Who really killed John F. Kennedy? How many whales inhabit the oceans? How will climate change? Does God exist? Strive as we might, answers to such questions cannot be known with certitude. Uncertainty means that more than one outcome is consistent with our expectations. Expectations are a result of judgement, sometimes based on technical mistakes and interpretive errors, and shaped by values and interests. Because uncertainty is a characteristic of every important decision, it is no surprise that society looks to science and technology to help clarify our expectations in ways that lead to desired outcomes.

Decision-making is forward-looking; consequently, decision-makers in governments and other organizations have traditionally looked to science and technology to quantify and if possible reduce uncertainties about the future. In many cases, particularly those associated with closed systems — or systems that can be treated as closed — understanding uncertainty is a straightforward technical exercise: probabilities in a card game, error analysis in engineering and manufacturing, or the actuarial science underlying many forms of insurance, for example. But in many other circumstances, systems are not closed, and understanding uncertainty in an open system is considerably more challenging. Many scientists have taken on the challenge of understanding such open systems — global climate, genetic engineering, and so on. And the process of securing the considerable public resources to pursue this challenge often results in their explicit promise to “understand and reduce uncertainties”.

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