Communication and Remote Working
The Diving Bell and the Butterfly [edit]
Figure: The Diving Bell and the Buttefly is the autobiography of Jean Dominique Bauby.
The Diving Bell and the Butterfly is the autobiography of Jean Dominique Bauby. Jean Dominique was the editor of the French Elle magazine, in 1995 at the age of 43, he suffered a major stroke. The stroke paralyzed him and rendered him speechless. He was only able to blink his left eyelid, he became a sufferer of locked in syndrome.
Figure: Jean Dominique Bauby was the Editor in Chief of the French Elle Magazine, he suffered a stroke that destroyed his brainstem, leaving him only capable of moving one eye. Jean Dominique became a victim of locked in syndrome.
Incredibly, Jean Dominique wrote his book after he became locked in. It took him 10 months of four hours a day to write the book. Each word took two minutes to write.
The idea behind embodiment factors 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 [edit]
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| bits/min | billions | 2000 | 6 |
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billion calculations/s |
~100 | a billion | a billion |
| embodiment | 20 minutes | 5 billion years | 15 trillion years |
Figure: Embodiment factors are the ratio between our ability to compute and our ability to communicate. Jean Dominique Bauby suffered from locked-in syndrome. The embodiment factors show that relative to the machine we are also locked in. In the table we represent embodiment as the length of time it would take to communicate one second’s worth of computation. For computers it is a matter of minutes, but for a human, whether locked in or not, it is a matter of many millions of 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.
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.
Figure: Marcel Renault races a Renault 40 cv during the Paris-Madrid race, an early Grand Prix, in 1903. Marcel died later in the race after missing a warning flag for a sharp corner at Couhé Vérac, likely due to dust reducing visibility.
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.
Figure: Caleb McDuff driving for WIX Silence Racing.
Human Communication [edit]
For human conversation to work, we require an internal model of who we are speaking to. We model each other, and combine our sense of who they are, who they think we are, and what has been said. This is our approach to dealing with the limited bandwidth connection we have. Empathy and understanding of intent. Mental dispositional concepts are used to augment our limited communication bandwidth.
Fritz Heider referred to the important point of a conversation as being that they are happenings that are “psychologically represented in each of the participants” (his emphasis) (Heider 1958)
Bandwidth Constrained Conversations
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Figure: Conversation relies on internal models of other individuals.
Figure: Misunderstanding of context and who we are talking to leads to arguments.
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.
A Six Word Novel [edit]
Figure: Consider the six word novel, apocraphally credited to Ernest Hemingway, “For sale: baby shoes, never worn”. To understand what that means to a human, you need a great deal of additional context. Context that is not directly accessible to a machine that has not got both the evolved and contextual understanding of our own condition to realize both the implication of the advert and what that implication means emotionally to the previous owner.
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.
Heider and Simmel (1944) [edit]
Figure: Fritz Heider and Marianne Simmel’s video of shapes from Heider and Simmel (1944).
Fritz Heider and Marianne Simmel’s experiments with animated shapes from 1944 (Heider and Simmel 1944). Our interpretation of these objects as showing motives and even emotion is a combination of our desire for narrative, a need for understanding of each other, and our ability to empathise. At one level, these are crudely drawn objects, but in another key way, the animator has communicated a story through simple facets such as their relative motions, their sizes and their actions. We apply our psychological representations to these faceless shapes in an effort to interpret their actions.
Computer Conversations [edit]
pods.notebook.display_plots('anne-bob-conversation{sample:0>3}.svg',
'../slides/diagrams', sample=IntSlider(0, 0, 7, 1))
Figure: Conversation relies on internal models of other individuals.
Figure: Misunderstanding of context and who we are talking to leads to arguments.
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.
Figure: Kevin O’Regan’s book, “Why Red Doesn’t Sound Like a Bell” is about the sensiorimotor perspective on feel and ranges from our senses to our consciousness.
The book, “Why Red Doesn’t Sound Like a Bell” by J. Kevin O’Regan (O’Regan 2011) suggests a sensorimotor approach to understanding our consciousness. One that depends on how our senses interact with the world around us. The implication is that our consciousness is as much a function of our environment as of our mind. This is particularly interesting for social interaction, where our external environment is populated by other intelligent entities. If we accept this interpretation it would imply that we should pay a lot of attention to modes of human to human interaction when developing environments in which we can feel comfortable and able to perform.
Figure: The Mind is Flat Nick Chater relates the extent to which how we are is determined by the data we see.
(Chater 2019)
Cognitive Diversity [edit]
Figure: Rebel Ideas by Matthew Syed focusses on the importance of cognitive diversity in decision making. The need for diversity is a consequence of uncertainty.
(Syed 2019)
Conclusions
- Both Local and Remote Environments are Important
- Regular Social Alignment is Missing
- Trust is easily lost and difficult to regain.
- More Structured Meetings might be Necessary
- Mechanisms to Hear Everyone
- There will be background processes for remote people.
- Is this healthy or us and them?
Next Steps
- Agree challenges and meeting tenets across both sites.
- Ensure local teams buy in.
- Rigorously apply those tenets.
- Rigorously review those tenets.
References
Chater, Nick. 2019. The Mind Is Flat. Penguin.
Heider, Fritz. 1958. The Psychology of Interpersonal Relations. John Wiley.
Heider, F., and M. Simmel. 1944. “An Experimental Study of Apparent Behavior.” The American Journal of Psychology 57: 243–59.
Lawrence, Neil D. 2017. “Living Together: Mind and Machine Intelligence.” arXiv. https://arxiv.org/abs/1705.07996.
O’Regan, J. Kevin. 2011. Why Red Doesn’t Sound Like a Bell: Understanding the Feel of Consciousness. Oxford University Press.
Syed, Matthew. 2019. Rebel Ideas: The Power of Diverse Thinking. John Murray.