An iterative regulatory process for robot governance

Abstract There is an increasing gap between the policy cycle’s speed and that of technological social change. This becoming broader more prominent in robotics, is, movable machines perform tasks either automatically or with a degree autonomy. because current legislation was unprepared for machine learning autonomous agents. As result, law often lags behind does not adequately frame robot technologies. state affairs inevitably increases legal uncertainty. It unclear what regulatory frameworks developers have to follow comply, resulting technology well wild, unsafe, can exacerbate biases lead discrimination. paper explores these issues considers background, key findings, lessons learned LIAISON project, which stands “Liaising development policymaking,” aims ideate alignment model robots’ appraisal channeling from hybrid top-down/bottom-up perspective solve this mismatch. such, seeks uncover extent compliance tools could be used as data generators purposes unravel optimal framing existing emerging