The trouble with Big Data? It is called the “recency bias”.

One of the problems with such a rate of information increase is that the present moment will always loom far larger than even the recent past. Imagine looking back over a photo album representing the first 18 years of your life, from birth to adulthood. Let’s say that you have two photos for your first two years. Assuming a rate of information increase matching that of the world’s data, you will have an impressive 2,000 photos representing the years six to eight; 200,000 for the years 10 to 12; and a staggering 200,000,000 for the years 16 to 18. That’s more than three photographs for every single second of those final two years.

The moment you start looking backwards to seek the longer view, you have far too much of the recent stuff and far too little of the old

This isn’t a perfect analogy with global data, of course. For a start, much of the world’s data increase is due to more sources of information being created by more people, along with far larger and more detailed formats. But the point about proportionality stands. If you were to look back over a record like the one above, or try to analyse it, the more distant past would shrivel into meaningless insignificance. How could it not, with so many times less information available?

Here’s the problem with much of the big data currently being gathered and analysed. The moment you start looking backwards to seek the longer view, you have far too much of the recent stuff and far too little of the old. Short-sightedness is built into the structure, in the form of an overwhelming tendency to over-estimate short-term trends at the expense of history.

To understand why this matters, consider the findings from social science about ‘recency bias’, which describes the tendency to assume that future events will closely resemble recent experience. It’s a version of what is also known as the availability heuristic: the tendency to base your thinking disproportionately on whatever comes most easily to mind. It’s also a universal psychological attribute. If the last few years have seen exceptionally cold summers where you live, for example, you might be tempted to state that summers are getting colder – or that your local climate may be cooling. In fact, you shouldn’t read anything whatsoever into the data. You would need to take a far, far longer view to learn anything meaningful about climate trends. In the short term, you’d be best not speculating at all – but who among us can manage that?

Short-term analyses aren’t only invalid – they’re actively unhelpful and misleading

The same tends to be true of most complex phenomena in real life: stock markets, economies, the success or failure of companies, war and peace, relationships, the rise and fall of empires. Short-term analyses aren’t only invalid – they’re actively unhelpful and misleading. Just look at the legions of economists who lined up to pronounce events like the 2009 financial crisis unthinkable right until it happened. The very notion that valid predictions could be made on that kind of scale was itself part of the problem.

It’s also worth remembering that novelty tends to be a dominant consideration when deciding what data to keep or delete. Out with the old and in with the new: that’s the digital trend in a world where search algorithms are intrinsically biased towards freshness, and where so-called link rot infests everything from Supreme Court decisions to entire social media services. A bias towards the present is structurally engrained in almost all the technology surrounding us, not least thanks to our habit of ditching most of our once-shiny machines after about five years.

What to do? This isn’t just a question of being better at preserving old data – although this wouldn’t be a bad idea, given just how little is currently able to last decades rather than years. More importantly, it’s about determining what is worth preserving in the first place – and what it means meaningfully to cull information in the name of knowledge.

What’s needed is something that I like to think of as “intelligent forgetting”: teaching our tools to become better at letting go of the immediate past in order to keep its larger continuities in view. It’s an act of curation akin to organising a photograph album – albeit with more maths….(More)