AI is our ‘Promethean fire’: using it properly means knowing its true nature – and our own minds

Future historians might regard 2023 as a landmark in the arrival of artificial intelligence (AI). But whether that future will prove utopian, apocalyptic or somewhere in between is anyone’s guess.

In February, ChatGPT set the record because the fastest app to succeed in 100 million users. It was followed by similar “large language” AI models from Google, Amazon, Meta and other big tech firms, which collectively look poised to rework education, healthcare and lots of other knowledge-intensive fields.

However, AI’s potential for harm was underscored in May by an ominous statement signed by leading researchers:

Mitigating the chance of extinction from AI needs to be a world priority alongside other societal-scale risks similar to pandemics and nuclear war.

In November, responding to the growing concern about AI risk, 27 nations (including the UK, US, India, China and the European Union) pledged cooperation at an inaugural AI Safety Summit at Bletchley Park in England, to make sure the protected development of AI for the advantage of all.

To achieve this, researchers give attention to AI alignment – that’s, the best way to make sure that AI models are consistent with human values, preferences and goals. But there’s an issue – AI’s so-called “dark secret”: large-scale models are so complex they’re like a black box, inconceivable for anyone to completely understand.

AI’s black box problem

Although the transparency and explainability of AI systems are essential research goalssuch efforts seem unlikely to maintain up with the frenetic pace of innovation.

The black box metaphor explains why people’s beliefs about AI are everywhere in the map. Predictions range from utopia to extinction, and lots of even consider a man-made general intelligence (AGI) will soon achieve sentience.

But this uncertainty compounds the issue. AI alignment needs to be a two-way street: we must not only ensure AI models are consistent with human intentions, but additionally that our beliefs about AI are accurate.

This is because we’re remarkably adept at creating futures that accord with those beliefs, even when we’re unaware of them.

So-called “expectancy effects”, or self-fulfilling prophecies, are well-known in psychology. And research has shown that manipulating users’ beliefs influences not only how they interact with AIbut how AI adapts to the user.

In other words, how our beliefs (conscious or unconscious) affect AI can potentially increase the likelihood of any end result, including catastrophic ones.

AI, computation, logic and arithmetic

We have to probe more deeply to know the idea of AI – like Alice in Wonderland, head down the rabbit hole and see where it takes us.

Firstly, what’s AI? It runs on computers, and so is automated computation. From its origin because the “perceptron” – a man-made neuron defined mathematically in 1943 by neurophysiologist Warren McCulloch and logician Walter Pitts – AI has been intertwined with the cognitive sciences, neuroscience and computer science.

This convergence of minds, brains and machines has led to the widely-held belief that, because AI is computation by machine, then natural intelligence (the mind) have to be computation by the brain.

But what’s computation? In the late nineteenth century, mathematicians Richard Dedekind and Giuseppe Peano proposed a set of axioms which defined arithmetic by way of logicand inspired attempts to ground all mathematics on a secure formal basis.

Although the logician Kurt Gödel later proved this goal was unachievablehis work was the start line for mathematician (and code-breaker) Alan Turing. His “Turing machine”, an abstract device able to universal computationis the inspiration of computer science.

Deep structure of perception

So, computation is predicated on mathematical ideas that trace back to efforts to define arithmetic in logic. But our knowledge of arithmetic exists prior to logic. If we wish to know the idea of AI, we want to go further and ask where arithmetic itself comes from.

My colleagues and I even have recently shown that arithmetic is predicated on the “deep structure” of perception. This structure is like colored glasses that shape our perception particularly ways, in order that our experience of the world is ordered and manageable.

Arithmetic consists of a set of elements (numbers) and operations (addition, multiplication) that mix pairs of elements to present one other element. We asked: of all possibilities, why are numbers the weather, and addition and multiplication the operations?

We showed by mathematical proof that when the deep structure of perception was assumed to limit the probabilities, arithmetic was the result. In other words, when our mind views the abstract world through the identical “colored glasses” that shape our experience of the physical world, it “sees” numbers and arithmetic.

Because arithmetic is the inspiration for mathematics, the implication is that mathematics is a mirrored image of the mind – an expression in symbols of its fundamental nature and creativity.

Although the deep structure of perception is shared with other animals and so a product of evolution, only humans have invented mathematics. It is our most intimate creation – and by enabling the event of AI, perhaps our most consequential.

A Copernican revolution of the mind

Our account of arithmetic’s origin is consistent with views of the 18th century philosopher Immanuel Kant. According to him, our knowledge of the world is structured by “pure intuitions” of space and time that exist prior to sense experience – analogous to the colored glasses we are able to never remove.

Kant claimed his philosophy was a “Copernican revolution of the mind”. In the identical way ancient astronomers believed the Sun revolved across the Earth because they were unaware of the Earth’s motion, Kant argued, philosophers who believed all knowledge is derived from sense experience (John Locke and David Hume, for instance) ignored how the mind shapes perception.

Although Kant’s views were shaped by the natural sciences of his daythey’ve proved influential in contemporary psychology.

The recognition that arithmetic is a natural consequence of our perception, and thus biologically based, suggests an analogous Kantian shift in our understanding of computation.

Computation isn’t “outside” or separate from us in an abstract realm of mathematical truth, but inherent in our mind’s nature. The mind is greater than computation; the brain isn’t a pc. Rather, computation – the idea for AI – is, like mathematics, a symbolic expression of the mind’s nature and creativity.

Promethean fire

What are the implications for AI? Firstly, AI isn’t a mind and won’t ever grow to be sentient. The idea we are able to transcend our biological nature and achieve immortality by uploading our minds to the cloud is just fantasy.

Yet if the principles of mind on which AI is predicated are shared by all humanity (and certain other living creatures as well), it could be possible to transcend the restrictions of our individual minds.

Because computation is universal, we’re free to simulate and create any end result we elect in our increasingly connected virtual and physical worlds. In this fashion, AI is actually our Promethean firea present to humanity stolen from the gods as in Greek mythology.

As a world civilisation, we’re likely at a turning point. AI won’t grow to be sentient and choose to kill us all. But we’re very able to “apocalypsing” ourselves with it – expectation can create reality.

Efforts to make sure AI alignment, safety and security are vitally essential, but might not be enough if we lack awareness and collective wisdom. Like Alice, we want to get up from the dream and recognise the fact and power of our minds.