Projects
Chair for Sociology of Technology

ASSISTANT

leArning and robuSt deciSIon SupporT systems for agile mANufacTuring environments

Funding: EU Horizon 2020 (6 Mio. €) // Start Date: 01.11.2020 // Duration: 36 months // Partners: 12

The EU-funded ASSISTANT project aims to develop breakthrough solutions for the manufacturing industry, using artificial intelligence to optimise production systems. One of the keystones of ASSISTANT is the creation of intelligent digital twins. By combining machine learning, optimisation, simulation, and domain models, ASSISTANT develops tools and solutions providing all required information to help production managers design production lines, plan production, and improve machine settings for effective and sustainable decisions that guarantee product quality and safety.

With a multidisciplinary consortium combining key skills in AI, manufacturing, edge computing and robotics, ASSISTANT aims to create intelligent digital twins through the joint use of machine learning (ML), optimization, simulation and domain models. The resulting tools permit to design and operate complex collaborative and reconfigurable production systems based on data collected from various sources such as IoT devices. ASSISTANT targets a significant increase in flexibility and reactivity, products/processes quality, and in robustness of manufacturing systems, by integrating human and machine intelligence in a sustainable learning relationship.

The ASSISTANT project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101000165 .


Institut Mines-Telecom // University College Cork // University of Patras // Flanders Make vzw // Biti Innovations AB // SIEMENS AG // INTRASORFT International // ATLAS Copco // SIEMENS Energy // Groupe PSA

HIRING

Human centric innovative approach and training for the management of human Resources through the Integration of the Next Generation of AI technologies

EU Erasmus+ // Start Date: 01.09.2020 // Duration: 36 months // Partners: 6

The project aims to prepare the current and next generation of human resources manager to the integration of artificial intelligence tools in their position. It’s objectives are: training the HR managers and students to the digital transformation to come in their work environment, valuing fair and responsible soft skills for implementing AI technologies at the work place and promoting a more open-minded HR generation opened to atypical career pathways.

Institut de Preparation à l’Administration et à la Gestion, IPAC Business School // Seinäjoen koulutuskuntayhtymä, Finland // haikara, France // ZAPIENS TECHNOLOGIES S.L. Spain

DataSkop

DataSkop. Was passiert mit meinen Daten?

Funding: BMBF, VDI/VDE (1,8 Mio €) // Start Date: 01.08.2020 // Duration: 36 months // Partners: 5

The BMBF, VDI/VDE funded project "DataSkop - Was passiert mit meinen Daten?" is developing a data donation platform to enable users sharing their personal data to support research and digital education. Our role in that project is to provide protypical use-, i.e. research-cases. The common goal of the project, however, is to tackle the opacity of algorithmic decision making systems on big or otherwise pivotal online platforms and services. Using organic, real user data, we are going to map, explore and investigate the different realities that branch out from discriminators implementend in recommenders and the like. The project is part of the BMBF's Digital Autonomy Hub.

Algorithm Watch // Uni Paderborn // FH Potsdam // Mediale Pfade

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