ETIAS system and new proposals to advance the use of AI in public services

Abstract

Eu-LISA is launching the European Travel Information and Authorization System (ETIAS), which seems an example of a different, human rights-oriented approach to AI within the law enforcement. However, the reality is quite different: the usual problems of the use of AI—lack of transparency, bias, opacity, just to name a few—are still on board. This paper critically assesses these promises of ETIAS and argues that it has serious issues that have not been properly dealt with. So as to argue the need to address these issues, the paper addresses ETIAS within the wider context of human rights and solidarity-based data governance. In this respect, ETIAS is seen as a tool which uses data for high value purposes, such as EU safety and security, yet it also calls for serious risk mitigation measures. Indeed, the risks related to law enforcement on the borders and in migration management are extremely serious due to the vulnerability of people who escape from poverty, wars, regimes, and other disasters. In the third part of this article, we articulate three proposals of such risk mitigation measures. We argue in favour of strengthening critical general safeguards in ETIAS, then elaborate a principle that should guide AI-based public service development (P4P principle) and end with a few IPR-related requirements for private sector involvement in such services. Adopting these measures could contribute to reduce the risk of building EU AI expertise upon data coming from the most vulnerable social groups of our planet.