Data, Deep Blue, and Emotional Intelligence

Consider for a moment the basic geometry that has been taught for centuries, based on the work of the Greek mathematician Euclid.

Squares, triangles, circles. The building blocks of how we see the world.

Now, imagine that instead of these fundamental shapes we had been taught the fractal geometry of Mandelbrot and the patterns arising from Chaos Theory.

Rather than circles, squares and triangles, our geometric reference points might have been the human nervous system, tree branches, the folding of DNA, complex weather systems, stock market activity, or earthquakes. 

 

If people had learned fractal geometry, rather than the ‘celestial perfection’ and model of order favoured by the church in interpreting Euclid, the way we see the world might be very different now.

Geometry is about patterns. The human brain is a pattern-seeking device.

Once recognised, patterns cannot go unnoticed. They change forever our sense of the world and how it unfolds in our minds.

We may also sometimes see patterns where no patterns exist. 

At its worst, this can lead to conspiracy theories and paranoia. Ron Howard’s 2002 movie, A Beautiful Mind, about the mathematician John Nash, superbly illustrates this. 

The truth is that what we see can change when we change the way we look. 

And this happens when we change our tools for looking, including for example the microscope, the telescope, or the X-ray.

These instruments allow us to see things that were previously invisible to the naked eye – such as tiny particles, distant stars, the insides of the body. 

But we could also extend this principle from the way we see the physical world to the way we think about it.

There exist certain moments when our collective human perception changes. 

It is largely accepted that our intellectual development is neither smooth nor linear. It extends in leaps. Thomas Kuhn called these leaps in understanding paradigm shifts. 

For example, a major paradigm shift occurred when it was realised or discovered that the earth was round and not flat, so shifting the pattern of the world in our head. 

Similar revolutions in our thinking have happened with Freud’s theories of psychology, Darwin’s theory of evolution, and Einstein’s theory of relativity.

One of the biggest changes in recent years has not involved any conceptual theory or discovery as such, but has been facilitated by computer technology. It is the revolution in thinking brought about by the use of data.

Data is now used strategically in sport – see the 2011 film, Moneyball, starring Brad Pitt, which reveals how modern professional teams and the way they play are strongly shaped by statistical analysis.

Businesses have long relied on financial data to succeed. And in education, judgements about students are increasingly informed by regular metrics and data sets and not just subjective teacher intuition.

At the same time, we are human beings, not robots, and we tend to ignore the data we don’t like.

The gambling industry is so profitable largely because of the mismatch between what we want to believe, and the unvarying laws of chance (the House always wins!).

The philosopher Søren Kierkegaard made fun of the way most of us concern ourselves with small things rather than honestly confronting the big things - health, happiness, the future of the planet. 

For decades as a species, we have ignored the data on climate change because it is not what we want to hear or believe.

The same data sets were available to all governments when modelling and responding to the Covid-19 pandemic, and yet the authorities in different countries have often done quite different things – fuelling the conclusion that the data was coloured by ideology and politics, depending on where you lived.

We still like to think that at least creatively we are ahead of data-led computers. How can a computer be better than us when thinking imaginatively or playing a game? 

And yet.

Grand Master Garry Kasparov famously lost at chess to IBM’s Deep Blue computer in 1997. Kasparov had agreed to play in his own words as a ‘defence of the whole human race’. He failed. 

In 2016, Google’s AlphaGo program defeated the top Go master, Lee Sedol, in a match watched by 80 million people.

All poker professionals now use Artificial Intelligence (AI) to train and to create ‘game theory optimal’ (GTO) strategies. The old world of bluff and personal ‘tells’ has largely died. 

But, still, when I hear people argue that only the quantifiable matters, I feel uneasy. Data is an incredibly useful tool, but to rely on it wholly is surely reductive.

We do well to remember Charles Dickens’s cautionary 1854 novel, Hard Times, and the character of Thomas Gradgrind – the School Superintendent dedicated to the pursuit of cold facts and numbers.

Data might help to generate knowledge, but it does not necessarily yield wisdom. It is up to us as human beings to interpret the data. 

Modelling mathematically optimal decisions may give strong recommendations based on logic, but such recommendations may take no account of values or feelings. And we know that these things matter. 

A good education will ensure that students have a strong understanding of the importance of data. 

A great education will also ensure they learn to appreciate emotional intelligence, the two elements combining to make more fully-rounded judgements, and giving soft edges to those patterns in our head.

Chris Greenhalgh
Principal & CEO

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