Prof. Britta Schinzel

Britta Schinzel studied mathematics, physics, and received a Dr. phil. in mathematics. She worked in the German computer-industry and was awarded her habilitaion from the Technical University of Darmstadt. As a professor at the RWTH Aachen in theoretical computer science, she worked within several areas of Artificial Intelligence, in interdisciplinary cooperation with medicine, biology, sociology etc. There she started to take interest in "computers and society" and gender studies in computing. Her last position was at the institute for computer science and social research at the university of Freiburg. Her main activities are placed within in the frame of "computers and society" and gender studies in technology and science. More specifically she worked in interdisciplinary research in technology assessment, empirical studies concerning the software developmental process, e-learning and gender studies, especially in computer science, and there again in foundations of IT, of visualization and medical imaging. Most recent publications: "Bildgebende Verfahren in der Medizin"; (Chap. V.9. Radiology),  in: Stephan Günzel, Dieter Mersch (Hrsg.): Handbuch Bild Metzler, will be published in 2014. "Weltbilder in der Informatik: Sichtweisen auf Profession, Studium, Genderaspekte und Verantwortung; Informatik Spektrum Sonderheft" (Ed.), Issue 3, June 2013 (Springer).

 

RESEARCH PROJECT

Analysis of brain simulation

With the architecture of information systems a new field of formation of human thought and knowledge has been created: code as an additional regulatory mechanism (Lessig 1999) expanded, designed, channeled and molded conventional mechanisms of knowledge and decision-making and human action. By this it also closes other ways and means of regulation, and even juridical and institutional regulators are suspended.
But architecture and design of code mostly underly only very limited regulation rules, they do not in general follow socially desirable ideas, nor are they attached to ethical guidelines. Because quality standards in computing are often not made explicit, in addition to the supply of quality standardization companies and certification bodies they may also be company-specific, experience driven or even follow individual imagination. This favors the I-Methodology (or ego-approach), i.e. the fact that decisions are guided by the attitudes and values of the developers and deciders, by their mental concepts. Thus, the development of information technology is indeed contingent, but it solidifies in interaction with political and market mechanisms in a momentum of its own.

The project proposed intends to identify relevant objectives, models, imginations of quality, ideas and background assumptions used in the design of systems in the context of neuroinformatics. Factors for both the production of knowledge as well as for the publication practice of research results shall exemplarily be explicated for newer AI methods and practices of Machine Learning used in modern neuroinformatics platforms and systems. Possible effects of these practices will be pointed out with regard to the validity of the developed knowledge, the norms and standards, as well as the exclusions produced. This may give suggestions for more adequate and poorer of undesirable consequences grown development strategies.

Methodically it is intended to look into the STEM area to apply the sophisticated theories and methodologies of feminist analyzes. Also the analysis of kinds of objectivity as developed by Lorraine Daston and Peter Galison will be used.

Research project - Neuro Simulation

Research project in collaboration with Martin Warnke (summer term 2021)

Mediation through Computational NeuroScience

Brain simulations are extremely far from actual brains and their performance. So how does the medium of computer simulation intervene in the process of understanding within neurosciences?

As the human brain normally is not directly accessible by invasive inspection, computer simulation is used in order to bridge the lack of knowledge about higher biological neural networks. Simulation and modeling in the context of neuroscience uses the theory of dynamic systems. Although it was developed for complex systems in physics, it has also found its way into the life sciences in order to analyze the behavior of complex natural systems, i.e. to represent and understand them in a simplified and standardized manner, to predict their behavior both theoretically and experimentally in comparison to reality.

However, with regard to the brain, the usual procedure is not possible: that a theory leads to a result through simulation, which is then either confirmed or falsified in the classical experiment. This is, because too little is known about the human brain, i.e. there is no theory of neurophysiology. In addition, usually experiments cannot be performed through a living brain but under very limited circumstances in vitro. In computational neuroscience, simulations therefore have a different status: they serve as experimental systems on computer models of the brain.

Experiments on computer models can succeed in simulating meaningfully for small layer sections with sufficiently precise layout assumptions. A theory then is not about the properties of the neuron layer in the brain (neither topographically nor functionally), but about the respective simulation. Various experimental results can be integrated into the computer models, as well as anatomical data, connection probabilities of the structural models, and much more. The simulation here is a description medium with which one can connect and compare findings from different areas and scales: it generates theories. It takes the vacant place of the nonexistent neurophysiological theory, it forms material-semiotic material.

A workshop “Neurological Computer-Simulations” collected well known scientists in the field of Computational NeuroScience, Media Theory, STS, Philosophy of Technology and Gender Studies in Technology. The demanding project investigates in the accessibility of brain sciences through simulation methods, the epistemological meaning of the simulation for scientific investigation of the brain, as well as especially in the media theoretic meaning of the nature of neurological observation through simulation.