The current pandemic is one of the most important events in modern history and there is barely anything required to qualify this claim. Yet, if it seems too absolute, consider the featuring headline from The Guardian on the 20th of March. The world shutting down is a pretty big deal. It’s definitely something that has me thinking all the time and writing on WordPress.

One of the first things that had caught my fancy was the use of models and simulations to predict the dynamics of contamination. Everything that we’re hearing, from the predicted trends of how the disease will spread, the number of deaths, how many critical care units will we need — all of this is coming out of some form of modelling. It is indeed an incredible feat of the human endeavour to be able to build these and use the results to keep us living. But, one must remember, as Edward O. Wilson, “an American biologist, naturalist, and writer” points out — that these are but ‘virtual worlds.’ Considering they’re only virtual worlds, and considering that crises often kill our ability for collective reflection, I believe it to be my utmost duty to sit down and reflect upon the truthfulness of these models. Especially as I benefit from the privilege of whatever truth they’re believed to have so far revealed.

In the following passage, from his book Consilience: The Unity of Knowledge, E.O. Wilson explains the Biologist’s process for building these large, systemic models:

“Biologists, it has been said, suffer from physics envy. They build physics like models that lead from the microscopic to the macroscopic but find it difficult to match them with the messy systems they experience in the real world. Theoretical biologists are nevertheless easily seduced … Armed with sophisticated mathematical concepts and high-speed computers, they can generate unlimited numbers of predictions about proteins, rain forests, and other complex systems. With the passage to each higher level of organisation, they need to contrive new algorithms, which are sets of exactly defined mathematical operations pointed to the solution of given problems. And so with artfully chosen procedures they can create virtual worlds that evolve into more highly organised systems (94).” 

He further notes, as a word of caution against overconfidence in these models, even if they come to the right conclusions, that:

“Many procedures may be false and yet produce an approximately correct answer. The biologists are at special risk of committing the fallacy of affirming the consequent: It is wrong to assume that because a correct result was obtained by means of theory, the steps used to obtain it are necessarily the same as those that exist in the real world (95).”

Which is to say, with reference to the models being used for COVID19, that these can first fail to predict something as simple as the total number of deaths, but even if they do that right, they  can still fail in predicting the processes through which that number is reached. These processes of contamination, in nature, do not have to be the same as those that are theorised in the model.

One must, at this point, also note that many of our organised and individual responses to the pandemic are based on the processes that these models intelligently assume or hypothesise, such as those of social distancing and complete shutdowns. I must also note that these are both historical ways of controlling pandemics, but this is the first time we’re having a pandemic in a world as global as ours, and just because something has worked always and continues to work (maybe not as effectively?) doesn’t mean it should be used: can we think up something better? But I am going to keep these specific opinions to myself and leave this link here for whoever wants to look into the details for the current COVID19 models.

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Coming back to E.O Wilson, after detailing the process through which these models are arrived at, and pointing out the limits of their ability, the wonderful man uses a brilliant allegory (is it one? if not, please leave a comment) to explain why these limits exist, and even perhaps, will always exist — I think Wilson would have said that they won’t always exist, I think that’s actually his main point in the book. He says:

“To see this point clearly, think of a blossom in a painting rendered photographic in detail and as beautiful as life. In our minds the macroscopic entity has truth because it matches real flowers sprung from the soil. From a distance we might easily confuse the image with the real thing. But the algorithms that created it are radically different. Its microscopic elements are flakes of paint instead of chromosomes and cells. Its developmental pathways exist in the brain of the artist, not in prescription by DNA of the unfolding of tissues. How do theoreticians know that their computer simulations are not just the paintings of flowers (95)?”

I shall leave it at this. Hmu for a conversation.

Thanks to PhotoMosh for glitching my screenshot.