ML – New Perspectives for Science

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New technologies in artificial intelligence and machine learning will change the world in the decades to come. These breakthroughs have led to algorithms being able to perform ever more complex tasks. The new Cluster of Excellence "Machine Learning – New Perspectives for Science" will deal with developments that can fundamentally change the process of scientific discovery. The focus will be on algorithms that recognize complex structures and causal relationships in scientific data and methods with which uncertainties can be managed in data-driven scientific models. Furthermore, techniques will be developed to enable scientists from different disciplines to better understand, interpret and control all stages of the machine learning process. Moreover, questions about the concept of scientific discovery and ethics are on the cluster's agenda. The spokespersons of the initiative are computer scientist Professor Ulrike von Luxburg and neuroscientist Professor Philipp Berens. In addition to the University of Tuebingen, the Max Planck Institute for Intelligent Systems and the Leibniz Institut für Wissensmedien are involved.

 

 Berens Foto Uni Tuebingen klein2

 

3 questions to Philipp Berens

Can you explain in three sentences what exactly the Cluster’s research will focus on?

At present, rapid progress is being made in the field of machine learning and artificial intelligence. We want to integrate this into the sciences: from medicine, geosciences and physics to sociology and linguistics. If machine learning is used more frequently in research, it will greatly change scientific practice and our understanding of science. Therefore, we also want to reflect on what these new technologies mean for the concept of scientific discovery.

What will be the biggest challenge?

Our fellow researchers come from many different disciplines in the biomedical science, natural sciences, humanities and social sciences. This means that very different discipline cultures will meet - it will certainly be a challenge to bring them together. At the same time, this is also extremely appealing to us - when can researchers devote time to finding out what other disciplines deem exciting?

Why did this project appeal to you personally?

I have worked between machine learning and neuroscience throughout my career: we have tried to answer neuroscientific questions with the tools of machine learning. It is extremely exciting to be able to do this now on a much larger scale - the scientific disciplines that the entire university has to offer.

 

U v Luxburg Foto Uni Tuebingen

 

2 questions to Ulrike von Luxburg

What results are you hoping for?

We want to find questions from many fields of research and achieve better answers than before with the instruments from the field of machine learning. At the same time, these problems can provide new inspiration for research in machine learning – because existing algorithms do not suffice to solve concrete research questions from the applied disciplines. If we succeed in getting this innovation cycle up and running in some fields of science, we will have achieved something.

Why did this project appeal to you personally?

The terms "artificial intelligence" and "machine learning" can cause great discomfort in public debates. Many people are concerned that part of the research takes place in multinational companies that pursue their own interests and are difficult to control. We want to counter this with research in a public context that promotes science, takes ethical concerns seriously and ultimately benefits the general public.

 

The full interview is available here (in German only).

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