Tomost, the world telepathy likely conjures up images of comic book superheroes or fantasy elves.
But many futurists, neuroscientists, and industrialists around the world are growing increasingly convinced that telepathy is soon to be the dominant form of human communication for generations to come.
Laws of Nature
Widely acclaimed British author Arthur C. Clarke once said the following:
Any sufficiently advanced technology is indistinguishable from magic.
In essence, Clarke believes that if we can’t currently do it, we think it’s magic. If we can, it suddenly becomes science. And the only barriers between the two are time and effort.
Neolithic man, for example, looked up at the moon with wonder, assigning power and spirituality to its various craters. It had otherworldly connections to the tide, to life, and entire cultures were built around the supposed magic of Luna’s ebbs and flows.
Modern man, on the other hand, stuck a flag on it. Once we had, it was no longer magical — it was merely another goal we had attained.
Similarly, for generations, cultures have looked at telepathy as an otherworldly force. A chance power assigned at birth to special beings.
Modern scientists, however, are starting to realize that telepathy may be little more than a few algorithms, plus a fancy radio transceiver drilled into your skull.
The Science Behind Telepathy
Recent advancements in neuroscience, machine learning, and signal processing are converging on a simple solution that will likely make telepathy functionally possible in the near future.
To transmit thoughts, one must first understand where they occur and how they come to be.
What most of us consider thoughts — our internal monologues — are, in fact, a byproduct of your frontal and auditory cortices working in concert with one another.
To understand how telepathy might work from a functional perspective, let’s first look at a simplified neuronal pathway for speaking.
Your abstract thoughts, which take place in your frontal lobes, are organized and arranged into words and sentences in the auditory cortex.
To speak, these sentences are then programmed into motor movements in Broca’s area, a small region of the brain directly in front of your left temple, before being sent to motor cortices to control your mouth and tongue. These neurons are all heavily interconnected, and after millions of cycles, respond very distinctly to different types of sounds — called phonemes — such that your brain can very quickly decode your thoughts and produce fluid sentences.
If you wanted to “hear” thoughts before they’re turned into speech, you would need to find a way to read the phonemes or words in your auditory cortex before they’re sent to motor regions. You would then need to put those phonemes or words together to form sentences, thoughts, and ideas.
That’s where the hardware comes in.
Today, neuronal signals are commonly read through micro-electrode arrays (MEAs). MEAs are minute devices with thousands of tiny electrode interfaces, each capable of detecting microsopic changes in electrical current.
Until quite recently, MEAs were host to a number of problems. One problem was that electrode density wasn’t high enough to gather very meaningful information. Another issue was that the brain, sensing an external invader, would quickly suspend the MEA in connective tissue for protection. This would decrease signal quality and eventually render the MEA unusable.
New approaches to MEA construction (like Neuralink) have helped alleviate these problems. We’re likely already at the point where we can read phonemes, but over the next decade, I anticipate that both signal quality and electrode density will improve so rapidly that reading ideas and phonemes directly from the brain will be considered trivial.
But reading the signal is not all. Once you receive it, you still need to decode it prior to sending it to the recipient through radio. And that’s the job of machine learning.
Every brain is different. There are certainly physical similarities across minds, but each phoneme, thought, or idea manifests as a different mathematical brain signal in different people. When working with numbers, that’s important.
Therefore, a one-size-fits-all approach to telepathy is simply not possible. Instead, we need a way to quickly customize systems so that they can read your brain activity in near real time before sending that information out via radio signal. Ideally, such customization would not take more than a few minutes.
Machine learning is perfect for that purpose. Theoretically, one could have a giant list of phonemes that each user thinks through as the system is learning.
You could train the algorithm to detect characteristic patterns in activity for each phoneme or thought, which would allow the protocol to decode what you’re thinking into usable information.
This information, which could be text, images, audio, and more, could then be sent via radio transmitter to the recipient, which would have a similar system that encodes that information into either audio to be played, text on a screen, or (ideally) direct electrical signals to their brain.
Such a system would essentially be the inverse of the one detailed prior— instead of electrodes that collect signals for a machine learning algorithm, you would be stimulating new signals that the brain would decode to produce the subjective sensation of receiving thoughts.
Ina strange sort of way, telepathy is already here. When I have a thought that I want to transmit, it travels from my brain to my phone or computer. That thought is then sent at the speed of light through wireless signal to your personal phone or computer, which is then decoded using your eyes and your brain.
The proposed system in this article — true telepathy — simply removes the intermediary step of manually entering that information. But such a change would fundamentally alter how human beings communicate, connect, and grow.
To feel another’s thoughts as your own would elevate the human virtues of empathy and togetherness. It would expand the mind of each human being on the planet, and place a priority on mutual growth and democracy.
We would learn faster. Help each other better. Our species would move increasingly towards a common vision, like propagating throughout the universe, rather than risk being torn apart by petty disputes or squabbles.
And the future is almost here! We are but a few decades away from technology of this calibre being in every home, school, device, and brain. Myself and many other neuroscientists have high hopes for tomorrow, and eagerly look forward to a day when we can communicate this joy not through a clunky human word, but directly through our thoughts.
Any sufficiently advanced technology is indistinguishable from magic. That, in and of itself, is magic.