  AI models and services are used in a growing number of highstakes areas,
resulting in a need for increased transparency. Consistent with this, several
proposals for higher quality and more consistent documentation of AI data,
models, and systems have emerged. Little is known, however, about the needs of
those who would produce or consume these new forms of documentation. Through
semi-structured developer interviews, and two document creation exercises, we
have assembled a clearer picture of these needs and the various challenges
faced in creating accurate and useful AI documentation. Based on the
observations from this work, supplemented by feedback received during multiple
design explorations and stakeholder conversations, we make recommendations for
easing the collection and flexible presentation of AI facts to promote
transparency.
