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Predictive video surveillance to prevent suicides in German jails; algorithmic risk assessment of domestic violence in Spain; predictive justice systems helping Italian courts decide whether a complaint is algorithmically sound or not. An automated decision-making system that suggests treatments for cancer patients in Switzerland, while others help profiling the unemployed and provide payments of welfare system benefits in Denmark. Sounds (France), smiles (Poland), faces (increasingly, everywhere): nothing seems to escape the realm of automated analysis and decision.
And yet, much of the debate in the field of algorithmic decision-making systems (ADMS) and so-called Artificial Intelligence privileges discourses of lofty ethical norms. Too little is known about the many ways in which these systems are already being used in practice.
Within these disparate use-cases, it is very important to ask what constitutes context-specific, fit-for-purpose policies with regards to ADMS. To do this we need evidence that will both inform and shape the needed actions, so that ADMS could be used to increase welfare and liberties, whilst also limiting their abuses through harmful surveillance, discrimination, and control.
We will share state-of-the art evidence about the practice of algorithmic decision-making processes already in use, taken from our brand new Automating Society 2020 report, covering 16 European countries: Belgium, Denmark, Estonia, Finland, France, Germany, Greece, Italy, Netherlands, Poland, Portugal, Slovakia, Spain, Sweden, Switzerland, UK.
In a first part, we will briefly present excerpts of our evidence-based research on issues of ADMS and lay out our recommendations for policies and government arrangements. In the second part we will discuss these with the audience.
- Introduction: Matthias Spielkamp, Executive Director, AlgorithmWatch
- Overview: Fabio Chiusi, Editor Automating Society Report 2020
- Poland: Alek Tarkowski, President of the Board, Centrum Cyfrowe