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

[Monika Halkort]

Hey katja

Ich wuerd euch super gern ein statement of interest schicken und am workshop teilnehmen. Aber ich schaff April 3 nicht. Komm fruehestens am dienstag April 9 days. Ist das  noch akzeptabel? Best mo

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On Mon, Apr 1, 2019 at 2:26 PM +0300, "Katja Mayer" <katja.mayer at univie.ac.at<mailto:katja.mayer at univie.ac.at>> wrote:


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
> , 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:  >.
>
> ORGANIZERS
> *Momin M. Malik*  >, Berkman Klein Center for
> Internet & Society at Harvard University
> *Katja Mayer*  >, Department of Science and
> Technology Studies, University of Vienna, and ZSI Centre for Social
> Innovation Vienna
> *Hemank Lamba* >, School
> of Computer Science, Carnegie Mellon University
> *Claudia Müller-Birn*  >, 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

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