Abstract
Members of the public are making substantial contributions to science as citizen scientists, and advances in technologies have enabled citizens to make even more substantial contributions. Technologies that allow computers and machines to function in an intelligent manner, often referred to as artificial intelligence (AI), are now being applied in citizen science. Discussions about guidelines, responsibilities, and ethics of AI usage are already happening outside the field of citizen science. We suggest such considerations should also be explored carefully in the context of citizen science applications. To start the conversation, we offer the citizen science community an essay to introduce the state-of-play for AI in citizen science and its potential uses in the future. We begin by presenting a systematic overview of AI technologies currently being applied, highlighting exemplary projects for each technology type described. We then discuss how AI is likely to be increasingly utilised in citizen science into the future, and, through scenarios, we explore both future opportunities and potential risks. Lastly, we conclude by providing recommendations that warrant consideration by the citizen science community, such as developing a data stewardship plan to inform citizens in advance of plans and expected outcomes of using data for AI training, or adopting good practice around anonymity. Our intent is for this essay to lead to further critical discussions among citizen science practitioners, which is needed for responsible, ethical, and useful use of AI in citizen science.
Highlights
Technologies that allow computers and machines to perform tasks normally requiring human intelligence are often referred to as artificial intelligence (AI)
We identified that some form of AI used in citizen science was found in 50 and 6 articles from Association of Computer Machinery Digital Library (ACM DL) and IEEE Xplore databases respectively
Future Applications of AI in Citizen Science In addition to more people integrating AI into a wider diversity of projects and improvement of existing methods, we foresee a wider array of AI technologies being applied to citizen science, which we explore in the section below
Summary
Technologies that allow computers and machines to perform tasks normally requiring human intelligence are often referred to as artificial intelligence (AI). Data collected by citizens are used by knowledge engineers, people who integrate knowledge into computer systems to solve complex problems normally requiring a high level of human expertise, to train AIs. Examples include citizen-science biodiversity projects iNaturalist (Van Horn et al 2018), Leafsnap and Pl@ntNet (as discussed in Bonnet et al 2016). Automated reasoning Software applications that allow citizen scientists to focus on more and machine learning engaging tasks, for example, focusing on observations of interactions, or developing/contributing to innovative projects in the field. As the use of AI grows and humans increasingly rely on machines to complete tasks, it is important that the citizen science community gathers data on how AI is used and on the ethical considerations that arise In contemplating this scenario, we give an overview of AI risks specific to citizen science (and sometimes broader), and are important to consider into the future. Citizen science presents a special opportunity to engage a wider cohort in training algorithms, which would help in not extending to algorithms the existing biases that are entrenching gender and racial discrimination in modern society
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