Artificial intelligence in research and development for sustainability: the centrality of explicability and research data management

Abstract

Sustainability constitutes a focal challenge and objective of our time and requires collaborative efforts. As artificial intelligence brings forth substantial opportunities for innovations across industry and social contexts, so it provides innovation potential for pursuing sustainability. We argue that (chemical) research and development driven by artificial intelligence can substantially contribute to sustainability if it is leveraged in an ethical way. Therefore, we propose that the ethical principle explicability combined with (open) research data management systems should accompany artificial intelligence in research and development to foster sustainability in an equitable and collaborative way.