Are you MIsusing the sciences to back up a claim?

As I wrote on my WordPress Blog page, I am using the sciences to back up my claims. I am not the only one and there are further blog formats that also use the sciences to back up their claims. The sciences I relate to scientific papers that are for example peer-reviewed. Now what’s the catch? Nowadays, I am certainly not the only one, you can open Google Scholar and then you type in what you are looking for and when you are lucky, which you likely are because we are saturated on the sciences, you find a scientific article that you are looking for – to confirm what you think and want to convey. Just to give you an example; Sex is awesome, oh suprise an older study confirms it is awesome. My obvservation is valid.

A former professor of mine referred to it as scientific “cherry-picking and I am delighted that she taught me about it, because indeed she is right. It is as easy these days to write a blog, possibly policy and investement suggestions and and cherry-pick the foundation for it as easy as it is not to. You could not do so and be honest, while following logical argumentation and analysing “its” meaning but hypothetically, the validity of your own argument is lost for further recognition, making what you write and what is to be read rather invalid, if not even stupid without scientific evidence. Instead we trust the sciences and how we read it, to then make a claim or to confirm the claim we try to make; “We should invest into bitcoin”, because in the future people will like it, according to this study and not carefully delibertion of it; its method and outcome and done for who by who and how. Logically and if we are being honest, it can also be not like that, because the future is too uncertain and more studies would have to be done etc. Some studies or the ability to publish is furthermore exclusive too, making the sciences limited to what I call a bit elitaire and exclusive towards different knowledge.

Now more about the sciences and how they are used, by who and why. You will find that a NGO X is making claims and then tends to use a study or at least parts of it to confirm their claim or to receive funding. In my field, known the field of sustainability something similiar can be found. “A” is sustainable minded and wants that people consume more sustainable and to do so needs money for purpose “B”. A will now look for an article on consumer studies and finds one (favored are studies by business consultencies and market research institutes) to confirm that 60% of consumers of a random sample group want to buy more sustainable. The study confirms what A was looking for, whilst ignoring wishful thinking which is that many people not actually want it and the fact that 40% don’t want to buy more sustainable etc. A yet receives some funding and the investment into for example sustainable apparel flops.

Now this goes further and further, making its way into the sciences itself, which is to research to confirm or to develop something that confirms the hypothesis, or what the client needs. This can happen if the research is steered towards a specific set of expected responses “How much do you like this?” instead of “How do you view this?” (Even if you ask how much do you like this, you make liking the main option). No? Ever been asked how much you dislike something that should be of liking and then rate it? My former professor (thank you at this point) referred to it as being the devils advocate. If you are an honest broker, you research and provide different options and the outcomes could be of choosing for the client. Ideally, you would be a pure scientist, making objective observation or picking objective studies by as much as possible (Pielke Jr, R. A., 2007). The latter tends to receive little funding because it can lead to non desired outcomes, obviously.

Now what is it that I want from you? Have a look at your resources and don’t use them, if you don’t want to and do if you want to. Why? Because its vicious and risks that investements and hopes are placed falsely. Have a look at studies that don’t confirm what you are looking for. It itches, but may give room for different spaces to thrive,for example new ideas, strategies, projects and policies and even not where they should not.

Recommended references:

Evans, A., Sleegers, W., & Mlakar, Ž. (2020). Individual differences in receptivity to scientific bullshit. Judgment and Decision Making15(3), 401.

Pai, M. (2020). How Prestige Journals Remain Elite, Exlusive And Exclusionary. Retrieved from: https://www.forbes.com/sites/madhukarpai/2020/11/30/how-prestige-journals-remain-elite-exclusive-and-exclusionary/?sh=5e90a3254d48

Pielke Jr, R. A. (2007). The honest broker: making sense of science in policy and politics. Cambridge University Press.

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Can we predict the future?

We cannot predict the future with certainty, but we can create possible scenarios. In sustainability one looks at trends such as in the ecology, economy and society to form possible images or scenarios of the future. For example one can see increasing policies supporting sustainable development, more companies to engage in sustainable production processes or at least ESG and also increasing consumer interests in such. Therefore, one could imagine that in 2050 earth will be quite sustainable, whatever that means exactly.

Can the future be predicted accuratly?

There is certain bias to it because we find daily changes, but also unexpected events that may drastically influence our imagined scenario. Such an example is Covid-19 or the Ukraine Russian war that hugely impacted and still does in terms of efforts towards sustainable development; energy transition, cooperation, peace building opportunities and unexpected emissions such as from war, also the fact that while people care, some do not and some may do differently.

Can unexpected events be accounted for?

To take these unexpected events into account wild cards can be used. Wildcards can relate to any event that can have a major impact, for example a terrorist attack, an earthquake, a pandemic, or more individual an unplanned pregnancy, a Sexual Transmitted Disease or other illnesses not accounted for etc. . These are important to take into account because as seen in the examples before, they can hugely disrupt predictions. [Can you think of more?]

Why are wildcards important?

Wildcards are important because the future is too uncertain to predict it fully, so wildcards help to think about what other scenarios could occur and how to prevent them or what could be done in the case of their occurrance. Often these can help in minimizing possible risks. One of such examples is intelligence analysis, in which possible scenarios are quickly predicted to, for example, prevent fatalities or economic shocks. However, they may and they may not include wildcards or they may be based on them.

“This is likely to happen, lets therefore implement a policy here or increase security there or pay attention to there.”

Can scenario analysis be biased?

Yes, this can happen by taking into account narrowed views, biased sources or limited expertise. This can happen because of personal and collective bias or because of limited or biased information used to predict the future. For example the scenario of the sustainable earth I described at the beginning is purposely very one sided, focusing only on “positive” developments; whereby likely many companies may not care or cannot care about sustainability. The same can account for people and different countries too. So the future of earth may as much be sustainable as much as it won’t or a mix of it. This is imporant to be aware of to understand possible bottlenecks such as the impact of poverty or inequalities that can serve as barrier for interests in sustainability as a whole.

Can bias be avoided?

I believe that bias cannot be avoided fully, because there most often is personal and collective bias, but bias can be reduced such as by fact-checking news- sources; by looking carefully validating and evaluating information (cross-referencing) as well as by checking into different developments. Of course one should do so in a particular lign of interest and boundaries (time/space/directions).

Can bias be encouraged?

One may also go with imagining any future such as done most often in science-fiction and here work fully with possible bias and hence, imaginary. Yet, the reality of how to get there, might be a bit vague, a bit too much of phantasma so that future predictions becomes quit difficult to predict with certainty or possibly unrealistic.

Questions? Let me know and also if you want more on that topic. Below you can find my summaries.

Recommended Resources:

Walsh, P. (2011). Intelligence and intelligence analysis. Willan.

Investopedia (2022). Forecasting. Retrievable here.