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Key Futures Fallacies
Another week, another flurry of AI/LLM announcements. The just published AI Index Report from Stanford is an excellent primer if your head is spinning and you need a solid orientation as to what is going on. One thing is for sure – this train is not slowing down…
Read on to learn how to identify three critical future fallacies – and what to do about them.
Decode. Disrupt. Transform.
During a conversation about futures thinking – specifically: how to improve our ability to anticipate and envision futures – at SXSW last month, a friend reminded me of a smart paper published by the environmental social scientist Adam Dorr in 2017. The paper itself, unfortunately, sits in a paywalled journal (not exactly the way to democratize futures thinking Elsevier!), so I’ll offer a cognitive and economic shortcut here to a few ideas well worth exploring in your organizational and personal futures thinking and leadership.
Dorr’s aim was to help his readers think more “clearly and realistically about possible futures.” His approach was to identify and unpack three informal fallacies that are especially common in our long-term thinking and tend to render future visions (and as a consequence, some of our work toward realizing preferred futures) “simplistic, static, and short-sighted”.
The fallacies he described:
the linear projection fallacy
the ceteris paribus fallacy
the arrival fallacy
If you subscribe to this digest, chances are you’re already well acquainted with the linear projection fallacy. The future unfolds gradually and then suddenly, and our linear intuition of change struggles to comprehend the speed and magnitude of the “suddenly” part in advance. Gradually and then suddenly is the concise history of the radical increase in the price-performance of computation, and it describes the rapidly unfolding future of AI, the global energy transformation, and the emerging bio economy.
The ceteris paribus fallacy is one that we often stumble into while congratulating ourselves for overcoming the linear projection fallacy with a good dose of exponential thinking. This is the “all else equal” fallacy we commit when envisioning a future largely determined by the change in a singlevariable (be it technological, social, economic, etc) over time. It would be foolish to think, for example, that the only meaningful change to the urban landscape of a city in 2035 will be the mass electrification of transportation. In an increasingly complex world, visions of the future must assume that all else will NOT be equal. Vectors of change will be interdependent, and change itself will be systemic and ecological. By learning to see and think in systems and to reason through cascading implications of change, we can reduce our susceptibility to ceteris paribus thinking about the future.
Finally, the arrival fallacy concerns the tendency for future visions (especially as goals or destinations) to remain static or fixed rather than be understood as part of a continuously evolving process of transformation. Essentially, the further forward we’re looking in time, the more we should expect the vision to change in response to a changing environment, advancing knowledge, and an evolving set of tools, possibilities, emergent risks, etc. If you have a 10-year vision for the future of your organization, industry, or community, you should plan to regularly revisit and refine that vision as you learn more about the challenges and solutions you’ll encounter and discover along the way. The process, like the link between our present and our future, must be dynamic.
Awareness of these fallacies can help us recognize them in our own thinking and in the future visions, narratives, and strategies we encounter and consume. This core set from Dorr is a good place to start, and another (open access) paper by Ivana Milojević provides an overview of several more common futures fallacies to explore. (via Jeffrey)
What We Are Reading
🧫 These textiles were grown by bacteria Are “microbial textiles” the next big thing? Using sugar from plant waste along with microbes, scientists are creating fabric fibers stronger than Kevlar, which could eventually help replace both leather and synthetic fabric made from fossil fuels. Jane ⇢ Read
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📱 The Surprising Consequences of Every Other App Copying TikTok Convergence on the TikTok model for apps doesn’t necessarily imply a long-term win for TikTok. Jeffrey ⇢ Read
💯 With 100 Million Users In Just 2 Months, OpenAI’s ChatGPT Becomes The Fastest-Growing App In History Revisiting an article on the growth of ChatGPT shows that it’s not only the technology itself that’s different, but the adoption has been rapid! In contrast to other radically new technologies, people know about and want to use it. Julian ⇢ Read
💽 The Data Delusion We collect ever more data – but does it ultimately do us any good? Pascal ⇢ Read
The Thin Wisps of Tomorrow
🙋 Did Google Bard learn from ChatGPT?
🚌 Are We Focussing on the Wrong Things? The Need to Rethink Transportation.
💣 Are we heading toward an AI security apocalypse?
🙊 Deepfakes Are Coming For Your Voice
🩺 You might not entirely trust an AI with your medical diagnosis yet – despite ChatGPT passing the medical exam.
👗 Fashion photographer Tim Tedder combines traditional photography and AI to create stunning new works.
🚌 Not that this comes as a surprise: Driverless cars are clogging up our cities.
Not all technology is good: Golf has a tech problem – people are hitting too far! 🏌️
In Other Parts of the Radical Universe
🧨 Disrupt Disruption - The Podcast: We brought Christina Nesheva, CEO at Officinae Bio, back to talk about leadership. Listen now.
📕 Disrupt Disruption – The Book: Get your copy of our bestselling book and learn how to decode the future, disrupt your industry, and transform your business here.