Tag: philosophy

Scenario planning versus forecasting – how uncertain is the future in the age of AI?

Author: Anna Maria Schuller, CUSAP Secretary

In recent years, Artificial Intelligence has been silently making history and breaking records, to the point where we have grown desensitised to its incredible capacity. It is thus not surprising that when three AI LLMs placed in the top five at the Metaculus Cup, a competition for forecasters, with one even snagging the top spot, no one really took notice.

Forecasts are a tricky thing, difficult to assemble, highly dynamic, and reliant on vast amounts of data. Perhaps more importantly, they are incredibly lucrative. Corporations shell out ridiculous sums of money every day to glimpse into the proverbial crystal ball. But the crux of the forecast is the same as that of most AI-generated work; It relies exclusively on previously gathered information and draws sweeping assumptions. Whether stated explicitly or not, some degree of “business as usual” must be assumed to generate predictions of the future. 

Statistically, this is a safe-ish bet, likely to be somewhat correct, most of the time. But systems are at their most vulnerable when events do not follow predictions based on historical patterns. In the age of disruption, relying on forecasts alone is to risk them failing when we need them the most. 

Military strategists were among the first to understand this. They realised that they needed to consider many possible futures, including unlikely but potentially consequential events, to prepare their forces for unexpected attacks. One of the most influential pioneers of this method  wasHerman Kahn, whose book  “On Thermonuclear War”  (1960) helped establish scenario-based thinking as a systematic approach to anticipating radically different futures. 

In the early 1970s, Pierre Wack, then an analyst at Shell, recognised the potential of scenario planning in the field of corporate strategy. In the lead-up to the 1973 oil crisis, Mr. Wack was searching for ways to prepare for the unforeseeable, recognizing that the global economy was on a trajectory that was becoming more and more unpredictable every year.

At its core, scenario planning identifies certain pre-determined elements as well as critical uncertainties in the status quo, isolates trends and drivers that are likely to have a significant impact on future outcomes, and then builds theoretically plausible scenarios around these findings. The scenarios are intended to span a great range of possibility, and largely neglect probabilistic weightings of events, in order to challenge the participants to engage with a greater field of risk and opportunity. It is a new way of thinking: rather than committing to forecasts, the strategist is able to test their plans against all of these scenarios to prepare for uncertainty. Scholarly interest in the methodology has transformed it into a tool for explorative studies in the fields of climate change mitigation, public health and epidemiology, political science, and many others. While many institutes, think tanks, and corporations have developed their own detailed methods, they share a general workflow:

Initially, the surrounding information landscape must be mapped, to provide context for the subsequent analysis. This scoping is often guided by asking participants to identify significant “drivers of change” in the ecosystem, challenging them to think multidimensionally. Instead of focusing on the plausibility of each of these drivers, they are evaluated based on their potential impact and urgency. This method focuses the discussion on the factors with the potential to radically reshape the future, without dismissing seemingly  low-impact, low-urgency drivers . 

The next stage involves the construction of multiple logical chains of geopolitical, economic, and societal events that lead to specific, distinct versions of the future – the different “scenarios”. Methods vary in how this stage is approached: Some choose to work backwards from a certain outcome, while others choose to develop scenarios from a set of pre-defined drivers. Most commonly, three to six significantly different scenarios are developed to achieve sufficient variability to challenge the strategist, without creating convergent or redundant scenarios. 

As alluded to previously, the strength of the scenario-based approach lies not in the information it synthesizes, but in its ability to help organizations and clients adapt their thinking and consider many trajectories simultaneously. To achieve this, the scenarios need to be crafted into compelling and communicable narratives. This includes the careful design of a title, storyline, and selective detailing to make the scenario tangible, while ensuring that the emerging narrative is consistent with the audience’s understanding of the world.

As an association focused on protecting and scrutinizing the scientific method, we must consider the challenges of this methodology when utilized for scientific publications. Firstly, as the method deliberately deprioritises  probability and quantification to enable creativity, the process is largely conversational and interpretive. Scenarios are developed in dialogue with experts, clients, and other stakeholders, who are likely to favor considering scenarios they deem plausible or familiar, and cannot be expected to differentiate critical uncertainties and pre-determined elements without expert guidance. This places a remarkable amount of responsibility on the skill and ability of the administrator to direct discussion and remain in line with the underlying principles of the method. 

It is also apparent that considering many futures requires more effort than analyzing a single prediction. The more detailed the analysis, the more potent it may be, however, beyond a certain point, additional analytical depth may become counterproductive. Excessive detail may slow or paralyze the process, ultimately resulting in a collection of many attempted forecasts that do not carry sufficient narrative weight.

Finally, the most dangerous challenge lies in the communication of the resultant work. If the storytelling behind the scenario does not reach the strategic decision makers in a way that encourages them to expand their own foresight, the whole method falls flat. Scenarios are inherently not actionable: they are not trajectories to be followed or predictions to be acted upon. Rather, they represent potential futures against which strategies can be tested, but they must be crafted in a way that enables this. 

Scenario planning has had a good run. It has established itself as common practice in military strategy, shepherded Shell through multiple financial crises and turbulence in the oil and gas industry, became the standard in many C-suite strategy meetings, and finally found its way onto the desks and into the publications of numerous scholars. 

But with AI outperforming human predictions, is it possible that the sun is setting on scenario planning? Is AI likely to reduce the uncertainty in the world to an extent that makes scenario planning redundant? Philosophically, I am not equipped to answer this question. Intuitively, I want to conclude that there is too much future for anyone (or anything) to predict with sufficient precision to make it universally useful. Scenario planning, in my view, does not replace forecasting, but clearly puts its limitations into perspective. If you are prepared for even the improbable, you can weather almost any disruption. 

In scholarship, scenario planning is an exercise, a mental experiment, essentially a conversation starter. I have had the great pleasure of sitting in on a scenario planning workshop focused on geopolitics in the context of climate change and industrialization. While initially skeptical of the narrative nature of the method, I can now confirm that not only do the scenarios allow scholars to think more creatively – they instil a sense of optimism that I believe is much needed to face the oncoming uncertainty.

What a global warming denier from the early 00s can teach us about science communication

An opinion piece by Anna Maria Schuller (CUSAP Secretary), edited by Meira van Schaik (CUSAP Blog Chief Editor), Asmi Manudhane, and Scott McSorley

In July 2001, just a few months after the Bush administration distanced itself from the Kyoto Protocol, an American author and military strategist called Bruce Berkowitz published an opinion piece in the periodical Digest of the Stanford University Hoover Institution titled “The Pseudoscience of Global Warming”.

The core issue that prompted Mr. Berkowitz to write this piece appears to be a call for de-industrialisation from climate activists, which in his view dominated conversations around climate action at the time. Concerned for the American economy, he perceived a commitment to minimizing global warming as a threat to growth and prosperity – a trade off which he deemed unjustified owing to a lack of evidence for true environmental change. 

In the past 25 years, overwhelming amounts of research have been conducted that make a conversation on the reality of climate change redundant. This scepticism however has endured; climate action is still often painted as an adversary to economic growth, prosperity, and national security by its opponents (be they politicians, scholars, or other public figures). 

More recently, this same fear of a forced de-industrialization brought about by a commitment to international treaties led the Trump administration to disavow the Paris Agreement, the UNFCCC, as well as the Energy Charter. The importance of a strong industrial economy has become the stake against which the validity of scientific claims on the necessity of immediate climate action is weighed. In 2001, Mr. Berkowitz believed that existing findings were too flimsy to justify climate action, especially if it were to place American industries in jeopardy. Lamenting the climate discussion’s “technical and arcane” nature, he stated that it would be polemic to orient economic policy on the mitigation of global warming . 

Underlying the point made by Mr. Berkowitz is the call to wait for “better data” to emerge before committing to climate action. It implies that recent scientific progress strips previous, more deductive methods of their credibility. I particularly take issue with the notion that tested scientific methods of obtaining environmental data should be discounted in their validity simply because they are not as intuitive as holding a thermometer in the wind. This line of argumentation is anti-intellectualism masquerading as academic rigour. Our notion of “better data” is furthermore compromised by our own bias – what data will be “good enough” to kick us into gear? 

It can be said that research in the natural sciences does carry with it some inherent exclusivity by merit of being comprehensible only to those with a strong background in a specific field, and is in many cases virtually inaccessible to those without unless through the medium of high-quality scientific communication. Demanding optimal scientific procedure is not in itself problematic either. However, intentionally or not, it has been used to discredit climate scientists, who have (with the backing of the peer review process) been able to provide ample evidence of an emerging climate crisis since the 1970s. Claiming their predictions are “pseudoscience” was a grave misuse of the term in 2001, and is unthinkable in serious academic circles in 2026. 

Fundamentally, this is a straw man argument – placing the onus on climate scientists to not only provide conclusions but also justify their worthiness of our attention and consideration. Climate scientists are forced to almost discredit themselves through numerous disclaimers of uncertainty, while also convincing partisan politicians and the general layperson of the reality of the climate crisis. It is not difficult to see that requiring scientists to publish only data that is “good enough” will open a Pandora’s box of scientific communication challenges and accusations of dishonesty – so what are they to do?

It is not the purpose of this article to pass judgement on Mr. Berkowitz’s academic rigour. His opinion piece however gives us a glimpse into the pathways of thinking that climate policy sceptics follow to justify global climate inaction. It is a masterclass in undermining climate science by listing completely truthful statements in a manner that insinuates incredibility. He points to 1) complications in long-term data collection, 2) vast amounts of assumptions and 3) high computing power required to generate holistic atmospheric models, as aspects that should make us wary of the conclusions they produce. As if added scientific complexity obscures their purpose and strips them of validity. 

The accessibility of scientific methods and conclusions remains climate science’s holy grail, but the lack of a simple answer should not lead to distrust in the scientific community. Challenges to their integrity are particularly hard to navigate for climate scientists, as they are simultaneously asked by policy makers to continuously increase the complexity of their methods and conclusions in a never-ending flood of climate reports. How much responsibility do scientists carry to editorialize their findings to minimize negative impact (that in itself is impossible to predict), or should it be their prerogative to editorialize as little as possible to allow each actor to carry forward their own analysis free of previous bias? Can we bias-proof scientific communication around the topic in a way that does not erode the public’s faith in climate publications? 

This paradox remains unsolved, and has evolved only minimally since the early 2000s. Approaching both new and old findings in the field with curiosity, and trusting the scientists behind these findings, is our only recourse to retaining a productive conversation. Climate action is both fortunately and unfortunately everyone’s business; from layperson to expert, from economist to ecologist, from child to senior citizen; our definitions of “sustainable”, “long-term”, and most importantly – “worthwhile” – vary vastly. Trust in climate scientists does not equal blind faith. The complexity of the scientific method makes its accessibility dependent on the ability of science communication to capture both nuance and urgency implied in evidence. Effective science communication is at the nexus of the climate crisis, and will be the key to restoring confidence in this ever-evolving discipline.