Why I left iNaturalist

Product philosophy: complexity vs “frictionless” apps

• Several commenters resonate with the tension the essay describes: tools that genuinely teach and deepen understanding often require effort and “friction,” which clashes with modern growth-driven UX ideals.
• Some compare this to generative AI trends where skill-building is treated as optional or even exclusionary.
• Birders note that many users choose eBird + Merlin because it’s easier, but some prefer iNaturalist precisely because it slows you down, forces judgment, and yields more trustworthy records.

iNaturalist, Seek, and user experience

• Many see iNaturalist as on par with, or even more personally impactful than, Wikipedia: a daily tool for learning species, ecosystems, and taxonomy.
• Seek is praised as a lightweight gateway for casual users and families; others find it naggy (e.g., repeated “don’t disturb nature” warnings) and switch to the main app.
• Several argue the current split is confusing: Seek feels like “just a feature” that should be the iNat mobile front door, with the full web UI as the real power-user interface.
• Complaints include clunky observation workflows, poor mobile performance, slow image loading, and an “old” feel, which discourage deeper engagement.

Scientific value and data quality

• Supporters emphasize iNat as a unique, massive biodiversity record feeding into GBIF, used in conservation organizations and research (e.g., species distributions, invasive species, modeling).
• One commenter reports that in their rare-plant work, iNat is a useful first-pass data source but often not publishable on its own.
• Another initially doubts real scientific use but is pointed to GBIF’s citation tracking showing thousands of iNat records in some studies.

AI models, openness, and data control

• A strong thread criticizes iNat’s closed machine-learning models as contrary to open science and to a 501(c)(3)’s public-interest mission, given that models are trained on community data.
• There are allegations of forum posts on this topic being “not approved” and effectively sidelined.
• Others agree models should be open but distinguish that from calls to “ban AI,” noting ML is now integral to large-scale scientific analysis.

Governance, leadership, and organizational design

• Long subthreads debate sociocracy, “unstructured anarchy,” and agile/flat structures.
• Critics say the described governance experiments lacked clear accountability, and that the author stepped out of formal leadership yet continued pushing strong product opinions.
• Defenders argue that non-hierarchical models can work when participants are aligned and trained, and that experiments in democratic governance shouldn’t be dismissed just because they’re hard.
• More broadly, commenters see a familiar pattern: as platforms scale, they introduce hierarchy, optimize for growth and risk management, and gradually alienate the early contributors who built their value.