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Artificial Intelligence

The Research Group

Artificial intelligence (AI) is a hot topic. Its actual and potential applications are legion, for example in the fields of medicine, industry, urban planning or the application of law. The various branches of science discuss not only what AI can do and which formerly human tasks it could take over, but also to what extent it should or may do so and what the consequences might be. Each science has found its own approach to the topic of AI.

The "Artificial Intelligence" research group of Die Junge Akademie would like to approach the topic through concrete applications of AI methods and thus enter into an interdisciplinary conversation about the possibilities and limits of selected AI applications. In doing so, the RG would also like to discuss technologically, socio-scientifically and legally informed regulatory proposals for AI use.

 

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In accordance with its interdisciplinary composition, very different perspectives determine the interest of the RG. Across the disciplinary boundaries, a positive and a normative perspective can be distinguished.


From a positive perspective, the RG is concerned with the prerequisites, potentials and consequences of the use of AI in selected areas of application. Questions include what an AI-supported evaluation of digital disease and patient data can do to make diagnoses or improve therapies. What would this look like? What requirements do AI innovations place on data quality and data generation in order to be able to fulfil their optimisation promises? At this level, the RG also considers indirect consequences of the use of AI. For example, the question arises as to which "new" tasks arise for which professional groups in order to make data available for AI applications ("data work"). How might the use of legal tech affect the legal system as a whole, like autonomously driving vehicles affect traffic as a whole? How does the use of AI in diagnosis and therapy change people's relationships within the healthcare system? Sociologically, the RG is also interested in the connection of AI with concrete utopias of optimisation and innovation. It asks about the concrete direction of these utopias, which alternatives for action they open up and close off.

 

From a normative point of view, the RG asks at what point AI use seems sensible and ethically and legally possible, and under what conditions. Can the problems of AI use in concrete applications be captured by regulation? In which areas should AI applications be generally prohibited? Staying with the above example: How should misdiagnoses or treatment errors resulting from AI applications be dealt with? What influence may AI-supported systems have on sovereign decisions? What requirements does data protection law impose? This level is thus primarily concerned with the regulation of AI applications. This, too, will have to be discussed primarily in relation to applications, since the use of AI applications in industrial production gives rise to different regulatory needs than their use in clinical diagnostics or for fighting crime.

 

2020: Workshop “Artificial Intelligence in Biobanking”

From 29 - 30 July 2022, the Artificial Intelligence research group is organising the workshop "Artificial Intelligence in Biobanking" in Berlin. The aim is to bring biobanking and artificial intelligence closer together and to shed light on its further implications. The focus will be on aspects such as IT processes, organisational workflows or quality management measures, as well as on broader issues of ethical, legal and social significance.

 

The workshop is organised by Isabel Nahal Schellinger and will be held in cooperation with the Central Biobank Charité (ZeBanC).

With contributions by:

  • Dr. med. Carol Geppert (MIA) (Institut für Pathologie | Universitätsklinikum Erlagen)
  • Dr. Dr. Christian Matek, M. Sc. (Institut für Pathologie | Universitätsklinikum Erlangen)
  • Prof. Dr. techn. Wolfgang Nejdl (Institut für Verteilte Systeme | Leibniz Universität Hannover)
  • Dr. Christina Schüttler (Central Biobank Erlangen | Universitätsklinikum Erlangen)
  • Thomas Endres und Jonas Mayer (TNG Technology)

FIRESIDE TALKS

23.03.2022

At the next fireside talk with the Artificial Intelligence research group, the guest will be Die Junge Akademie alumna Ulrike von Luxburg. Von Luxburg is a professor of computer science at the University of Tübingen and a fellow at the Max Planck Institute for Intelligent Systems. She works on the theoretical foundations of machine learning and is also interested in the influence of artificial intelligence (AI) research on future society. The members of the RG would like to talk to Ulrike von Luxburg about her work and the potentials and challenges of AI applications for society and science. They are also interested in what experiences she has had as a scientist in the public discussion about the social significance of AI. 

 

- Past dates -

 

26.01.2022

Together with the research group Transfer of Innovation in Academia, RG Artificial Intelligence hosted a fireside evening with astrophysicist and Erium founder Theo Steininger. The members of Die Junge Akademie talked to him about his scientific and entrepreneurial path. Among other things, Theo Steininger  addressed 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.