Valuable actions and actionable values: Tinkering with principles and practices in AI ethics

What does it mean to ‘put principles into practice’? As machine learning algorithms and Artificial Intelligence are given increasing control over our lives (delivering credit scores and welfare risk assessments and monitoring borders with facial recognition), public, private and civil society organisations have proliferated numerous guidelines foregrounding different ethical principles (e.g. – fairness, accountability, transparency) meant to ensure that these systems do not cause harm to already marginalised groups. Putting these principles ‘into practice’, however, is not as straightforward as it seems. The Algorithm and AI Register, which collects information about algorithms used by city governments (namely Helsinki and Amsterdam), is one recent attempt to make good on these ethical principles, but it has been subsequently criticised for not living up to its own lofty ideals. This article is based on long-term ethnographic fieldwork with one of the companies behind the Register. Building on recent work from valuation studies, which studies empirically how abstract values are enacted through mundane routines and procedures, we argue that rather than moving from principles to practices, downstream as it were, the process is more iterative and it is not just practices but also principles which are shaped in the proceedings. We introduce two concepts, valuable action and actionable values, to sensitise researchers to the deeper interrelation of values and actions and argue that in order to make more ‘ethical’ algorithms we need to think more symmetrically about principles and practices.