Everyone agrees that artificial intelligence should be fair, transparent, and accountable. That sentence could have been written in 2018, and it would have been just as true then as it is now. The difference is that in 2018, arriving at consensus on those principles felt like the hard part. In 2026, we know better. The hard part was never agreeing on what AI ethics should look like. The hard part is making anyone actually do it.
A growing body of research confirms what practitioners and regulators have been circling for years: the global AI ethics landscape has converged around a remarkably stable set of principles. Transparency. Fairness. Non-maleficence. Accountability. Privacy. These five values appear in the vast majority of the more than 200 ethics guidelines and governance documents that researchers have catalogued worldwide. A landmark review by Anna Jobin, Marcello Ienca, and Effy Vayena, published through ETH Zurich and later expanded through broader global analysis, found that transparency appeared in 86 per cent of guidelines examined, justice and fairness in 81 per cent, and non-maleficence in 71 per cent. The world, it turns out, has been surprisingly good at articulating what responsible AI ought to involve. The world has been catastrophically bad at enforcing it.
