[SIGCIS-Members] Call for Tutorials: ACM FAT* 2019 (Conference in Fairness, Accountability & Transparency)

Michael Ekstrand michaelekstrand at boisestate.edu
Thu Sep 6 12:53:30 PDT 2018


Could you deliver a session that would further practice and knowledge
around societal implication and risks of algorithmic systems? The second
ACM Conference on Fairness, Accountability, and Transparency (ACM FAT*
2019) is soliciting a wide variety of tutorials to be delivered on January
29, 2019 in Atlanta, Georgia.

- *Hands-on Tutorials*  (90 or 180 mins) should give ACM FAT*’s broad
audience the chance to experiment with new software packages to deal with
the issues of the conference.

- *Translation Tutorials* (45 or 90 mins) aim to "translate" between
disciplines; for instance, by explaining computer science concepts in a way
that will be practically useful for lawyers, policy makers, and other
practitioners, or by explaining legal, policy, or social science concepts
in a way that will guide computer scientists in their future technical
explorations.

- *Implications Tutorials* (45 or 90 mins) should cover known legal,
policy, medical, or socio-economic effects of unfair algorithmic systems,
lack of interpretability of machine learning models, biases in the data, or
other ACM FAT* related issues. We particularly encourage submissions by
civil rights lawyers, policy advocates, civil society representatives, and
others who work closely with individuals and communities affected by
algorithmic systems.

3 page tutorial descriptions (+1 page for Hands-On Tutorials), are due
September 13, 23:59 AoE Time, and those successful will be notified on
October 15.

More information, including more detailed information about formats and
types of session, is available here:
https://fatconference.org/2019/cftutorials.html

Best wishes,

Michael and Michael
Publicity Co-Chairs, ACM FAT* 2019


-- 
Michael D. Ekstrand — michaelekstrand at boisestate.eduhttps://md.ekstrandom.net
Assistant Professor, Dept. of Computer Science, Boise State University
People and Information Research Team (PIReT) —
http://coen.boisestate.edu/piret/
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