In the remainder of this book, then, I suppose that a theory of ideal justice confronts a moderately rugged landscape. More specifically I assume there are a number of optima with significant basins of attraction—so that in a significant proportion of the option space there are gradients to be climbed. Thus, also, a significant proportion of the option space is correlated within itself; within a certain significant space, the justice of a social world is correlated with the justice of other near social worlds. However, we must suppose that the landscape is sufficiently rugged such that the Orientation Condition is well grounded: all the high optima (which would include the ideal) are not closely related to each other, so we really do need to locate the ideal before we can arrive at confident all-things-considered recommendations about which social worlds we should move to.
3 THE NEIGHBORHOOD CONSTRAINT AND THE IDEAL
3.1 Rawls’s Idea of a Neighborhood
In a seldom-noticed discussion responding to Derek Parfit’s objection to the difference principle, Rawls advances a conception of alternative social worlds in a “neighborhood.” Parfit’s objection is based on the example in figure 2-5.63 The difference principle selects distribution (3) because the least well-off do best. But Rawls claims that a justification of the difference principle is that the shares of the better-off are not gained at the expense of the least well-off. As Rawls stresses in his later work, the difference principle expresses reciprocity, a commitment of the better-off not to gain at the expense of those who are already less well-off. Yet we see that under distribution (2) the Indians do better than they do under (3), so it would seem that the gains for British under distribution (3) do after all come at the expense of the Indians, who “lose” 5 units.
Rawls’s reply is multifaceted. He insists that the difference principle does not refer to rigid designators such as “Indians” and “British” but to whomever the least well-off class might consist. However, he continues on:
Ignoring the matter of names for a moment, consider what can be said to the Indians in favor of (3). Accepting the conditions of the example, we cannot say that the Indians would do no better under any alternative arrangement. Rather, we say that, in the neighborhood of (3), there is no alternative arrangement that by making the British worse off could make the Indians better off. The inequality in (3) is justified because in that neighborhood the advantages to the British do contribute to the advantages of the Indians. The conditions of the Indians’ being as well off as they are (in that neighborhood) is that the British are better off.
Figure 2-5. A “counterexample” to the difference principle
This reply depends, as does the difference principle itself, on their being a rough continuum of basic structures, each very close (practically speaking) to some others in the aspects along which these structures are varied as available systems of social cooperation. (Those close to one another are in the same neighborhood). The main question is not (3) against (2), but (3) against (1). If the Indians ask why there are inequalities at all, the reply focuses on (3) in relation to reasonably close and available alternatives in the neighborhood. It is in this neighborhood that reciprocity is thought to hold.64
In explaining the idea of a neighborhood Rawls explicitly relies on a distance metric—“a rough continuum of basic structures, each very close (practically speaking) to some others in the aspects along which these structures are varied as available systems of social cooperation.” We might take the idea of being “close (practically speaking)” as simply about feasibility, but that interpretation would suggest that distribution (2) is irrelevant simply because it is infeasible, but Rawls never defends that claim (also, the idea of “close and available alternatives in the neighborhood” would be redundant if the neighborhood is simply defined by the available alternatives). Rawls’s basic claim is that there is a continuum of structures that are close in terms of the variance in their structure, but not necessarily from the perspective of their inherent justice. A natural interpretation of this idea, given the analysis thus far, is that there is a continuum of basic structures (the x-axis in figure 2-4), on which some are close to others, but we should not confuse this type of practical closeness with close in terms of justice scores (as shown by the very different y-axis scores of many close x-axis worlds). This makes perfect sense if we model the problem of justice in terms of moderately rugged landscapes, in which it does not follow that those that are close in terms of basic structures are necessarily also close in terms of justice.
Rawls thus paints an especially interesting picture: there is a continuum of basic structures, somewhere on this continuum we can locate an ideal that orients our quest for justice, but at any given time, the recommendations of the principles of justice are confined to a neighborhood within this continuum. I believe that this idea of a neighborhood of related social worlds is fundamental to political philosophy and to the evaluation of ideal theory, as I shall now endeavor to show.
3.2 The Social Worlds We Know Best
The initial presentation of an evaluative perspective Σ (§II.1.1) and an array such as figure 2-4 presupposed that evaluative perspective Σ yields an evaluation of all social worlds in the domain {X}, which according the Social Realizations Condition must include the ideal. The discussion of the Maximal Precision Requirement (§II.2.2) introduced another variable: the precision (and accuracy) of Σ’s judgment for any social world. Now on what we might call the Comprehensive Knowledge Assumption, whatever level of precision (and accuracy) Σ’s judgments possess is, roughly, invariant across all social worlds. Given any two social worlds (i and m) in the domain {X}, Σ’s judgments are (again, approximately) equally precise and accurate. But this simply cannot be right: our current social world is in the domain, and the evidential basis for judgments about the justice of the world we actually live in must be greater than judgments about merely possible worlds. For all nonexistent social worlds, we must rely for the most part (but see below) on predictive models to judge their social realizations; for our current world we can employ our best models to understand it, but we also have masses of direct evidence as to its realization. Indeed, our models are often developed from our current data, or at least with the constraint that they must cohere with what we know about our social world (think how important reports of the Factory Commission were to Marx’s theory in Capital).65
I realize that some deny this: there is a persistent strain in political philosophy that the ideal world would be organized along straightforward and simple lines. In his utopian novel Looking Backward Edward Bellamy described “a social order at once so simple and logical that it seems but the triumph of common sense.”66 Or, as Cohen seems to suggest, the motivational structure underlying a socialist economy in an advanced technological society can be crystallized in the ethos of a friendly camping trip.67 The supposition that the social institutions of the ideal will be simple and predictable is by no means restricted to socialist utopias—anarcho-capitalists seem to truly believe that actual societies will function as predicted by relatively straightforward microeconomics and the theory of the firm.68 We must not confuse simple models of the ideal (they are extraordinarily easy to create) with plausible predictions of the social realizations of a set of institutions for large-scale societies. Those confident that they know the “simple and logical” workings of ideal mass societies should, perhaps, reflect on the surprising intractability of social norms in small-scale societies in the face of concerted, well thought out, and well-funded interventions by the United Nations and other agencies. While there have been some notable and important successes in altering specific norms such as female genital cutting in some locations, in other places these interventions have not met with success, and sometimes initial success has faded as targeted norms were readopted.69 And this concerns a few specific norms in villages whose population is measured in the thousands. And as we shall see in more detail presently, actual socialist utopian experiments were unable to achieve their sought-after social rea
lizations (§II.4.1). When we realize new social worlds we are always struck by features we did not quite anticipate; important causal relations emerge that even our best models did not include.70 This is not to dismiss the pursuit of ideals; it is, however, to dismiss the claim that we can be confident about a social realization of a far-off ideal because it will be such a simple and predictable world. And even if we granted this outlandish claim, it surely could not be said that all the worlds on the way to the ideal are likewise simple and knowable (unlike the world we actually live in, which is far less knowable because we have so much more information about it?). Moreover if we granted all this—if it were simple worlds all the way from here to utopia—then we would be facing a simple, not a complex, optimization problem, and the ideal would not be necessary (§II.2.3). It is the very complexity of the interactions of justice-relevant institutions that is the most plausible basis of the rugged optimization problem, which, in turn, requires orientation by an ideal.
I take it as a given, then, that the precision and accuracy of judgments of justice of our current social world are greater than yet-to-be realized worlds, most especially ones that are far off. We also know that in the sort of moderately rugged landscapes presupposed by ideal theory, the justice value (as measured on the y-axis) of a world is correlated with its x-axis (i.e., similar) neighbors; simply knowing the justice of world i is informative about the justice of worlds plus or minus some x-axis distance ∂ (the smoother the landscape, the larger ∂, §II.2.3). Take, then, our current social world, j, and consider social worlds j ± distance ∂ (we also assume that the terrain is moderately rugged, so that ∂ is considerably less than the range within the domain {X})—the entire landscape is not correlated throughout as it is on the climbing model.71 For these possible social worlds, not only do we have modeling information as to the extent they would realize justice, but we have correlation information based on our great knowledge of our present world, j; the justice of our present world’s neighbors (as determined by SO, the similarity ordering) is correlated with the justice of our present world, j. Only in high-dimensional landscapes is this not the case (§II.2.2). So we have a larger evidentiary base for conclusions about the justice of j ± ∂ than for social worlds a greater distance than ∂ from j. “Experience and information,” Xueguang Zhou concludes, “gained in the past decrease the cost of learning in the neighborhood of the familiar area and put a higher price tag on explorations into unfamiliar territory.”72 Again, this provides powerful evidence that our judgments about the social worlds j ± ∂ have greater precision and accuracy than those outside our neighborhood, where we do not possess correlation information. In a moderately rugged landscape the area outside our neighborhood (i.e., j ± ∂) almost surely encompasses many social worlds.
Another consideration should lead us to reject the Comprehensive Knowledge Assumption. As I have said, our models of social worlds are attuned to our current world, in which they have been developed. Given this, a natural way to predict other social worlds is to predict the nature of the most proximate social world, which, by the very nature of a perspective, is the world with the relevant features most similar to our current world (§II.1.2). A model attuned to our j world will have to be only minimally adjusted when applied to an almost identical world; its reliability in worlds j ± 1 thus should not be terribly far from j. Having done this, we can then apply the revised model to worlds that are j ± 2, and so on, each time adjusting for some slightly different features of the new social world. Now despite its obvious attractions, this procedure leads to rather quickly dropping reliabilities as we move away from j. Again, it needs to be stressed that for ideal theory to be a plausible alternative to Sen’s climbing model, determining the justice of social worlds must be a modestly complex problem insofar as the relevant dimensions of evaluation are interconnected.73 This means, though, that as the mapping function understands them, the justice of different features are coupled; varying one will result in changes in the way other features contribute to the overall justice score.
Our models of such complex, interconnected, systems are characterized by error inflation.74 An error in predicting the workings of one feature will spread to errors in predicting the justice-relevant workings of interconnected features, magnifying the original error. As this new erroneous model is used as the basis for understanding yet further social worlds, the magnified errors become part of the new model, which is then itself subject to the same dynamic. In complex systems small errors in predicting one variable at an early application of the model lead to drastic errors in predicting the overall system state a rather small number of iterations out (depending on the complexity—ruggedness—of the system), as errors in the initial estimate of one variable both propagate to other variables and become magnified in subsequent periods (i.e., further-out social worlds). The quintessential example of this is weather forecasting. Our predictive models of weather systems ten days out are drastically inferior to our models predicting tomorrow’s weather (which in turn is much inferior to looking outside and observing the current weather). It is crucial to stress that this problem of error inflation is part and parcel of the very complex interdependencies that create rugged optimization landscapes, and only if we have such a rugged landscape is there good reason to move beyond Sen’s climbing model (§II.2.3). So the problem of error inflation is intrinsic to the ideal theorizing project. The only way to avoid it is to have a simple, aggregative view of the features related to justice, but then Sen is entirely right—in such smooth optimization landscapes the ideal is otiose.
3.3 The Neighborhood Constraint and the Ideal
We are now in a better position to understand the importance of a neighborhood of basic social structures or, as I have been saying, of social worlds. A neighborhood delimits a set of nearby social worlds characterized by relatively similar justice-relevant social structures. In this rough continuum of social worlds some are in the neighborhood of our own social world (and many are not); our understanding of the justice of alternative social worlds in the neighborhood of our own social world is far deeper than outside it. This neighborhood will include those social worlds whose justice is significantly correlated with that of our current world; if our predictive models are powerful, it may extend somewhat further. For simplicity, I assume that there is a clear boundary between the worlds that are in our neighborhood and those that are too dissimilar for us to make as firm judgments about, though of course this is an idealization (§I.3.3), which we will relax (§II.4.2).
Figure 2-6 incorporates the idea of a neighborhood into a rugged landscape model, with some indication in the shaded areas that our knowledge fades (and does not abruptly halt) when we leave our neighborhood, as our models become increasingly error prone. Here, our current world is j, our neighborhood runs from b to d, and b is the “local optimum” (LO)—the most just alternative in our neighborhood. We can immediately see the difficulty of pursuit of the ideal given the Neighborhood Constraint. While moving from j to b takes us to a more just social world, it also moves us further away from the global optimum (GO). So we face a dilemma. On the one hand, our understanding of the alternatives to our present world is limited. As we leave our neighborhood the precision and accuracy of our estimations of the justice of social worlds drops off sharply: we must rely solely on our predictive models (since outside our neighborhood the justice of other social worlds is not correlated with our present justice), and the reliability of these models rapidly decreases as we move to increasingly unfamiliar worlds. In contrast, within our neighborhood there may be relatively obvious local optima, about which our judgments are reasonably reliable, and we are in a position to make well-grounded recommendations that moves to them will increase justice.75 And this is manifestly important. To make a reasonable recommendation that a society or polity should work toward creating a new social world, a theory must have reasonable grounds for predicting what that world would be like.76 On the other hand, ideal theory is intended to orien
t our quest for justice, but if the ideal (i.e., global optimum) lies outside our neighborhood, we do not know a great deal about it. To be sure, we may have some suspicion as to the direction in which the ideal lies, but we must remember that judgments outside of our neighborhood are not very reliable; if the ideal is not near (and almost all ideal theorists suppose it is not)77 we are apt to have only rather vague ideas as to how it will work. But then an ideal theory is faced with what I shall call
The Choice: In cases where there is a clear optimum within our neighborhood that requires movement away from our understanding of the ideal, we often must choose between relatively certain (perhaps large) local improvements in justice and pursuit of a considerably less certain ideal, which would yield optimal justice.
Figure 2-6. An idealized neighborhood
It is important to stress that The Choice is not an outlying hard case for the ideal theorist; it is precisely the sort of situation with which ideal theory is designed to deal. If local improvements never led us away from the ideal, Sen’s climbing model would be adequate; essentially, all we would need to do is to move toward the global optimum. But as Simmons’s reply to Sen (§I.1.3) makes clear, the Orientation Condition—and so ideal theory—gets traction when local climbing can move us away from the ideal. Nevertheless, though this is manifest, implicit in writings of some ideal theorists is that we never face a significant instance of The Choice. Recall Rawls’s conviction that ideal justice provides guidance for thinking about justice in our nonideal societies, assisting to “clarify difficult cases of how to deal with existing injustices” and to orient the “goal of reform,” helping us to see “which wrongs are more grievous and hence more urgent to correct” (§I.1.2). But implicit in The Choice is that to pursue the goal of the ideal we must forego some obvious increases in justice in our neighborhood; rather than the ideal informing us about urgent matters that we must correct, it must sometimes encourage us to turn our backs on some increases in justice—to recommend that we do not move in that direction, as it will take us further from the ideal. This is inherent in the very idea of an ideal theory that is distinct from Sen’s climbing model. If alleviating the most pressing problems of justice was always part of moving toward the ideal, we would not need the Orientation Condition, because we would not require the ideal to orient our search for justice: the ordering of social states by the Social Realizations Condition would suffice. Our model allows us to see that the ideal theorist cannot have it both ways: that we must orient ourselves by the ideal yet never forgo local opportunities for significant, perhaps great, increases in justice. It is inherent in the project of ideal theory that we must confront The Choice.
The Tyranny of the Ideal Page 11