Science for Robot Policy

There is an increasing gap between the policy cycle's speed and technological change. This gap is very noticeable in healthcare robotics, where policies are scattered and cover the issues robots entailed unevenly. This disconnect results in robot developers failing to integrate essential legal considerations into their designs, user safety not always being ensured, and the development of systems that may cause harm to patients. While other sectors enjoy evidence-based policies that translate policy goals into practical guidance, these frameworks have yet to emerge for robotic technology. 

Research objectives

SAFE&SOUND ushers in a new knowledge-policy relationship model for robots to facilitate the integration of legal requirements into the design of robotic technology in simulators, testing zones, and living labs, and reuse the data generated from this process for evidence-based policies on robots.

• RO1: Identify regulatory gaps for personal care robots 

• RO2: Test uncovered legal challenges for personal care robots

• RO3: Leverage robot testing zones data to support evidence-based policy change

• RO4: Investigate science for robot policy conception, effectiveness and sustainability

Methods

SAFE & SOUND's overarching methodology is anticipatory regulation, an emerging, proactive, iterative legal approach for empirically framing fast-evolving technological changes. This novel method is inclusive and collaborative, future-facing, proactively engages with innovation, has an iterative mindset and is outcomes-based. Moreover, it counts with decentralized experimentation to enable diverse responses to the regulation of early-stage opportunities and risks where national or global policies and standards are still to be established. SAFE & SOUND uses robot testbeds, open data, interaction between regulators and developers, and active patient engagement to support regulators' proactive, engaged role in the healthcare robot innovation process.