Making Decisions When the Future’s Unclear

Decision-making under uncertainty is all about how people - consumers, businesses, investors - make choices when they don’t know what the future holds. It’s a key topic in behavioral economics, finance, and decision theory.

What Do We Mean by "Uncertainty"?

Uncertainty kicks in when you can’t predict the outcome of a decision - and you can’t even assign a solid probability to what might happen. This usually comes down to two things:

• You’re missing critical information
• The situation is too complex or unpredictable

Real-world example. A farmer has to choose between planting corn or wheat. They don’t know what the weather will be like, so they can’t estimate the risk of drought. That’s uncertainty. Or think of tech startups entering brand-new markets. There’s no historical data - just educated guesses. Still, some investors will take the leap, especially if they’re optimistic and cash-rich.

Uncertainty vs. Risk: What’s the Difference?

It’s easy to mix them up, but they’re not the same:

• Risk: You know the possible outcomes and can attach probabilities to them (think gambling or insurance).
• Uncertainty: You don’t have enough info to assign any meaningful probabilities (think disruptive innovation or global crises).

In traditional economics, we often try to model decisions as if they were based on risk - even when they’re not. We fill in the gaps with assumptions, experience, or stats to make the problem "workable."

Example. A business owner launches a product in an unfamiliar market. There’s no data to fall back on. Still, they build a few scenarios, assign rough probabilities, and proceed. But here’s the catch: people tend to underestimate uncertainty and overestimate how well they can predict outcomes - especially in the stock market.

How Do We Decide When We’re Unsure?

Even without clear odds, economics gives us tools to think through uncertain choices:

• Expected Utility: You weigh the possible outcomes and go with the one that gives you the highest average benefit.
• Game Theory: Useful when others are making decisions too, and your outcomes depend on what they do. More broadly, game theory looks at how people’s choices are interconnected - how your decision depends on what others do, and how theirs depends on you. This holds true whether or not there’s uncertainty about the others’ actions. Some games are played with perfect information, where everyone knows exactly what moves have already been made. Others involve imperfect information, where certain details - like a player’s past decisions or private knowledge - are hidden from view. Either way,
• Behavioral Models: Like Prospect Theory, which looks at how people often fear losses more than they value gains.

Example. Say an investor has two options: a safe 2% return, or a riskier one with a chance at 6% - but also a 30% risk of loss. What they choose depends on their personal comfort with risk. According to Prospect Theory, many people would still pick the safe 2%, even if the riskier option has a higher expected return. Sound familiar? Most of us have said “better safe than sorry” at least once.

Why Information Matters

Information is powerful - because it helps reduce uncertainty.

That’s why companies (and individuals) are willing to pay for it - whether it’s market research, expert advice, or reliable data. Better information often means better decisions.

Example. A company planning to expand into a new country might pay for a market study. It’s pricey, sure - but it might save them from a failed investment. Similarly, online shoppers often read reviews to avoid making a bad purchase. Just hope the reviews weren’t all written by the same person with 10 different accounts…

Time Makes It Trickier

When a decision affects the future, uncertainty grows.

You have to consider not just what could happen, but when. That’s where discounting comes in - we tend to value immediate benefits more than future ones.

Example. Someone deciding whether to go to college faces big upfront costs. The payoff? Years away - and tied to a job market that might change completely. Or consider a family buying a house with a 30-year mortgage. They have to think about future income, inflation, interest rates... all of which are uncertain.

In the Real World, Decisions Are Subjective

Uncertainty is everywhere in real-life economics.

Even though models try to turn it into something neat and quantifiable, real decisions rely heavily on intuition, judgment, and personal estimates.

If we want to understand how people actually make choices, we need to look at how they react to unknowns - and how much they trust what they know.

The best economic models combine data and probabilities with psychological insights and real human expectations.

And maybe, just maybe, leave room for surprises - because if there’s one rule about uncertainty, it’s that something will almost always go off script.