SAIL Spring School: Focus on AI evaluation – ethics and innovation combined!

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The SAIL Spring School at Bielefeld University from 26th to 28th. March 2025 will focus on AI assessment and interdisciplinary exchange.

Die SAIL Spring School an der Universität Bielefeld vom 26.-28. März 2025 thematisiert KI-Bewertung und interdisziplinären Austausch.
The SAIL Spring School at Bielefeld University from 26th to 28th. March 2025 will focus on AI assessment and interdisciplinary exchange.

SAIL Spring School: Focus on AI evaluation – ethics and innovation combined!

The topics surrounding artificial intelligence (AI) are the focus of this year's SAIL Spring School, which will take place from March 26th to 28th in the CITEC building at Bielefeld University. The main theme of the event is “Innovating AI Evaluation: Beyond Accuracy and Precision”. Methods for evaluating AI will be discussed, with the focus on interdisciplinary exchange between researchers from different disciplines. Discussions include ethical and societal implications, interpretable AI, as well as mathematical guarantees and user reviews, such as aktuell.uni-bielefeld.de reported.

A central aspect of the SAIL Spring School is the presentation of current research results. International experts give tutorials and participants have the opportunity to present their work in the form of poster presentations. Junior Professor Dr. David Kappel from the Technical Faculty of Bielefeld University will take part in the event and contribute his expertise on the security of machine learning systems. In addition, the research of Clarissa Sabrina Arlinghaus, who deals with social exclusion in human-technology interaction in hybrid teams, will be presented.

Research on human-technology interaction

Arlinghaus' poster presentation addresses a method for LLM-supported coding of qualitative data. This innovative method improves the efficiency of analyzing qualitative data, which is often more time-consuming than analyzing quantitative data. The use of LLM makes it possible to automatically sort and categorize interviews. She highlights that human-technology teams follow social rules, but there are differences in the intensity of social interactions. Employees express a greater appreciation for human attention compared to interaction with robots. The feeling of being excluded by people is perceived as more threatening than exclusion by machines, which has far-reaching social implications.

Arlinghaus also emphasizes the relevance of human contact in hybrid teams for the psychological well-being of employees. This shows the need to take social dynamics into account when designing human-technology interactions. LLM-supported coding offers an accessible solution for everyone, even those without programming knowledge, thanks to templates and instructions provided.

Ethical dimensions of AI

The debate about the ethical issues surrounding AI is not only held at the SAIL Spring School, but is also comprehensively covered in the publications of the German Ethics Council. This examines the effects of digital technologies and artificial intelligence on human self-image and interactions. The focus is on the philosophical discussion of central concepts such as intelligence, reason, action and responsibility ethikrat.org explained.

A central aspect of the Ethics Council is the focus on four areas of application: medicine, school education, public communication and public administration. By analyzing the complex interactions between humans and technology, the key question is whether the use of AI expands human authorship or leads to a loss of it.

Current research results on the ethical embedding of AI illustrate the need for a well-founded discussion about the responsible use of technologies. The challenges include not only data protection and loss of autonomy, but also responsibility and transparency when AI systems make incorrect decisions. das-wissen.de highlights that ethics in AI development is essential to ensure that these technologies are designed fairly, transparently and in line with societal values.

Interdisciplinary collaboration between the fields of computer science, law, ethics and civil society is seen as essential in order to develop ethical guidelines and master the challenges of rapid technological developments. Education and awareness are also key to engaging the public in the discussion about AI and ethics and promoting the responsible use of these technologies through regular training.