Is AI Really ‘Intelligent’?

Anyone who engages in serious dialogue with a Large Language Model (LLM) may get the impression they are interacting with an intelligence. But many experts in the field argue the impression is just that. In philosopher Daniel Dennett’s words, such systems display “competence without comprehension”.

The hype about Artificial General Intelligence (AGI) from big corporations and their celebrity spokespersons has prompted a backlash, in which scepticism turns to cynicism, often tinged with paranoia about how “stochastic parrots” may start to control our lives.

“Intelligence” itself has become an overheated topic, one that calls for less assertiveness, more cool thinking, and refreshed attempts at a starting point.

What Is Intelligence? by Google luminary Blaise Agüera y Arcus is the first book in a new series from MIT in collaboration with Antikythera, a think tank focused on “planetary-scale computation as a philosophical, technological, and geopolitical force”. A foreword from series editor Benjamin Bratton makes the bold claim that “computation is a technology to think with” and that the building blocks of our reality are themselves computational.

Research on intelligence has a chequered history, tainted by eugenics, statistical manipulation and a banal obsession with metrics. Agüera y Arcas counters this by opening up the topic as wide as it can go. A physics graduate with a background in computational neuroscience, he is something of a polymath. He draws explanatory frameworks from microbiology, philosophy, linguistics, cybernetics, neuroscience and industrial history.

His book presents almost as a sequence of foundation lectures in these areas. Its release has been accompanied by dozens of online talks and interviews, in which Agüera y Arcas presents the case that we are up for a seismic shift in how we think about intelligence – biological and artificial.

“Few mainstream authors claim that AI is ‘real’ intelligence,” he writes. “I do.”

Could the nerds be right?

The fundamental case against the “I” in AI is that intelligence is organic, derived from sensory interaction with a physical environment. Agüera y Arcas turns the tables with the premise that computation is the substrate for intelligence in all life forms.

The claim builds on an apparently crude proposition: prediction is the fundamental principle behind intelligence and “may be the whole story”.

What he means by prediction here is something much more radical than what we see with autocorrect. He explains it in biological terms as a process of pattern development. Single cells like bacteria predict sequences of events that may influence their capacity for survival. The synaptic learning rules in single neurons give rise to local sequence prediction.

Agüera y Arcas recounts how his journey into the enigmatic terrain of AI reached a turning point with his counterintuitive recognition that “the nerds were right”: in computation, bigger really was better and might actually be the key to moving from Artificial Narrow Intelligence (ANI) – the kind that can play chess – to Artificial General Intelligence (AGI), which can participate in a philosophical discussion.

Setting aside his contempt for the apparently simplistic dedication to scaling up, Agüera y Arcas returned to the biology lab for a reassessment of what was observable in living systems. If every form of life is an aggregation of cooperative parts, he reasoned, the evolution of cells into organs and organisms may be a matter of predictive modelling.

A central tenet of What is Intelligence? is that every form of life is an aggregation of cooperative parts. Links proliferate through patterns that enable increasingly complex functions. When Agüera y Arcas says the brain is computational, it’s not a metaphor: it is not that brains are like computers, they are computers.

Correlations between biological and mechanical forms of intelligence are his deep and abiding interest. What is Intelligence? follows What is Life?, a shorter book in which Agüera y Arcas lays the groundwork for this larger, more ambitious publication.

The two questions remain interwoven, if not fused, in his analysis, which draws on the foundational work of physicist Ewin Schrödinger, mathematicians Alan Turing, John von Neumann and Norbert Weiner, and microbiologist Lynn Margulis.

These are the originators of modern thinking about artificial intelligence, and the quest for origins runs through all Agüera y Arcas’ lines of enquiry.

It is worth noting that Antikythera, the publishing series launched with this book, is named after an ancient device found in a shipwreck off the coast of Greece, which has been called the original analog computer.

Computation was discovered as much as it was invented, Bratton says in his foreword. This might apply to the Antikythera. If it is indeed the first computer, it was literally discovered at the bottom of an ocean.

But it corroborates Bratton’s statement in another sense. As a device for tracking astronomical phenomena, the Antikythera testifies to computation as an aspect of how the universe works.

- Author: Jane Goodall, The Conversation