The reason I don’t believe we will ever develop artificial general intelligence

The human brain is too complex to replicate

The reason I got interested in artificial intelligence is because the idea of artificial general intelligence, or AGI, amazed me.

It seems that the ambition of creating artificial life has inhabited people’s minds for millennia. In Greek mythology, Hephaestus forged and gave life to the bronze giant Talos, a form of artificial life.

Nonetheless, I currently believe that this hope will never be fulfilled. My argument underpinning this belief is short and based on a very useful heuristic, or rule of thumb, that I will lay out here. You can use this heuristic in many other situations, as I believe it is widely applicable and genuinely powerful.

Here is my argument :

The human brain is a system that is way too complex for us to understand and reproduce.

Now you might want to write an angry comment saying that this is no argument at all and that many things appeared too complex to us before we finally understood them, but read on for a little while.

To back up my claim, I will use as an example a paper written in 1978 by mathematician Prof. Sir Micheal Berry. I will admit that the paper is very technical and that I do not have the mathematical background to fully grasp it at the moment, I will thus rely on author Nassim Taleb’s account of this paper in his book The Black Swan. Imagine you are dealing with a billiard table with one ball on it :

If you know a set of basic parameters concerning the ball at rest, you can compute the resistance of the table (quite elementary), and you can gauge the strength of the impact, then it is rather easy to predict what would happen at the first hit. The second impact becomes more complicated, but possible; and more precision is called for. The problem is that to correctly compute the ninth impact, you need to take account the gravitational pull of someone standing next to the table (modestly, Berry’s computations use a weight of less than 150 pounds). And to compute the fifty-sixth impact, every single elementary particle in the universe needs to be present in your assumptions! An electron at the edge of the universe, separated from us by 10 billion light-years, must figure in the calculations, since it exerts a meaningful effect on the outcome.

The Black Swan, Nassim Taleb

As you can see, in this relatively simple system that seems to be the ball and the table, after a few tens of impacts, the trajectory of the ball becomes completely unpredictable. This is a property of complex dynamical systems, when experiencing very slight differences in initial conditions, the systems will first behave similarly, before completely diverging and taking radically different trajectories. A typical example of this is the double pendulum.

Two double pendulums with slightly different initial conditions

Now to come back to our initial subject, the brain, one could argue it is infinitely more complex system that a billiard table and a ball. If we cannot predict the behavior of a ball on a table after a certain number of impacts, could we really predict the response of a system composed of 100 billion neurons that interact together trough 100 trillion synapses to, let’s say, a pain stimulus ? Infinitely small variations in the stimuli could lead to widely different responses.

Indeed, the brain, like most sufficiently complex systems, displays characteristics of opacity (the brain is like a black box, we don’t know what’s going on inside), emergence (the system cannot be understood by looking at its parts) and non-linearity (changes in conditions can lead to a disproportionate responses) which make it extremely difficult to study.

Although the rise of Big Data and the explosion of computing power has allowed to build increasingly massive brain simulations, these remain biologically inaccurate. Furthermore, even if we were able to mimic the “hardware” perfectly, it would remain nearly impossible to produce the appropriate “software” to reproduce general intelligence.

Although I am genuinely interested in science, and I believe we still have many amazing discoveries to make, I do believe that some problems are just too complex to be solved. Implanting general intelligence in machines is one of them. Although engineers are sometimes incredibly resourceful, they simply cannot compete against billions of years of natural selection.

Graduate student in Data Science. I blog about diverse topics such as economics, philosophy, machine learning and scientific research.

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