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  • Author or Editor: Sreeja Nair x
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A critical challenge policy-makers deal with in responding to problems concerns gaps and reliability issues with respect to the information they are using as well as the difficulties and risks associated with accurately anticipating the future. Failing to correctly identify the bounds and range of these uncertainties and assuming a greater level of certainty in the short-term than may exist in the long – ‘policy myopia’ – is a major cause of policy failure. This paper reviews the literature on uncertainty and its implications for policy-makers, especially aspects of policy adaptation and learning which can help avoid myopic responses.

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This chapter introduces the idea of ‘policy myopia’ as a pressing source of failure in policy making and explores the possibility of developing policies that learn to help mitigate its impacts. It notes that while the problem of bounded rationality and short-term uncertainty is widely acknowledged as the central existential condition for all policy making, the long-term problem of an uncertain, and sometimes unknowable, future is rarely acknowledged. As uncertainty deepens, so too does the probability of policy failure. In these circumstances, actors need to design policies with flexibility and adaptation built in. Where policy solutions are robust over a range of possible scenarios and over time, one can say policies have learning capacity organised into them. Yet, in cases of radical uncertainty, learning may not be possible (or indeed preferable) at all. This reminder of the limits of learning is important. Updating one's belief systems assumes that a certain amount of knowledge exists in the first place.

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