Dr. Aleš Završnik is a Senior Researcher Associate at the Institute of Criminology at the Faculty of Law in Ljubljana and Associate Professor at the Faculty of Law University of Ljubljana (Slovenia). He is currently EURIAS Fellow 2017/18 at the Collegium Helveticum, ETH, in Zurich. In the past he was a postdoctoral fellow of the Norwegian Research Council at the University of Oslo (2012) and a postdoctoral fellow at the Max-Planck-Institute für ausländisches und internationals Strafrecht in Freiburg i. Br. (2009). He co-managed several international scientific networks of the COST (European Cooperation in Science and Technology) programme that were dedicated to technology, law, surveillance and delinquency on the Internet (e.g. currently Action CA16121 “From Sharing to Caring: Socio-Technical Aspects of the Collaborative Economy” and Action IS0807 “Living in Surveillance Societies” or the Action IS0801 “Cyberbullying” in the past). His research interest lay in the intersection of law, crime, technology, and fundamental rights. Currently, he leads a research project funded by the Slovenian National Research Agency “Law in the age of big data: Regulating privacy, transparency, secrecy and other competing values in the 21st century” (2014 - 2017). His most recent scientific achievements include edited book “Big Data, Crime and Social Control” (Routledge, 2018); and  “Drones and Unmanned Aerial Systems: Legal and Social Implications for Security and Surveillance” (Springer, 2015). He organised several conferences in these research areas, e.g. “Big data: Challenges for Law and Ethics” (Ljubljana, 2017) and “Spy in Sky: Regulatory issues of drones and unmanned aerial systems” (Ljubljana, 2013). He was an independent Ethics Expert with the European Research Council (ERC) and for the REA, the research arm of the European Commission, for Horizon 2020 projects.

Mapping crime and Artificial Intelligence The research intends to analyse techniques for mapping crime in public space with crime predictive software in France. Similarly to predictions in other contexts, such as predictive analytics for product recommendations made by Amazon, movies by Netflix, or...