Toward a Philosophy of Forecasting
Or, To Forecast is Human
Why do we forecast? The world is imbued with uncertainty and the human condition is largely one of uncertainty. Forecasting is the means of gaining knowledge about the future, thereby reducing uncertainty. Humans are constantly forecasting, at both micro and macro levels. At micro levels, at the level of the unconscious mind, the brain is a prediction machine, constantly making predictions about what is to happen next. At macro levels, at the level of human society, there is also an obsession with trying to gain knowledge about the future. There is a high premium being put on getting forecasts about the future, often regardless of whether they’re accurate or not, since they at least seem to reduce uncertainty in the moment. People fight change and hold on to the status quo since change makes the prediction work of the brain more difficult.
Between those two, at the level of the conscious mind, we see the same thing. We suffer from our uncertainty about the future and are therefore constantly seeking knowledge, to reduce the uncertainty. To forecast is therefore very human. The philosophy of forecasting I’m outlining, Epistemism (described here), therefore, is based on the goal of pursuing knowledge and reducing uncertainty. Epistemism holds that some uncertainty is reducible and that the way to achieve that is through forecasting.
When I talk about forecasting, note that I’m in practice referring to superforecasting, as per Tetlock, as opposed to pure finger-in-the-air speculation from political pundits or pure financial extrapolation in finance departments, which is less useful. To have forecasts that truly increase our knowledge about the future, it is necessary to apply the learnings from Superforecasting and leverage the wisdom of the crowd. Other types of forecasts contain very little knowledge. They may only generate information, which is very different. Superforecasts, or just forecasts from now on, are those that contain knowledge rather than just information. They can be said to have a high knowledge quotient, or embodied knowledge potential.
Can we achieve full certainty? Epistemism holds that uncertainty is never fully reducible to zero. There will always be black swans and events that cannot be foreseen in any way. Even in the present moment, the fleeting instance where the past meets the future, we can never have full certainty regarding the world.
There are views, from recent thinkers that have refined Berkeleyan theories of immaterialism, such as Thomas Metzinger and Donald Hoffman. They make strong claims about the illusoriness of reality, arguing the extent to which the outside world is different from our experience of it. However, they do assume that there is an outside world, even if we can only access it through glimpses or imperfect interpretations. For forecasting to be possible, however, we must assume that there is at least a minimum modicum of shared reality, so that it is possible for different people to forecast on the same basis. Epistemism only requires the knowledge that has been created to be retrievable by others, through oral or written communication. It is therefore consistent with Metzinger and Hoffman to the extent that knowledge can be retrieved by someone else from the outside world. Since they both allow for some kind of objective reality, Epistemism holds given those constraints. Especially if there is no objective reality, and we only operate to our best hypothesis, largely creating our own realities, then knowledge, in the form of the little objective knowledge we can get, would be even more paramount.
Leaving the present increases uncertainty. This holds in either direction. Going forward, into the future, the further we go, the less epistemic certainty there is. The same holds for going further back in the past. Memories are fallible, and all history is a perspective, a narrative placed upon discrete events. History in a sense is therefore back-casting, of trying to increase epistemic certainty regarding the past. For forecasting to be possible, however, there must be a past and a future, since there is something there that we are trying to increase our certainty about, which must in some sense already exist.
The level of certainty may be highest in close proximity to the present, but the usefulness of forecasts increases in the other direction. A forecast stating that I will still be typing in my laptop in the next second embodies very little knowledge, while one accurately capturing the state of the world a decade out would have a large knowledge quotient. Early ACE-era Good Judgment forecasts were mostly in the timeframe of less than a year or two out. This year, however, there was an academic tournament called Persuasion, where we forecasted on much longer timeframes. Further research is needed to determine if we can find an “epistemic sweet spot” where the product of forecasting ability and usefulness of the forecast – is optimized. There is also a need to taxonomize different types of knowledge in terms of its differing forecastability, opening up for a whole field of “uncertainty studies”.
We should also note that uncertainty seems anecdotally to be on an upward trajectory. This is hard to measure quantitatively, but one attempt – the World Uncertainty Index – shows one measure of uncertainty over the past decades steadily increasing. Since we can assume that all change causes increased uncertainty, there should have been less uncertainty before the industrial revolution, given that the pace of change, by any objective measure, was just slower. Change is largely driven by our technologies, and since technology is combinatory, where the number of permutations constantly increase, so should change, and thereby uncertainty.
With this increased uncertainty, it would therefore be beneficial with greater adoption of Epistemism for decision-making. Epistemism makes decision making simple, or at least simpler, given that the option that most increases knowledge, or our ability to create knowledge by making forecasts, is always preferable. As is outlined here, Epistemism is a longtermist philosophy. As opposed to some other longtermist philosophies, however, Epistemism may be less susceptible to fanaticism, since the creation of the knowledge optionality is in the present and has a natural ceiling.
Similarly, it would be beneficial if we adapted our language to better incorporate uncertainty. Epistemism is compatible with philosophies that hold that communication is to some extent possible, even if there of course is information loss in the process. There are many thinkers such as Wittgenstein who have pointed out the inadequacies of language. But similarly to metaphysics, as long as language is able to communicate knowledge to any small degree, Epistemism holds. Even if language is deeply flawed and most information gets lost in communication, some level of knowledge should still be able to be transmitted. It is perhaps true that as C.K. Ogden noted, much of the world’s troubles can be ascribed to the illusion that a thing exists just because we have a word for it. But this should not remove our credence in the epistemic value of all words. And it might be essential to be able to invent new words in order to speculate about their existence prior to potentially bringing them into being. But it would be preferable to integrate levels of uncertainty, and correspondingly, levels of forecasting, into our communication. Scott Alexander does this very well in Astral Codex Ten, where he leads with the level of epistemic uncertainty of his essays. Superforecasting does this well, with its focus on always arriving at a probabilistic forecast with a precise number. A lot of knowledge is compressed into a single number – its level of precision, its distance from the end points of 0 and 100, its distance from the midpoint of complete uncertainty, etc.
Given the need for knowledge in the world, the adoption of Epistemism would also be a useful in the world since it is a very egalitarian philosophy. Holding that the only thing that matters is knowledge potential, the ability to create knowledge through forecasting, provides the grounds for a neutral assessment. In fact, Epistemism is completely species-neutral, and would value contributions to forecasting and knowledge creation equally whether they come from machines (or animals/aliens) or humans.
Lastly, for this post, we should note that Epistemism is a philosophy that is inherently optimistic about the future. Given the belief that knowledge can be pursued and can be increased, there is an inherent belief that the future will be better. Further, the more knowledge we gain, the better we forecast, and the better that future would be. So this argues for constant experimentation, and constantly optimizing for learning new things.