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Robotics: Enabler and inhibitor of the Sustainable Development Goals

par Haidegger, Tamás;Mai, Vincent;Mörch, Carl Maria;Boesl, Dominik D.O.;Jacobs, An;Rao R, Rao B.;Khamis, Alaa;Lach, Luca;Vanderborght, Bram
Référence Sustainable production and consumption, 43, page (422-434)
Publication Publié, 2023-12

Article révisé par les pairs

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Résumé :

Robotics has the power to help our society in managing many current and foreseeable challenges, and contribute to a responsible future, as formally structured in the United Nations' Sustainable Development Goals (SDGs) initiative. Prior work has already investigated the impact of Artificial Intelligence (AI) on the SDGs, using a systematic consensus-based expert elicitation process. However, the existing literature has not focused on the intricacies of robotics and the unique dynamics this domain presents regarding the SDGs. In this vein, this work adapts an established approach, to focus on and dive deeper into the field of robotics and social responsibility. We introduce a multidisciplinary analysis of both the enabling and disabling roles of robotics, in achieving the SDG-presented, major economic, social and environmental priorities. The United Nation's 17 SDG and the 169 Targets, were individually examined within the context of state-of-the-art robotics already documented in scientific literature. The significance and the quality-of-evidence of enabling/inhibiting impacts, were assessed by an international panel of experts, to quantify the positive or negative effect of the applied robotic systems. Results from this study indicate that robotics has the potential to enable 46 % of the Targets, particularly for the industry and environment-related SDGs, forecasting a huge impact on our production systems and thus on our entire society. Inversely, robotics could inhibit 19 % of the SDG Targets, mainly through exacerbation of inequalities and tensions in the SDGs. The objective of this paper is to assess and grade the current impact of the robotics megatrend on the SDGs, provide comparable data, and encourage the robotics community to work on these targets, in a unified way and eventually improve the quality of the related outcomes.