20 and 21 September 2023: Course on Reinforcement Learning for Adaptive Hybrid Intelligence.

Reinforcement learning (RL) is one of the main paradigms of machine learning, in which artificial agents learn optimal behaviour from interaction data. Recent years have seen notable breakthroughs in this field in robotics, games such as Atari and Go, and in ChatGPT. While the focus on autonomous and active learning makes reinforcement learning a powerful tool, deployment of a reinforcement learning agent as an assistant or collaborator (that is, as a hybrid intelligence) raises specific challenges.

In this two-day SIKS/HI course we will take a look at the foundations of reinforcement learning and various extensions that are important for hybrid intelligence.

This course is coordinated by Prof. Rineke Verbrugge (RUG), Dr. Erman Acar (UvA) and Dr. Herke van Hoof (UvA).

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16 and 17 February 2023: Course on Social artificial intelligence

Social AI aims to develop AI systems that have the ability to engage in natural social interaction with human beings. It is a multi-disciplinary field combining insights from social psychology and artificial intelligence to improve and design effective interactive technology. This includes, e.g., social robots, virtual humans and conversational agents. From a technical perspective, social AI aims to develop new algorithms to endow social AI systems with more human-like abilities to understand and generate social behaviour (e.g., using techniques such as emotion recognition and natural language processing). From a social psychology perspective, social AI studies the psychological effects of interacting with social AI systems on people’s perceptions and behaviour. From an applied perspective, social AI systems can be used for various practical purposes such as social skills training and behaviour changes.  

Each of these themes is explained in lectures with a focus on various aspects related to these themes, presented by researchers in the field. The course is organised in two parts. On the first day, a more theoretical perspective is provided on social psychology and interactive technologies. On the second day, a more practical, design-oriented perspective is provided.  

The course is coordinated by course directors Tibor Bosse (Radboud University) and Koen Hindriks (VUA) 

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21, 22, 28, 29 June 2022 : Course on Responsible HI

AI technologies play an increasingly important part of our lives in many domains such as health and wellbeing, smart cities, social media, energy, art and culture, and robotics. Considering this pervasiveness and impact of AI on our society, it is more important than ever that AI researchers understand this context and can translate this understanding into development of AI technologies and methods that meet the needs and opportunities of people and societies. In this course we address several dimensions of Responsible and Trustworthy AI, such as AI governance; bias, non-discrimination & fairness; privacy & data ethics; and human-AI interaction. We approach these topics through an integrated treatment of technical, ethical, legal and societal aspects, as well as practical considerations. The course includes exercises to allow participants to reflect on responsibility aspects of their own and others’ research.

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22, 27, 28 September 2021: Course on Explainable AI

In politics, industry and science, much attention is paid today to the ethical and social aspects of AI, the risks of big data and the increasing power of incomprehensible and opaque algorithms, which are seemingly objective, “value-free” and neutral, but which make radical decisions without human intervention, that may deeply influence people and their future. The call for Explainable AI therefore sounds louder all the time. This two-day course will be divided over four afternoons.

This course has been designed by scientific course director Dr. Afra Alishahi (Tilburg University) and Prof. Rineke Verbrugge (University of Groningen).

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25-26 May 2021: Course on neuro-symbolic systems

Neuro symbolic systems that combine learning and reasoning are sometimes called “the 3rd wave of AI”, after the first wave of symbolic and the second wave of machine learning methods. This course is using a survey paper by Frank and Annette to structure a 2 day course on neuro-symbolic systems, including three international keynote speakers: Pascal Hitzler from Kansas, Luciano Serafini from Trento, and Sara Magliacane from Amsterdam.

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