So It’s the Future Now, Right? (Right?)

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Predicting the future may be impossible, but that doesn’t stop us from wanting us to try. Humans have a propensity for wanting to believe in the shamanic foresight of witches, Tarot cards, seers, oracles and prophets.

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Given that this is the time for forecasts, could we learn from lessons past to be better prepared for what’s next?

(Spoiler, we are no nearer to perfecting precognition precisely because of the presence of us humans in the machine.)

Also, as Amanda Rees, a historian of science at the University of York, says in an article for Wired, “The clearest lesson from the history of the future is that knowing the future isn’t necessarily very useful.”

Rees argues, “There is an assumption that the more scientific the approach to predictions, the more accurate forecasts will be. But this belief causes more problems than it solves, not least because it often either ignores or excludes the lived diversity of human experience.”

People have long tried to find out more about the shape of things to come. Strategies of divination such as astrology, palmistry, numerology, and Tarot depend on the practitioner’s mastery of a complex theoretical rule-based system, their ability to interpret it, and our propensity to take it at face value.

Understanding previous events as indicators of what’s to come has allowed some forecasters to treat human history as a series of patterns, where clear cycles can be identified in the past and can therefore be expected to recur in the future. The dialectic materialism of Karl Marx and Frederick Engels is a classic example (yet to be proved correct despite the best efforts of certain political groups to fast-forward historical change).

Another set of forecasters argue that the pace and scope of techno-economic innovation are creating a future that will be qualitatively different from past and present.

Adherents of this approach search not for patterns, but for emergent variables from which futures can be extrapolated. “So rather than predicting one definitive future, it becomes easier to model a set of possibilities that become more or less likely, depending on the choices that are made.”

Examples of this would include war games (such as the Desert Crossing 1999 games played by US Central Command in relation to Saddam Hussein’s Iraq) and theoreticians like Alvin Toffler who have extrapolated from developments in IT, cloning and AI to explore a range of potential desirable, dangerous, or even post-human futures.

“But if predictions based on past experience have limited capacity to anticipate the unforeseen, extrapolations from techno-scientific innovations have a distressing capacity to be deterministic,” says Rees. “Ultimately, neither approach is necessarily more useful than the other, and that’s because they both share the same fatal flaw — the people framing them.”

Could new advanced technologies built on super-powered computer processors and AI algorithms simulate the future any better?

Rees thinks not, “Despite the promise of more accurate and intelligent technology, there is little reason to think the increased deployment of AI in forecasting will make prognostication any more useful than it has been throughout human history.”

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.”

Rather than depending on technological advances, other forecasters have turned to the strategy of crowdsourcing predictions of the future. Assembling a panel of experts to discuss a given topic, the thinking goes, is likely to be more accurate than individual prognostication.

“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.”

COVID-19 is a case in point. We are all by now familiar with news stories featuring the modelling that scientists are making for the spread of the disease and its likely effect on various populations or health systems. Outcomes from best to worst case scenarios are modelled with politicians using this as one factor to weigh in their decision making (others being economic impact and social libertarian policy).

Whatever the approach, and however sophisticated the tools, the trouble with predictions is their proximity to power, contends Rees.

“Throughout history, futures have tended to be made by white, well-connected, cis-male people. This homogeneity has had the result of limiting the framing of the future, and, as a result, the actions then taken to shape it.”

Her prescription is to be humble in the face of what we don’t know; to be sensible and merge newer techniques with a slightly older model of forecasting — one that combines scientific expertise with artistic interpretation.

“It would perhaps be more helpful to think in terms of diagnosis, rather than prediction, when it comes to imagining — or improving — future human histories.”

Perhaps this is what writer HG Wells meant in the 1930s when he called for “professors of forethought,” rather than history, to explore the implications of the development of new inventions and devices.