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Artificial Intelligence

The Research Group

Artificial Intelligence (AI) is a hot topic. The social relevance and interdisciplinary importance of AI need no further introduction. Far-reaching debates in every branch of science are discussing whether, and to what extent AI can replace tasks currently carried out by humans (e.g. in medicine, industry, urban planning and application of law) and whether and to what extent AI should do so (philosophy, ethics, legal studies etc.). Running athwart all these discussions is the new EU data protection law, which a broad consensus agrees, is massively hampering technological research on and with AI. However, scientific discussions and debates on AI suffer particularly from the fact that, although the scientific branches involved all have a point of contact with the subject of AI, these relationships are dissimilar and vary individually. As a result, often these discussions are taking place at cross-purposes. This is having an especially unfortunate effect on the urgently needed specification of the political, legal and philosophical “primary definitions” linked to AI: If it is not clear what AI is, can and should do in concrete terms, discussions of “AI and responsibility,” “AI and human dignity” and “AI and trust” can easily get lost in abstraction, providing no additional insight.

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One focus of the “Artificial Intelligence” research group within Die Junge Akademie will therefore be, to establish concrete terms of application in AI, instead of attempting to approach challenges in a larger general sense and “solve” problems. The research group will contribute solidly informed suggestions, in terms of both technology and legal philosophy, for concrete regulations in selected AI case studies; building upon the wide-reaching interdisciplinary expertise of our members. The great issues, e.g. of responsibility and ethical principles, will not go disregarded. Indeed, these issues will be applied in a tailored manner to the concrete case studies and, ultimately, guide suggested regulations

26.01.2022: FIRESIDE TALK

Together with the research group Transfer of Innovation in Academia, RG Artificial Intelligence is hosting a fireside evening with astrophysicist and Erium founder Theo Steininger. Our members will talk to him about his scientific and entrepreneurial path. Among other things, Theo Steininger will address technical, social and legal points in the field of artificial intelligence.

2021/22 Understanding Blood-brain Dynamics with Statistical Learning

The brain serves only as a cooling system for the blood - at least that's what Aristotle believed. Even though medicine and neuroscience have made some progress since then, the dynamics between neuronal activity and the fluctuations of various messenger substances and metabolic products in the blood are still insufficiently understood. The reason for this is, among other things, the complexity and effort of a parallel measurement of brain and blood parameters over several hours, and furthermore the existence of manifold interactions and feedback loops between these parameters, which quickly push classical statistical analysis methods to their limits.

The project aims to combine biomedical and mathematical-statistical expertise to decipher and understand complex data structures. For this purpose, the neuronal activity and the dynamics of various blood parameters of test subjects with balanced age and gender ratios were recorded in time with parallel EEG/blood measurements. Even in condensed form, this results in hundreds of snapshots of physiological parameters in the brain and blood per test subject and sleep lead. Accurate understanding of these interactive blood-brain dynamics requires correspondingly complex modelling and analysis as well as methods that are sufficiently scalable for such data volumes and allow relevant influencing variables and interpretable effects to be identified.

To bring together different expertise from neuroscience, medicine, statistics and mathematics, the project team, which consists of Martin Dresler, Nadja Klein, Isabel Schellinger and Timo de Wolff, is planning mutual visits and project meetings in 2021 and 2022 with participating PhDs and post-doctoral students. A joint publication is also planned.

2020: Workshop “AI and University”

On 10 and 11 January 2020, the RG Artificial Intelligence is organising its first workshop in Frankfurt am Main entitled "AI and University". On the first day, the workshop will deal with the topic "AI research despite basic data protection regulations". On the second day, the focus will be on "Using AIs in Education" (so-called Learning Analytics).

The first workshop day starts with an impulse from Prof. Nikolaus Marsch. Marsch teaches constitutional law and data protection law at Saarland University and is one of the best experts on the subject in Germany. He has habilitated on the fundamental rights and European dimensions of data protection. Prof. Dirk Ifenthaler could be won for a keynote lecture on Learning Analytics on the second day. Ifenthaler heads the Chair for Learning, Design and Technology at the University of Mannheim and is UNESCO Deputy Chair of Data Science in Higher Education Learning at Curtin University in Australia. He is also the editor of several journals and special volumes on learning analytics and heads several relevant research projects, such as the BMBF project STELA (Utilizing Learning Analytics for Study Success).

In the future, the research group aims to make its voice heard - not only, but especially - in the field of education with concrete proposals for regulation (model rules) in science policy.