People who know me are aware that I often complain that applying blindly the so-called “precautionary principle” is leading to inaction.
However, fear does not prevent danger, so tells a popular French saying. Similarly, data should not prevent any decision making.
In a paper about the precautionary principle (in French), Gaspard Koenig states that “the precautionary principle central idea, and its most important drawback, lies in the will to avoid any uncertainty whatsoever. Then, when in doubt, forbear.”
I do agree. And the ultimate paradox lies in the fact that the more data are to be handled, the more parameters are to be tuned, the less certain the decision is. Big Data leads our leaders not to decide anything anymore. The data overflow paralyzes.
Therefore, the automatic usage of the precautionary principle has to be suppressed, especially when it comes to institutionalizing it (let us not talk here of its addition to the French Constitution, certainly the most astonishing legislative act one has witnessed in the past decades).
Let us investigate the GMO example (also mentioned by Gaspard Koenig in his paper). Many studies and tons of data, most of them rather contradictory, are implying that GMO’s could represent a threat in the end, in 20, 30 or 50 years from now, either through a wave of cancers, or some alteration of our genetic material. Maybe. Until then, thanks to GMO’s, millions of people could have been fed better (or even fed at all), but instead they will starve. To death. So, do we act according to our conscience or do we let data validate our paralysis?
Beyond the comfort of data-backed analysis lies the necessary power of decision-making. Data may only sustain decision processes, whereas making the decision is a privilege of mankind. Besides, in the years when massive data processing systems have emerged (in the eighties), were we not speaking of “Decision Support Systems”?
Hence, one must rely on data, but without hiding behind a stack of them. It must be clear that data sets, even “big” ones, always harbor a part of uncertainty, not about today [we are absolutely sure that using GMO’s at a worldwide scale would reduce global hunger], but about tomorrow [as GMO’s may generate risks for health and environment]. Why? Because even the most refined predictive model based upon Big Data will never reach 100% reliability ever.
And even Nate Silver, the half-god of predictive models in the US (see a slightly ironical portrait in French, here) starts his cult book – “The Signal and the Noise” – by a foreword basically telling the reader that”the more data, the more problems” there are…
Therefore, people in charge have to take a risk, whatever its height. Give up the sacred precaution. And this to everyone’s benefit, since taking a risk is the only way to open breaches, to make a breakthrough. Thinking about it, with the precautionary principle, the Apollo XI moon landing would never have happened…
So, say yes to Big Data for the Blitzkrieg, and no to the Maginot Line of the precautionary principle. Or, with a balanced point of view, say yes to the D-Day, and no to the Atlantic Wall.
Your data must give rise to movement, not to motionlessness, to action, not to dejection, must help conquer new grounds, not defend one’s turf.
You have data, that is for sure. You want to take action, that is most probable. So, do not hesitate, have your data elicited, so as to break the wall and take the most enlightened decisions!
[French version: Libérez vos données: révoquez le principe de précaution!]
Data Elicitation 