As effective as artificial intelligence can be at solving some problems, AI will be hard pressed to solve some sorts of problems, as much as some have hoped “experts” in the past could “solve” difficult social, economic or political problems involving conflicts between winners and losers.
The term wicked problem has become a standard way for policy analysts to describe a social issue whose solution is inherently elusive. By definition, wicked problems are difficult to define and even harder to solve because aspects of a problem are interconnected with others that also must be solved.
Also, causes and effects of the problem can be complex and not fully understood. Also, potential solutions have externalities, when the solution to one problem creates unintended consequences that become new problems themselves. These consequences can be positive or negative, but they are external to the original problem's intended solution.
Especially in any area of public policy, value judgments also must be made, as stakeholders have different interests that often conflict. As any proposed solution inevitably involves winners and losers, AI can only suggest solutions. Political, social and economic interests will affect whether any proposed solution can be implemented.
Classic examples of wicked problems include climate change, substance abuse, international relations, health care systems, education systems, and economic performance.
For wicked problems, data may be scarce, unreliable, or biased, while causal relationships might be quite difficult to pinpoint.
Correlation, as the old adage goes, is not necessarily causation.
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