Experiences with Improving the Transparency of AI Models and Services
November 11, 2019 Β· Declared Dead Β· π CHI Extended Abstracts
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Authors
Michael Hind, Stephanie Houde, Jacquelyn Martino, Aleksandra Mojsilovic, David Piorkowski, John Richards, Kush R. Varshney
arXiv ID
1911.08293
Category
cs.CY: Computers & Society
Cross-listed
cs.HC
Citations
51
Venue
CHI Extended Abstracts
Last Checked
3 months ago
Abstract
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.
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