Regulating Algorithmic Assemblages: Looking Beyond Corporatist AI Ethics

The perceived potential of artificial intelligence (AI) systems, broadly characterised, has seen a massive surge of investment in research and development, and their penetration into many decision-making processes of commercial, political and public organisations. Here, AI systems ubiquitously work behind the scenes to infuse decision-making processes with intelligence extracted from big data. This intelligence is used to develop highly personalised predictions or targeted services. While the personalisation phenomenon can provide notable efficiencies and economic gains in delivering services, or allocating scarce state resources, it is also often accompanied by unintended negative effects. Media and academic accounts have focussed on the potential negative impacts on individuals or categories of individuals, but there has been much less consideration of broader consequences or ripple effects of incorporating AI into existing social systems.

This chapter explores these consequences and ripple effects through an ‘AI ethics’ perspective, the dominant overarching discourse concerned with ‘regulating’ AI for the good of society. Yet ‘AI ethics’ is far removed from ‘AI law’ and is often presented as self-policing by private corporate actors in their use of AI systems, as sanctioned by government. The discussion critiques that self-policing, first, by locating AI ethics within long-standing traditions of corporate social responsibility and institutional ethical frameworks with all their in-built shortcomings, that frequently translate into a systemic inability to be truly Other-regarding. Second, this chapter shows, referencing the recent EU AI ethics initiative, that even well-intentioned initiatives may shoot past their target by simply assuming the desirability of AI applications, regardless of their wider impacts. Such an approach restricts itself to tinkering with system details whose consequences are relatively minor in comparison to the much broader impacts of AI within social systems, as captured by the idea of ‘algorithmic assemblage’.