10.5281/zenodo.5211103
https://zenodo.org/records/5211103
oai:zenodo.org:5211103
Hadassah Drukarch
Hadassah Drukarch
0000-0001-9695-8990
eLaw Center for Law and Digital Technologies
Carlos Calleja
Carlos Calleja
0000-0003-0852-4290
eLaw Center for Law and Digital Technologies
Eduard Fosch-Villaronga
Eduard Fosch-Villaronga
0000-0002-8325-5871
eLaw Center for Law and Digital Technologies
An iterative regulatory process for robot governance
Zenodo
2021
Robot governance
Policy Cycle
Robot technology
Evidence- based policy
2021-08-17
eng
10.5281/zenodo.5211102
https://zenodo.org/communities/eu
1
Creative Commons Attribution 4.0 International
There is an increasing gap between the policy cycle's speed and that of technological and social change. This gap is becoming broader and more prominent in robotics, i.e., movable machines that perform tasks either automatically or with a degree of autonomy, since current legislation was unprepared for machine learning and autonomous agents and, as a result, often lags behind and does not adequately frame robot technologies. This state of affairs inevitably increases legal uncertainty. It is unclear what regulatory frameworks developers have to follow to comply, often resulting in technology that does not perform well in the wild, is unsafe, and can exacerbate biases and discrimination. This paper explores these issues and considers the background, key findings, and lessons learned of the LIAISON project, which stands for Liaising robot development and policymaking, and aims to ideate an alignment model between robots' legal appraisal channeling robot policy development from a hybrid top-down/bottom- up perspective to solve this mismatch. As such, LIAISON seeks to uncover to what extent compliance tools could be used as data generators for robot policy purposes to unravel an optimal regulatory framing for existing and emerging robot technologies.
European Commission
10.13039/501100000780
779966
Being safe around collaborative and versatile robots in shared spaces