Upending Science
  • 10th October, 2017
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Upending Science

By Steven Sidley, Chief Strategist, Ixio Analytics

Chris Andersen, erstwhile editor-in-chief of Wired Magazine and curator of TED, recently made the comment that algorithms have upended science. His reasoning was straightforward - science has always progressed from hypothesis to proof. Or, to put it somewhat differently, a model is proposed and then tested against its intent. If it doesn’t work, then a new model is sought. 

But disciplines like data science often take an entirely different route to discovery. A beautiful example of this was Walmart’s data algorithms, which uncovered the startling fact that consumers stock up on Pop Tarts before a storm. No amount of modelling could have predicted that - the statistical foraging of data science excavated this fact. 

This is not to say that modelling or the hypothesis development and proof have had their days. On the contrary, the more that scientists know about their worlds, the more they are able to take leaps of theoretical logic, and wait for experimental evidence to catch up. This is the story of general relativity - there was not a whit of experimental evidence when it was published by Albert Einstein in 1915, and now, over 100 years later, its predictions continue to gain the support of evidence (the latest being gravitational waves). 

But data science and machine learning often dance to a different tune. Statistics, which underpins much of data science, gives us a set of lenses through which we can look for patterns, without knowing a priori what those patterns might be. Take a tsunami of data, filter it through any number of statistical transformations or neural nets, and see what appears on the other side. Without the scientist’s intent, (or at least without even fuzzy intent) a judicious use of these filters might produce startling results, like statistically significant correlations between two hitherto unrelated data structures.

Once a correlation is unearthed, traditional science can be re-introduced, models and hypotheses can be constructed, causation can be captured and locked down. Or we can simply iterate algorithms, dream up new statistical or learning filters and watch the change of colour of these correlations against their new backgrounds, making their conclusions easier and easier to draw, even if actual causation stays out of reach. 

So data science is often an iterative exploration - we don’t always know what we will find. Traditional science is the opposite - we think we know exactly what we are looking for, and set out looking for a way to prove it. Put the two together, and the chances of unique and useful discoveries multiply. 

At Ixio Analytics we chase these twin rainbows. Out data scientists are steeped in traditional scientific methods. We propose, we forage, we model, we filter. And at the end, we discover. 

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About Author

Steve has over 35 years’ experience in diverse areas of business, technology, telecommunications, media, information management and private equity and has worked at operational, executive and board levels. After qualifying with an MSc (Computer Science) from the University of California Los Angeles in 1979, Steve spent the next 17 years in California. This was the Cambrian period of technological development, particularly on the West Coast of the US, and he was fortunate enough to be involved with a great deal of new technology. This included working as an engineer on the Space program at Hughes, followed by designing video games at Tronix, a stint as an artificial intelligence researcher at Citicorp research in Los Angeles, and a period spent designing computer peripherals. Steve also founded one of Los Angeles’ most successful computer animation companies, Sidley Wright, which was sold to National Video Systems in 1994. Steve returned to South Africa in 1995 where he has held a number of C-level positions in blue chip companies including as the Group Chief Technology Officer for Anglo American plc. In South Africa, Steve has successfully co-founded two companies and continues to work on private equity and venture capital transactions. Steve also serves on several boards of directors. Steve is an award-winning novelist, and has published 4 books with Pan MacMillan.

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