[Air-L] ACM FAT* 2020: Call for Critiquing/Rethinking FAT* Sessions and for Tutorials

Veale, Michael m.veale at ucl.ac.uk
Thu Aug 29 02:22:20 PDT 2019


The 2020 ACM Conference on Fairness, Accountability, and Transparency in Computing Systems (ACM FAT* 2020) in Barcelona, Spain on January 27–30 2020 promises to be a lively event, with almost 300 submitted full papers across 5 tracks now under review.

There is still time to get involved! This can be either through:
1. A session for the CRAFT programme — flexible sessions (e.g. panels, debates, unconferences, art exhibit) focussed on Critiquing and Rethinking Accountability, Fairness and Transparency (in the spirit of the CRACT workshop at NeurIPS).
2. A tutorial for the main conference.

## CRAFT: Critiquing and Rethinking Accountability, Fairness and Transparency ##

The success of the field of fairness, accountability, and transparency has also attracted much critique and renewed attention to the limitations of achieving these goals in systems that implement statistical, machine learning, optimization, or autonomous computing techniques. A number of prominent studies acknowledge that addressing societal problems embedded in such computing systems may require more holistic approaches. In the spirit of reflection and response, we invite academics of all disciplines and people representing different communities of practice (including journalism, advocacy, organizing, education, art, public authorities) to contribute to a program that will be subject to its own review process and that will be embedded in the ACM FAT* conference.

These sessions might, for example, be any of the following (or more): Interactive Workshop / Panel / Debate / Unconference / Art Exhibit or Other Artistic Intervention / Site Visit / Poster or Demo Session / Lightning Talk(s) / Rump Session. This is not, however, a route for submission of a conventional academic paper. 

They need not be organised by academics: all interested groups are more than welcome to submit.

We are especially interested in proposals that:
* Are accessible to people coming from multiple communities of practice (academic, industry, journalistic, artistic, activist, organizing, etc.)
* Go beyond a conventional academic approach of critiquing FAT*
* Offer a vision that helps fulfil the aims of the CRAFT call

Chairs:
Seda Guerses, TU Delft
Seeta Peña Gangadharan, London School of Economics
Suresh Venkatasubramanian, U Utah

| CRAFT proposal pre-registration: September 9th
| CRAFT proposal submission: September 12th
| CRAFT notification date: October 3th
| https://fatconference.org/2020/callforcraft.html

## TUTORIALS ##

We are soliciting three types of tutorials for 2020: hands-on tutorials, translation tutorials, and implications tutorials. We will give presenters 45 or 90 minutes for translation and implication tutorials, and 90 or 180 minutes for hands-on.

* Hands-on tutorials should offer a broad audience the chance to experiment with new software packages designed to support ACM FAT* efforts.
* Translation tools translate between disciplines; for instance, by explaining computer science concepts in a way that will be practically useful for lawyers, policy makers, social scientists 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 should cover known legal, policy, 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.

| Tutorials proposal pre-registration: September 9th
| Tutorials proposal submission: September 12th
| Tutorials notification date: October 3th
| https://fatconference.org/2020/callfortutorials.html 

Chairs:
Reuben Binns, Oxford University
Michèle Finck, Max Planck Institute for Innovation and Competition
Margaret Mitchell, Google

--
Michael Veale
Lecturer in Digital Rights and Regulation
Faculty of Laws, University College London
@mikarv / https://michae.lv



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