The human sciences aren’t real sciences

Science News for Students,

Yes, you heard that right: the human sciences are fake sciences.

The human sciences are all about acquiring knowledge on human behaviour and human interactions, normally within the context of society.

Its name suggests that it is highly scientific, rigorous and objective. But given that it’s a strange set up of ‘ human analysing human’ — and let’s not forget how unpredictable and irrational us humans can be — , it seems to me that there are certain limitations as to how scientific the human sciences are.

In fact, I’m arguging that is isn’t scientific at all.

Change my mind.

Let’s start with defining the key term so we’re on the same page.

Karl Popper is famous for outlining the scientific method, which pretty much defines the fine line between real science and fake science. (Fake science is like those chain messages your mum gets on Whatsapp about how eating fruit after a meal can give you cancer.) Or as he calls it, science and pseudoscience.

The scientific method is all about conjuring up a hypothesis, creating a range of empirical tests to observe whether the theory is true. When creating these tests, you’re trying to disprove (the word he uses is falsify) your hypothesis. Eventually you prove that it is true. It’s a process with observation, reliable experimentation and evidence-based theories.

Well, a clear similarity between the natural and human sciences is the ways of knowing adopted by both of their respective methodologies. They both use a lot of sense perception — whether it be to observe particles or humans — and utilise logical reasoning to explain an observation.

More concretely, it may be the case that the human scientist forms a hypothesis based on observation, such as how the reduction in interest rates in an economy influences consumer spending; this is often followed by a process of hypothesis testing (employing statistical techniques in order to determine whether a hypothesis is true), using collated data and specifically-designed surveys. The element of precision in both the formation of the hypothesis and means of testing it also alludes to the idea of this idea of being justifiable and, ultimately, ‘scientific’.

Let’s look at the example of surveys, a key way of understanding human beahviour in the sphere of politics. But there’s an issue with using them. Namely, they heavily rely on the human scientist being able to construct open, unbiased questions. One example from a ‘Yes Prime Minister’ episode demonstrated that starting a survey about National Service with the question ‘are you worried about the number of young people without jobs’ may yield a completely opposing response to when the survey starts ‘are you worried about the danger of war’ (see clip below — you won’t regret it!).

Yes Prime Minster, Leading questions

Here, the ability of the survey to almost manipulate the subject demonstrates the unscientific subjectivity of the human sciences and the difficulty of observing human behaviour itself.

Even after taking into account the implications of leading questions, the issue of separating causation and correlation when assessing the data from a survey is problematic once again. For example, the hypothesis that people with big feet are better readers could be tested with a survey, asking individuals to submit their shoe size and assess their reading age, and the hypothesis would be proved as true. However, this falls short of the human scientist’s aim, to understand human behaviour, since shoe size does not cause a heightened reading age. Rather, the analysis of data may ignore the confounding variable: age. Given this second flaw in the methodology encompassed within the human sciences, one may consequently conclude that the knowledge claims in the human sciences are not truly evidence-based and, as a result, are impeded from being ‘scientific’.

I hear your point here. We’ve had some incredible predictions by human scientists. For example, the survey scientist Drew Linzwer predicted the 2012 US election results (with Obama winning 332 votes and Romney 206), drawing on knowledge claims in the human sciences (such as how income or ethnicity can affect voting habits) in order to purposefully, and indeed scientifically, make a functioning model capable of prediction.

Despite the critique that humans are difficult to observe due to the discrepancies in their behaviour — for example, acting differently in the presence of a teacher rather than a friend — , Linzwer’s accuracy in his model suggests that this is not the case. Instead, it demonstrates the need for a more complex analysis, rather than suggesting that the human sciences are simply ‘unscientific’ because here, the knowledge acquired in the human sciences was able to be applied to an entire country.

My issue with this argument is this: I don’t think sciences should have an amalgamations of theories to explain a singular phenomena. There is a real beauty in true science. For example, we can explain the mass defect of a particle, just by using E = mc², and we can explain planetary motion, just with Kepler’s laws. There’s a simplicity in true science, that we don’t quite get with Linzwer.

When Linzwer incorrectly predicted the 2016 (stating that Hillary would win), his excuse was that he didn’t include the effect of Hillary’s emails being brought up again the week before the election. When we’re getting to that level of detail, I can rest my case.

Whilst knowledge claims in the human sciences are precise, rigorously derived and useful, its methodology is greatly flawed. The difficulties of observing humans and gathering data may suggest that it is prevented from becoming a ‘scientific’ area of knowledge to a greater extent.

But, I’ll give you this. The complexities of human behaviour relative to the natural world’s behaviour may mean that we need different criteria as to what constitutes as scientific and, ultimately, whether the difficulty in understanding and deriving knowledge claims is sufficient to jeopardise its status as a ‘scientific’ area of knowledge.

Hannah is an incoming undergraduate at Imperial College London studying Electronic and Information Engineering. Having achieved 45 points in the International Baccalaureate, she is a proponent of intellectual curiosity and mastery in all fields. Hannah is an avid reader and enjoys all things STEM, politics, philosophy and languages related. Follow for some thoughts, advice and a community!

Let’s leave the accolades for a second. All you need to know about me is this: I love a good discussion & I’m all about building strong communities.