Trading Off Non-Functional Properties of Machine Learning

Focus topic: Artificial Intelligence
Type of funding: Project funding programmes
Programme: CZS Breakthroughs
Funded institution:
  • Johannes Gutenberg-Universität Mainz

How decentralised should data be stored to protect privacy, and how does that affect energy consumption? Conflicts of goals of this kind are analysed in a research centre for machine learning.

Goals

The aim of the project is to establish an interdisciplinary research centre at the Johannes Gutenberg University Mainz. Here, interactions and dependencies of different properties of machine learning are to be analysed and weighed. Decisions made by algorithms will be examined with regard to transparency and fairness as well as data protection and the efficient use of resources such as electricity. The focus is on competing needs, for example: How decentralised can data be stored and processed to protect privacy, to what extent does this affect energy consumption? Various conflicting goals are identified and characterised in order to create workable compromises for the application. Ethical and legal aspects are to be considered. The solutions found are to be put to use in an AI lab at Mainz University of Applied Sciences.

Involved persons:

Florian Jenner

Program Manager

Phone: +49 (0)711 - 162213 - 22

E-mail: florian.jenner@carl-zeiss-stiftung.de

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Prof. Dr. Stefan Kramer

Johannes Gutenberg-Universität Mainz

Detailed information:

Focus topic: Artificial Intelligence
Programme: CZS Breakthroughs
Type of funding: Project funding programmes
Target group: Professors
Funding budget: 4.995.000 €
Period of time: July 2022 - June 2028

Funded institution:

Johannes Gutenberg-Universität Mainz
Johannes Gutenberg-Universität Mainz