Open Law Lab: “I have been working on the giant effort to make a comprehensive, user-centered taxonomy of legal issues that people have in the US. It’s called LIST, Legal Issues Taxonomy, and up in its growing glory at the site https://taxonomy.legal.
Note: this new taxonomy was previously called National Subject Matter Index v2 (NSMIv2), since it’s built from the early-2000s work from legal aid groups to make standard codes for their work, called the National Subject Matter Index (NSMI v1).
As I’ve been building out this taxonomy, I’ve been researching how we can be evaluating the quality + impact of a taxonomy project. The Legal Issues Taxonomy has been built primarily to help those working on legal apps, machine learning projects, and web development to have standard codes. These can help them consistently label problems, develop classifiers, and create interoperable and smarter resources for people seeking help. But as we know from other AI, tech, and infrastructure projects — well-intentioned efforts can have unexpected harms. Particularly for vulnerable groups, do seemingly technocratic efforts like taxonomies + AI classifiers have concerning impacts on equity, access, or bias? To that end, upon the recommendation of Open Referral‘s Greg Bloom, I have been reading the MIT press book Sorting Things Out: Classification and its Consequences by Geoffrey Bowker and Susan Leigh Star…”