AI for CS

Description

The Conservation Standards community has generated a lot of good information to support good conservation practice, such as in the Conservation Standards websites and Resource libraries, attached to CCNet Listserv conversations, various webinar channels, embedded within Miradi files, and stored in other research and evidence libraries. Information about the effectiveness of conservation actions is also stored in related databases such as those developed and managed by Panorama and Conservation Evidence.

But this information can be hard to find for many reasons - the source is often obscure, the search capabilities are limited, and our multitude of global languages are poorly supported. Further, it takes additional time and effort to understand if the sources are reliable. 

Recent advances in Artificial Intelligence (AI) offer resolutions to these issues. “Search” has been reinvented, and translation quality is now close to natural-language. Generative AI (e.g. ChatGPT) can create new information from sources (including audio, video, images), and not just present existing data. AI tools can search all globally available data, or they can be customized to search only defined, trusted sources.

We envisage a service where practitioners can enter a natural-language question, in their own language, and have answers generated, in their language, from a trusted set of resources from the global conservation community.  

Lead: Annette Stewart and Kari Stiles