The use of AI documentation such as repository cards (model and dataset cards), as a means of transparently discussing ethical and inclusive problems that could be found within the outputs and/or during the creation of AI artefacts, with the aim of inclusivity, fairness and accountability, has increasingly become part of the ML discourse. As limitations and risks centred documentation approaches have become more standard and anticipated with launches of new development e.g Chatgpt/GPT-4 system card and other LLM model cards.

This talk highlights the inclusive approaches that the broader open source community could explore when thinking about their aims when creating documentation.