How Should We Really Think About the Future?
AI-generated, human-reviewed.
The way we talk and plan for the future is often deeply flawed—from overreliance on sci-fi tropes to a misplaced faith in statistics. On Intelligent Machines (IM 837), designer and futures expert Nick Foster explains why we must cultivate more robust, multi-layered ways of thinking about what's coming next.
Drawing from Foster’s new book Could, Should, Might, Don’t: How We Think About The Future, the Intelligent Machines panel dives into actionable frameworks for individuals, technologists, and businesses navigating uncertainty—especially across artificial intelligence, design, and technology strategy.
Nick Foster, whose career spans design roles at leading tech companies like Google and Sony, argues that most people and organizations rely on narrow or oversimplified ways to imagine the future. Instead of gravitating toward predictions or mimicking sci-fi, Foster proposes that every forward-looking discussion falls into one of four mindsets:
Could: The realm of imagination and possibility, often dominated by sci-fi and speculative ideas. It's about what could exist, but not necessarily should.
Should: The prescriptive lens—what ought to be built, grounded in ethics and aspiration. This is where “should we do this?” becomes central.
Might: The domain of scenarios and probabilities, familiar to strategic planners and data analysts. Here, the focus is on what might plausibly happen, often using statistics or scenario planning.
Don’t: The cautionary approach—what futures must be avoided or resisted, raising issues around risk, unintended consequences, and ethical red lines.
On Intelligent Machines, Foster cautions that individuals and companies often default to just one of these, missing crucial nuance and the full range of possible futures.
Foster and the hosts critique the overreliance on science fiction as a roadmap for real-world innovation. According to Foster, leaders and engineers (especially in Silicon Valley) frequently use sci-fi “as a substitution for real imagination.” This results in fixating on familiar images—flying cars, Jetsons gadgets, or terms from fiction—to the detriment of genuine creative inquiry.
Similarly, the “numeric fiction” of data projections—charts, forecasts, dotted lines—can be dangerously persuasive. Foster warns that, after a certain point, projecting numbers into the future stops being science and becomes story; these projections can mislead both organizations and the public.
Foster introduces the idea of the “future mundane”—a future that feels familiar, lived-in, and evolutionary rather than wholly disruptive. He notes that while technological, social, or cultural changes can be significant, most people will experience the future as a slightly altered version of the present. This “normalization” process means that even the biggest innovations, like self-driving cars, quickly become ordinary.
On Intelligent Machines, Foster encourages listeners to consider how the future will blend new technologies with ongoing routines, habits, and objects from the past. The advice? Don’t ignore small shifts or think of the future as a distant land populated by “other people”—it will be your lived reality too.
Foster argues that major tech companies—and anyone responsible for long-term planning—should aim for breadth across all four mindsets. A robust approach requires not just excitement for what’s possible or probable, but also an honest look at what should and shouldn’t be done.
Businesses and teams often get stuck in one mode (e.g., “could” for moonshots or “might” for scenario analysis), which leads to blind spots and tunnel vision. Foster challenges leaders to deliberately blend imaginative exploration, ethical reasoning, rigorous scenario planning, and clear-eyed risk assessment.
Most predictions about the future are limited by unexamined assumptions.
Four common mindsets shape our thinking about the future: could (imagination), should (ethics/prescription), might (probabilities/scenarios), and don’t (caution/risks).
Relying only on data projections (“numeric fiction”) or sci-fi references limits true innovation.
The “future mundane” concept reminds us: profound changes often arrive gradually and feel familiar.
Tech companies and individuals should balance all four approaches when planning and designing for the future.
Better futures emerge from critical, multi-layered thinking—not from pursuing a single predictive method or hoping for a sci-fi world.
According to Nick Foster on Intelligent Machines, preparing for the future—whether in AI, technology, or daily life—means embracing uncertainty, challenging your habitual thought patterns, and refusing to settle for easy answers. The most successful leaders, teams, and individuals will practice open-ended, multi-modal thinking: imagining what’s possible, questioning what’s right, exploring what’s likely, and warning about what to avoid.
Ready to reimagine how you approach tomorrow? Listen to the full conversation and explore the ideas from Could, Should, Might, Don’t for a richer, more realistic way to think about what’s next.
Subscribe to Intelligent Machines.
