Can we predict the future?

This is one of the chore questions many people ask themselves every day, from company executives, to the individual, to families, to the politicians, lecturers, counterterrorism agencies, movie and novel writer, policy maker, up to the little child and freshly high school graduate as they choose for their study or later on a certain career.

Can the future be predicted?

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.

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.

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