Article by Viktor Mayer-Schönberger: “Much is being said about AI governance these days – by experts and pundits, lobbyists, journalists and policymakers. Convictions run high. Fundamental values are said to be at stake. Increasingly, AI governance statutes are passed. But what do we really mean – or ought to mean – when we speak about AI governance? In the West, at least three distinct categories of meaning can be identified.
The first is by far the most popular and it comes in many different variations and flavours. It’s what has been driving recent legislation, such as the European Union AI Act. And perhaps surprisingly, it has quite little to do with artificial intelligence. Its proponents scrutinise output of AI processing, and find the output wanting, for a variety of reasons. …But expecting near perfection from machines while accepting much less from humans does not lead to better outcomes overall. Rather, it keeps us stuck with more flawed, albeit human outputs… Moreover, terms such as ‘fair’ and ‘responsible’, frequently used in such AI governance debates, offer the advantage of vast interpretative flexibility, facilitating their use by many groups in support of their very diverse agendas. These different AI governance voices mean very different things, when they use the same words – and from their vantage point that’s more often a feature than a bug, because it gives them and their cause anchorage in the public debates.
The second flavour of AI governance offers a very different take. By focusing on the current economic landscape of digital and online services, its proponents suggest that AI governance is less novel and rather a continuation of digital and internet governance debates that have been raging for decades (Mueller Citation2025). They argue that most building blocks of AI have been around for some time – data, processing power and self-learning algorithms – and been utilised quite unevenly in the digital economy, often to the effect that large economic players got larger. ..
The third flavour of AI governance shifts the focus away from how technology affects fairness or markets, yet again. Instead, the attention is on decision-making. If AI is much about helping humans make better decisions, either by guiding them to the supposedly best choice or by choosing for them, AI governance isn’t so much about technology than about how and to what extent individual decision-making processes are shaped by outside influence. It situates the governance question apart from the specifics of a particular technology and asks: How are others, especially society, shaping and altering individual decision-making processes?…(More)”.
