HUMAINE: Human multi-agent immersive negotiation competition
Rahul R. Divekar, Hui Su, et al.
CHI EA 2020
AI models and services are used in a growing number of high-stakes 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.
Rahul R. Divekar, Hui Su, et al.
CHI EA 2020
Peter F. Sweeney, Matthias Hauswirth, et al.
VM 2004
Dakuo Wang, Liuping Wang, et al.
CHI 2021
Priya Nagpurkar, Michael Hind, et al.
CGO 2006