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This chapter pursues a sub-research question on whether artificial intelligence technologies (AI) contribute to the broadening of environmental sciences beneficiaries. One of the motivations to introduce AI to science processes derives from the AI’s systematic way of thinking: Unrecognized biases involve even sciences related to approaching problems (King & Robert in Artificial intelligence and machine learning in science. In Science, technology and innovation outlook 2018: Adapting to technological and societal disruption. OECD Publishing, Paris, 2018). Therefore, the expectation of adopting AI is to combine both human and AI thinking (transcendence of automation and augmentation) to gain more efficient and effective solutions (Kasparov, 2017; King & Roberts, 2018; Raisch & Krakowski in Academy of Management Review, 2020). On the other hand, scientists have not thoroughly examined whether AI’s introduction will broaden beneficiaries of sciences. Policymakers acknowledge the cities’ responsibility to address the rise of poverty, hunger, resource consumption, and a loss of biodiversity (NAS in Pathways to urban sustainability: Challenges and opportunities. National Academies Press, Washington DC, 2016). When AI adoption augments human cognitive skills to rule better quality services for diversified people, it will lessen conflicting elements in urban resilience practices. |
