26 Nov
2024
26 Nov
'24
2:12 p.m.
Liebe EST-ler,
wir haben eine Einladung und eine gute Nachricht:
Durch das große Engagement von Dietlind Hüchtker ist es gelungen, eine
TT-Fast Track Professur *„Wissensgeschichte und politische
Epistemologien von Biowissenschaften und Medizin im 20. Jahrhundert” für
Prof. Birgit Nemec* am Fakultätszentrum für transdisziplinäre
historisch-kulturwissenschaftliche Studien einzurichten. Der Wechsel vom
Institut für Medizingeschichte an der Charité Berlin wird bereits am
1.12.2024 erfolgen. Ein Forschungsschwerpunkt wird Rahmen eines ERC
Forschungsprojektes gefördert und gilt dem Engagement von Patient:innen
mit arzneimittelbedingten Behinderungen sowie dem Wandel im Umgang mit
Risiken seit der Contergan-Katastrophe. https://fakzen-thks.univie.ac.at/
Zudem wird Donnerstag und Freitag die*Tagung "Automated Order"*
stattfinden, die Markus Ramsauer und ich mit Kolleg:innen veranstalten.
Es geht um die Frage der Gesellschaftsbeschreibung durch neue
statistische Verfahren, insbesondere Clusteringverfahren. Wer in letzter
Zeit über die Frage von Algorithmen im US Wahlkampf diskutiert hat, über
die Sicherung von Privatheit in Zeiten von AI nachdenkt oder mehr über
die Geschiche der Sentiment Analysis erfahren will, ist ganz herzlich
willkommen: Teilnahme ist unangemeldet möglich über Zoom (links auf der
Homepage) oder Ihr kommt auf einen Kaffee im ifk vorbei
(Reichratsstrasse 17, das Gebäude zwischen NIG und Hauptgebäude)
https://automated-order.univie.ac.at/
Mit bestem Gruß
Anna Echterhölter
Clustering: Automated Order in the Social Sciences
International Workshop, organized by Anna Echterhölter
<https://ifg.univie.ac.at/ueber-uns/mitarbeiterinnen/wissenschaftliche-mitarbeiterinnen/anna-echterhoelter/> and
Markus Ramsauer
<https://ifg.univie.ac.at/ueber-uns/mitarbeiterinnen/projektmitarbeiterinnen/markus-ramsauer/> in
cooperation with the working group “How is AI Changing Science
<https://howisaichangingscience.eu/projektbeschreibung/>”, University of
Vienna <https://fsp-wissenschaftsgeschichte.univie.ac.at/>, and the
International Research Center for Cultural Studies (ifk).
Date: November 28-29, 2024
Venue: International Research Center for Cultural Studies
(Internationales Forschungszentrum Kulturwissenschaften
<https://www.ifk.ac.at/>), Reichsratsstraße 17, 1010 Vienna (ground floor)
Online audience: Please use the following Zoom links:
Donnerstag, 28.11.
<https://us06web.zoom.us/j/87831389185?pwd=hPBpZ9CTmXdNqOj8M0dTeJ9MSJMQcn.1>us06web.zoom.us/j/87831389185
<https://us06web.zoom.us/j/87831389185?pwd=hPBpZ9CTmXdNqOj8M0dTeJ9MSJMQcn.1>
Meeting-ID: 878 3138 9185
Kenncode: mcX7T5
Freitag, 29.11.
<https://us06web.zoom.us/j/87613835276?pwd=xoYRKgybbq6HACrqcCpZ3Eme3F4EDn.1>us06web.zoom.us/j/87613835276
<https://us06web.zoom.us/j/87613835276?pwd=xoYRKgybbq6HACrqcCpZ3Eme3F4EDn.1>
Meeting-ID: 876 1383 5276
Kenncode: ZwhF8y
Download the poster:here
<https://automated-order.univie.ac.at/fileadmin/user_upload/i_geschichte/Ueber_uns/MitarbeiterInnen/Echterhoelter/Automated-Order-Plakat__.pdf>
The workshop is part of the research project HiACS, funded by one of
Europes largest research funding institutions, the Volkswagen Foundation
Hannover. Members are Jens Schröter and Andreas Sudmann, University of
Bonn, Alexander Waibel and Fabian Retkowski KIT/Carnegie Mellon, as well
as Anna Echterhölter and Markus Elias Ramsauer, University of Vienna:
howisaichangingscience.eu/projektbeschreibung/
<https://howisaichangingscience.eu/projektbeschreibung/>
Programme
Thursday, November 28, 2024
13.00 CET / Opening remarks / 7 am EST /
Julia Boog-Kaminski
<https://www.ifk.ac.at/kontakt-team/dr-in-julia-boog-kaminski.html>andAndreas
Gehrlach
<https://www.ifk.ac.at/kontakt-team/dr-andreas-gehrlach.html>(IFK):
Welcome to the IFK
Anna Echterhölter
<https://ifg.univie.ac.at/ueber-uns/mitarbeiterinnen/wissenschaftliche-mitarbeiterinnen/anna-echterhoelter/>andMarkus
Ramsauer
<https://ifg.univie.ac.at/ueber-uns/mitarbeiterinnen/projektmitarbeiterinnen/markus-ramsauer/>(University
of Vienna): Introduction
13.20 CET / Keynote I / 7.20 am EST /
Evangelos Pournaras
<https://eps.leeds.ac.uk/computing/staff/6446/professor-evangelos-pournaras>(University
of Leeds):
Privacy as a Collective Value and how to Protect it in the Era of AI
14.20 CET coffee break
14.30 CET / Panel I – Perspectives from Media Ethnography and
Archaeology / 8.30 am EST /
Chair:Jens Schröter
<https://www.medienkulturwissenschaft-bonn.de/mitarbeiter_prof_dr_jens_schroeter_team6.html>(University
of Bonn)
14.30-15.00 Fabian Retkowski
<https://isl.anthropomatik.kit.edu/english/21_9385.php> (Karlsruhe
Institute of Technology) and Andreas Sudmann
<https://www.medienwissenschaft.uni-bonn.de/personen/abteilung-personenverzeichnis/projektmitarbeiterinnen-drittmittel/andreas-sudmann> (University
of Bonn): Automated Coding: Multilabel-Classification in Ethnography
15.00-15.30 CETAndreas Sudmann
<https://www.medienwissenschaft.uni-bonn.de/personen/abteilung-personenverzeichnis/projektmitarbeiterinnen-drittmittel/andreas-sudmann>andJens
Schröter
<https://www.medienkulturwissenschaft-bonn.de/mitarbeiter_prof_dr_jens_schroeter_team6.html>(University
of Bonn):
AI in Science and Epistemic Media
15.30 CET coffee break
16.00 CET / Panel II – Clustering and Detecting Tensions within the
Social Order / 10 am EST /
Chair:Clemens Apprich
<https://medientheorie.uni-ak.ac.at/en/project/univ-prof-mmag-dr-clemens-apprich-2/>(University
of Applied Arts, Vienna)
16.00-16.30 CET Fenwick McKelvey
<https://www.concordia.ca/faculty/fenwick-mckelvey.html>(Concordia
University, Montreal):
US Elections and the Electric Cluster Making Machine
16.30-17.00 CET Orit Halpern
<https://tu-dresden.de/gsw/slk/germanistik/digitalcultures/die-professur/inhaber-in?set_language=en>(Dresden
University of Technology):
Mirror Worlds: Clustering, AI, and the Management of Catastrophe
17.00-17.30 CET Aaron Gluck-Thaler
<https://histsci.fas.harvard.edu/people/aaron-gluck-thaler>(Harvard
University):
Identification through Pattern Recognition in Cold War America
17.30 CET coffee break
18.00 CET / Keynote II / 12.00 am EST /
Rebecca Lemov
<https://histsci.fas.harvard.edu/people/rebecca-lemov>(Harvard
University): History of Sentiment Analysis
Chair:Markus Ramsauer
<https://ifg.univie.ac.at/ueber-uns/mitarbeiterinnen/projektmitarbeiterinnen/markus-ramsauer/>(University
of Vienna)
20.00 CET dinner (ASPIC, Garnisongasse 10)
Friday, November 29, 2024
09.00 CET / Panel III – Automated Social Order / 3 am EST /
Chair:Sarah Davies
<https://sts.univie.ac.at/en/about-us/scientific-staff/wissenschaftliche-ma/sarah-davies/>(University
of Vienna)
09.00-09.30 CET Dinah Pfau
<https://www.deutsches-museum.de/forschung/person/dinah-pfau-2>(Deutsches
Museum, Munich):
Epistemology of a Matrix, or How Communication Technology Invented the Human
09.30-10.00 CET Eva-Maria Gillich
<https://ekvv.uni-bielefeld.de/pers_publ/publ/PersonDetail.jsp?personId=162644614>(Bielefeld
University): Norms out of Patterns
10.00-10.30 CET Tobias Matzner
<https://www.uni-paderborn.de/en/person/65695>(Paderborn University):
On some Similarities between Clustering and Embeddings
10.30 CET coffee break
11.00 CET / Panel IV – Clustering: Work and Health / 5 EST /
Chair:Christian Dayé
<https://www.tugraz.at/arbeitsgruppen/sts/publikationen/christian-daye>(Graz
University of Technology)
11.00-11.30 CET Phoebe Moore <https://phoebevmoore.wordpress.com/>:
(University of Essex):
Affective Computing at Work: Policy Provocations and Rights for the Left
11.30-12.00 CET Rudolf Seising
<https://www.deutsches-museum.de/forschung/person/rudolf-seising-2>(Deutsches
Museum, Munich): Fuzzy Sets and Systems: An Alternative Approach to Blur
and Inaccuracy for AI in the 20th Century
12.00-12.30 CET Wrap Up
13.00 CET lunch (Gastwirtschaft Blauensteiner, Lenaugasse 1)
The research project and workshop are made possible by the Volkswagen
Foundation.
Visit MiniSeg, the new benchmark video segmentation model, or a database
of European research projects using AI. Also more on the working group
HIACS: https://howisaichangingscience.eu/
The venue is provided by ifk: https://www.ifk.ac.at/
For more in formation on the history of science working group in Vienna:
https://fsp-wissenschaftsgeschichte.univie.ac.at/
Conference Abstract
Clustering -- Automated Order in the Social Sciences
ai\research\explorations workshop IV
Organized by the Viennese working group of the project “How is AI
Changing Science” in cooperation with the International Research Center
for Cultural Studies (IFK) Vienna
28.-29. November 2024
One of the key elements in unsupervised learning is clustering. Thus,
this particular data practice sits at the core of modern Artificial
Intelligence, which is based on artificial neuronal networks. Whereas
classification operates by organizing labeled data into specific
categories, clustering relies on cheaper, unlabeled data for deciphering
similarities inside a given set.
While many scientific disciplines might be interested in this new
element of technical progress, the social sciences should be. The
workshop poses the open question if unsupervised data clustering has the
potential of identifying and generating new patterns of the social. This
idea is not new. As Orit Halpern has remarked, attempts to break free
from stable categories like race, identity, territory, or ethnicity with
the help of pattern recognition can be found e.g. in the works of
political scientist Karl Deutsch already in the 1960s (Halpern 2014, p.
191). Can clustering come up with entirely new orders of the social,
such as tribes of movements identifiable from telephone data, do they
detect political party affiliation, friendship or kinship-patterns that
are not blood-related, and thus resemble totemistic orders? Or does
automatization in the analysis of social data reproduce older
hierarchies and familiar stratifications with necessity? While it is
crucial not to fall prey to techno-utopian fantasies of non-situated
(AI) technologies ‘overcoming’ race, class or gender, the transformative
potential of clustering practices for analysis and reorganization of
society and resource management in crisis should not be dismissed entirely.
While the history of quantification has made great strides to trace
centers of calculation (Didier 2021; Wiggins and Jones 2023), while the
cold war genealogy of AI is being established (Seising 2018; Dick 2021;
Babintseva 2023), the history of data has developed additional
perspectives. The focus lies with the practical handling of digital
information as element of scientific or bureaucratic practices (Suchman
2006; Aronova 2017; Rheinberger 2018; De Chadarevian and Porter 2018;
Dommann and Stadler 2020; Schlicht et al. 2021). The workshop singles
out one particular episode from such a data journey (Leonelli and
Tempini 2020). There are general discussions of classification and
clustering (Arabie, Lawrence and de Soete 1996; Brunton and Kutz 2019;
Bowker 2001), some already with respect to data practices within
specific methods, and even fewer in the social sciences and humanities
(Boumans and Leonelli 2020).
Clustering practices are typical for automated learning across the
disciplines, which relies on large amounts of data, thereby introducing
an element of noise and ambiguity. They do seemingly replace human
cognition as source of social order. Thus, automated ordering can be
said to introduce a novel element of ambiguity to the representation of
society. From this position we ask, if clustering algorithms like
K-means introduce elements of irrationality into planning processes or
sociological methods. The automated social order comes with a new level
of imprecision. The history of rationality is thus faced with a new
ambiguity, after the probabilistic revolution of the 19th century did
already alter the accepted forms of evidence (Krüger et al. 1987). When
during the cold war, “reason almost lost its mind” (Erickson et al.
2013), the mind now seems to prevail over rational forms of conclusion.
We are particularly interested in this new mechanism that seemingly
replaces conscious order with an automated process of matchmaking. As
Sabina Leonelli has emphasized for the case of biology, clustering is
the very pre-condition for data to become a representation of the world
(Leonelli 2023, p. 317-318). Yet, in unsupervised learning, the outcomes
seem to be uncontrollable. It stands to reason, which kind of tradeoff
between rational planning and seemingly irrational ordering the new
branch of computational sociology may soon come up with. Are we close to
accepting a new age of similarities and epistemologies of similitudes
which abandons factual evidence in exchange for patterns and noisy data
clouds?
Following the suggestions of the history of data this conference
approaches AI in social sciences from the perspective of one key
practice. The workshop invites media archaeologists, historians of
science and quantification as well as computational sociologists and
data curators to reflect on the history, promise a potential of
clustering. For this we want to establish both, the analogue and digital
histories of clustering.
The Project: How is AI Changing science
The workshop is funded by the Volkswagen Foundation and part of a larger
research project. We ask how artificial intelligence (AI) technologies
do affect research and science? By following this perspective, the
project is less concerned with research on AI per se than with how
different disciplines use AI as a tool and as an epistemic entity within
larger (post)digital infrastructures. The central focus lies on how
heterogeneous concepts and operations of the social sciences and
humanities, on the one hand, and the natural and technical sciences, on
the other, are integrated into applications of AI. Research on the
latter will also explore the extent to which critical perspectives
inform and accompany the use of AI. The project concentrates on
artificial neural networks (ANN) because of their dominant status among
current AI approaches. Hence, the project not only explores the
similarities and differences between the various areas of application of
AI, but also sheds light on the cultural and national specificities
inherent to these processes in an international context, particularly in
Europe and the USA.
howisaichangingscience.eu/projektbeschreibung/
<https://howisaichangingscience.eu/projektbeschreibung/>
Members: Anna Echterhölter, Markus Elias Ramsauer University of Vienna,
Jens Schröter and Andreas Sudmann, University of Bonn and Alexander
Waibel and Fabian Retkowski KIT/Carnegie Mellon
Literature:
Arabie, Phipps, Lawrence J. Hubert, and Geert De Soete. Clustering and
Classification. Singapore: World Scientific 1996.
Aronova, Elena, von Oertzen, Christine und Sepkoski, David:
Introduction: Historicizing Big Data. In: Osiris 32/2017, S. 1–17.
Babintseva, Ekaterina: Rules of Creative Thinking: Algorithms,
Heuristics, and Soviet Cybernetic Psychology. In: BJHS Themes, Volume 8:
Histories of Artificial Intelligence: A Geneology of Power 2023, S. 81-95.
Boumans, Marcel, and Sabina Leonelli: From Dirty Data to Tidy Facts:
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Data Journeys in the Sciences, edited by Sabina Leonelli and Niccolò
Tempini. Heidelberg: Springer 2020, S. 79–101.
Bowker, Geoffrey C.: Biodiversity Datadiversity. In: Social Studies of
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Brunton, Steven L., and J. Nathan Kutz. ‘Classification and Clustering’.
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De Chadarevian, Soraya and Porter, Theodore: Introduction: Scrutinizing
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Dick, Stephanie: Of Models and Machines: Implementing Bounded
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Didier, Emmanuel: Quantitative Marbling, New Conceptual Tools for the
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