[Air-L] CfP Critical Data Science workshop at ICWSM 2019 in Munich

[Katja Mayer]

Dear Colleagues

we have extended the deadline to April 3rd.

https://projects.iq.harvard.edu/critical-data-science

With best regards

Katja Mayer


Am 05.03.19 um 10:33 schrieb Katja Mayer:
> CALL FOR PAPERS
> *Workshop on Critical Data Science*
> at the 13th International AAAI Conference on Web and Social Media 
> (ICWSM-2019),
> Munich, Germany, June 11, 2019
>
> https://projects.iq.harvard.edu/critical-data-science
>
> *Submissions deadline: March 25, 2019*
> *Acceptance notification: April 12, 2019*
>
> We invite submissions to the Workshop on Critical Data Science, taking 
> place on June 11, 2019 at the 13th International AAAI Conference on 
> Web and Social Media (ICWSM-2019) in Munich, Germany.
>
> -------------
> The social world is far messier than technical training prepares one 
> for. Among data scientists trained in fields like computer science and 
> statistics are those experiencing a sense of vertigo: we start to 
> realize both the ways in which modeling breaks down on human beings, 
> requiring different notions of rigor, and the potentially negative 
> social impacts of modeling, requiring responsible engagement and 
> activity.
>
> We define “critical data science” as our vision of the practice of 
> working with and modeling data (the “data science”), combined with 
> identifying and questioning the core assumptions commonly underlying 
> that practice (the “critical”). The workshop seeks to combine cultures 
> of critique with those of practice, bringing together data scientists 
> and scholars from computer science and the social sciences around 
> responsibly carrying out data science on social phenomena, and 
> creating sustainable frameworks for interdisciplinary collaboration.
>
> The workshop will involve short reflective presentations by 
> participants, combined with a creative group-based activity to further 
> support reflection of their own and neighboring scientific practices 
> and to create opportunities for further cooperation. The workshop will 
> conclude with a wrap-up for collecting resources and discussing future 
> outcomes, and producing a draft compilation of best practices and a 
> list of priorities for further engagement.
>
> Submissions may either be non-archival 2-page statements of interest 
> or motivation, or archival papers up to 4,000 words. Accepted archival 
> papers will be published in Workshop Proceedings of the 13th 
> International AAAI Conference on Web and Social Media 
> <https://www.frontiersin.org/research-topics/9706>, a special issue of 
> the journal Frontiers in Big Data. Open Access publishing costs will 
> be waived for authors without institutional support for covering these 
> fees.
>
> Topics include:
>
>  * What should be standards and practices both of methodological rigor,
>    and of respect for subjects, when carrying out computational
>    research on social systems?
>  * What role can discussions of methods and instruments play in larger
>    critiques of the limitations of data science?
>  * What are points of fundamental disagreement or diverging
>    orientations/priorities between disciplines?
>  * What can we learn from the long tradition of critical scrutiny in
>    statistics?
>  * What combinations of experiences and/or readings has led data
>    scientists to recognize, and perhaps even adopt, ‘non-technical’
>    ways of framing the world? How do and can these ways of knowing
>    interact with a modeling approach?
>  * What philosophical commitments or normative orientations, if adopted
>    by data scientists, would produce a principled data science? How can
>    those be realized in interdisciplinary teams?
>  * What might it look like to use modeling critically and reflexively,
>    or to contextualize what we can or cannot know from modeling from
>    within the modeling process?
>  * What can we learn from works looking at the social impact of
>    implemented model-based systems?
>  * What sorts of practices, coalitions, and collaborations can include
>    marginalized voices into data science rather than exclude them?
>  * Beyond a space for critical reflection, what can be the positive
>    project of a critical data science?
>  * How can we design collaborations in critical data science?
>
> See https://projects.iq.harvard.edu/critical-data-science for more 
> information and submission instructions.
>
> Contact: <criticaldatasci2019 at gmail.com 
> <mailto:criticaldatasci2019 at gmail.com>>.
>
> ORGANIZERS
> *Momin M. Malik* <momin_malik at cyber.harvard.edu 
> <mailto:momin_malik at cyber.harvard.edu>>, Berkman Klein Center for 
> Internet & Society at Harvard University
> *Katja Mayer* <katja.mayer at univie.ac.at 
> <mailto:katja.mayer at univie.ac.at>>, Department of Science and 
> Technology Studies, University of Vienna, and ZSI Centre for Social 
> Innovation Vienna
> *Hemank Lamba* <hlamba at cs.cmu.edu <mailto:hlamba at cs.cmu.edu>>, School 
> of Computer Science, Carnegie Mellon University
> *Claudia Müller-Birn* <clmb at inf.fu-berlin.de 
> <mailto:clmb at inf.fu-berlin.de>>, Institute of Computer Science, Freie 
> Universität Berlin
>
-- 
Dr. Katja Mayer
https://rri.univie.ac.at
https://www.katjamayer.net

Old address: School of Governance, Technical University Munich
Computational Social Science and Big Data
katja.mayer at hfp.tum.de