They Blinded Them With Science

Recently, we were told that Mars was closer to the earth than it has been at any time in the past 60,000 years. This gained much media attention, and sparked a wider interest in astronomy amongst the general public.

This was followed by the revelation that the Earth was in danger of being hit by an asteroid. As this seemed to be of considerable significance, rather than just a general curiosity, all the data was re-examined, and the recalculations indicated that we should be safe after all, as there was only a 1 in 909,000 chance of it hitting.

One might think that, in the light of such a dramatic reinterpretation of the data, someone might similarly return to the Mars data to see if the figures there were incorrect too. But although both cases are essentially the same mathematically, the approach and resulting presentation were very different.

It seems that someone, somewhere, noticed that Mars seemed to be getting closer to the Earth. Curious as to whether or not this was so, they gathered the data from recent observations, and traced its orbit back in time to estimate its more historic position. Out of this popped the media-friendly statistic that the last time Mars was so close was 60,000 years ago. A sensible margin of error here might be 1%, but "60,000 +/- 600 years" doesn't make for as nice headlines.

So why is one portrayed as much more accurate than the other? Of course, there are differences in the calculations, but essentially it comes down to scientists presenting their information in a way to make it more palatable to the public. But should science be something which can be played in a particular way in order to make it more acceptable to certain audiences? Science is as much value-judgement based as anything else, and the universe is not the large clockwork instrument the Victorians believed it to be.

What is really at stake is the different way that issues can be presented to the public. And especially when it comes to anything technical, be it physics, chemistry or computer science, the general public are all too willing to believe what they are being told. The gurus all tell us about the Next Big Thing. The scientists all tell us How It Is. All the critical analysis is done for us, and as a result we accept sloppy reporting without question.

We all want to believe that the latest methodology or technology will make us better people, more productive workers, and even rich. But the Latest Thing may just be the Same Old Thing from a different angle. It is important not to forget any lessons we have already learnt, not to instantly abandon what we know to be right just to keep up with the all-singing, all-dancing bandwagon.