When looking to predict the future, one historian of science suggests we need to think probabilistically:
The central message sent from the history of the future is that it’s not helpful to think about “the Future.” A much more productive strategy is to think about futures; rather than “prediction,” it pays to think probabilistically about a range of potential outcomes and evaluate them against a range of different sources. Technology has a significant role to play here, but it’s critical to bear in mind the lessons from World3 and Limits to Growth about the impact that assumptions have on eventual outcomes. The danger is that modern predictions with an AI imprint are considered more scientific, and hence more likely to be accurate, than those produced by older systems of divination. But the assumptions underpinning the algorithms that forecast criminal activity, or identify potential customer disloyalty, often reflect the expectations of their coders in much the same way as earlier methods of prediction did.
Social scientists have long hoped to contribute to accurate predictions. We want to both better understand what is happening now as well as provide insights into what will come after.
The idea of thinking probabilistically is a key part of the Statistics course I teach each fall semester. We can easily fall into using language that suggests we “prove” things or relationships. This implies certainty and we often think science leads to certainty, laws, and cause and effect. However, when using statistics we are usually making estimates about the population from the samples and information we have in front of us. Instead of “proving” things, we can speak to the likelihood of something happening or the degree to which one variable affects another. Our certainty of these relationships or outcomes might be higher or lower, depending on the information we are working with.
All of this relates to predictions. We can work to improve our current models to better understand current or past conditions but the future involves changes that are harder to know. Like inferential statistics, making predictions involves using certain information we have now to come to conclusions.
The idea of thinking both (1) probabilistically and (2) plural futures can help us understand our limitations in considering the future. In regards to probabilities, we can higher or lower likelihoods regarding our predictions of what will happen. In thinking of plural futures, we can work with multiple options or pathways that may occur. All of this should be accompanied by humility and creativity as it is difficult to predict the future, even with great information today.