How to develop foresight?
In times of accelerated change, the ability to predict what will happen in the future seems to be equally coveted and rare. We all want to know how the future is going to unfold and as a result make our decisions with a greater sense of certainty and confidence. However, considering the complexity of economic, political and social systems, how achievable is real foresight?
According to Nassim Taleb, the author of ‘The Black Swan’, foresight is nothing but an illusion. We cannot know the future, he claims, because of our inability to predict extreme events, the non-repeatable outliers (i.e. black swans). The Financial Crisis is a case in point. Given the rarity of events with extreme impact, it will be difficult to refute Taleb’s argument that we can’t anticipate and plan for the outliers. However, not all events are unforeseeable ‘black swans’; most events come out of the building up of small incremental changes, which are observable and therefore potentially predictable.
‘How predictable something is depends on what we are trying to predict, how far into the future, and under what circumstances’, says Philip Tetlock in his book ‘Superforecasting’. Tetlock is the initiator of the Good Judgment Project, a forecasting tournament, in which 2800 volunteers competed to answer roughly 500 questions on various geopolitical topics, from the movement of Syrian refugees to the stability of the Eurozone. The tournaments identified a small group of people, the top 2 percent, whose forecasts were significantly more accurate than the average. He called them the superforecasters. Using probabilistic thinking, superforecasters can judge how high-stakes events are likely to unfold three months, six months, a year, or a year and a half in advance. Tetlock found that foresight is not only real; it is also the product of particular ways of thinking, of gathering information, of updating beliefs. This is good progress, but as Tetlock concedes, the big question, the questions that really matters, namely ‘how does this all turn out?’ cannot be answered by the superforecaster.
This is because the ability to develop a big, provocative or counterfactual question requires a different kind of mindset. Tetlock therefore suggests complementing the probabilistic approach of the superforecaster with the big-think approach of the superquestioner. The profession traditionally occupied with tackling big questions about the future is scenario planning. Scenario planners (or futurists) apply counterfactual thinking to imagine possible futures with the intention of informing long-term strategies in private or public organizations. They construct future scenarios based on inferences from the past, which they project forward into the future. The historian Niall Fergusson argues that without adequate historical training, they might be susceptible to heuristic biases (e.g. confirmation bias). Whether it’s the lack of historical training or a shortcoming of the method at large, future scenarios tend to be too crude to serve as a foundation for good decision-making. Fergusson’s provocative exclamation ‘I want the goddamn probabilities please’ in a debate with the futurist Peter Schwartz (‘The art of the long view’) can be seen as a confirmation of the need for Tetlock’s superforecasting, which should be used to fine-tune and occasionally overhaul the scenarios of the futurist.
However, counterfactual thinking is not enough to construct and de-construct superquestions. What is equally important is a deeper insight into the analogies between the present and the past, the rough regularities that influence the flow of events. Abstract meta-rules and not precise facts can guide our thinking about the future. Because meta-rules can only be generated from large data sets, historians propose the return to long-term history. Only by scaling their inquiries over many decades, centuries or even millennia can historians understand the genesis of global trends and identify the transient and the enduring in the past data. Another prerequisite for superquestions, and part of historical training, is empathy. Historians must get into other people’s heads and interpret the events from their perspective in the particular context of their times. This need for detachment from the personal and the present is key to asking good questions about the future.
What becomes clear is that foresight is neither a domain of the statistician, nor the prerogative of the humanist. It should be a collaborative effort based on feedback loops. Nassim Taleb said that epistemology, history, and statistics aim at understanding the truth: ‘They all address the question of what one knows, except that they are all to be found in different buildings, so to speak.’ The superforecaster/superquestioner approach suggested by Tetlock is an attempt to break out of the silos and gather hard and soft sciences in one room.