A better future rather than faster robots: 'Sustainable Robotics' as a new academic field

A manifesto published in Nature Machine Intelligence proposes Sustainability Robotics, a field that would assess robots not only by technical performance but also by their environmental, social, and economic contributions. Sukho Song of DGIST led the international collaboration with Barbara Mazzolai of the Italian Institute of Technology and Mirko Kovač of Empa and EPFL.
The proposal responds to rapid advances in robotics and physical AI alongside worsening climate change, biodiversity loss, and resource depletion. It calls for shifting the central question from how to improve robot performance to what role robots should play in a sustainable future.
The framework expands on Green Robotics, which seeks to lessen robots’ impacts through biodegradable materials, lower energy use, and more recyclable and repairable components. Sustainability Robotics would also aim for robots to directly address challenges through environmental monitoring, ecosystem restoration, disaster response, health care, and critical-infrastructure maintenance.
Its three principles are minimally invasive, universally accessible, and symbiotic. Minimally invasive robots should reduce effects on ecosystems and society. Universal accessibility means robots should be deployable where needed regardless of income or location. The symbiotic principle, given particular emphasis by the researchers, calls for positive relationships among people, the environment, and the economy.
Under this approach, evaluation would include environmental and social consequences as well as efficiency and task performance. The authors contrast robots that support ecosystems, such as coral reef restoration robots, with technologies that can impose environmental costs, such as deep-sea mining robots. Song said the goal is not simply faster or more powerful robots, but systems that reach places of greatest need and benefit both people and nature. The manifesto argues that robot design should prioritize robots’ relationships with the world and consider who benefits and what costs remain.