talk · Friday 25 September · SAL B

What is the Role of "AI" in the Centers for Biodiversity Informatics of the Future?

Matthew Yoder · Designing Institutional Knowledge Data Science Centres for Biodiversity

Recording time 3:48:59–4:03:06Open on Vimeo ↗

The short versionBiodiversity informatics centres are about people. AI raises the importance of standards, storage, openness and distributed risk, and centres should fuel researchers' curiosity rather than be driven by the technology.

Overview

What this was about

Yoder reflected on the sociocultural impact of AI on a biodiversity informatics centre, drawing on the experience of the endowed Species File Group (about 10 staff and about 100 collaborative projects), which is considering growing from a group into an alliance. He set out ten observations: storage rather than compute is the bottleneck; standards matter more than ever; centres must spot and harden community-built AI tools; administrators, the public and researchers are ambivalent about AI; data protection walls are both necessary and futile; AI noise makes 'open' costly to maintain; and risk should be spread across networks of people. He concluded that centres are long-term havens for people who use technology, and that AI should serve life.

Why it matters. The talk offers a practical, non-technical view of how AI affects the running, funding, security and mission of long-lived informatics centres.

Key ideas

In the room

  • The Species File Group has been endowed for about 15 years, has about 10 full-time staff and about 100 collaborative projects, and is exploring a move from group to alliance to share risks and benefits.
  • Mathematics, where AI output can be verified with the Lean system, shows that principles proposed for organisations in response to AI are largely just good principles for any centre.
  • The biggest bottleneck is storage, not compute. Aggregating data into commercial clouds enables AI models that communities may resent, so the community needs shared or 'infinite' storage.
  • Standards are more important than ever: to parse data with AI you still need a standard to parse into. Standards are 'a sea of stability' in the AI wave.
  • Citizen scientists and taxonomists now build long-needed tools with LLMs; centres must notice them and harden them for the long term.
  • Administrators are enthusiastic but visionary rather than practical; social media and some colleagues (e.g., journal editors) are hostile, and corporate partnerships are contested.
  • Walls and silos are inevitable, required and pointless: data leak eventually, so hiding protected-species locations is futile, yet Cloudflare-style walls are now ubiquitous.
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Notable moments

In their words

Transcript

Automatically generated captions can contain mistakes, especially in names and technical terms. Times are relative to the room recording.

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