About the Project
visuAAL is a four-year (2020-2024) Marie Skłodowska-Curie Actions Innovative Training Network, funded by the European Union, that aims at bridging the knowledge gap between users’ requirements and the appropriate and secure use of video-based AAL technologies to deliver effective and supportive care to older adults managing their health and wellbeing.
visuAAL will seek to increase awareness and understanding of the context-specific ethical, legal, privacy and societal issues necessary to implement visual system across hospital, home and community settings, in a manner that protects and reassures users; outputs will stimulate the development of a new research perspective for constructively addressing privacy-aware video-based working solutions for assisted living.
visuAAL will provide a transdisciplinary and cross-sectoral combination of training, nonacademic placements, courses and workshops on scientific and complementary skills to 15 high achieving Early Stage Researchers (ESRs). These newly hired ESRs will contribute through their individual research projects to fulfil visuAAL's aims.
visuAAL brings together 5 universities:
• Chair of Communication Science, Human-Computer Interaction Center, RWTH Aachen University, Germany
• The Swedish Law and Informatics Research Institute (IRI), Stockholm University, Sweden
• The Trinity Centre for Practice and Healthcare Innovation, School of Nursing and Midwifery, Trinity College Dublin, Ireland
• Computer Vision Lab, TU Wien, Austria
• Department of Computing Technology, Universidad de Alicante, Spain (Project Coordinator)
This Consortium is complemented by 14 partner organizations from Austria, Germany, Ireland, Italy, Portugal, Spain, Sweden, and United Kingdom; that will contribute to the research and training activities.
For more information about visuAAL, see https://www.visuaal-itn.eu/
Algorithmic fairness in AI for active assisted living
Algorithmic decision making became enmeshed into daily life. In active assisted living data is analysed and interpreted with the intention to support people in various ways: recognizing behaviour, events, emotions, needs; creating ambient intelligence; predicting activities and proposing treatment strategies. Machine learning as prerequisite of intelligence is applied. Taking into account recent success, it can be claimed, that not only a set of specific algorithms but also a lot of example data is needed to run the learning methods. And usually those building the algorithms are not trained in law or the social sciences, while experts in discrimination law do not know how to audit modern machine learning algorithms. Further complicating matters is that even experts in computer science and mathematics often struggle with interpreting the output of many modern machine learning algorithms. Unsurprisingly assessing and guaranteeing fairness and transparency in machine learning is a wide open research and that is the topic of the PhD proposal
The outcome leads to better understanding of algorithmic fairness and transparency. Strategies and paradigms for fairer algorithms are proposed. Policies and legal frameworks in addition to (machine) learning strategies are investigated to ensure an equitable outcome of applying machine learning for AAL
• Main Supervisor: Prof M. Kampel (TU Wien)
• Second Supervisor: Prof P. Wahlgren (Stockholm University)
• Co-Supervisor: Prof R. Sablatnig (TU Wien)
• Advisor: Prof R. Bonsack (Universidade Católica Portuguesa) Dr. R. Planinc (Cogvis GMBH)
• Secondment 1: University of Alicante (Supervisor F. Florez) M18-M20: Training and research on learning strategies
• Secondment 2: Stockholm University (Supervisor P. Wahlgren), M25-M27: Investigating legal frameworks and policies
Enrolment in Doctoral degree(s):
Doctoral Programme in Computer Science, Vienna University of Technology
How to apply?
Submit your application to https://www.visuaal-itn.eu/esr-vacancies. Please, ensure that you select vacancy number ESR11.
For questions related to this project proposal, please contact [Email Address Removed]
For all other questions, please use the following email address, clearly indicating the visuAAL vacancy number ESR11: [Email Address Removed]