2024/03/01 by Matthias C. Rillig, India Mansour, Stefan Hempel +3 · 2 voices · 19 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Environmental Science · #Artificial intelligence #Biology #Cell Image Analysis Techniques #Citizen science #Computer science #Credibility #Data science #Ecology #Environmental resource management #Environmental science #Explainable Artificial Intelligence (XAI) #Generative grammar #Generative model #Government (linguistics) #Political science #Species Distribution and Climate Change #Workflow
paper · pdf · doi:10.1111/ele.14397
published in Ecology Letters 27(3), e14397 (Wiley)
openalex publication_date 2024/03/01 · openalex created_date 2024/03/05 · openalex updated_date 2026/08/01
Generative artificial intelligence (AI) models will have broad impacts on society including the scientific enterprise; ecology and environmental science will be no exception. Here, we discuss the potential opportunities and risks of advanced generative AI for visual material (images and video) for the science of ecology and the environment itself. There are clearly opportunities for positive impacts, related to improved communication, for example; we also see possibilities for ecological research to benefit from generative AI (e.g., image gap filling, biodiversity surveys, and improved citizen science). However, there are also risks, threatening to undermine the credibility of our science, mostly related to actions of bad actors, for example in terms of spreading fake information or committing fraud. Risks need to be mitigated at the level of government regulatory measures, but we also highlight what can be done right now, including discussing issues with the next generation of ecologists and transforming towards radically open science workflows.