In just over 30 years, humans will be able to upload their entire minds to computers and become digitally immortal. – Ray Kurzweil, Global Futures 2045 International Congress, 2013. Without even considering the ethical, philosophical, social or legal scope of such a statement, it’s important to consider if it actually makes any sense. To try to give an educated guess, we have to move away from computer science and look at what biology and neuroscience can teach us.
The sensible world
In his book Being There: Putting Brain, Body and World Together Again, Andy Clark explains that:
The biological mind is, first and foremost, an organ for controlling the biological body. Minds make motions, and they must make them fast – before the predator catches you, or before your prey gets away from you. Minds are not disembodied logical reasoning devices.
To better understand this assertion, it’s essential to know that our bodies are literally covered with sensors – chemical, mechanical, visual, thermal, proprioceptive (perception of the body), noniceptive (perception of pain). All of them inform the brain about the outside world (exteroception) and the inner world (interoception), allowing it to regulate the body. The majority of our brain is actually dedicated to the processing of sensory information, and the largest part of that is devoted to visual information, occupying the entire occipital lobe and large parts of the temporal and parietal lobes. We are mostly visual beings who, incidentally, think.
If someone wants to “upload his entire mind to a computer,” the problem of sensors must be solved. A quick and dirty solution could be to not worry about them and just pretend that all sensory neurons would remain silent forever. However, 50 years ago, Donald O. Hebb conducted a series of experiments to study the effects of sensory deprivation. He generously paid students to recline 24/7, taking care to deprive them of most of their senses using glasses, helmets, gloves and so on. The majority of the students abandoned the experiment after two or three days because they were no longer able to develop coherent thoughts and began to suffer from auditory and visual hallucinations. The experiences evoked considerable interest from the CIA (which financed the original study) and they later “improved” the process up to the point where it was transformed into an instrument of psychological torture.
The electric body
Consequently, if we want to “upload our brain” without going insane, it’s imperative for the uploaded brain to be connected to an artificial body that can perceive the outside world and act on it. But what kind of artificial body do we have today? Robotic bodies where retinas are replaced by cameras and muscles by motors? To some extent, yes, but this solution would be only a pale replica, far from the complexity and intelligence of the human body, as nicely explained by Rolf Pfeiffer and Josh Bongard’s book “How the Body Shapes the Way We Think”.
During childhood, a brain learns through experience to control its body and to leverage its specifics. For example, consider the fingertips, which are sufficiently soft and sensitive that we can easily grasp small objects. There’s no need for the brain to send a precise command – the intelligence is in the body itself. Imagine trying to do the same thing with thimbles over each finger, and you will understand how your body automatically solves a number of problems all by itself.
What about the artificial eyes we’d need? Even though high-resolution cameras now exist, the eyes we’re born with each have approximately five million cones and 100 millions rods, plus the various “preprocessing” stages, from the horizontal, bipolar, amacrine and ganglion cells. We are indeed very far from being able to reproduce a full artificial retina, even though some amazing research in Paris has succeeded in helping the vision-impaired see again.
As a first step, we could therefore use those simplified robotic bodies with their reduced sensory and motor skills. Would it affect our minds? Yes. Our cognition depends on the interactions we have with the world, and this interaction is conveyed by both our perceptions and our actions. If you change them, you also change the sensory experience of the world as well as its underlying logic.
Cognition is embodied.
But let’s assume that we’ve solved the problems of sensors and muscles and all the rest, and accept that the uploaded brain won’t truly reflect our mind. Now comes the big challenge: uploading the brain. But what is a brain exactly? This term usually refers to the cortex and possibly some subcortical structures, including the amygdala, hippocampus and basal ganglia. But the central nervous system is actually made of several other structures that are no less critical, including the cerebellum, thalamus, hypothalamus, medulla and brain stem.
Making the connections
If we consider the whole central nervous system, we are facing an average of 86 billion neurons, and each of these neurons contacts an average of 10,000 other neurons, representing a grand total of approximately 860 billion connections. This is really huge. So exactly what do we have to upload into the computer? The type, the size and the geometry of each neuron? Its current membrane potential? The size and position of the axon and its state of myelination? The complete geometry of the dendritic tree? The location of the various ion pumps? The number, the position and the state of the different neuro-mediators? Any of these could be critical, and they can only be taken into account in state-of-the-art computer models (and for a few neurons only). The problem is that we do not know exactly what it is that makes us who we are and different from anyone else (and I’m not even talking about learning).
As a fallback – and only if we had the proper tools to record each of these parameters once – we could try to transfer everything. However, this would require potentially some thousands or even millions of pieces of information for a single neuron. If you consider just the number of neurons, we would reach a figure in the zetta domain (for your information, the order is kilo, mega, giga, tera, peta, exa and zetta, multiplying by 1,000 at each step). This number is so huge that it cannot yet be manipulated as a whole by computer science. And we are talking only about the brain’s storage, because we also have to ensure that this model runs in real time, since nobody would happily accept a silicon mind that runs at reduced speed. From a purely technical perspective, we are thus very far (really very far) from making this to happen.
Worse, research indicates that Moore’s Law – which suggests that computer power doubles every 18 months – is reaching its limits, suggesting that we may never attain the necessary level of technology. The Human Brain Project foresaw this problem and planned from the beginning to use only simplified models of neurons and synapses. If you’re interested in more accurate models, take a look at the OpenWorm project, which doesn’t pretend to simulate any more than a few neurons.
The bird in the machine
This idea of transferring one’s brain into a machine is widespread in both literature and cinema. It has gained renewed interest with recent advances in artificial intelligence. However, there may be some confusion regarding what is actually artificial intelligence (AI) and what are its goals.
When media cover artificial intelligence, they generally refer to machine learning and robotics, neither of which really seeks to understand the brain or cognition (with some notable exceptions, such as the work of Pierre-Yves Oudeyer). This confusion likely stems from the fact that new algorithms have been designed that enable excellent performance on tasks that were previously thought to be reserved for humans – recognizing images, driving a car and so on.
But if machine learning and robotics are progressing at an amazing speed, this does not tell us anything about how the biological brain works (at least not directly). If we want to know, we have to look at neuroscience and more specifically at computational neuroscience. A parallel could be drawn between aeronautics (AI) and ornithology (neuroscience). Even though the early attempts at flying were directly inspired by the flight of birds, this was abandoned long ago in favor of the design of ever more efficient aircraft (speed, payload, etc) using techniques specific to aeronautics. To better understand birds, you must turn to ornithology and biology. Hence, talking about uploading a brain to a computer because of the progress of AI makes as much sense as gluing feathers on an airplane and pretending it’s an artificial bird.
No one knows if it will ever be possible to “upload a brain to a computer.” But what is certain today is that in the current state of science, this statement makes no sense and will remain so without a major epistemological breakthrough in our understanding of the brain and how it works.