Maximization is a Lofty Goal

Maximization is characteristic of the goals in capitalist economics.  Corporations are legally required to maximize profit, and according to the most extreme views of market economics, humans are supposed to be rational self-maximizers (Homo economicus) and the maximization of personal profit or utility is supposed to create the most efficient possible economy (efficient market hypothesis).  In general, sellers are expected to minimize cost and maximize profit in order to succeed.  On the surface, it sounds as if this minimization of cost should result in an efficient economy, but the other component, the maximization of profit, ensures this cannot happen.

The problem with the economy of rational self-maximizers is that rather than the hypothetical outcome of peak efficiency, we get lots of (ignoring externalized costs) efficient transactions at a scale so tremendous that the overall efficiency is lower.  Things that aren’t realistically that important, such as Starbucks and Apple, are made into mission-critical parts of the economy. The successes and failures of such enterprises have impacts completely disproportionate to their true importance.  They may minimize their personal costs, but the imperative to maximize profit means that the overall cost to the world, the resource intensity, is pulled up along with it.

By reducing our goal from maximum to just enough, we will reduce our overall resource intensity.  This could even have a profound enough effect to fulfill a larger proportion of demand (especially when combined with the shift from private property to community services).  Certainly there won’t be as much pushing product on people who really don’t want it.  There won’t be many emergency trips to get syrup or plastic cups in the absence of rational maximization.

Another issue that I have touched on before is that the maximization problem presented by the above-mentioned hypotheses can be reduced to a knapsack problem and is thus NP-complete.  In other words, the need to perform combinatorial optimization in order for the economy to be efficient ensures it will not be.  One thing that becomes clear when studying optimization is that generally, optimization problems can be efficiently solved only if the function or system being optimized is monotone or convex.

Constraint satisfaction problems (CSPs) may be a better method for economic decision-making.  Rather than maximizing sets of variables, we simply impose constraints on the range of values we would like the variables to take.  CSPs can be efficiently solved with restricted conditions, by relaxing the constraints or by reformulating them as a homomorphism problem.  It is already clear that the economy of the future will have to operate within ecological constraints.  If we must do so while also forcing a fragmented population to maximize profit and utility, we are much less likely to succeed at meeting our goals than if we are solving a CSP only.

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