The artificial intelligence cooperative: READ-COOP, Transkribus, and the benefits of shared community infrastructure for automated text recognition

READ-COOP demonstrates that a cooperative business model has potential to sustain and support innovation in AI and ML infrastructures while promoting democratic participation and equitable ownership in particular contexts, in this case the cultural heritage sector. We suggest that cooperative frameworks are particularly suitable for AI infrastructures initially funded through public grants, providing a sustainable transition from public development to long-term, sustainable community-ownership, where focussed tool providers have adequate community support. We recommend wider application and exploration of cooperative models for innovation in AI and ML technologies for responsible creation, governance, and use, although we recognise READ-COOP's unique context, community, and success may be an outlier.