I’m giving serious thought to this, as much as I’m trying to save money and travel less:
Call for Papers for the Conference „Scraping the Demos“: Political
epistemologies of Big Data
Organizers: Research Group Quantification and Social Regulation
(Weizenbaum Institute for the Networked Society) and DVPW Thematic Group
“Internet and Politics. Electronic Governance”
Date: 8-9 July 2019 (lunch-to-lunch)
Conference location: WZB Berlin Social Science Center, Reichpietschufer
50, D-10785 Berlin, Germany
Responsible: Dr. Lena Ulbricht firstname.lastname@example.org
The conference explores political epistemologies of big data. Political
epistemologies are practices by which societies construct politically
relevant knowledge and the criteria by which they evaluate it. These
practices and criteria may originate in scientific, political, cultural,
religious, and economic contexts. They evolve over time, vary between
sectors, are inherently political and therefore subject to conflict. Big
data is the practice of deriving socially relevant knowledge from
massive and diverse digital trace data. The rise of digital technologies
in all social spheres has enabled new epistemic practices which have
important political implications: Political elites see digital
technologies as sources of new and better tools for learning about the
citizenry, for increasing political responsiveness and for improving the
effectiveness of policies.
Practices such as “big data analysis”, “web scraping”, “opinion mining”,
“sentiment analysis”, “predictive analytics”, and “nowcasting” seem to
be common currency in the public and academic debate about the present
and future of evidence-based policy making and representative democracy.
Data mining and web scraping, techniques to access information “hidden”
behind the user interface of a website or device, seem to establish
themselves as epistemic practices with political implications. They
generate knowledge about populations and the citizenry which diverge in
many ways from previous ways of “seeing” and constructing the demos.
Data that is based on digital collection tools is often much more
personal, it can relate different kinds of information and in many cases
offer an improved predictive capability. Therefore, survey methods and
traditional administrative data may lose influence on political
epistemologies. To rely on big data means to rely on data sources that
accumulate information without awareness of the concerned individuals.
This epistemic shift can be observed in policy advice, government and
administration, and political campaigning. Emerging research strands
such as “computational social sciences,” “social physics,” “policy
analytics”, “policy informatics”, and “policy simulations” strive for
better evidence, more transparency and responsiveness in policy making
and governments such as in the UK, or, as in Australia, have set up
strategies of “open policy making”, “agile policy making” and “public
service big data”.
Political parties and advocacy groups use digital data to address
citizens and muster support in a targeted manner; public authorities try
to tailor public policy to public sentiment measured-online, forecast
and prevent events (as in predictive policing, preemptive security and
predictive healthcare), and continuously adapt policies based on
real-time monitoring. An entire industry of policy consultants and
technology companies thrives on the promise related to the political
power of digital data and analytics. And finally, academic research
engages in digitally enhanced computational social sciences, digital
methods and social physics on the basis of digital trace data, machine
learning and computer simulations. The political implications of these
epistemic practices have yet to be examined in detail. Indeed, the rise
of digital technologies in all social spheres may alter the relations
between citizens and political elites in various ways: it could improve,
impoverish (or simply change) political participation, policy
transparency, accountability of political elites and, and decision-making.
The aim of the conference is to bring together scholars from various
related disciplines working on the topic, including, but not limited to:
political communication, elections and party politics, science and
technology studies, political theory, history, sociology and philosophy
of science, critical data studies and computational social sciences.
These fields of research have addressed various aspects related to
political epistemologies in the digital age – but there have been only
few opportunities to relate them, to compare similar practices in
different fields (for example in public policy and in political
campaigning) and to examine the broader picture in order to generate
theories about the political epistemologies of big data, algorithms and
artificial intelligence. Contributions can be both, conceptual or empirical.
The conference is interested in research concerning the following
questions and similar topics:
• What are the political epistemologies underlying the use of big data
and related phenomena such as algorithms, machine learning and
artificial intelligence in political contexts?
• Which scientific, political, social and economic practices make use of
digital data and methods? How do these practices construct knowledge
which is deemed as politically relevant? By which
(rhetoric/procedural/technical) means do these practices and the actors
involved substantiate their claims to political relevance?
• What insights can we gain from the computational social sciences in
relation to traditional social science methods when it comes to
political behavior, public opinion, policy making etc.?
• How are digitally mediated political epistemologies related to other
political epistemologies? How are they embedded in institutional
practices and values?
• Which interpretive conflicts do we witness with regard to the
knowledge produced and legitimized by digital technologies; which are
its major challengers? In which ways do epistemic practices based on big
data, compared to other epistemic practices, influence the chances for
challenging political knowledge claims?
• How can we place political epistemologies in a historical or cultural
• What are the implications of digitally mediated political
epistemologies for evidence-based policy making and for representative
democracy? Which conceptions of participation, representation and good
governance are embedded in the related practices? How do big
data-related epistemic practices reconfigure democratic concepts? Do we
witness a new form of technocracy?
• How should democratic societies shape and regulate big-data-based
epistemic practices? Which contributions can we expect from algorithmic
accountability, data protection and research ethics?
The conference will provide academic reflections to current public
debates about the state of democracy in the digital age, considering
that in 2019 various elections take place in German speaking countries,
at the level of the European Parliament and within the German federal
states of Bremen, Hamburg, Saxony, Brandenburg and Thuringia, as well as
in Austria and Switzerland (regional and federal level). The keynote
will be held by professor Daniel Kreiss, the author of a seminal book
about the use of data-related practices in political campaigning
(“Prototype Politics” 2016). The conference will also include artistic
interventions and a lab.
The conference will offer childcare, will be video-recorded, and held in
English. If the funding application is successful, the travel costs of
paper presenters will be covered. The organizers plan on following up
the conference with a publication project.
Abstracts should make explicit on which theories, methods and, if
applicable, empirical material the paper is based. Please send your
abstract of 300-500 words until February 24 to the following address:
Preliminary program structure
8 July 2019
14.00 Welcome address
14.15 Keynote by professor Daniel Kreiss + discussion
16.00 Paper presentations
17.30 Lab and art exhibition
9 July 2019
9.00 Paper presentations
11.00 Paper presentations
12.30 Paper presentations or panel discussion