Strategic Foresight in the Age of AI & Magical Overthinking

What’s the role of leadership in a world with AIs and predictive models? What might have been fantasy even ten years ago when I was CDO of Los Angeles — Turing-tested AIs — are now commonplace, and hard questions like “How should I redesign my city?” can now be answered in a chatbot. (I know, I’ve tried.) At the same time, we see the shortcomings of these tools every day, ranging from the hilarious to the dangerous. So, what is one to do? I think reframing the questions from prediction to planning is needed, or to borrow a phrase from X’s thoughtful piece, from magical overthinking to strategic foresight.

This need for strategic foresight was highlighted both in a recent, sharp World Economic Forum article by Roger Spitz and Amanda Montell's entertaining timely book, "The Age of Magical Overthinking."

Written by the Chair of the Disruptive Futures Institute, the WEF article argues that traditional methods of prediction, which often rely on past data, aren't enough anymore. We’re in an era where changes are rapid and often unexpected, making old ways of planning less effective which cautioned, "Traditional predictive models, reliant on past data, are increasingly inadequate in our unpredictable world." For local governments, this should hit home, as they often don’t have historical data. So algorithmic or AI-based prediction is little more than patchwork guesswork. Governments that rely on historical data will be fundamentally incomplete and fail to adapt to new, unforeseen circumstances. Instead, governments should incorporate AI systems that are capable of scenario planning and simulating a range of future possibilities, thereby enhancing decision-making processes to be more adaptive and forward-thinking.

The question we should be asking is “What are all the things that could happen, and how could we prepare?"

Instead, what we are typically asking is, “What will happen, and what should we do?"

The latter is folly, and the former is indeed the work of governance: strategic planning and foresight.

As Spitz put it, “Foresight is preparation, not prediction… we can the build resilience to sustain even the most serious of outcomes.”

Montell’s book dovetails beautifully here, exploring how our personal and collective thought patterns can lead us astray if we're not careful. She dives into the world of 'magical overthinking' where our cognitive biases, supercharged by the digital information flood, often distort our perception of reality. She eloquently notes, "Our brains, bombarded by a ceaseless stream of data, tend to fall into patterns of magical overthinking, where we see connections and patterns where none exist." This insight struck a chord with me, underscoring the critical need for local governments to adopt more sophisticated decision-making frameworks that account for these biases. When integrating AI, governments should be wary of these biases, particularly in how data is interpreted and used by AI systems. Montell's exploration suggests the need for transparency in AI operations to prevent 'magical overthinking'—or over-reliance on AI without critical evaluation of its output. This transparency can help mitigate the risk of making decisions based on flawed or biased AI analyses.

For those of us working in the public sector, this insight is critical. It’s about more than just understanding the risks; it’s about preemptively crafting strategies that can adapt to whatever the future holds. This kind of foresight can reframe how a city plans, manages, and engages.

Put another way, if we are going to overthink ourselves or with AI, let’s do it in a productive way: planning for the future, not trying to predict it. And let’s build and leverage scenario planning tools that surface biases, our own or the technologies’, not hide them, so we can make better decisions together for what comes next.

N.B.: At Euna Solutions , we recognize the urgency of this transformation. Our tools, such as Euna Budget and Euna Grants , are designed to aid local governments in strategic forecasting and planning. These solutions facilitate scenario-based budgeting and efficient grant management, enabling governments to plan effectively for various potential futures and ensure that resources are aligned with both immediate needs and long-term objectives of the community.