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Results: ANITA Workshop

The Anonymous Big Data workshop was organized in the context of the ANonymous bIg daTA (ANITA) project. ANITA aims to systematically examine and validate the feasibility of using artificial intelligence and advanced machine learning to generate synthetic data that preserve individual privacy as well as retain enough substantive and statistical information to ascertain its usefulness for market(ing) research purposes.


Invitation: ANITA Workshop

We would like to invite you to the expert workshop of the ANonymous bIg daTA (ANITA) project. ANITA aims to systematically examine and validate the feasibility of using artificial intelligence and advanced machine learning to generate synthetic data that preserve individual privacy as well as to retain enough substantive and statistical information to ascertain its usefulness for market(ing) research purposes. In the face of stricter data protection regulations within Europe (GDPR), the success of this approach would allow safe cross-organizational data sharing and thus facilitate data-driven innovation and research processes distributed across industries.


Overcoming privacy issues by generating ‘fake’ customer data

Abstract: Privacy is a fundamental right of customers . Over the years, we observe growing attention for privacy concerns, due to wider availability of data and the the development of methodologies which jointly allow for more fine-grained and individual analyses of customers’ needs and wants. This leads to benefits for consumers, but this can also be perceived as pervasive. The associated privacy concerns have led to a critical attitude towards the collection and analysis of individual customer data. In this talk, I will discuss one of the possible directions to alleviate such privacy concerns. I will discuss a paper in which we develop generative networks that are able generate individual-level data of customers, that are non-existing, but mimic data of real customers.


BIG DATA UND PRIVACY – EIN SPANNUNGSFELD?

Big Data und Open Data gelten als Treibstoff für Innovationen, als das „new oil“ einer digitalen Ökonomie und Gesellschaft. Aber auch Forschung und Wissenschaft profitieren von der Digitalisierung, etwa indem bislang unzugängliche Datenbestände miteinander kombiniert werden können. Doch diesen Vorteilen steht ein zunehmendes Unbehagen beim Teilen persönlicher Daten und das steigende Interesse am Schutz der Privatsphäre gegenüber. Big Data und Marketing Analytics scheinen mit dem Datenschutz im Widerspruch zu stehen. Doch ist diese Skepsis gerechtfertigt? Worin bestehen die Vorteile von Big Data und Marketing Automation für Konsument/inn/en? Und müssen wir zum Schutz unserer Privatsphäre gänzlich auf diese verzichten?


VORTRAG ZU CRM UND DATENSCHUTZ

Im Rahmen der Marketing-Praxis Vortragsreihe referiert der namhafte Datenschutzexperte Dr. Stephan Winklbauer (Partner bei Aringer, Herbst und Winklbauer Rechtsanwälte) gemeinsam mit Christoph Wenin (CISO und Datenschutzbeauftragter von REWE) zum Thema: „Der gläserne Kunde oder nur geniales Marketing? Die JÖ-Karte im Zeitalter der DSGVO. Rechtliche Grundlagen und Funktionsweise eines Kundenbindungsprogrammes.“


THE PROJECT HAS STARTED!

On October 1st the research project “AI-Based Privacy-Preserving Big Data Sharing for Market Research” (in short “Anonymous Big Data”) has started. It is funded by FFG and aims to systematically validate the feasibility of using deep recurrent neural network architectures to generate synthetic sequential raw data that preserve individual privacy and, at the same time, retain enough information to be used for market research. In this project Vienna University of Economics and Business collaborates with Mostly AI Solutions MP GmbHGeorge Labs GmbH and Statistik Austria.