Debates on Science in Recent Centuries
I want to argue for a doctrine and practice of objectivity that privileges contestation, deconstruction, passionate construction, webbed connections, and hope for transformation of systems of knowledge and ways of seeing.
— Donna Haraway, Situated Knowledge
For years I heard about debates between scientists and creationists in the USA. I largely ignored those debates because it felt like it was mostly a media phenomenon. There were little arguments and a lot of shrieking from both sides.
Ignoring it worked well for a while, but over time there were more and more debates popping up that – for me at least – all have the same basic topics:
- science vs. gender studies1
- science vs. fake news
- measure everything: effectiveness of policies, workplace happieness, workout progress, …
In principle I should be on the science-side of the debate. But the proponents of that side often use arguments that I need to distance myself from. So here is a word of warning:
I am going to argue against science. Or rather: I am going to argue that science is not what many people seem to believe. Most notably, I am going to argue that there is no such thing as "scientific fact". If you are among the people who scream "yeah science, bitches!" and run away, this article might not be for you.
"Science" can be understood in a wider sense, but many people understand it as "empirical research". This means that you collect a lot of data and deduce something from that. There are many intricacies to this process which I am not going to get into.
You need a large dataset to do empirical research. If you run a business with two employees for less than a year you can not really measure anything. The same goes for the influence of volcanic eruptions on air travel. There is just not enough data.
But there is one classical argument that clearly shows the limits of empiricism:
Imagine you are a brain in a vat that is connected to a computer simulation (like in the movie "Matrix"). I am not arguing that this is the case. I am just saying that you cannot be certain that this is not the case. Everything you sense, all data you collect could be completely unrelated to the real world.
So if you do not trust your senses, the only thing you have left is your mind.2 Descartes famously took this route and found "I think, therefore I am".3 I personally believed this was the way to go until I heard about this argument by Kant:
In his "Transcendental Aesthetic" Kant argues that you cannot think of a world without space and time. But interestingly, for Kant this does not mean that we can be sure that space and time really exist. Quite the opposite: If we can not think of a world without it, this clearly shows that space and time are properties of the way we think. Even if the world is completely different from what we experience, we are simply not capable of thinking about it in other terms than space and time.
You can apply this argument to other concepts. My favourite one is contradiction: We cannot think of a world where two contradicting facts are true at the same time. So maybe the world is actually full of contradictions but we are incapable of thinking that.4
So clearly there is no way of knowing something. But we can still guess. Science ultimately is about making the best guesses possible, or making less bad guesses over time. One key concept here is Popper's falsification:
Before Popper, people would have seen a white swan and proposed the theory that "all swans are white". They would than have looked at 100 swans and, if they were all white, concluded that the theory was correct. Popper instead argued that you can never prove a theory. Instead, it is only possible to disprove a theory (by finding a black swan).5
It is important to note that empirical research and therefore falsification is not always possible. Areas like ethics, math, epistemology, or politics6 are simply not measurable. They can only be approached by rationality alone (and maybe emotions).
Choosing a Theory
All models are wrong, but some are useful
— George Box
So say we have some data and several theories that explain this data equally well. Ockham's razor is the pragmatic approach: Just pick the simplest one and stick with it until it is disproved.
This is practical, but thinking about alternate theories can open new ways of thinking about the world. Always picking the simplest explanation can make you blind for other approaches that may ultimately prove more robust or powerful. Thomas Kuhn even proposed that finding the right paradigm is ultimately much more relevant to science as a whole than gathering data.
Finally, choosing a theory is not a-political: I could believe that jews are conspiring to oppress us all. There is probably no data that disproves this theory. But I choose to be non-racist.
I do see some issues with gender studies, but I also think that their consequent refusal of the very concept of objectivity is interesting and important. I do definitely see issues with fake news, but I do not think that idolizing science is any better. I do see merit in measuring a lot of things, but I also see the work involved and the potential dangers7. I do see the value of science, but I also see its limitations.
In this article I cited philosophers from the last four centuries. None of this is new. But unfortunately, many recent arguments seem to be helplessly uninformed. So in some way I agree with the science proponents: We need to get more people understand the merits of science – but also its limitations.
If you understand german, this articel on Lann Hornscheidt is another example.↩︎
I omit the question what "mind" actually means here. What is the difference between "knowing" and "understanding"? Can a machine ever "think"?↩︎
He then went on and proved the existence of god.↩︎
It may not be impossible, but really really hard. You should try, it's fun!↩︎
It is important to note that the possibility of proof-by-example depends on the structure of the theory: "All swans are white" can only be falsified, "A non-white swan exists" can only be verified.↩︎
Politics, not policy!↩︎
Measuring employee happiness might very well make the employees unhappy.↩︎