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Brian Lim <[log in to unmask]>
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Brian Lim <[log in to unmask]>
Tue, 6 Nov 2018 20:58:41 +0800
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2nd Workshop on Explainable Smart Systems (ExSS) 


Held in conjunction with ACM Intelligent User Interfaces (IUI), Los Angeles,
California, 16-20 March 2019


Smart systems that apply complex reasoning to make decisions and plan
behavior, such as clinical decision support systems, personalized
recommendations, and machine learning classifiers, are difficult for users
to understand. This workshop will follow on from the very successful ExSS
2018 workshop held at IUI with the goal of bringing together researchers in
academia and industry who have an interest in making smart systems
explainable to users and therefore more intelligible and transparent. This
topic has attracted increasing interest to provide glimpses into the
black-box behavior of these systems in order to provide more effective
steering or training of the system, better reliability and improved
usability. This workshop will provide a venue for exploring issues that
arise in designing, developing and evaluating smart systems that use or
provide explanations of their behavior.




Researchers in academia or industry who have an interest in making smart
systems explainable to users are invited to submit papers up to 6 pages (not
including references) in ACM SIGCHI Paper Format. These paper submissions
can be of two types: (1) position papers summarizing authors' existing
research in this area and how it relates to the workshop theme and (2)
papers offering an industrial perspective on the workshop theme or a
real-world approach to provide explanations. Suggested contribution types
include, but are not limited to:

- What is an explanation? What should they look like?

- Are explanations always a good idea? Can explanations "hurt" the user
experience, and in what circumstances?

- When are the optimal points at which explanations are needed for a
particular system?

- How can we measure the value of explanations or how the explanation is
provided? What human factors influence the value of explanations?

- What are "more explainable" models that still have good performance in
terms of speed and accuracy?


Papers should be submitted via Easychair
( by end of December 3rd
2018 and will be reviewed by committee members. Position papers do not need
to be anonymized. At least one author of each accepted position paper must
attend the workshop. 


Paper authors will present their work as part of a thematic panel. The
second part of the workshop will consist of sub-group activities focused on
how to design and show explanations for a real-world system. 


For further questions please contact the workshop organizers at
<[log in to unmask] <mailto:[log in to unmask]> >.



Submission deadline: 3 December 2018

Notification to Authors: 14 January 2019 

Camera-ready copies due: 15 February 2019

Workshop: 20 March 2019



Brian Lim - National University of Singapore 

Advait Sarkar - Microsoft Research, Cambridge

Alison Smith-Renner - Decisive Analytics Corporation, USA 

Simone Stumpf - City, University of London, UK 



Gagan Bansal - University of Washington, USA 

Fan Du - University of Maryland, USA 

Malin Eiband - University of Munich, Germany 

Melinda Gervasio - SRI, USA 

Dave Gunning - DARPA, USA 

Judy Kay - University of Sydney, Australia 

Bran Knowles - University of Lancaster, UK 

Per Ola Kristensson - University of Cambridge, UK 

Todd Kulesza - Microsoft, USA 

Mark W. Newman - University of Michigan, USA 

Jim Nolan - Decisive Analytics Corporation, USA 

Kenton O'Hara - Microsoft Research Cambridge, UK 

Forough Poursabzi-Sangdeh - Microsoft, USA 

Stephanie Rosenthal - Carnegie Mellon University, USA 

Harold Soh - National University of Singapore 

Jo Vermeulen - Aarhus University, Denmark 

Jurgen Ziegler - University of Duisburg, Germany

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