=Paper=
{{Paper
|id=Vol-2582/abstract1
|storemode=property
|title=ExSS-ATEC: Explainable Smart Systems and Algorithmic Transparency in Emerging Technlologies 2020 (workshop abstract)
|pdfUrl=https://ceur-ws.org/Vol-2582/abstract1.pdf
|volume=Vol-2582
|authors=Alison Smith-Renner,Styliani Kleanthous,Brian Lim,Tsvi Kuflik,Simone Stumpf,Jahna Otterbacher,Advait Sarkar,Casey Dugan,Avital Shulner
|dblpUrl=https://dblp.org/rec/conf/iui/Smith-RennerKLK20a
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==ExSS-ATEC: Explainable Smart Systems and Algorithmic Transparency in Emerging Technlologies 2020 (workshop abstract)==
https://ceur-ws.org/Vol-2582/abstract1.pdf
ExSS-ATEC: Explainable Smart Systems and Algorithmic
Transparency in Emerging Technologies 2020
Alison Smith-Renner Styliani Kleanthous Brian Lim
Decisive Analytics Corporation OUC & Rise Research Centre National University of Singapore
Arlington, VA, USA Nicosia, Cyrpus Singapore
alison.renner@dac.us styliani.kleanthous@gmail.com brianlim@com.nus.edu.sg
Tsvi Kuflik Simone Stumpf Jahna Otterbacher
University of Haifa City, University of London OUC & Rise Research Centre
Haifa, Israel London, UK Nicosia, Cyprus
tsvikak@is.haifa.ac.il simone.stumpf.1@city.ac.uk jahna.otterbacher@me.com
Advait Sarkar Casey Dugan Avital Shulner
Microsoft Research IBM Research University of Haifa
Cambridge, UK Cambridge, MA, US Haifa, Israel
advait@microsoft.com cadugan@us.ibm.com avitalshulner@gmail.com
ABSTRACT KEYWORDS
Smart systems that apply complex reasoning to make decisions and Explanations; visualizations; machine learning; intelligent systems;
plan behavior, such as decision support systems and personalized intelligibility; transparency; fairness; accountability
recommendations, are difficult for users to understand. Algorithms
allow the exploitation of rich and varied data sources, in order to ACM Reference format:
support human decision-making and/or taking direct actions; Alison Smith-Renner, Styliani Kleanthous, Brian Lim, Tsvi Kuflik, Simone
however, there are increasing concerns surrounding their Stumpf, Jahna Otterbacher, Advait Sarkar, Casey Dugan, and Avital
transparency and accountability, as these processes are typically Shulner. 2020. ExSS-ATEC: Explainable Smart Systems and Algorithm
opaque to the user. Transparency and accountability have attracted Transparency in Emerging Technologies 2020. In Proceedings of the IUI
increasing interest to provide more effective system training, better workshop on Explainable Smart Systems and Algorithmic Transparency in
reliability and improved usability. This workshop will provide a Emerging Technologies (ExSS-ATEC’20), Cagliari, Italy, 2 pages.
venue for exploring issues that arise in designing, developing and
evaluating intelligent user interfaces that provide system
1 Background
transparency or explanations of their behavior. In addition, our goal
is to focus on approaches to mitigate algorithmic biases that can be Smart systems that apply complex reasoning to make decisions and
applied by researchers, even without access to a given system’s plan behavior, such as clinical decision support systems,
inter-workings, such as awareness, data provenance, and validation. personalized recommendations, home automation, machine
learning classifiers, robots and autonomous vehicles, are difficult for
a user to understand [2]. Fairness, accountability and transparency
are currently hotly discussed aspects of machine learning systems,
CCS CONCEPTS especially for deep learning systems that are seen to be very difficult
to explain to users. Textual explanations and graphical
• Human-centered computing~Human computer
visualizations are often provided by a system to give users insight
interaction (HCI)~Interactive systems and tools • Computing
into what the systems is doing and why it is doing it [3–6] and work
methodologies~Machine learning • Computing
is starting to investigate how to best engage in transparency design
methodologies~Artificial intelligence
[1]. However, there are still numerous issues and problems
regarding explanations and algorithm transparency that demand
ExSS-ATEC ’20. March 17, 2020, Cagliari, Italy
Copyright © 2020 for this paper by its authors. Use permitted under Creative further attention, such as how can we build (better) explanations or
Commons License Attribution 4.0 International (CC BY 4.0) transparent systems, what should be included in an explanation and
how should they be presented, when should explanations be
deployed, or when do they detract from the user experience, how
can transparency expose biases in data or algorithmic processes,
and how can we evaluate explanations or system transparency,
especially from a user perspective.
ExSS-ATEC ’20, March 17, 2020, Cagliari, Italy Smith-Renner et al.
machine learning, and that some of the world’s best AI innovations
The ExSS-ATEC 2020 workshop brings together academia come from the humanities powered by computing.
and industry together to address these issues. This workshop is a
follow-on from the ExSS 2018 and 2019 workshops in combination 3.1 Workshop Committee
with the ATEC 2019 workshop previously held at IUI. This The workshop committee includes Gagan Bansal (UW), Veronika
workshop includes a keynote, paper panels, and group activities, Bogina (Haifa University), Robin Burke (UC Boulder), Jonathan
with the goal of developing concrete approaches to handling Dodge (OSU), Fan Du (Adobe), Malin Eiband (LMU), Michael
challenges related to the design and development of explanations Ekstrand (Boise State), Melinda Gervasio (SRI), Fausto Giunchiglia
and system transparency. ExSS-ATEC 2020 is supported by the (U Toronto), Alan Hartman (Afeka), Judy Kay (U Sydney), Bran
Cyprus Center for Algorithm Transparency (CyCAT). Knowles (U Lancaster), Todd Kulesza (Google), Tak Lee (Adobe),
Loizos Michael (Cyprus), Shabnam Najafan (Delft), Alicja
Piotrkowicz (U Leeds), Forough Poursabzi-Sangdeh (Microsoft),
2 Workshop Overview Gonazalo Ramos (MSR), Stephanie Rosenthal (CMU), Martin
The workshop keynote is Dr. Carrie Cai, focusing on current Schuessler (TU Berlin), Ramya Srinivasan (Fujitsu), Mike Terry
challenges for explainable smart systems. Nine accepted papers are (Google), Sarah Völkel (U Munich), and Jürgen Ziegler (U
presented as three themed panel sessions. Accepted papers are: Duisburg).
• Jung et al. “Transparency of Data and Algorithms in a Persona
System: Explaining Data-Driven Personas to End Users” 3.1 Workshop Organizers
• Dodge and Burnett, “Position: We Can Measure XAI The workshop organizing committee includes: Alison Smith-
Explanations Better with ‘Templates’” Renner, Director of the Machine Learning Visualization Lab for
• Hepenstal et al., “What Are You Thinking? Explaining Decisive Analytics Corporation and PhD Candidate at University of
Conversational Agent Responses for Criminal Investigations” Maryland, College Park; Dr. Styliani Kelanthous, senior
• Stockdill et al., “Cross-Domain Correspondences for researcher in the Faculty of Pure and Applied Sciences at Open
Explainable Recommendations” University of Cyprus and RISE Research Centre, Cyprus; Dr. Brian
• Lindvall and Molin, “Verification Staircase: A Design Strategy Lim, Assistant Professor in the Department of Computer Science at
for Actionable Explanations” the National University of Singapore, Prof. Tsvi Kuflik, professor
• Larasati et al., “The Effects of Explanation Styles on Users’ and former head of the Information Systems Department at the
Trust” University of Haifa, Israel; Dr. Simone Stumpf, Senior Lecturer
• Ferreira and Monteiro, “Do ML Experts Discuss Explainability at City, University of London, Jahna Otterbacher, founder of the
for AI Systems? A Discussion Case in the Industry for a Behavioral & Language Traces research lab, which is housed in the
Domain-Specific Solution” Faculty of Pure and Applied Sciences, Open University of Cyprus;
• Zürn et al., “What If? Interaction with Recommendations” Dr. Advait Sarkar, senior researcher at Microsoft Research in
• Chromik and Schuessler, “A Taxonomy for Human Subject Cambridge (UK); Casey Dugan, manager of the AI Experience
Team at IBM Research Cambridge (MA, USA); and Avital
Evaluation of Black-Box Explanations in XAI”
Shulner, PhD student in the Information Systems Department at
The second part of the workshop is structured around hands-on
the University of Haifa, Israel.
activity sessions in small subgroups of 3-5 participants.
REFERENCES
3 Key People [1] Malin Eiband, Hanna Schneider, Mark Bilandzic, Julian Fazekas-Con, Mareike
Haug, and Heinrich Hussmann. 2018. Bringing Transparency Design into
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3.1 Keynote Speaker InformationInteraction&Retrieval. https://doi.org/10.1145/3172944.3172961
[2] Alyssa Glass, Deborah L. McGuinness, and Michael Wolverton. 2008. Toward
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