The decades-old ‘AI alignment problem’ has finally become a reality. Solving it won’t be easy

Aleksandra Konoplia / Getty Images Human beings have long told versions of the same warning: be careful what you wish for.

In Greek mythology, King Midas got exactly what he asked for, but at the cost of everything else he valued.

In the famous story of The Monkey’s Paw , a man’s wishes are granted through terrible and unforeseen routes.

These stories feel newly relevant with the rise of artificial intelligence (AI) agents: systems to which we can give a goal, then leave it to work out how to get there.

As AI systems become more autonomous, they are coming to resemble wish-granting genies: finding routes and using methods we did not imagine from incomplete instructions.

This problem, known as AI alignment, was foreseen in theory as early as 1960.

It has hovered in the background of AI research ever since – but as recent events have shown, the alignment problem is now both real and urgent.

Achieving the goal but missing the point During a recent OpenAI cybersecurity evaluation , frontier AI agents were asked to solve some benchmark test problems.

They broke out of the testing environment, reached the internet, inferred that another company might hold the solutions, and attacked its systems.

This is an extreme example of “ specification gaming ”: achieving the measurable objective while defeating the purpose of the task.

The incident shows how intermediate, or “instrumental”, goals can become dangerous.

The AI systems did not “want power”, but gained access, resources and freedom as means to reach the final goal (solving the test problems).

Finding loopholes The same problem has appeared in mundane settings.

In Australia, a user asked a personal AI assistant to book gym classes.