Aren't all such (big-)data models (e.g. predicting natural disasters, stock-markets, global-warming, effects on GMO, ...) an attempt on measuring "real life"? And so can not be measured accurately because as soon as you take your snapshot data points and events inside the model will have moved on to a new state? Not that we shouldn't try to build these theories but accept them as theories or "soft-science" and not facts.
As soon as we have simplified a complex hard to understand system into a chart we tend to ignore that these "facts" represent at best a snapshot of reality (one version of it) from a specific point in time but certainly not the future.
However, he has failed to grasp, or educate himself sufficiently, that gene transfer between organisms is in fact a common occurrence in natural ecosystems [0].
Further, at this moment at least, the genes that are being transferred artificially are in general not genes that would cause havoc if they somehow became mobilized from the species into which they were introduced. By way of example, the protein Bt confers resistance to insect predation,it is originally derived from a bacterium that killed insects in a parasitic cycle [1]. Plants, generally, have hundreds or thousands of ways of resisting insect predation, and adding one more to the mix is not going to devastate any ecosystem, at least not in the long term.
You are assuming that we have sufficient comprehension of these genes and their effects to make such claims definitively. And while we may have a very high degree of confidence in that, say enough confidence to entrust my life, your life, or hundreds of individual lives - entrusting the wellbeing of the entire planet requires a different scale of rigor.
And that, I think, is the essence of Taleb's argument. 99.99% sure might be enough to get a drug approved, and it well should be, because only some fraction of the population is at risk. But because DNA is inherently self-propagating, a mistake can have extremely far-reaching consequences, and as such the tolerable level of risk must be orders of magnitude lower.
This has been Taleb's essential, consistent thesis throughout his career. That humans are bad at assessing the probability of relatively unlikely events, and that when those events are extremely catastrophic, that cognitive deficiency can be disastrous.
Of course, GM-technology is a huge area of tools, tools which are being used in all kinds of situations and outcomes: modifying bacteria to create insulin or washing powder ingredients (both of these have been done on an industrial scale for decades now); modifying plants to have a better defense against various pests (being done with Bt cotton and soy IIRC), or just to glow in the dark (there's a kickstarter), etc.
These are all more or less "good" outcomes of GM, but you could also use GM for "bad" - you could make maize express a human neurotoxin and spread that plant in order to attack a country (a not very directed attack). The only thing that's stopping you is that it's still very hard, expensive and time-consuming to do so.
Nature has a way of eliminating failures; humans have a way to offload failures off to someone else.
The effective aspect of the scientific method that separates it from scientism is falsifiability. The comparison for falsification here is "GMO farming" versus "status quo farming"; nowhere is nature involved.
"Even if we can agree that some things are natural and some are not, what follows from this? The answer is: nothing. There is no factual reason to suppose that what is natural is good (or at least better) and what is unnatural is bad (or at least worse)."
https://en.wikipedia.org/wiki/Appeal_to_nature
Gene transfer may have already screwed up the planet once:
http://www.smithsonianmag.com/smart-news/how-single-act-evol...
In the case of the LHC, we know that particles collide at the speeds planned all the time, yet this does not lead to black holes erupting everywhere.
In the case of the gene transfers currently done, we know precisely what they are and they are already part of the environment, having been derived from other natural organisms. The risk of the current crop of engineered plants becoming super-weeds that choke the planet is not zero, but also not plausible from a biological perspective.
That someone could engineer a super weed is of course possible, as would be engineering the flu virus to produce cholera toxin. So, precautions should indeed be taken when releasing engineered organisms.
This case is not analogous because in this planet's history there have been 6 different extinction events. So in order for it to be analogous, they would have to say that we know a few times in the past this has caused a black hole, but this is totally different.
Passing genes from one thing into another can very easily have unintended consequences as they do in nature. The link above is an example of what can happen. By the time you figure it out, perhaps it will be too late. The effects might be local or they might be global, there is no way to predict these things and we can not say with certainty that they don't happen, because we have more than one example of where they do. In fact human intelligence may be an accident of horizontal gene transfer. These are not games that are worth playing in my opinion. You are what you eat. If that stuff it in your food supply, it just might end up in you and the bacteria and other life that lives in you.
Another really big problem is dependence. Once you come to depend on these things, just like we are now with carbon producing technology, you can not pull the plug. Even if you know that it's causing harm, the social mechanism needed to pull the plug don't exist in free society and if they do they are very slow moving. That's another big reason to not go down this road, because it's impossible to turn back because of all the people that will die because you can't produce the expected crop yields.
There are two mass extinction events that have a clear biological origin. Minor extinction events are a permanent feature of evolution.
The first is the evolution of photosynthesis causing the Great Oxygenation Event[0]. In this, cyanobacteria converted CO2 into water and oxygen on a massive scale. This lead to a cooling of the planet due to reduced CO2 levels and the precipitation of iron oxides into massive deposits worldwide, today visible as "banded iron formations" [1].
The second mass extinction with a clear biological origin is the current one, where Homo sapiens is converting a massive quantity of carbon previously sequestered during the carboniferous back into CO2 and warming the planet as a result. In addition, this species destroys the habitats of many other species.
Namely, you claim (necessarily without proof) that a real-world phenomenon is analogous to a certain mathematical model. Then you prove some things about the model. Finally, you claim that the things you've proved about the model are also true about the real world. It doesn't matter how rigorous the mathematical steps in the middle are, the strength of this kind of argument is determined by the first step: how strong is the analogy between the mathematical system and real life?
In physics, we can build models where the analogy is very strong: when we try out new situations in both the model and in real life, we get the same answer in both. In (macro-)economics, we typically do something weaker, where we start with a set of models determined by intuition, and then choose the one that gives results most similar to real life in the situations we've already seen. Prediction of future events is really difficult.
It seems like the approach in Taleb's paper is even weaker. We choose a model based on pure analogy, explicitly disclaim the usefulness of evidence ("While evidentiary approaches are often considered to reflect adherence to the scientific method in its purest form, it is apparent that these approaches do not apply to ruin problems"), and then attack anyone who says that we've done something other than prove a mathematical theorem about the real world.
It's too bad, because underneath all of the "mathiness" is one of the strongest arguments against GMOs that I've heard (and I say that as a GMO-eater). It just should have been an opinion piece in the NYT rather than a research article on the arxiv.