What is the nature of machine intelligence and how does it differ from humans? In this talk we explore embodiment factors, the extent to which our intelligence is locked in and how this makes us fundamentally different form the machine intelligences we are creating around us.
The Diving Bell and the Butterfly 
The Diving Bell and the Butterfly is the autobiography of Jean-Dominique Bauby.
In 1995, when he was editor-in-chief of the French Elle magazine, he suffered a stroke, which destroyed his brainstem. He became almost totally physically paralyzed, but was still mentally active. He acquired what is known as locked-in syndrome.
Incredibly, Bauby wrote his memoir after he became paralyzed.
His left eye was the only muscle he could voluntarily move, and he wrote the entire book by winking it.
O M D P C F B V
H G J Q Z Y X K W
How could he do that? Well, first, they set up a mechanism where he could scan across letters and blink at the letter he wanted to use. In this way, he was able to write each letter.
It took him 10 months of four hours a day to write the book. Each word took two minutes to write.
Imagine doing all that thinking, but so little speaking, having all those thoughts and so little ability to communicate.
The idea behind this talk is that we are all in that situation. While not as extreme as for Bauby, we all have somewhat of a locked in intelligence.
Embodiment Factors 
|~100||a billion||a billion|
|embodiment||20 minutes||5 billion years||15 trillion years|
Let me explain what I mean. Claude Shannon introduced a mathematical concept of information for the purposes of understanding telephone exchanges.
Information has many meanings, but mathematically, Shannon defined a bit of information to be the amount of information you get from tossing a coin.
If I toss a coin, and look at it, I know the answer. You don’t. But if I now tell you the answer I communicate to you 1 bit of information. Shannon defined this as the fundamental unit of information.
If I toss the coin twice, and tell you the result of both tosses, I give you two bits of information. Information is additive.
Shannon also estimated the average information associated with the English language. He estimated that the average information in any word is 12 bits, equivalent to twelve coin tosses.
So every two minutes Bauby was able to communicate 12 bits, or six bits per minute.
This is the information transfer rate he was limited to, the rate at which he could communicate.
Compare this to me, talking now. The average speaker for TEDX speaks around 160 words per minute. That’s 320 times faster than Bauby or around a 2000 bits per minute. 2000 coin tosses per minute.
But, just think how much thought Bauby was putting into every sentence. Imagine how carefully chosen each of his words was. Because he was communication constrained he could put more thought into each of his words. Into thinking about his audience.
So, his intelligence became locked in. He thinks as fast as any of us, but can communicate slower. Like the tree falling in the woods with no one there to hear it, his intelligence is embedded inside him.
Two thousand coin tosses per minute sounds pretty impressive, but this talk is not just about us, it’s about our computers, and the type of intelligence we are creating within them.
So how does two thousand compare to our digital companions? When computers talk to each other, they do so with billions of coin tosses per minute.
Let’s imagine for a moment, that instead of talking about communication of information, we are actually talking about money. Bauby would have 6 dollars. I would have 2000 dollars, and my computer has billions of dollars.
The internet has interconnected computers and equipped them with extremely high transfer rates.
However, by our very best estimates, computers actually think slower than us.
How can that be? You might ask, computers calculate much faster than me. That’s true, but underlying your conscious thoughts there are a lot of calculations going on.
Each thought involves many thousands, millions or billions of calculations. How many exactly, we don’t know yet, because we don’t know how the brain turns calculations into thoughts.
Our best estimates suggest that to simulate your brain a computer would have to be as large as the UK Met Office machine here in Exeter. That’s a 250 million pound machine, the fastest in the UK. It can do 16 billion billon calculations per second.
It simulates the weather across the word every day, that’s how much power we think we need to simulate our brains.
So, in terms of our computational power we are extraordinary, but in terms of our ability to explain ourselves, just like Bauby, we are locked in.
For a typical computer, to communicate everything it computes in one second, it would only take it a couple of minutes. For us to do the same would take 15 billion years.
If intelligence is fundamentally about processing and sharing of information. This gives us a fundamental constraint on human intelligence that dictates its nature.
I call this ratio between the time it takes to compute something, and the time it takes to say it, the embodiment factor (Lawrence 2017). Because it reflects how embodied our cognition is.
If it takes you two minutes to say the thing you have thought in a second, then you are a computer. If it takes you 15 billion years, then you are a human.
So when it comes to our ability to compute we are extraordinary, not compute in our conscious mind, but the underlying neuron firings that underpin both our consciousness, our subconsciousness as well as our motor control etc.
If we think of ourselves as vehicles, then we are massively overpowered. Our ability to generate derived information from raw fuel is extraordinary. Intellectually we have formula one engines.
But in terms of our ability to deploy that computation in actual use, to share the results of what we have inferred, we are very limited. So when you imagine the F1 car that represents a psyche, think of an F1 car with bicycle wheels.
Just think of the control a driver would have to have to deploy such power through such a narrow channel of traction. That is the beauty and the skill of the human mind.
In contrast, our computers are more like go-karts. Underpowered, but with well-matched tires. They can communicate far more fluidly. They are more efficient, but somehow less extraordinary, less beautiful.
Bandwidth Constrained Conversations 
Embodiment factors imply that, in our communication between humans, what is not said is, perhaps, more important than what is said. To communicate with each other we need to have a model of who each of us are.
To aid this, in society, we are required to perform roles. Whether as a parent, a teacher, an employee or a boss. Each of these roles requires that we conform to certain standards of behaviour to facilitate communication between ourselves.
Control of self is vitally important to these communications.
The high availability of data available to humans undermines human-to-human communication channels by providing new routes to undermining our control of self.
The consequences between this mismatch of power and delivery are to be seen all around us. Because, just as driving an F1 car with bicycle wheels would be a fine art, so is the process of communication between humans.
If I have a thought and I wish to communicate it, I first of all need to have a model of what you think. I should think before I speak. When I speak, you may react. You have a model of who I am and what I was trying to say, and why I chose to say what I said. Now we begin this dance, where we are each trying to better understand each other and what we are saying. When it works, it is beautiful, but when misdeployed, just like a badly driven F1 car, there is a horrible crash, an argument.
A Six Word Novel 
But this is a very different kind of intelligence than ours. A computer cannot understand the depth of the Ernest Hemingway’s apocryphal six word novel: “For Sale, Baby Shoes, Never worn”, because it isn’t equipped with that ability to model the complexity of humanity that underlies that statement.
Computer Conversations 
Similarly, we find it difficult to comprehend how computers are making decisions. Because they do so with more data than we can possibly imagine.
In many respects, this is not a problem, it’s a good thing. Computers and us are good at different things. But when we interact with a computer, when it acts in a different way to us, we need to remember why.
Just as the first step to getting along with other humans is understanding other humans, so it needs to be with getting along with our computers.
Embodiment factors explain why, at the same time, computers are so impressive in simulating our weather, but so poor at predicting our moods. Our complexity is greater than that of our weather, and each of us is tuned to read and respond to one another.
Their intelligence is different. It is based on very large quantities of data that we cannot absorb. Our computers don’t have a complex internal model of who we are. They don’t understand the human condition. They are not tuned to respond to us as we are to each other.
Embodiment factors encapsulate a profound thing about the nature of humans. Our locked in intelligence means that we are striving to communicate, so we put a lot of thought into what we’re communicating with. And if we’re communicating with something complex, we naturally anthropomorphize them.
We give our dogs, our cats and our cars human motivations. We do the same with our computers. We anthropomorphize them. We assume that they have the same objectives as us and the same constraints. They don’t.
This means, that when we worry about artificial intelligence, we worry about the wrong things. We fear computers that behave like more powerful versions of ourselves that will struggle to outcompete us.
In reality, the challenge is that our computers cannot be human enough. They cannot understand us with the depth we understand one another. They drop below our cognitive radar and operate outside our mental models.
The real danger is that computers don’t anthropomorphize. They’ll make decisions in isolation from us without our supervision, because they can’t communicate truly and deeply with us.
Some researchers talk about transhumanism, releasing us from our own limitations, gaining the bandwidth of the computer. Who wouldn’t want the equivalent of billions of dollars of communication that a computer has?
But what if that would destroy the very nature of what it is to be human. What if we are defined by our limitations. What if our consciousness is born out of a need to understand and be understood by others? What if that thing that we value the most is a side effect of our limitations?
AI is a technology, it is not a human being. It doesn’t worry it is being misunderstood, it doesn’t hate us, it doesn’t love us, it doesn’t even have an opinion about us.
Any sense that it does is in that little internal model we have as we anthropomorphize it. AI doesn’t stand for anthropomorphic intelligence, it stands for artificial intelligence. Artificial in the way a plastic plant is artificial.
Of course, like any technology, that doesn’t mean it’s without its dangers. Technological advance has always brought social challenges and likely always will, but if we are to face those challenges head on, we need to acknowledge the difference between our intelligence and that which we create in our computers.
Your cat understands you better than your computer does, your cat understands me better than your computer does, and it hasn’t even met me!
Our lives are defined by our desperate need to be understood: art, music, literature, dance, sport. So many creative ways to try and communicate who we are or what we feel. The computer has no need for this.
When you hear the term Artificial Intelligence, remember that’s precisely what it is. Artificial, like that plastic plant. A plastic plant is convenient, it doesn’t need watering, it doesn’t need to be put in the light, it won’t wilt if you don’t attend to it, and it won’t outgrow the place you put it.
A plastic plant will do some of the jobs that a real plant does, but it isn’t a proper replacement, and never will be. So, it is with our artificial intelligences.
I believe that our fascination with AI is actually a projected fascination with ourselves. A sort of technological narcissism. One of the reasons that the next generation of artificial intelligence solutions excites me is because I think it will lead to a much better understanding of our own intelligence.
But with our self-idolization comes a Icarian fear of what it might mean to emulate those characteristics that we perceive of as uniquely human.
Our fears of AI singularities and superintelligences come from a confused mixing of what we create and what we are.
Do not fool yourselves into thinking these computers are the same thing as us, they never will be. We are a consequence of our limitations, just as Bauby was defined by his. Or maybe limitations is the wrong word, as Bauby described there are always moments when we can explore our inner self and escape into our own imagination:
My cocoon becomes less oppressive, and my mind takes flight like a butterfly. There is so much to do. You can wander off in space or in time, set out for Tierra del Fuego or King Midas’s court. You can visit the woman you love, slide down beside her and stroke her still-sleeping face. You can build castles in Spain, steal the golden fleece, discover Atlantis, realize your childhood dreams and adult ambitions.
Enough rambling. My main task now is to compose the first of those bedridden travel notes so that I shall be ready when my publisher’s emissary arrives to take my dictation, letter by letter. In my head I churn over every sentence ten times, delete a word, add an adjective, and learn my text by heart, paragraph by paragraph.
The flower that is this book, that is this fight, can never bud from an artificial plant.
- twitter: @lawrennd
- blog: http://inverseprobability.com
- podcast: http://thetalkingmachines.com
- Natural vs Artifical Intelligence
Hilbert, Martin, and Priscila López. 2011. “The World’s Technological Capcity to Store, Communicate and Compute Information.” Science 332 (6025): 60–65. https://doi.org/10.1126/science.1200970.
Lawrence, Neil D. 2017. “Living Together: Mind and Machine Intelligence.” arXiv. https://arxiv.org/abs/1705.07996.