Technology and Ethics

The debate around the ethics of artificial intelligence has become a fixture of tech conferences and government white papers. We are told that we must embed values into algorithms, that we must avoid bias, and that we must ensure transparency. These are, on the surface, entirely reasonable demands. Yet one cannot help but wonder whether this very focus on ethics, however well-intentioned, may be serving as a convenient smokescreen. The concern is not that ethics is unimportant; it is that by channelling our anxieties into a manageable, abstract discourse, we may be sidestepping more uncomfortable questions. Who writes the ethical guidelines? Who decides what counts as a 'fair' algorithm? In practice, the loudest voices in the ethics debate are often those with the most to gain from the continued, unfettered deployment of AI systems — the tech giants themselves. By framing the issue as a technical problem to be solved through better code and ethics committees, they can position themselves as responsible actors while simultaneously deflecting calls for more radical interventions, such as structural break-ups or outright bans on certain applications. Furthermore, the language of ethics can be strategically vague. Terms like 'responsible AI' or 'human-centric design' are difficult to pin down, and almost impossible to enforce. When a company claims to follow 'ethical principles', it is often making a promise that is more marketing than substance — a phenomenon some critics have termed 'ethics washing'. None of this is to dismiss the value of ethical inquiry. But we should be wary of a discourse that allows the most powerful players to set the terms of the debate while their business models remain largely unchallenged. True accountability may require us to look beyond ethical codes and question the very concentration of data and power that underpins the AI industry.