top AI conference papers. He won the Microsoft Research Asia Collaborative Grant in 2016, and the Digital Drift Best Paper on Deep Learning for Visual Analysis in 2016, CVGIP Best Paper Awards from 2015-2017, the Outstanding Research Award from MOST Taiwan in 2018, and Ta-You Wu Memorial Award From MOST Taiwan in 2018.
  • Hung-yi Lee received the M.S. and Ph.D. degrees from National Taiwan University (NTU), Taipei, Taiwan, in 2010 and 2012, respectively. From September 2012 to August 2013, he was a postdoctoral fellow in Research Center for Information Technology Innovation, Academia Sinica. From September 2013 to July 2014, he was a visiting scientist at the Spoken Language Systems Group of MIT Computer Science and Artificial Intelligence Laboratory (CSAIL).
  • Su-Ling Yeh received her B.S. and M.S. degrees in Psychology from National Taiwan University (NTU), Taiwan, and Ph.D. degree in cognitive psychology from the University of California, Berkeley, USA. Since 1994, she has been with the Department of Psychology, NTU and was awarded Lifetime Distinguished Professorship in 2012. She is a recipient of Academic award of Ministry of Education and Distinguished Research Award of National Science Council of Taiwan. She is an APS (American Psychological Science) fellow, and 2019-20 Stanford-Taiwan Social Science Fellow at the Center for Advanced Study in the Behavioral Sciences, Stanford University. She serves as associate director of NTU Center for Artificial Intelligence and Advanced Robotics. Her research interests include cognitive neuroscience, perception, attention, consciousness, multisensory integration, aging, and applied research on display technology, eye tracking device, affective computing, and AI/robots.
  • Yueh-Hsuan Weng is an Assistant Professor at FRIS, Tohoku University and a Visiting Scientist at RIKEN-AIP in Tokyo. He has been appointed as Tohoku University Prominent Research Fellow (2021), Stanford Law School’s TTLF Fellow (2018-2021), Visiting Assistant Professor at The University of Hong Kong (2018), Peking University’s Yahoo! Research Fellow (2010-2014). He received his Ph.D. in Law from Peking University and his M.S. in Computer Science from National (Yang Ming) Chiao Tung University. He is strongly interested in interdisciplinary studies, especially in issues concerning the interface between Artificial Intelligence and Law, including Robot Law, Social Robotics, and Legal Informatics. During his Ph.D. studies, he has founded ROBOLAW.ASIA and CHINA-LII, which are China’s first initiatives in AI Law and Free Access to Law. Currently he is also an Associate Editor of Delphi – Interdisciplinary Review of Emerging Technologies (Berlin: Lexxion Publisher).
  • Jane Yung-jen Hsu is a professor and department chair of Computer Science and Information Engineering at National Taiwan University. Her research interests include multi-agent systems, intelligent data analysis, commonsense knowledge, and context-aware computing. Prof. Hsu is the director of the Intel-NTU Connected Context Computing Center, featuring global research collaboration among NTU, Intel, and the National Science Council of Taiwan. She serves on the editorial board of Journal of Information Science and Engineering (2010-), International Journal of Service Oriented Computing and Applications (Springer, 2007-2009) and Intelligent Data Analysis (Elsevier/IOS Press, 1997-2002). She is actively involved in many key international AI conferences as organizers and members of the program committee. In addition to serving as the President of Taiwanese Association for Artificial Intelligence (2013-2014), Prof. Hsu has been a member of AAAI, IEEE, ACM, Phi Tau Phi, and an executive committee member of the IEEE Technical Committee on E-Commerce (2000) and TAAI (2004-current).
  • John Shawe-Taylor has contributed to a number of fields ranging from mathematics of graph theory through cryptography to statistical learning theory and its applications. In graph theory central contributions were to the classification of cubic distance regular graphs, while in cryptography his RSA prime generation algorithm was incorporated into an international standard. However, his main contributions have been in the development of the analysis and subsequent algorithmic definition of principled machine learning algorithms founded in statistical learning theory. This work has helped to drive a fundamental rebirth in the field of machine learning with the introduction of kernel methods and support vector machines. His work in this area has progressed on several parallel fronts: the refinement of the fundamental statistical results that underpin the approach and can be extended to related algorithms and data analysis techniques; the mapping of these applications onto novel domains including work in computer vision, document classification and brain scan analysis; and the extension of learning to improving the representations that are created for learning on different application domains. He has also been instrumental in assembling a series of influential European Networks of Excellence (initially the NeuroCOLT projects and later the PASCAL and PASCAL2 networks). The coordination of these projects has influenced a generation of researchers and promoted the widespread uptake of machine learning in both science and industry that we are currently witnessing. He has also coordinated two influential European research projects, the KerMIT project, the CompLACS (Composing Learning for Artificial Cognitive Systems) and most recently the X5gon project developing AI tools for enhancing access to Open Educational Resources.
  • Marija Slavkovik is a professor at the University of Bergen in Norway. Her area of research is Artificial Intelligence (AI) with expertise in collective reasoning. Slavkovik is active in the AI subdisciplines of: multi-agent systems, machine ethics and computational social choice. Slavkovik believes that the world can be improved by automating away the boring, repetitive and dangerous human tasks and that AI has a crucial role to play towards this goal. In AI, the big problem she hopes to solve is the efficient self-coordination of systems of artificial intelligent agents. In machine ethics, Slavkovik is active in engineering machine ethics problems – How can we build autonomous systems and artificial agents that behave ethically? Want to know what is happening in machine ethics since it stopped being an SF-only topic? There is a tutorial for that. Slavkovik co-organised a Dagstuhl Seminar in 2019 on this topic. She is also one of the guest editors of the Special Issue on Ethics for Autonomous Systems of the AI Journal.
  • Yvonne Rogers, Chair of Interaction Design, Dept of Computer Science, Faculty of Engineering Science, UCL. Her research interests are in the areas of ubiquitous computing, interaction design and human-computer interaction. A central theme is how to design interactive technologies that can enhance life by augmenting and extending every day, learning and work activities. This involves informing, building and evaluating novel user experiences through creating and assembling a diversity of pervasive technologies.
  • Nuria Oliver is a computer scientist. She holds a Ph.D. from the Media Lab at MIT. She is the first female computer scientist in Spain to be named an ACM Distinguished Scientist and an ACM Fellow. She is also a Fellow of the European Association of Artificial Intelligence and a IEEE Fellow. She is a member of the Academia Europaea and the fourth and youngest female member of the Spanish Royal Academy of Engineering. In 2018 she was named Engineer of the Year by the Professional Association of Telecommunication Engineers of Spain and she received an honorary doctorate from the University Miguel Hernandez
  • Jan Hajič is a professor of Computational Linguistics and the director of Large Research Infrastructure LINDAT/CLARIAH-CZ at Charles University, Prague, since 2010. His interests are in machine translation and creating large language resources, and in ways to make them available to the research community as well as to the commercial innovation scene. He has experience with both commercial research (IBM Research) and academic
    environments (Johns Hopkins University, University of Colorado in Boulder, Norway Academy of Sciences, Charles University); he has published over 200 papers with more than 11 thousand citations (h-index 46), and is listed among the world’s most influential computer scientists by in 2021. He has also experience as a (Co-)PI of many EU- and US-funded projects, including the European Language Grid and European Language Equality; he is the Chair of META-NET, the Multilingual Europe Technology Alliance Network, member of the LIND (Language
    INDustry) High Level Expert Group of the EC, and of the EOSC Task Force on FAIR metrics, among others.

Location: UCL AI Centre, London
Date: 30 November 2021
Time: 11h00 – 13h00 GMT
Registration: instructions to be provided by invitation

The Delegation of the European Union to the UK and the Embassy of Slovenia to the UK have joined forces with IRCAI to organise a field visit for the EU member States Digital Counsellors to the UCL Artificial Intelligence Centre. Organised as part of the EU Delegation activities in cooperation with the Slovenian Presidency to the EU.

The Ministry of Foreign Affairs of the Republic of Slovenia, Slovenian Presidency and the International Research Center Artificial Intelligence (IRCAI) have joined forces to organize a number of events in close cooperation with Slovenian embassies and other permanent representatives in at least 15 countries around the world. The aim of this effort is to set an active agenda for AI during the Slovenian Presidency and to provide a basis for continuing and promoting bilateral discussions in the field of AI and sustainable development beyond the Presidency.

The Delegation of the European Union to the United Kingdom, opened in February 2020. The Delegation of the European Union (EU) in the UK is one of the 143 diplomatic representations of the EU around the world. It has been established following the United Kingdom’s (UK) withdrawal from the EU to promote EU policies in the UK by engaging with Her Majesty’s Government, political actors, the media, academia, business, the civil society and the wider British public. They analyse and report on the political, social, and economic situation in the UK to headquarters in Brussels and assist shaping the future EU-UK relations. Together with the embassies of EU Member States they also raise awareness on the rights of EU citizens in the UK after Brexit.

The UCL Artificial Intelligence Center and International Research Center Artificial Intelligence (IRCAI) will co-host a visit to UCLs facilities in London by EU Member States Digital Counsellors delegation of EU. Slovenia currently holds the presidency of the European Council and is also a funder to International Research Center Artificial Intelligence (IRCAI). The delegation will visit UCL Artificial Intelligence Centre’s facilities in Holborn. UCL also holds the UNESCO Chair in Artificial Intelligence and within its current remit the chairholder John Shawe-Taylor is also director of IRCAI.

– Promote the UCL AI Centre and IRCAI Centre to senior diplomats in the EU Delegation and EU member states in London
– Present tangible results in AI to EU Member States counsellors in London with an interest in Digital affairs and AI
– Create positive/enthusiasm for AI with the EU delegates
– Create a report to be uploaded into the IRCAI library

11:00 – 11:30 GMT – Welcome
Opening and Introduction
David Barber on UCL AI Centre
John Shawe-Taylor on IRCAI Centr
Benjamin Guedj on Inria London Programme at UCL
Beatrice Covassi, Minister Counsellor, EU Delegation to the UK

Overview of the field and current topics in UCL AI Centre and IRCAI Centre to EU member states
– Current work and Challenges
– Reach and Research and Development
– Future Plans

11:30 – 12:00 GMT – Presentation 1
Presentations on tangible real-life use of AI in solving COVID-19
Delmiro Fernandez-Reyes

Key topics presented:

Key advances in AI technology for Healthcare
– Impacts on humans/society
– Global South and vaccinations
– Improved technology for vaccine development

12:00 – 12:30 GMT – Presentation 2
Presentations on tangible real-life use of AI in solving decarbonisation
Aidan O’Sullivan

Key topics presented:
– Innovative research in AI technology for Climate Change
– Achieving make net-zero a reality
– State-of-the-art artificial intelligence to leverage opportunities for energy efficiency in energy-intensive industries
– Re-engineering for the way societies produce and consume

12:30 – 13:00 GMT – Networking reception offered by the Embassy of Slovenia in the UK

David Barber – is the Director of the UCL Centre for Artificial Intelligence and Director of the UKRI Centre for Doctoral Training in Foundational AI. His main research interests are in probabilistic modelling approaches to AI and Machine Learning, multisensory integration, aging, and applied research on display technology, eye tracking device, affective computing, and AI/robots.

John Shawe-Taylor is UNESCO Chair for Artificial Intelligence at UCL, Director of the International Research Center Artificial Intelligence (IRCAI). He as contributed to a number of fields ranging from mathematics of graph theory through cryptography to statistical learning theory and its applications. His main contributions have been the developing of principled analysis of machine learning and the coordination of European Networks of excellence that were influential in promoting the uptake of machine learning and AI in both research and commercial application.

Delmiro Fernandez-Reyes is the Chair of the Programme Committee for AI and Healthcare at IRCAI. Professor of Biomedical Computing at UCL Department of Computer Science and Adjunct Prof. in Paediatrics at the College of Medicine of the University of Ibadan (COMUI) Nigeria. He founded the UCL – University of Ibadan African Computational Sciences Centre for Health and Development (ACSC4HD). He leads work focuses on AI approaches and research in the biomedical and healthcare domain to tackle global health challenges and sustainable provision of healthcare. Currently he is focused on a COVID-19 scalable population level integrative vaccine development programme.

Aidan O’Sullivan is the Chair of the Programme Committee for AI and Climate Change at IRCAI, and Associate Professor in Energy and Artificial Intelligence at UCL Energy Institute where he leads the Energy Systems and Artificial Intelligence Lab and the department’s Data Analytics Research theme. He is also the founding course director for the Energy Systems and Data Analytics MSc, an innovative programme that combines the study of energy systems and sustainability with data science and machine learning.

Benjamin Guedj is director of the Inria London Programme, a joint structure to foster scientific collaboration between Inria and University College London as part of a strategic France-UK partnership. He has broad interests in statistical learning theory and machine learning, with a focus on PAC-Bayes learning, computational statistics, generalisation bounds for deep learning, data-efficient machine learning.


International Research Centre in Artificial Intelligence
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