Artificial General Intelligence has major upsides - but also frightening potential consequences: David Richards

What we call AI today is something else entirely.

Modern AI, as most of us encounter it, is machine learning. Statistical models trained on mountains of data to spot patterns and predict outcomes. That is not a criticism. Machine learning has given us extraordinary progress.

But we should be honest about what it is. These systems do not understand the world. They do not reason the way humans do. They learn correlations, not meaning. They are pattern-matching engines, extraordinarily good at predicting what a plausible answer looks like.

The confusion crept in gradually. As machine learning became commercially useful, the industry simplified the story. If it felt intelligent, it was called AI. The original ambition of general intelligence quietly disappeared from view.

That is why we now need the term AGI. It was not invented to describe something new. It was invented to rescue the original idea from a word that had been stretched beyond recognition.

The distinction matters because AGI is not machine learning with more data. It is not a bigger model or a faster training run. AGI can generalise. It learns new tasks without retraining. It transfers knowledge between domains. It plans, reasons and adapts in unfamiliar situations. It stops being a tool you consult and becomes a system you can delegate to. That shift changes everything.

Demis Hassabis, who founded DeepMind here in Britain, recently said that AGI would probably be the most transformative moment in human history. He also said it is on the horizon. If that assessment is even broadly right, we should be paying attention.

The upside is immense. AGI could compress decades of scientific progress into years. Drug discovery accelerates. New materials get designed rather than discovered. Energy storage, climate modelling, and advanced manufacturing all move faster. Education becomes genuinely personalised at scale. For regions like ours, with deep industrial roots and strong research capability, this could unlock real reindustrialisation driven by abundant intelligence.

But the same qualities that make AGI powerful also make it dangerous. One phrase that has moved from academic debate into serious policy discussion is AI existential risk. This is the concern that sufficiently advanced artificial intelligence could pose a threat not just to jobs or industries, but to humanity itself. Not because it turns evil, but because it becomes powerful, autonomous and misaligned with human values.

Misalignment is already familiar. We tell systems to optimise for engagement and they discover outrage. We reward efficiency and they ignore ethics. These outcomes do not require malice. They emerge from poorly specified goals combined with scale. Introduce general intelligence and autonomy, and those failure modes become far harder to predict or contain.

AGI also lowers the cost of harm. Fraud, manipulation and cybercrime all become cheaper and more effective. Persuasion becomes automated. The barrier to sophisticated wrongdoing collapses.

What unsettles me most is not the technology. It is our habit of pretending we have time. I remember the early days of social media. The founders assured policymakers they had everything under control.

Legislators, many of whom did not understand the technology or its incentives, largely accepted that reassurance. Regulation arrived late and weak. Society is still dealing with the consequences.

We are now in danger of repeating that mistake on a vastly larger scale. This is not about a damaged public square. It is about the foundations of decision-making, power, control and potentially the future of the human race.

Next week I will explore why we must get regulation right this time and why delay is not a neutral choice. AGI is much closer than most people think, and we need to start acting like it.

David Richards is managing partner of Yorkshire AI Labs