Details Publications
Data Recording for Responsible Robotics
- Author(s)
- Jon Skerlj, Maximilian Braun, Sophia Witz, Svenja Breuer, Marieke Bak, Sebastian Scholz, Abdeldjallil Naceri, Ruth Müller, Sami Haddadin, Iris Eisenberger
- Abstract
The last decades have seen continuous attempts to advance the application of robotics and artificial intelligence (AI) research in several areas such as healthcare environments. However, using (semi)autonomous robots in healthcare also poses risks that need to be addressed throughout the systems' lifecycle. In this work, we present our version of a data recorder, as the output of an interdisciplinary research collaboration that addresses relevant social, ethical, legal, and technical aspects of advanced robotics in healthcare. We use social science insights from interviews and ethnographic fieldwork with relevant stakeholders as well as ethical and legal analyses to derive and implement four technical requirements for a data recorder to enhance accountability and transparency of a service humanoid robot, GARMI, assisting in healthcare. We present a tool to log and visualize data from human-robot interactions as a means of including non-expert users and other relevant stakeholders in accountability relationships, which also helps us to enhance the transparency of advanced robotics in general and to fulfill the examined requirements of the Medical Device Regulation (MDR) and the General Data Protection Regulation (GDPR).
- Organisation(s)
- Department of Innovation and Digitalisation in Law
- External organisation(s)
- Technische Universität München, Karl-Franzens-Universität Graz
- Pages
- 103-109
- No. of pages
- 7
- DOI
- https://doi.org/10.1109/ARSO56563.2023.10187414
- Publication date
- 2023
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 505002 Data protection, 202035 Robotics, 505010 Medical law
- Keywords
- ASJC Scopus subject areas
- Artificial Intelligence, Electrical and Electronic Engineering, Computer Vision and Pattern Recognition, Computer Science Applications
- Portal url
- https://ucrisportal.univie.ac.at/en/publications/cf3d1900-e5b9-4f40-9907-fd4e03696ca2