at Queens’ College SCR Talk on Mar 1, 2021 [reveal]
Neil D. Lawrence, Computer Lab, University of Cambridge

#### Abstract

In this talk I will introduce the importance of uncertainty in decision making and describe how it provides a mathematical justification for procrastination through the game of Kappenball.

## Laplace’s Demon

Philosophical Essay on Probabilities Laplace (1814) pg 3

$\text{data} + \text{model} \stackrel{\text{compute}}{\rightarrow} \text{prediction}$

If we do discover a theory of everything … it would be the ultimate triumph of human reason-for then we would truly know the mind of God

Stephen Hawking in A Brief History of Time 1988

## Life Rules

Conway’s game of life has three simple rules.

• Survival Every cell surrounded by two or three other cells survives for the next turn.
• Death Each cell surrounded by four or more cells dies from overpopulation. Likewise, every cell next to one or no cells at all dies from isolation.
• Birth Each square adjacent to exactly three cells gives birth to a new cell.

## Laplace’s Gremlin

Philosophical Essay on Probabilities Laplace (1814) pg 5

## Information and Embodiment

### 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.

Stories, between humans.

I have a great dislike for Russell; I cannot explain it completely, but I feel a detestation for the man. As far as any sympathy with me, or with anyone else, I believe, he is an iceberg. His mind impresses one as a keen, cold, narrow logical machine, that cuts the universe into neat little packets, that measure, as it were, just three inches each way. His type of mathematical analysis he applies as a sort of Procrustean bed to the facts, and those that contain more than his system provides for, he lops short, and those that contain less, he draws out.

Norbert Wiener in a letter to his family, 1913

### 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.

See also a recent review paper on Human Cooperation by Henrich and Muthukrishna (2021).

## 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.

## Richard Feynmann on Doubt

One thing is I can live with is doubt, and uncertainty and not knowing. I think it’s much more interesting to live with not knowing than to have an answer that might be wrong.

Richard P. Feynmann in the The Pleasure of Finding Things Out 1981.

## Thanks!

For more information on these subjects and more you might want to check the following resources.

# References

Heider, F., Simmel, M., 1944. An experimental study of apparent behavior. The American Journal of Psychology 57, 243–259.
Henrich, J., Muthukrishna, M., 2021. The origins and psychology of human cooperation. Annual Review of Psychology 72, 207–240. https://doi.org/10.1146/annurev-psych-081920-042106
Laplace, P.S., 1814. Essai philosophique sur les probabilités, 2nd ed. Courcier, Paris.