Comment by European Economic and Social Committee (EESC)

The EESC calls for a ban on use of AI for automated biometric recognition in publicly and privately accessible spaces, except for authentication purposes in specific circumstances, as well as for automated recognition of human behavioural signals in publicly and privately accessible spaces, except for very specific cases, such as some health purposes, where patient emotion recognition can be valuable. [...] The AIA aims to ban real-time remote biometric identification (with facial recognition, for example) for law enforcement and categorise it as ‘high risk’ when used for other purposes. This leaves ‘post’ and ‘near’ biometrics recognition allowed. It also leaves biometric recognition not aimed at identifying a person, but rather at assessing a person’s behaviour from their biometric features (micro expressions, gait, temperature, heart rate, etc.) allowed. The limitation to ‘law enforcement’ allows biometric identification, as well as all other forms of biometric recognition not aimed at identification of an individual, including all mentioned forms of ‘emotion recognition’ for all other purposes, by all other actors, in all public and private places, including at the workplace, shops, stadiums, theatres etc. This leaves the door wide open to a world where we are constantly being ‘emotionally assessed’ for whatever purpose the actor assessing us deems necessary. [...] AI used by law enforcement authorities and in migration, asylum and border control management for making individual (criminal or security) risk assessments poses a risk of harm to the presumption of innocence, the right of defence and the right to asylum of the EU Charter. AI systems in general merely seek correlations that are based on characteristics found in other ‘cases’. Suspicion in these instances is not based on actual suspicion of a crime or misdemeanour by the particular person, but merely on characteristics that that person happens to share with convicted criminals (such as address, income, nationality, debts, employment, behaviour, behaviour of friends and family members and so on). Unverified source (2021)