I recall science being about careful experimentation to gather data to challenge some theory and occasionally come up a better replacement. As computers became more accessible, we began coding old theories into simulations that produced huge amounts of results that can produce dazzling graphics.
Within my lifespan, the idea of loving science converted from loving that act of converting observations into new theories into loving the act of visualizing some old theory.
Computers are to blame. I recall the initial excitement about computers making observation collection and analysis easier and faster. Computers would allow science to progress faster.
Instead, what happened is that computers immortalized older science. The new objective is to compute old theories in more detail for even more dazzling graphics, like the endless zooms of Mandelbrot sets.
While there are new discoveries that add to our scientific knowledge, there are many old science ideas that are enshrined for their ability to generate pleasing data.
I suspect it was easier to retire old theories when they required hard study to make sense of mathematical equations using pen and paper. Theories needed to be good to motivate the effort to continue to use them. Once they became captured into computers, they reproduce effortless and present their predictions to any one with access to a computer. Now, we have no reason to challenge old theories, their expressions are self-replicating and easily transmitted from one computer to another.
These theories may have some mathematical expression for publication, but for all practical purposes they exist in software code that only the coder needs to read. For everyone else, the theories are expressed in generated data that can populate graphs or visualizations when given the seed of some initial conditions.
The computer can create the data we once had to work hard to collect from the real world. It has come to the point where many people are convinced that the entire Universe is actually a computer simulation. It is feasible that a computer can use predefined code to produce every observation available to humans. At some point it will become more productive for us to ignore our observations and pay attention to the construction of simulation we live within.
The same computation advances that improved the visualization of old theories also enabled the massive collection of observational data. If all the world is really a simulation, the observed data lives in perfect harmony with the simulated data.
Science has moved from products of human intellect to artificial intelligence such as neural networks. Neural networks come up with scientific models it a vast array of weights assigned to each different input in many layers. The first layer is direct observations, but all the rest of the layers are watching the results from the prior layers. Nearly all of the neural network processes simulated data.
Neural networks have been successful at learning. The learning is the discovery of some model of how the observations work. In many cases, the learning has been so reliable that we trust to neural networks what we once trusted only to other humans.
The neural networks learned a theory of how the world works but it never has to tell us exactly what that theory is. We never ask the neural network to express its thinking in mathematical formulas.
Humans accept that they have no need to understand what the computer has learned. There is no need to communicate science from one human to another. All that is needed is to download the code or the data to another computer.
We reached a point where we have in our data stores a mixture of both simulated data and actual observations. We put them in the same schema and we use similar naming conventions for their references.
We treat both observed and simulated data are equals. This builds on our confidence that the Universe is a simulation. When seeking an observation, we choose between simulation and sensor based on which is easiest to obtain. Either one tells us the same thing.
In this blog, I stubborn segregate these data. I describe simulated data as dark data, a term I generalized from the discussions about dark matter and dark energy in cosmology. This is the part of the Universe we can not see but our sciences tells us must exist. Contrasting to dark data is bright data like stars in the night sky are accessible from our sensors.
I cling to my earliest experiences (before even handheld calculators) where I had to visualize reality with actual observations. A theory of gravity for example needed to be demonstrated in experiment with dropping objects under a strobe light and seeing the different distances covered at each strobe.
I imagine an alternate reality where we have modern computation capabilities but we never bothered to simulate software coding of our scientific theories. In such a reality where we continued to visualize theories through sensor observations, I expect we would be learning more than we are learning today. In particular, we would be rejecting old theories when they fail to explain what we are seeing.
Today, I see us doubting our observations before we doubt our theories.
A perfect example of this is the current COVID19 pandemic. From the start, it became a tragic comedy of disbelieving our eyes.
- Initial observations of some new type of ailment had to come from some new virus
- The newness of virus and the initial isolated first cases meant it had to come from some exotic animal and thus traced to some unsanitary meat market
- The patients frequently indicated symptoms that established protocols dictated the quick use of ventilators
- Once human-to-human transmission was evident, the only permissible ventilator was the most invasive kind because science told us that the other types produce infectious aerosols
- The increase in fatal cases was evidence of a particularly deadly version of the virus so more ventilators were needed
- Death rates increased when invasive ventilators were used up, often connected to patients for weeks at time before they died
- We then committed to global lock downs due to science of flattening the curve to keep the new cases within the supply of ventilators
- The new case rates have flattened confirming the theories
- The fatality rate remains high so the lock down must continue
- The only solution is a vaccine to rid humanity of the virus supposedly behind all this mess
All of this is traceable to a simulation result. The observations never challenged the theory. Instead new observations advanced to the next predefined theory.
This all played out like a play already scripted by the science. It may be a poorly written play where scene proceeds by the author’s blindness to the situation that he actually set up, ever departing from realism as he takes the story to increasing levels of incredibility.
We are led to believe that in this crisis that at each step seems increasingly dire, there is no time to assess whether the observations challenge the previous assumptions. Instead, the new information justifies escalating our response through invocation of additional science to address the perceived situation.
Reaching the point of convincing ourselves that we are facing a existential threat to our entire species, all based on observations coming from science rather than our senses.
Recently there has been increasing discussion that the scenario described by the science is not supported by observations.
Doctors are noticing that they are treating multiple incompatible disease patterns that are unlike anything they have experienced before. For example, they are noting that patients with low oxygen levels in their blood are not exhibiting the distress normally expected. Despite the low readings, the patient is coherent and comfortable and claims to fill fine. This continues to a point when the patient’s condition suddenly worsens and may die very quickly.
Other patients are showing the distress of low blood oxygen as normally expected.
Doctors are also noticing that initial policies dictated immediate intubation for invasive ventilation had been resulting in lower than normal survival rates. Some have taken the risk to act on their observations instead of following the science, deciding to use non-invasive ventilation and then improvising partial protection of the aerosols through applying a cloth mask over the ventilation mask. They have been observing higher survival rates.
This new information is not scientifically proven but the higher survival rates encourage them to continue to disobey the science dictating the use of invasive ventilation. Lurking behind these observations is that the invasive ventilation itself may have contributed to the higher fatality rates at first.
The initial reports of high fatality might be due to evidence-based medicine rather than to the disease itself.
I notice that there is global consensus condemning China for their initial responses. I’m inclined to give them more credit to what was happening. They probably recognized very early on that the disease conditions were not like anything seen before and that the patients were not responding according to what science predicted. They might have recognized that the treatment practices themselves were contributing to the fatality rate and that some people may be better off less intensive care.
In both China and Western societies, the population is conditioned to trust science. They would recognize that a patient was in a condition qualified for intensive care and they would not accept anything less than obtaining that care. Meanwhile, there might have been growing evidence that such care was not working. There is no way to effectively communicate this. The population would perceive they were being denied science-based care because that is exactly was happening due to the loss of confidence in that science.
The above is pure conjecture about what might have happened early on in China. I don’t have any evidence that this happened. I have heard western doctors describe the novelty of the conditions they are treating and the novelty of the effectiveness of unapproved alternate care.
There is a difference between doctors treating actual patients, and the scientists setting the policies based on evidence-based medicine. The doctors are trained to be keen observers. They will notice that the conditions and the patient responses are not obeying the predictions of the science. They will quickly lose confidence in the established procedures and either take the personal risk of deviating from those procedures or of refusing to continue something they can see is counter productive.
I am suspicious that the initial emphasis on quickly administering invasive ventilation may have contributed to the higher initial death rate. Because of the predicted risks of aerosols from the less invasive ventilators, those were not allowed to be used at all. In early cases, a large majority of those getting invasive ventilation would end up dying with that in place.
The public instead sees the heart-warming story of the minority who survive and credit the ventilators for their survival thus emphasizing the need for ever more invasive ventilators. There were no interviews of the thoughts of those who succumbed under the same ventilators.
There are known risks to invasive ventilators in the first place. A lot can go wrong in their installation, operation, and removal. Doctors are noticing that for many patients (those with happy hypoxia) the invasive ventilators makes the situation worse than if they were just given oxygen. Perhaps the procedures are changing to use such ventilators less but the predominant public perception is that such ventilators are an absolute requirement for treatment so that we need to continue to build stocks of them to prepare for future outbreaks.
Another observation is the uncertainty in many of the parameters of the epidemic itself, such as when it first appeared in countries outside of China, how many people are already infected, and how many deaths are truly attributed to the virus either directly or through aggravating some other condition. The epidemiology science directed doctors to attribute deaths to the disease as long as the patient tests positive for it, even if they do not exhibit the symptoms.
Further, the scarcity of test kits lead to a science-based decision to use them only for patients with qualifying symptoms even though the primary benefit was to isolate the patients rather than to give them more effective care. An alternative approach could have used those kits for random sampling to assess earlier on how widely the infection was in the population. Science instructed us to recognize the first patient in an area to be the first infected person. As a result, there would be no earlier infected person and thus a random sampling of the population would certainly return zero positive cases.
As testing kits became more readily available and applied, we see a relatively constant proportion of positive results for those tested. Recent antibody testing for people previously exposed to the virus is also showing that the disease may have been circulating earlier than expected.
In combination, the actual rates of fatality and of need for hospitalization may be much lower than previously feared.
If this turns out to be true, I wonder whether we might have come to this conclusion earlier. Our science lead us to fear to the worst. If this is a naturally occurring virus that jumped to humans, then a reasonable assumption is that it would behave similar to other natural occurring viruses.
It was science that proposed that some super deadly corona virus could emerge. We accepted that this might be the time science was warning us about. We used the observations to confirm this fear rather than to confirm the assumption that this would be no worse than a bad flu season. The rush to conclude that this must be the predicted bad scenario could have been a result of getting observations that conflicted with the science of initial conclusions. Instead of leading to questioning the initial conclusion about the virus, the observations supported the idea that this virus was particularly unusual and thus unusually scary. Subsequent surprises reinforced the reasons to fear this particular outbreak until the entire global economy shut down.
In addition to the details about the parameters about the pandemic, there are also questions about the virus itself. The virus itself has not been isolated and proven to cause the conditions being reported. In particular, there appears to be multiple ailments, each one being deadly in different ways. Further confusing matters is the liberal approach to attribute all conditions to the virus when the patient tests positive. It is not clear we are dealing with a single disease.
The testing being used is testing for free RNA that may not be associated with the virus at all. Yet, we assert that the positive test result is proof of presence of the virus and thus any conditions observed may be attributed to the virus.
Science is guiding us into combining multiple condition patterns to be different expressions of a very simple mRNA virus. The science is informing us this particular mRNA must code for many different vulnerabilities within the human body because we see so many different and unusual symptoms in patients testing positive.
There might be multiple conditions floating around. The pandemic has focused medical attention on just these conditions because other areas of medicine are mostly shut down. Some of these conditions have been around longer but never before studied as a wide-spread common cause.
As long as we keep escalating the progression of the presumption that this virus is the virus that science told us to fear, we don’t have the luxury to pay attention to observations and allow ourselves to ask whether the observations challenge the science that got us to this point.
Perhaps the real agent behind this pandemic is science itself. Given a sufficiently dire circumstance, science can shut down our natural defenses of critically thinking about observations we can clearly see. Science tells us that if this is the disease it warned us would come, then we have no choice but place all trust on science at the expense of paying attention to what we are seeing.