FSTP from the H2020 COVR Project
Liaising robot development & policymaking
This project aims to link robot development and policymaking to reduce the complexity in robot legal compliance in the context of COVR.
The project LIAISON
As depicted in Figure 1, LIAISON conceives an effective way to extract compliance and technical knowledge from the COVR Toolkit and direct these data to policy and standard makers to unravel an optimal regulatory framing, including decisions to change, revise, or reinterpret existing regulatory frameworks for existing and emerging robot technologies. More practically, LIAISON’s objective is to clarify what regulatory actions policy and standard makers should take to provide compliance guidance, explain unclear concepts or uncertain applicability domains to improve legal certainty, and inform future regulatory developments for robot technology use and development at the European, National, Regional, or Municipal level (Fosch-Villaronga and Drukarch 2020). This is achieved through the LIAISON model, depicted in Figure 1 below. In general terms, the LIAISON model puts forward a threefold model through which by (a) interacting with compliance tools (in this case in interaction with the COVR Toolkit, but it could also be in interaction with the Assessment List of Trustworthy AI (ALTAI) model developed by the EC)7; (b) extracting knowledge from them in partnership with developers and other actors; and (c) sharing this knowledge with engaged regulators to support regulatory action, we can govern robot technology more effectively (Fosch-Villaronga and Heldeweg 2018, Fosch-Villaronga and Heldeweg, 2019).
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Drukarch, H., Calleja, C., and Fosch-Villaronga, E. (2022). LIAISON: Liaising robot development and policymaking to reduce the complexity in robot legal compliance. In: Pons, J. L. (2022) Interactive Robotics: Legal, Ethical, Social and Economic Aspects. Biosystems & Biorobotics, vol. 30, Springer., 212-219, https://doi.org/10.1007/978-3-031-04305-5_37
Drukarch, H., Calleja, C., and Fosch-Villaronga, E. (2023). An iterative regulatory process for robot governance. Data & Policy, Cambridge University Press, 5:e8, 1-22
Contribution to a CEN Workshop Agreement
CWA 17835:2022 on Guidelines for the development and use of safety testing procedures in human-robot collaboration
As a result of his participation to LIAISON and the H2020 COVR, Dr. Eduard Fosch-Villaronga contributed to the CEN Workshop Agreement CWA 17835:2022 on Guidelines for the development and use of safety testing procedures in human-robot collaboration.