An Artistic Research Into The Use of Personal Data for Political Communication

Frischknecht, Max (26 March 2021). An Artistic Research Into The Use of Personal Data for Political Communication In: Deep City: Climate Crisis, Democracy, and the Digital. EPFL Lausanne. 24.03 – 26.03.2021.

Facebook, Twitter, and other social networks transform political communication. Simultaneously, the misuse of personal data for divisive social media campaigns has intensified political conflicts. Political actors collect personal data about potential voters to create specific target groups through psychological analysis methods. The analysis enables to predict the reaction of a person towards an advert and is incorporated in the design process. Known as Micro Targeting, this technique implements the voter‘s worldview into the adverts’ argumentation. It is believed that the PR agency Cambridge Analytica contributed to Donald Trump‘s election victory with this method. In Switzerland, the elections in October 2019 showed that Swiss parties increasingly use personal data for their campaigns. Some parties obtained data from data brokers, used psychological models for behavior prediction, and created thousands of nuanced Micro Targeting adverts. This personalization of advertisement is problematic because it prevents the comparison and diversity of information while isolating the citizens. It promotes the polarization of opinions and prevents democratic consensus-building. As a result and given the much-cited „over-complexity“ of digital technology, there is an increasing need for improved literacy regarding that matter. This work uses design methods like prototyping and information visualization as tools to understand and mediate the technological conditions which lie beneath such political communication. The ongoing series Scripted Loopholes investigates individual technological components and phenomena to gradually arrive at an understanding of how behavioral predictions work and what role they play in political communication. So far, this included working with and on Facebook's prediction of advertisement interests, machine learning algorithms to identify persons, places, and more from private Facebook messages, and, mapping political communication on Twitter during the Swiss ballot meeting in October 2019.

Item Type:	Conference or Workshop Item (Speech)
Division/Institute:	Bern Academy of the Arts Bern Academy of the Arts > Institute of Design Research Bern Academy of the Arts > Institute of Design Research > Knowledge Visualization
Name:	Frischknecht, Max0000-0001-8043-1895
Subjects:	N Fine Arts > N Visual arts (General) For photography, see TR T Technology > T Technology (General)
Language:	English
Submitter:	Max Frischknecht
Date Deposited:	05 May 2021 14:35
Last Modified:	19 Apr 2022 21:45
URI:	https://arbor.bfh.ch/id/eprint/14666