Harnessing robot experimentation to optimize the regulatory framing of emerging robot technologies. (13th June 2022)

• Record Type: Journal Article
• Authors: Calleja, Carlos; Drukarch, Hadassah; Fosch-Villaronga, Eduard
• Is Part Of: Data & policy. Volume 4(2022)
• Publication Date: 2022-06-13
• Subjects: evidence-based policymaking -- exoskeletons -- regulation -- robots -- safety -- testbeds; Policy sciences -- Periodicals; Policy sciences -- Statistical methods -- Periodicals; Policy sciences -- Data processing -- Periodicals; Decision making -- Data processing -- Periodicals; 320.60727
• DOI: 10.1017/dap.2022.12
• Languages: English
• ISSNs: 2632-3249

Abstract

Abstract: From exoskeletons to lightweight robotic suits, wearable robots are changing dynamically and rapidly, challenging the timeliness of laws and regulatory standards that were not prepared for robots that would help wheelchair users walk again. In this context, equipping regulators with technical knowledge on technologies could solve information asymmetries among developers and policymakers and avoid the problem of regulatory disconnection. This article introduces pushing robot development for lawmaking (PROPELLING), an financial support to third parties from the Horizon 2020 EUROBENCH project that explores how robot testing facilities could generate policy-relevant knowledge and support optimized regulations for robot technologies. With ISO 13482:2014 as a case study, PROPELLING investigates how robot testbeds could be used as data generators to improve the regulation for lower-limb exoskeletons. Specifically, the article discusses how robot testbeds could help regulators tackle hazards like fear of falling, instability in collisions, or define the safe scenarios for avoiding any adverse consequences generated by abrupt protective stops. The article's central point is that testbeds offer a promising setting to bring policymakers closer to research and development to make policies more attuned to societal needs. In this way, these approximations can be harnessed to unravel an optimal regulatory framework for emerging technologies, such as robots and artificial intelligence, based on science and evidence.