The dark side of public values in algorithmic systems

Recent discussions around artificial intelligence and algorithmic systems increasingly speak of ‘public values’ being under threat. Big tech is thought to realise values like efficiency and accuracy at the expense of collectively held values like privacy, autonomy, solidarity and equality. However, there are dangers involved in invoking public values without specifying what they are and how they are to be realised. In this article, drawing on ethnographic studies of algorithmic systems (across five European countries and a variety of fields) we explain how various uses of values can lead to practical problems, even to the opposite of originally stated objectives. We offer a list of five problems which arise when values are ‘disconnected’ from local specificities, from the people who must realise them or from other values. Our list includes: value narrowing, value tickboxing, value pushing, value mismatch and value projection.