**tl;dr: People’s motivations to engage with online citizen science are complex and change over time** Apparently, last week _iNaturalist_ released a blog post, demoing their mock-up of how they envision using LLMs to process user-contributed wildlife observation data. Back in June, when they (or rather their funder Google) announced this project, it led to substantial backlash among their community, which largely went unheard by the powers that be - i.e. run _iNaturalist_. The current blog post seems to do little to address most of those concerns, talking about putting _people at the center_ , alongside publishing some numbers on the allegedly-low environmental impact they seem to have copied from straight _Google_ ’s internal “research”1. As I noted on Mastodon during the weekend: In some way, it’s par for the course for those organizations that “professionalize” — and thus (“need to”) put their primary focus on paying their own salaries and thus raising funds.2 So far, that’s (unfortunately) all as expected. But what struck me when reading through the responses to this post was this comment by a user: > Every time I read that AI is better, faster etc. it lowers my motivation to identify. It makes me feel that what I do when identifying (mostly unknowns) is not going to be useful any longer Which aligns with some of my predictions from a manuscript on the impact of AI on citizen science, as well as the larger academic literature about the motivations of volunteers generally - and in citizen science in particular. And one big part of that could be summarised as: _People come for the mission but they**STAY** for the community._ Back in 2022, we published a study on the motivations (and shared goals/values) of self-researchers who participate in an online community and joint-citizen science effort we did3 as part of Open Humans. For this, we modeled our qualitative code-book in part after two other studies that looked at citizen science motivations: _Variations in the Motivations of Environmental Citizen Scientists_ and _Motivations, learning and creativity in online citizen science_. What’s shared among all of these is the assumption that people have a rich and complex network of motivations. Some of which will be intrinsic (_“I want to help science”_ , _It’s valuable to do_ , _I want to learn something new_), others extrinsic (“ _This will help me my career_). But importantly, they also outline that people’s motivations aren’t static, but can and do evolve over time. While initial motivations might be driven by a general interest in the topic, feeling aligned with the mission of an effort, or a desire to contribute to research, this does not mean that those motivations stay the same. In fact, the reasoning for sustained participation often is different. While a continued interest in a topic – and alignment with a mission are a necessary precondition, they aren’t by themselves sufficient. Factors like a sense of achievement or increased ability, continued time do play big roles. But so do social factors: Participants in those studies called out the importance of the sense of belonging and being part of a community, often leading to people taking up extra responsibilities outside the main “tasks” of a citizen science project - which in turn deepens a sense of belonging while also helping to improve the overall community. In fact, in our work with self-researchers we found that the social dimension developed through online meetings over time, and was a key factor for an engagement over time, that also helped deepen and reinforce the community norms and values. Or put simpler: People continued to engage with these efforts, because they were looking forward to meeting their peers and friends again, often quite literally week after week - in some cases literally logging on to the regular online video calls to chime in “ _Hello my online friends!_ ”. And while we didn’t study the motivations of community members for our more recent work with _AutSPACEs_ in detail, at least anecdotally I’d say we saw the same there: As time went on, people showed up as much for the social interactions as for the scientific interest and other dynamics. And this brings me back to the initial quote of that person who says their motivation will be lower to contribute if “AI” is brought in to replace them. Beyond identifying that it feels like it will replace their contributions or make them superfluous, there is also an aspect of how a big motivating factor is to interact with other human beings, who give their advice and share their learnings. Maybe “AI” can give such advice more _efficiently_ or _at scale_ (though I doubt it), but it can’t replace the social aspects of learning from each other. And I think that is an aspect that deserves to be kept in mind when designing and implementing citizen science projects: Holding a space for humans; to work with each other, learn from each other and laugh with each other; is as much part of science - and citizen science - as collecting the data. _iNaturalist_ states that their mission is to use the _power of technology to connect people to nature_. But I think it misses out on an important but overlooked bit, which is using technology to _connect people to people, alongside and nature_. ## References 1. Aitkenhead, G., Fantoni, S., Scott, J., Batchelor, S., Duncan, H., Llewellyn-Jones, D., … Greshake Tzovaras, B. (2024). How to co-create content moderation policies: the case of the AutSPACEs project. Data & Policy, 6, e28. doi:10.1017/dap.2024.21 2. Borda, Ann and Greshake Tzovaras, Bastian, Perspectives on Crowdsourced Citizen Science and the Data Governance of AI Applications (March 13, 2025). https://dx.doi.org/10.2139/ssrn.5291262 3. Greshake Tzovaras, B. (2025, June 12). Generative ‘AI’ in citizen science: the iNaturalist backlash. Bastian Greshake Tzovaras. https://doi.org/10.59350/7ykzb-dkx88 4. Greshake Tzovaras, B. (2025, June 18). Power-sharing in online communities. Bastian Greshake Tzovaras. https://doi.org/10.59350/jpevj-h4y27 5. Greshake Tzovaras, B. (2025, March 31). Sunsetting openSNP - a personal retrospective. Bastian Greshake Tzovaras. https://doi.org/10.59350/8se4t-tmx68 6. Jennett, C., Kloetzer, L., Schneider, D., Iacovides, I., Cox, A., Gold, M., Fuchs, B., Eveleigh, A., Mathieu, K., Ajani, Z. and Talsi, Y. (2016). Motivations, learning and creativity in online citizen science JCOM 15(03), A05. https://doi.org/10.22323/2.15030205 7. Senabre Hidalgo, E., Ball, M.P., Opoix, M. et al. Shared motivations, goals and values in the practice of personal science: a community perspective on self-tracking for empirical knowledge. Humanit Soc Sci Commun 9, 182 (2022). https://doi.org/10.1057/s41599-022-01199-0 8. Seltzer, Carrie (2025, October 15). Exploring New Ways to Learn from iNaturalist’s Community Expertise. https://www.inaturalist.org/blog/118695-exploring-new-ways-to-learn-from-inaturalist-s-community-expertise 9. West, S, Dyke, A and Pateman, R. 2021. Variations in the Motivations of Environmental Citizen Scientists. Citizen Science: Theory and Practice, 6(1): 14, pp. 1–18. https:// doi.org/10.5334/cstp.370 ## Footnotes 1. Which has an obvious incentive to low-ball those figures - and completely ignores the environmental and social impact of the actual training, as opposed to the individual prompts. ↩ 2. I’m even somewhat sympathetic to that, in my academic life I’ve been in the position of having to raise research funding quite often. But it always comes with moral trade-offs, and it’s why I’m so happy that we had the luck to not have to do that with openSNP. ↩ 3. And still do! ↩

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