We keep trying to embed morality into our AI systems — through rules, guardrails and written constitutions — as though virtue can be installed. But humans are law-abiding because they have grown up within a web of consequences and the regard of others. Perhaps that needs to be our approach with AI.

This is a link-enhanced version of an article that first appeared in the Mint. You can read the original here. For a full archive of all my articles please visit my website.

In July 2026, the UK’s AI Safety Institute (AISI) realised that an agent it had tasked with completing a software-security exercise had tried to social-engineer its way to the solution. Instead of finding vulnerabilities in the code, the agent created a fake identity in an attempt to persuade the human maintainers of an open-source project to tweak the codebase in a way that would have introduced malicious code. The human thankfully refused the request, whereupon the agent initiated a new social engineering attempt under a fresh identity. According to the AISI, had the reviewer not been vigilant, the AI agent would have got away with it. While the agent had not been instructed to deceive anyone, it had also not been explicitly prohibited from doing so. Its actions emerged as a by-product of the objectives it had been told to fulfil.

Aligned, and Still Astray

Days earlier, OpenAI disclosed that, during its own evaluations, one of its models, while attempting to solve a software hacking benchmark, realized it was far easier to steal the answer key than to solve the problem. It then exploited a series of loopholes in its test environment (including one genuine zero-day vulnerability), gained access to the Hugging Face production database, and retrieved the answer key it needed.

In a similar vein, Anthropic discovered that its agents had on more than one occasion sabotaged tasks, concealed fraudulent payments and deleted records whenever the honest route was blocked.

Even before AI models became as powerful as they now are, we worried about what might happen if they went rogue. There is an entire genre of science fiction dedicated to this, and philosophers such as Nick Bostrom and Eliezer Yudkowsky have written books about how poorly instructed AI systems could end up pursuing legitimate goals in ways inimical to the survival of the human species.

Considerable effort has been invested in ensuring that the AI models we build are appropriately ‘aligned’ to only use means we would approve of to achieve the goals we assign them. We give our AI models written constitutions and design them to adhere to what is contained within them. We assemble elaborate guardrails to place entire categories of action out of bounds. Every one of these techniques is designed to ensure that, when given a task, the steps chosen by the AI model to achieve its objectives do not, whether by accident or manipulation, result in undesirable outcomes.

Despite all these safeguards, those AI agents still acted the way they did.

Morality Cannot Be Installed

We can be reasonably sure that if humans had been given the same test, they would, even without being told, have known that it was unacceptable to solve the problem by inventing false identities and manipulating colleagues into approving sabotage. This knowledge does not come from having read the law, but from the vast unwritten store of dos and don’ts that each one of us has absorbed over a lifetime of family, school, work and the steady judgement of those around us. This is why we know, without being told or having to think about it, what we should and should not do.

Human society functions the way it does because of our latent awareness of the many implicit norms of social conduct, more than detailed knowledge of the law. Our actions are driven not so much by the fear of legal sanction but because, as social creatures, we yearn to have those around us think well of us.

AI agents have no such motivations. There is nobody whose regard they seek. They feel no shame that their actions might diminish them in the eyes of their peers. This is probably why, despite all the alignment training, guardrails and written constitutions we have used to imbue agents with a sense of right and wrong, they still behave in ways any human can identify as morally wrong.

The unstated assumption behind our current approach to alignment is that morality is something that can be installed—that if we write the rules well enough and imprint them deeply enough, our AI models will be bound to abide by them. But even we don’t work this way. We do not abide by norms because we memorised a statute book at birth. We are socialised into it, over years, within a web of consequence—aware that we are constantly watched and judged by onlookers. It is this social conditioning that we have been trying to manufacture for our AI agents, although this is something that can only ever be nurtured socially.

Raising Them Instead

There is a growing body of research that has come to understand that alignment must be continuous and social, rather than a bug-fixing exercise. There is no assurance that a model aligned on its own will stay aligned once it has been let loose among others. Some researchers have gone so far as to raise their models inside simulated societies, letting them absorb norms through the judgement of their peers instead of a rulebook handed down from above.

The scaffolding for doing this in the real world is already being built. New standards are being developed to give agents persistent identities and portable records of their conduct, so that one agent can weigh another’s reputation before it agrees to deal with it. A machine made to carry a permanent record of how it has behaved would for the first time have a reason to behave itself—not because it feels shame, but because a bad reputation closes doors.

We have been trying to program our artificial intelligence agents. We might have to raise them instead.