Rational life plans and the stopping problem

Image: a poor solution to the stopping problem

In earlier posts I discussed the question of “rational plans of life” (linklinklinklink) and argued that standard theories of rational decision making under uncertainty don’t do well in this context. I argued instead that rationality in navigating and building a life is not analogous to remodeling your kitchen; instead, it involves provisional clarification of the goals and values that one embraces, and then a kind of step-by-step, self-critical direction-setting in the choices that one makes over time in ways that honor these values.

Brian Christian and Tom Griffiths’ Algorithms to Live By: The Computer Science of Human Decisions provides a very interesting additional perspective on this problem of living a life. The authors describe the algorithms that computer science has discovered to handle difficult choice problems, and they make an effort to both explain (generally) how the problem is solved formally and how it finds application in ordinary situations of human decision-making over an extended time — such as the challenging question of where to stop for a meal on a long road trip, or which candidate to hire as an executive assistant.

The key features of decision-making that drive much of their discussion are time and uncertainty. We often have to make decisions and choices among options where we do not know the qualities of the items on offer (restaurants to consider for a special meal, individuals who are prospective friends, who to hire for an important position), the likelihood of success of a given item, and where we often cannot return to a choice we’ve already rejected. (If we are driving between Youngstown and Buffalo there are only finitely many restaurants where we might stop for a meal; but once we’ve passed New Bangkok Restaurant at exit 50 on the interstate, we are unlikely to return when we haven’t found a better choice by exit 55.)

The stopping problem seems relevant to the problem of formulating a rational plan of life, since the stream of life events and choices in a person’s life is one-directional, and it is rare to be able to return to an option that was rejected at a prior moment. In hindsight — should I have gone to Harvard for graduate school, or would Cornell or Princeton have been a better choice? The question is literally pointless; it cannot be undone. Life, like history, proceeds in only one direction. Many life choices must be made before a full comparison of the quality of the options and the consequences of one choice or another can be fully known. And waiting until all options have been reviewed often means that the earlier options are no longer available — just like that Thai restaurant on the Ohio Turnpike at exit 50.

The algorithms that surround the stopping problem have a specific role in decision-making in ordinary life circumstances: we will make better decisions under conditions of uncertainty and irreversibility if we understand something about the probabilities of the idea that “a better option is still coming up”. We need to have some intuitive grasp of the dialectic of “exploration / exploitation” that the stopping problem endorses. As Christian and Griffiths put it, “exploration is gathering information, and exploitation is using the information you have to get a known good result” (32). How long should we continue to gather information (exploration) and at what point should we turn to active choice (“choose the next superior candidate that comes along”)? If a person navigates life by exploring 90% of options before choosing, he or she is likely to do worse than less conservative decision-makers; but likewise about the person who chooses after seeing 5% of the options.

There is a very noticeable convergence between the algorithms of stopping and Herbert Simon’s theory of satisficing (link). (The authors note this parallelSimon noted that the heroic assumptions of economic rationality are rarely satisfied in actual human decision-making: full information about the probabilities and utilities associated with a finite range of outcomes, and choice guided by choosing that option with the greatest expected utility. He notes that this view of rationality requires an unlimited budget for information gathering, and that — at some point — the cost of further search outweighs the probably gains of finding the optimal solution. Simon too argues that rational decision-makers “stop” in their choices: they set a threshold value for quality and value, initiate a search, and select the first option that meets the threshold. “Good enough” beats “best possible”. If I decide I need a pair of walking shoes, I decide on price and quality — less than $100, all leather, good tread, comfortable fit — and I visit a sequence of shoe stores, with the plan of buying the first pair of shoes that meets the threshold. But the advantage of the search algorithm described here is that it does not require a fixed threshold in advance, and it would appear to give a higher probability of making the best possible choice among all available options. As a speculative guess, it seems as though searches guided by a fixed threshold would score lower over time than searches guided by a balanced “explore, then exploit” strategy, without the latter being overwhelmed by information costs.

In one of the earlier posts on “rational life plans” I suggested that rationality comes into life-planning in several different ways:

We might describe this process as one that involves local action-rationality guided by medium term strategies and oriented towards long term objectives. Rationality comes into the story at several points: assessing cause and effect, weighing the importance of various long term goals, deliberating across conflicting goals and values, working out the consequences of one scenario or another, etc. (link)

The algorithms of stopping are clearly relevant to the first part of the story — local action-rationality. It is not so clear that the stopping problem arises in the same way in the other two levels of life-planning rationality. Deliberation about longterm objectives is not sequential in the way that deciding about which highway exit to choose for supper is; rather, the deliberating individual can canvas a number of objectives simultaneously and make deliberative choices among them. And choosing medium-term strategies seems to have a similar temporal logic: identify a reasonable range of possible strategies, compare their strengths and weaknesses, and choose the best. So the stopping problem seems to be relevant to the implementation phase of living, not the planning and projecting parts. We don’t need the stopping algorithm to decide to visit the grandchildren in Scranton, or in deciding which route across the country to choose for the long drive; but we do need it for deciding the moment-to-moment options that arise — which hotel, which restaurant, which stretch of beach, which tourist attraction to visit along the way. This seems to amount to a conclusion: the stopping problem is relevant to a certain class of choices that come as an irreversible series, but not relevant to deliberation among principles, values, or guiding goals.

(Christian and Griffiths describe the results of research on the stopping problem; but the book does not give a clear description of how the math works. Here is a somewhat more detailed explanation of the solution to the stopping problem in American Scientistlink. Essentially the solution — wait and observe for the first 37% of options, then taken the next option better than any of those seen to date — follows from a calculation of the probability of the distribution of “best choices” across the random series of candidates. And it can be proven that both lower and higher thresholds — less exploration or more exploration — lead to lower average payoffs.)

Slime mold intelligence

We often think of intelligent action in terms of a number of ideas: goal-directedness, belief acquisition, planning, prioritization of needs and wants, oversight and management of bodily behavior, and weighting of risks and benefits of alternative courses of action. These assumptions presuppose the existence of the rational subject who actively orchestrates goals, beliefs, and priorities into an intelligent plan of action. (Here is a series of posts on “rational life plans”; linklinklink.)

It is interesting to discover that some simple adaptive systems apparently embody an ability to modify behavior so as to achieve a specific goal without possessing a number of these cognitive and computational functions. These systems seem to embody some kind of cross-temporal intelligence. An example that is worth considering is the spatial and logistical capabilities of the slime mold. A slime mold is a multi-cellular “organism” consisting of large numbers of independent cells without a central control function or nervous system. It is perhaps more accurate to refer to the population as a colony rather than an organism. Nonetheless the slime mold has a remarkable ability to seek out and “optimize” access to food sources in the environment through the creation of a dynamic network of tubules established through space.

The slime mold lacks beliefs, it lacks a central cognitive function or executive function, it lacks “memory” — and yet the organism (colony?) achieves a surprising level of efficiency in exploring and exploiting the food environment that surrounds it. Researchers have used slime molds to simulate the structure of logistical networks (rail and road networks, telephone and data networks), and the results are striking. A slime mold colony appear to be “intelligent” in performing the task of efficiently discovering and exploiting food sources in the environment in which it finds itself.

One of the earliest explorations of this parallel between biological networks and human-designed networks was Tero et al, “Rules for Biologically Inspired Adaptive Network Design” in Science in 2010 (link). Here is the abstract of their article:

Abstract Transport networks are ubiquitous in both social and biological systems. Robust network performance involves a complex trade-off involving cost, transport efficiency, and fault tolerance. Biological networks have been honed by many cycles of evolutionary selection pressure and are likely to yield reasonable solutions to such combinatorial optimization problems. Furthermore, they develop without centralized control and may represent a readily scalable solution for growing networks in general. We show that the slime mold Physarum polycephalum forms networks with comparable efficiency, fault tolerance, and cost to those of real-world infrastructure networks—in this case, the Tokyo rail system. The core mechanisms needed for adaptive network formation can be captured in a biologically inspired mathematical model that may be useful to guide network construction in other domains.

Their conclusion is this:

Overall, we conclude that the Physarum networks showed characteristics similar to those of the [Japanese] rail network in terms of cost, transport efficiency, and fault tolerance. However, the Physarum networks self-organized without centralized control or explicit global information by a process of selective reinforcement of preferred routes and simultaneous removal of redundant connections. (441)

They attempt to uncover the mechanism through which this selective reinforcement of routes takes place, using a simulation “based on feedback loops between the thickness of each tube and internal protoplasmic flow in which high rates of streaming stimulate an increase in tube diameter, whereas tubes tend to decline at low flow rates” (441). The simulation is successful in approximately reproducing the observable dynamics of evolution of the slime mold networks. Here is their summary of the simulation:

Our biologically inspired mathematical model can capture the basic dynamics of network adaptability through iteration of local rules and produces solutions with properties comparable or better than those real-world infrastructure networks. Furthermore, the model has a number of tunable parameters that allow adjustment of the benefit-cost ratio to increase specific features, such as fault tolerance or transport efficiency, while keeping costs low. Such a model may provide a useful starting point to improve routing protocols and topology control for self-organized networks such as remote sensor arrays, mobile ad hoc networks, or wireless mesh networks. (442)

Here is a summary description of what we might describe as the “spatial problem-solving abilities” of the slime mold based on this research by Katherine Harman in a Scientific American blog post (link):

Like the humans behind a constructed network, the organism is interested in saving costs while maximizing utility. In fact, the researchers wrote that this slimy single-celled amoeboid can “find the shortest path through a maze or connect different arrays of food sources in an efficient manner with low total length yet short average minimum distances between pairs of food sources, with a high degree of fault tolerance to accidental disconnection”—and all without the benefit of “centralized control or explicit global information.” In other words, it can build highly efficient connective networks without the help of a planning board.

This research has several noteworthy features. First, it seems to provide a satisfactory account of the mechanism through which slime mold “network design intelligence” is achieved. Second, the explanation depends only on locally embodied responses at the local level, without needing to appeal to any sort of central coordination or calculation. The process is entirely myopic and locally embodied, and the “global intelligence” of the colony is entirely generated by the locally embodied action states of the individual mold cells. And finally, the simulation appears to offer resources for solving real problems of network design, without the trouble of sending out a swarm of slime mold colonies to work out the most efficient array of connectors.

We might summarize this level of slime-mold intelligence as being captured by:

  • trial-and-error extension of lines of exploration
  • localized feedback on results of a given line leading to increase/decrease of the volume of that line

This system is decentralized and myopic with no ability to plan over time and no “over-the-horizon” vision of potential gains from new lines of exploration. In these respects slime-mold intelligence has a lot in common with the evolution of species in a given ecological environment. It is an example of “climbing Mt. Improbable” involving random variation and selection based on a single parameter (volume of flow rather than reproductive fitness). If this is a valid analogy, then we might be led to expect that the slime mold is capable of finding local optima in network design but not global optima. (Or the slime colony may avoid this trap by being able to fully explore the space of network configurations over time.) What the myopia of this process precludes is the possibility of strategic action and planning — absorbing sacrifices at an early part of the process in order to achieve greater gains later in the process. Slime molds would not be very good at chess, Go, or war.

I’ve been tempted to offer the example of slime mold intelligence as a description of several important social processes apparently involving collective intentionality: corporate behavior and discovery of pharmaceuticals (link) and the aggregate behavior of large government agencies (link).

On pharmaceutical companies:

So here’s the question for consideration here: what if we attempted to model the system of population, disease, and the pharmaceutical industry by representing pharma and its multiple research and discovery units as the slime organism and the disease space as a set of disease populations with different profitability characteristics? Would we see a major concentration of pharma slime around a few high-frequency, high profit disease-drug pairs? Would we see substantial under-investment of pharma slime on low frequency low profit “orphan” disease populations? And would we see hyper-concentrations around diseases whose incidence is responsive to marketing and diagnostic standards? (link)

On the “intelligence” of firms and agencies:

But it is perfectly plain that the behavior of functional units within agencies are only loosely controlled by the will of the executive. This does not mean that executives have no control over the activities and priorities of subordinate units. But it does reflect a simple and unavoidable fact about large organizations. An organization is more like a slime mold than it is like a control algorithm in a factory. (link)

In each instance the analogy works best when we emphasize the relative weakness of central strategic control (executives) and the solution-seeking activities of local units. But of course there is a substantial degree of executive involvement in both private and public organizations — not fully effective, not algorithmic, but present nonetheless. So the analogy is imperfect. It might be more accurate to say that the behavior of large complex organizations incorporates both imperfect central executive control and the activities of local units with myopic search capabilities coupled with feedback mechanisms. The resulting behavior of such a system will not look at all like the idealized business-school model of “fully implemented rational business plans”, but it will also not look like a purely localized resource-maximizing network of activities.


Here is a very interesting set of course notes in which Prof. Donglei Du from the University of New Brunswick sets the terms for a computational and heuristic solution to a similar set of logistics problems. Du asks his students to consider the optimal locations of warehouses to supply retailers in multiple locations; link. Here is how Du formulates the problem:
*     Assuming that plants and retailer locations are fixed, we concentrate on the following strategic decisions in terms of warehouses.

  • Pick the optimal number, location, and size of warehouses 
  • Determine optimal sourcing strategy
    • Which plant/vendor should produce which product 
  • Determine best distribution channels
    • Which warehouses should service which retailers

The objective is to design or reconfigure the logistics network so as to minimize annual system-wide costs, including

  • Production/ purchasing costs
  • Inventory carrying costs, and facility costs (handling and fixed costs)
  • Transportation costs

As Du demonstrates, the mathematics involved in an exact solution are challenging, and become rapidly more difficult as the number of nodes increases.

Even though this example looks rather similar to the rail system example above, it is difficult to see how it might be modeled using a slime mold colony. The challenge seems to be that the optimization problem here is the question of placement of nodes (warehouses) rather than placement of routes (tubules).

Declining industries

Why is it so difficult for leaders in various industries and sectors to seriously address the existential threats that sometimes arise? Planning for marginal changes in the business environment is fairly simple; problems can be solved, costs can be cut, and the firm can stay in the black. But how about more radical but distant threats? What about the grocery sector when confronted by Amazon’s radical steps in food selling? What about Polaroid or Kodak when confronted by the rise of digital photography in the 1990s? What about the US steel industry in the 1960s when confronted with rising Asian competition and declining manufacturing facilities?

From the outside these companies and sectors seem like dodos incapable of confronting the threats that imperil them. They seem to be ignoring oncoming train wrecks simply because these catastrophes are still in the distant future. And yet the leaders in these companies were generally speaking talented, motivated men and women. So what are the organizational or cognitive barriers that arise to make it difficult for leaders to successfully confront the biggest threats they face?

Part of the answer seems to be the fact that distant hazards seem smaller than the more immediate and near-term challenges that an organization must face; so there is a systematic bias towards myopic decision-making. This sounds like a Kahneman-Tversky kind of cognitive shortcoming.

A second possible explanation is that it is easy enough to persuade oneself that distant threats will either resolve themselves organically or that the organization will discover novel solutions in the future. This seems to be part of the reason that climate-change foot-draggers take the position they do: that “things will sort out”, “new technologies will help solve the problems in the future.” This sounds like a classic example of weakness of the will — an unwillingness to rationally confront hard truths about the future that ought to influence choices today but often don’t.

Then there is the timeframe of accountability that is in place in government, business, and non-profit organizations alike. Leaders are rewarded and punished for short-term successes and failures, not prudent longterm planning and preparation. This is clearly true for term-limited elected officials, but it is equally true for executives whose stakeholders evaluate performance based on quarterly profits rather than longterm objectives and threats.

We judge harshly those leaders who allow their firms or organizations to perish because of a chronic failure to plan for substantial change in the environments in which they will need to operate in the future. Nero is not remembered kindly for his dedication to his fiddle. And yet at any given time, many industries are in precisely that situation. What kind of discipline and commitment can protect organizations against this risk?

This is an interesting question in the abstract. But it is also a challenging question for people who care about the longterm viability of colleges and universities. Are there forces at work today that will bring about existential crisis for universities in twenty years (enrollments, tuition pressure, technology change)? Are there technological or organizational choices that should be made today that would help to avert those crises in the future? And are university leaders taking the right steps to prepare their institutions for the futures they will face in several decades?

Values, directions, and action


Several earlier posts have raised the question of rational life planning. What is involved in orchestrating one’s goals and activities in such a way as to rationally create a good life in the fullness of time?

We have seen that there is something wildly unlikely about the idea of a developed, calculated life plan. Here is a different way of thinking about this question, framed about directionality and values rather than goals and outcomes. We might think of life planning in these terms:

  • The actor frames a high-level life conception — how he/she wants to live, what to achieve, what activities are most valued, what kind of person he/she wants to be. It is a work in progress.
  • The actor confronts the normal developmental issues of life through limited moments in time: choice of education, choice of spouse, choice of career, strategies within the career space, involvement with family, level of involvement in civic and religious institutions, time and activities spent with friends, … These are week-to-week and year-to-year choices, some more deliberate than others.
  • The actor reviews, assesses, and updates the life conception. Some goals are reformulated; some are adjusted in terms of priority; others are abandoned.

This picture looks quite a bit different from more architectural schemes for creating and implementing a life plan considered in earlier posts, including the view that Rawls offers for conceiving of a rational plan of life. Instead of modeling life planning after a vacation trip assisted by an AAA TripTik (turn-by-turn instructions for how to reach your goal), this scheme looks more like the preparation and planning that might have guided a great voyage of exploration in the sixteenth century. There were no maps, the destination was unknown, the hazards along the way could only be imagined. But there were a few guiding principles of navigation — “Keep making your way west,” “Sail around the biggest storms,” “Strive to keep reserves for unanticipated disasters,” “Maintain humane relations with the crew.” And, with a modicum of good fortune, these maxims might be enough to lead to discovery.

This scheme is organized around directionality and regular course correction, rather than a blueprint for arriving at a specific destination. And it appears to be all around a more genuine understanding of what is involved in making reflective life choices. Fundamentally this conception involves having in the present a vision of the dimensions of an extended life that is specifically one’s own — a philosophy, a scheme of values, a direction-setting self understanding, and the basics needed for making near-term decisions chosen for their compatibility with the guiding life philosophy. And it incorporates the idea of continual correction and emendation of the plan, as life experience brings new values and directions into prominence.

The advantage of this conception of rational life planning is that it is not heroic in its assumptions about the scope of planning and anticipation. It is a scheme that makes sense of the situation of the person in the limited circumstances of a particular point in time. It doesn’t require that the individual have a comprehensive grasp of the whole — the many contingencies that will arise, the balancing of goods that need to be adjusted in thought over the whole of the journey, the tradeoffs that are demanded across multiple activities and outcomes, and the specifics of the destination. And yet it permits the person to travel through life by making choices that conform in important ways to the high-level conception that guides him or her. And somehow, it brings to mind the philosophy of life offered by those great philosophers of life, Montaigne and Lucretius.

Deliberation, rationality, and reasoning


Recent posts have raised questions about formulating a rational plan of life. This way of putting the question highlights “rationality,” which has the connotation of short-term, one-off decision making. And this implication plainly does not fit the problem of life planning very well — as noted in the two prior posts on this topic. Living a life is more like the making of a great sculpture than it is planning a Napoleonic military campaign. But what if we shifted the terms of the question and asked instead, what is involved in being deliberative and reflective about the direction of one’s life? Does this give more room for bringing the idea of rationality into the idea of a life plan?

Being deliberative invokes the idea of considering one’s goals reflectively and in comparison, considering strategies and actions that might serve to bring about the realization of these goals, and an ongoing consideration of the continuing validity of one’s goals and strategies. Instrumental rationality takes a set of goals as being fixed; deliberative rationality works on the assumption that it is possible to reason reflectively about one’s goals themselves. This is the thrust of Socrates’ “unexamined life” — the good life requires reflection and deliberation about the things one seeks to achieve in life. Here is how Aristotle describes deliberation in the Nicomachean Ethics, book 3:

We deliberate about things that are in our power and can be done; and these are in fact what is left. For nature, necessity, and chance are thought to be causes, and also reason and everything that depends on man. Now every class of men deliberates about the things that can be done by their own efforts. And in the case of exact and self-contained sciences there is no deliberation, e.g. about the letters of the alphabet (for we have no doubt how they should be written); but the things that are brought about by our own efforts, but not always in the same way, are the things about which we deliberate, e.g. questions of medical treatment or of money-making. And we do so more in the case of the art of navigation than in that of gymnastics, inasmuch as it has been less exactly worked out, and again about other things in the same ratio, and more also in the case of the arts than in that of the sciences; for we have more doubt about the former. Deliberation is concerned with things that happen in a certain way for the most part, but in which the event is obscure, and with things in which it is indeterminate. We call in others to aid us in deliberation on important questions, distrusting ourselves as not being equal to deciding. (Nicomachean Ethics, book 3)

What Aristotle focuses on here is choice under conditions of uncertainty and complexity. Deliberation is relevant when algorithms fail — when there is no mechanical way of calculating the absolutely best way of doing something. And this seems to fit the circumstance of planning for a life or career.

How does “deliberation” come into the question of life plans? It is essential.

(1) The goals a person pursues in life cannot be specified exogenously; rather, the individual needs to consider and reflect on his or her goals in an ongoing way. Aristotle was one of the first to reveal that often the goals and goods we pursue are, upon reflection, derivative from some more fundamental good. But Kant too had a position here, favoring autonomy over heteronomy. Reflection allows us to gain clarity about those more fundamental goods that we value.

(2) The strategies and means that we choose may have only a superficial correspondence to our goods and values which is undercut by more rigorous examination. We may find that a given mode of action, a strategy, may indeed lead to good X, but may also defeat the achievement of Y, which we also value. So deliberative reflection about the strategies and actions we choose can allow us to more fully reconcile our short-term strategies with our long-term goals and goods.

Economists and philosophers have sometimes maintained that values and goals do not admit of rational consideration. But this is plainly untrue. At the very least it is possible to discover positive and negative interactions among our goals and desires — the desire to remain healthy and the desire to eat ice cream at every meal are plainly in conflict. Less trivially, the goal of living life in a way that is respectful of the dignity of others is inconsistent with the goal of rising to power within a patriarchal or racist organization. It is possible that there are values that are both fundamental and incommensurable — so that rational deliberation and reflection cannot choose between them. But it is hard to think of examples in which this kind of incommensurability arises as a practical problem.

Consider Bruce, Jorge, and Filippo. Bruce believes that being wealthy by the age of 60 is the most important thing in his life. Jorge believes that attaining a state of spiritual fulfillment by the age of 60 is most important. And Filippo believes that having circumstances of life by age 60 in which he is involved in satisfying work, has successful family relationships and friendships, and has enough income and wealth to support a decent middle-class life is most important. Are there reasonable considerations that any one of these individuals could bring to bear against another to suggest that the other’s goals are incomplete or defective?

Aristotle addresses Bruce directly by asking how wealth could possible be a fundamental good. What does Bruce want to gain by achieving great wealth? Aren’t these activities and goods more fundamental than the wealth itself? This line of argument perhaps succeeds in persuading Bruce to give more thought to what he wants out of life — not wealth, but the things that wealth permits him to do.

Jorge may seem to be just like Bruce except he values spiritual fulfillment rather than money. Indeed, they are similar in that there is only one dimension to their life goals. But Jorge can at least maintain against Bruce that his goal is good in itself, not because of its ability to bring about some other desirable thing.

Finally, Filippo. Filippo has a more complex set of life goals, none of which reduces to a combination of the others. It is true that these goals require tradeoffs in behavior and effort; strategies that enhance friendships may depress the attainment of wealth, for example. But I think it is Filippo that we think of when we imagine a person with a reflective and deliberative life plan: a person who has identified a small but plural set of longterm goals, and who recognizes that it is necessary in the moment to find ways of balancing the attainment of one with what it takes to attain more of the other.

We might think of life planning as being less like a blueprint for action and more like a navigational guide. We might think of the problem of making intermediate life choices as being guided by a compass rather than a detailed plan — the idea that we do good work on living if we guide our actions by a set of directional signals rather than a detailed map. Life outcomes result from following a compass, not moving towards a specific GPS point on a map.

There is an analogy with business planning here. Consider the actions and plans of a CEO of a company. His or her choices in concrete decision moments are guided by several important considerations: remain profitable; prepare the ground today for viable business activity tomorrow; create an environment of trust and respect among the employees of the company; make sure that company choices also take the wellbeing of the community into account; treat employees fairly; anticipate changes in the marketplace that might dictate change in process or product within the company. But there is no certainty, no fixed prescription for success, and no algorithm for balancing the goods that the firm’s leadership pursues. The successful firm will have built its success over a long series of decisions oriented towards the fundamental values of the business.

(The reference to Napoleon in Jena in the graphics above is pertinent because of the implications that Hegel drew from his experience of Napoleon as a “world historical figure”. Hegel was clear that, even with a brilliant commander and a great general staff, Napoleon’s ambitions in Europe were based on an unavoidably incomplete knowledge of the terrain of history. “The Owl of Minerva spreads its wings only at the falling of the dusk.)

A fresh approach to life plans

There isn’t a clear philosophy of life-planning in the literature. So let’s start from scratch. What do we need in order to make a plan for any temporally extended project?

  • An assessment of the outcomes we want to bring about
  • An assessment of the likely workings of the natural and social environment in which action will occur
  • A theory about how to achieve those outcomes — strategy and tactics
  • An assessment of the likelihood of negative interactions among various aspects of the plan
  • An assessment of the riskiness of the environment
  • A backup plan if things go off the rails — plan B!

We would like to arrive at a plan that has a high probability of success, and one for which there are soft landings available when future expectations are not fulfilled. If my goal is to become a symphony conductor but I also know that the qualifications needed would equally qualify me to be a performer, and if performing itself is an agreeable outcome, then aiming at conductor is less risky.

We know what it is to be rational about limited choices like choosing a new car, picking a vacation destination, or investing retirement savings. Each of these decisions falls within a broad degree of certainty of assumptions for us: we know that we enjoy the beach more than the opera, that we want a fair degree of security in our retirement accounts, or that we need a car that is good in wet weather. That is to say, we know a lot about our tastes, our future needs, and our current circumstances. So small-gauge choices like these depend fairly simply on locating a solution that serves our tastes and preferences in our current and near-future circumstances. With these conditions fixed, we can then go about the information gathering that allows us to assess how well the available sets of alternatives serve our tastes, needs, and circumstances.

Sometimes we can even reduce our choice situations to a simple set of cost-benefit tradeoffs: I’ll get a 20% improvement in crash-worthiness by paying an additional $10,000 for the car I choose; I’ll have a chance on a 10% annual return on an investment if I accept a greater degree of risk; etc. And I might find that I like the tradeoff for one set of costs but not for another — more safety is worth $10,000 to me but not $50,000. Or I will accept the greater investment risk when it means moving from 1% chance of losing everything to a 3% chance, but not to a 10% chance.

A life plan isn’t like this, however. Consider the space of choices that confronts the 20-year old college student Miguel: what kind of work will satisfy me over the long term? How much importance will I attribute to higher income in twenty years? Do I want to have a spouse and children? How much time do I want to devote to family? Do I want to live in a city or the countryside? How important to me is integrity and consistency with my own values over time? These kinds of questions are difficult to answer in part because they don’t yet have answers. Miguel will become a person with a set of important values and commitments; but right now he is somewhat plastic. It is possible for him to change his preferences, tastes, values, and concerns over time. So perhaps his plan needs to take these kinds of interventions into account.

Another source of uncertainty has to do with the future of the world itself. Will the economy continue to provide decent opportunities for young people, or will income stratification continue to increase? Will climate change make some parts of the world much more difficult for survival? Will religious strife worsen so that safety is very difficult to achieve? Is Mary Poppins or William Gibson the better prognosticator of what the world will look like in thirty years? A plan that looks good in a Mary Poppins world may look much worse in the Sprawl (Gibson’s anti-utopian city of the future).

And then there is the difficult question of akrasia — weakness of the will. Can I successfully carry out my long term plans? Or will short term temptations make it impossible for me to sustain the discipline required to achieve my long term goals? (Somewhere Jon Elster looks at this problem as a collective action problem across stages of the self. Is this a reasonable approach?) For that matter, how much should future goods matter to me in the present?

It is worth asking whether life plans actually exist for anyone. Perhaps most people’s lives take shape in a more contingent and event-driven way. Perhaps guided opportunism is the best we are likely to do: look at available opportunities at a given moment, pursue the opportunity that seems best or most pleasing at that point, and enjoy the journey. Or perhaps there are some higher-level directional rules of thumb — “choose current options that will contribute in the long run to a higher level of X”. In this scenario there is no overriding plan, just a series of local choices. This alternative is pretty convincing as a way of thinking about the full duration of a person’s life, as any biographer is likely to attest.

Consider an analogy with the life of a city or state: decisions and policies are established at various points in time. These decisions contribute to the life course of the city; monuments established in 200 BCE continued to inform Roman life in 300 AD. But Rome was indeed not built in a day, and its eventual course was not envisaged or planned by any of its founders and leaders. A city’s “life” is the complex resultant of deliberation at many points in time, struggle, and contingency. And perhaps this describes a person’s life as well.

This point of view has a lot in common with Herbert Simon’s 1957 concept of bounded rationality and satisficing rather than maximizing as a rule of rational decision-making (Models of Man). Instead of heroically attempting to plan for all contingencies over the full of one’s life, a bounded approach would be to consider short periods and make choices over the opportunity sets available during those periods. And if we superimpose on these choices a higher-level set of goals to be achieved — having time with family, living in conformity to one’s moral or religious values, gaining a set of desired character traits — then we might argue that this decision-making process will be biased towards outcomes that favor one’s deeper values as well as one’s short-term needs and interests.

This approach will not optimize choices over the full lifetime; but it may be the only approach that is feasible given the costs of information gathering and scenario assessment.

So what about a rational life plan? At this point the phrase seems inapropos to the situation of a person’s relationship to his or her longterm “life”. A life is more of a concatenation of a series of experiences, projects, accidents, contingencies — not a planned artifact or painting or building. A life is not a novel, a television series, or a mural with an underlying storyboard in which each element has its place. And therefore it seems inapt to ask for a rational plan of life. Individuals make situated and bounded deliberative decisions about specific issues. But they don’t plot out their lives in detail. 


What seems more credible is to ask for a framework of navigation, a set of compass points, and a general set of values and purposes which get invested through projects and activities. The idea of the bildungsroman seems more illuminating — the idea of a young person taking shape through a series of challenging undertakings over time. Development, formation, values clarification, and the formation of character seem more true to what we might like to see in a good life than achieving a particular set of outcomes.


Where, then, do thinking and reasoning come into the picture? This is where Socrates and Montaigne seem to be relevant. They look at living as an opportunity for deepening self-knowledge and articulation of values and character. “To philosophize is to learn how to die” (Montaigne) and “The unexamined life is not worth living” (Socrates). The upshot of these aphorisms seems to be this: reasoning and philosophizing allow us to probe, question, and extend our values and the things we strive for. And having examined and probed, we are also in a position to assess and judge the actions and goals that are presented to us at various stages of life. How does a college major, a first job, a marriage, or a parenting challenge frame the future into which the young person develops? And how can practical reflection about one’s current values help to give direction to the future choices he or she makes later in life?
Practical rationality perhaps amounts to little more than this when it comes to constructing a life: to consider one’s best understanding of the goods he or she cares most about, and acting in the present in ways that shape the journey towards a future that better embodies those goods for the person and his or her concerns.

How to do cephalapod philosophy

How should researchers attempt to investigate non-human intelligence? The image above raises difficult questions. The octopus is manipulating (tenticlating?) the Rubik’s cube. But there are a raft of questions that are difficult to resolve on the basis of simple inductive observation. And some of those questions are as much conceptual as they are empirical. Is the octopus “attempting to solve the cube”? Does it understand the goal of the puzzle? Does it have a mental representation of a problem which it is undertaking to solve? Does it have temporally extended intentionality? How does octopus consciousness compare to human consciousness? (Here is a nice website by several biologists at Reed College on the subject of octopus cognition; link.)

An octopus-consciousness theorist might offer a few hypotheses:

  1. The organism possesses a cognitive representation of its environment (including the object we refer to as “Rubik’s cube”).
  2. The organism possesses curiosity — a behavioral disposition to manipulate the environment and observe the effects of manipulation.
  3. The organism has a cognitive framework encompassing the idea of cause and effect.
  4. The organism has desires and intentions.
  5. The organism has beliefs about the environment.
  6. The organism is conscious of itself within the environment.

How would any of these hypotheses be evaluated?

One resource that the cephalapod behavior theorist has is the ability to observe octopi in their ordinary life environments and in laboratory conditions. These observations constitute a rich body of data about behavioral capacities and dispositions. For example:

Here we seem to see the organism conveying a tool (coconut shell) to be used for an important purpose later (concealment) (link). This behavior seems to imply several cognitive states: recognition of the physical characteristics of the shell; recognition of the utility those characteristics may have in another setting; and a plan for concealment. The behavior also seems to imply a capacity for learning — adapting behavior by incorporating knowledge learned at an earlier time.

Another tool available to the cephalapod theorist is controlled experimentation. It is possible to test the perceptual, cognitive, and motor capacities of the organism by designing simple experimental setups inviting various kinds of behavior. The researcher can ask “what-if” questions and frame experiments that serve to answer them — for example, what if the organism is separated from the shell but it remains in view; will the organism reaquire the shell?

A third tool available to the cephalapod researcher is the accumulated neuro-physiology that is available for the species. How does the perceptual system work? What can we determine about the cognitive system embodied in the organism’s central nervous system?

Finally, the researcher might consult with philosophers working on the mind-body problem for human beings, to canvass whether there are useful frameworks in that discipline that might contribute to octopus-mind-body studies. (Thomas Nagel’s famous article, “What is it Like to Be a Bat?”, comes to mind, in which he walks through the difficulty of imagining the consciousness of a bat whose sensory world depends on echo-location; link.)

In short, it seems that cephalapod cognition is a research field that necessarily combines detailed empirical research with conceptual and theoretical framing; and the latter efforts require as much rigor as the former.

Rationality over the long term

image: Dietrich Bonhoeffer with his students

Millions of words have been written on the topic of rationality in action. Life involves choices. How should we choose between available alternatives? Where should I go to college? Which job should I accept? Should I buy a house or rent an apartment? How much time should I give my job in preference to my family? We would like to have reasons for choosing A over B; we would like to approach these choices “rationally.”

These are all “one-off” choices, and rational choice theory has something like a formula to offer for the decider: gain the best knowledge available about the several courses of action; evaluate the costs, risks, and rewards of each alternative; and choose that alternative that produces the greatest expected level of satisfaction of your preferences. There are nuances to be decided, of course: should we go for “greatest expected utility” or should we protect against unlikely but terrible outcomes by using a maximin rule for deciding?

There are several deficiencies in this story. Most obviously, few of us actually go through the kinds of calculations specified here. We often act out of habit or semi-articulated rules of thumb. Moreover, we are often concerned about factors that don’t fit into the “preferences and beliefs” framework, like moral commitments, conceptions of ourselves, loyalties to others, and the like. Pragmatists would add that much mundane action flows from a combination of habit and creativity rather than formal calculation of costs and benefits.

But my concern here is larger. What is involved in being deliberative and purposive about extended stretches of time? How do we lay out the guideposts of a life plan? And what is involved in acting deliberatively and purposively in carrying out one’s life plan or other medium- and long-term goals?

Here I want to look more closely than usual at what is involved in reflecting on one’s purposes and values, formulating a plan for the medium or long term, and acting in the short term in ways that further the big plan. My topic is “rationality in action”, but I want to pay attention to the issues associated with large, extended purposes — not bounded decisions like buying a house, making a financial investment, or choosing a college. I’m thinking of larger subjects for deliberation — for example, conquering all of Europe (Napoleon), leading the United States through a war for the Union ( Lincoln), or becoming a committed and active anti-Nazi (Bonhoeffer).

The scale I’m focusing on here corresponds to questions like these:

  • How did Napoleon deliberate about his ambitions in 1789? How did he carry out his thoughts, goals, and plans?
  • How did Abraham Lincoln think about slavery and the Union in 1861? How did his conduct of politics and war take shape in relation to his long term goals?
  • How did Richard Rorty plan his career in the early years? How did his choices reflect those plans? (Neil Gross considers this question in Richard Rorty: The Making of an American Philosopher; link.)
  • How did Dietrich Bonhoeffer deliberate about the choices in front of him in Germany in 1933? How did he decide to become an engaged anti-Nazi, at the eventual cost of his life?

What these examples have in common is large temporal scope; substantial uncertainties about the future; and extensive intertwining of moral and political values with more immediate concerns of self-interest, prudence, and desire. Moreover, the act of formulating plans on this scale and living them out is formative: we become different persons through these efforts.

The intriguing question for me at the moment is the issue of rational deliberation: to what extent and through what processes can individuals engage in a rational process in thinking through their decisions and plans at this level? Is it an expectation of rationality that an individual will have composed nested sets of plans and objectives, from the most global to the intermediate to the local?

Or instead, does a person’s journey through large events take its shape in a more stochastic way: opportunities, short term decisions, chance involvements, and some ongoing efforts to make sense of it all in the form of a developing narrative? Here we might say that life is not planned, but rather built like Neurath’s raft with materials at hand; and that rationality and deliberation come in only at a more local scale.

Here is a simple way of characterizing purposive action over a long and complex period. The actor has certain guiding goals he or she is trying to advance. It is possible to reflect upon these goals in depth and to consider their compatibility with other important considerations. This might be called “goal deliberation”. These goals and values serve as the guiding landmarks for the journey — “keep moving towards the tallest mountain on the horizon”. The actor surveys the medium-term environment for actions that are available to him or her, and the changes in the environment that may be looming in that period. And he or she composes a plan for these circumstances– “attempt to keep moderate Southern leaders from supporting cecession”. This is the stage of formulation of mid-range strategies and tactics, designed to move the overall purposes forward. Finally, like Odysseus, the actor seizes unforeseen opportunities of the moment in ways that appear to advance the cause even lacking a blueprint for how to proceed.

We might describe this process as one that involves local action-rationality guided by medium term strategies and oriented towards long term objectives. Rationality comes into the story at several points: assessing cause and effect, weighing the importance of various long term goals, deliberating across conflicting goals and values, working out the consequences of one scenario or another, etc.

As biologists from Darwin to Dawkins have recognized, the process of species evolution through natural selection is inherently myopic. Long term intelligent action is not so, in that it is possible for intelligent actors to consider distant solutions that are potentially achievable through orchestrated series of actions — plans and strategies. But in order to achieve the benefits of intelligent longterm action, it is necessary to be intelligent at every stage — formulate good and appropriate distant goals, carefully assess the terrain of action to determine as well as possible what pathways exist to move toward those goals, and act in the moment in ways that are both intelligent solutions to immediate opportunities and obstacles, and have the discipline to forego short term gain in order to stay on the path to the long term goal. But, paradoxically, it may be possible to be locally rational at every step and yet globally irrational, in the sense that the series of rational choices lead to an outcome widely divergent from the overriding goals one has selected.

I’ve invoked a number of different ideas here, all contributing to the notion of rational action over an extended time: deliberation, purposiveness, reflection, calculation of consequences, intelligent problem solving, and rational choice among discrete alternatives. What is interesting to me is that each these activities is plainly relevant to the task of “rational action”; and yet none reduces to the other. In particular, rational choice theory cannot be construed as a general and complete answer to the question, “what is involved in acting rationally over the long term?”.

Michael Bratman is the philosopher who has thought about these issues the most deeply; Intention, Plans, and Practical Reason. Manuel Vargas and Gideon Yaffe’s recent festschrift on Bratman’s work, Rational and Social Agency: The Philosophy of Michael Bratman, is also a useful contribution on the subject. Sarah Paul provides a nice review of Rational and Social Agency here.

Strategic action fields

Sometimes a rethinking of ontology and social categories results in an important step forward in social theory. This appears to be the case in some recent reflections on the relationships that exist between social movements theory and the sociology of organizations.  The presumption of existing writings on these fields is that they refer to separate but related phenomena.  One is more about social actors and the other is more about stable social structures.  What happens when we consider the possibility that they actually refer to the same kinds of social phenomena?

This is the perspective taken by Neil Fligstein and Doug McAdam in a recent contribution to Sociological Theory, “Toward a General Theory of Strategic Action Fields”(link). (They develop these ideas more fully in A Theory of Fields.) In the Sociological Theory article they write:

We assert that scholars of organizations and social movements — and for that matter, students of any institutional actor in modern society — are interested in the same underlying phenomenon: collective strategic action. (2)

Fligstein and McAdam formulate their novel approach in terms of the idea of “strategic action fields.” They put it forward that “strategic action fields … are the fundamental units of collective action in society” (3). Power and advantage play key roles in their construction: “We too see SAFs as socially constructed arenas within which actors with varying resource endowments vie for advantage. Membership in these fields is based far more on subjective ‘standing’ than objective criteria” (3).

Here are types of social items they include in this theory:

  1. strategic action fields 
  2. incumbents, challengers, and governance units 
  3. social skill 
  4. the broader field environment 
  5. exogenous shocks, field ruptures, and the onset of contention 
  6. episodes of contention 
  7. settlement (2) 

This approach is importantly couched at the level of social ontology: what sorts of things should we identify and analyze as explanatory factors in our theories? The move to SAFs is a move against the idea of the fixity of social “structures,” institutions, and organizations. For example, they write against the ontology of new institutionalism: “The general image for most new institutionalists is one of routine social order and reproduction” — or in other words, a static set of rules and constraints within which action takes place. Their ontology, on the other hand, emphasizes the fluidity of the constraints and circumstances of action from the actors’ points of view; so the field shifts as actors undertake one set of strategies or another. “This leaves great latitude for the possibility of piecemeal change in the positions that actors occupy” (5).

So both stability and change are incorporated into a single framework of analysis: actors react strategically to the field of constraints and positions within which they act, with results that sometimes reinforce current positions and other times disrupt those positions.

They account for what looks like institutional rigidity by calling out the power of some actors to maintain their positions in the social order: “Most incumbents are generally well positioned and fortified to withstand these change pressures. For starters they typically enjoy significant resource advantages over field challengers” (9). But institutions should not be expected to maintain their structures indefinitely: “The expectation is that when even a single member of the field begins to act in innovative ways in violation of field rules, others will respond in kind, precipitating an episode of contention” (9).

So what is intended by the idea of “strategic action” in this theory? Here is what they have to say on that subject:

We define strategic action as the attempt by social actors to create and maintain stable social worlds by securing the cooperation of others. Strategic action is about control in a given context. The creation of identities, political coalitions, and interests serves to promote the control of actors vis-a-vis other actors. (7)

Here is one other interesting ontological feature of this approach. Their language suggests some parallels with assemblage theory (link), in the sense that social constructs fit upwards and downwards into strategic action fields at a range of fields. “We conceive of all fields as embedded in complex webs of other fields” (8). This set of ideas seems to suggest an unexpected affinity to “actor-network theory” and the sociological ideas of Bruno Latour (ANT) (link). But at the other end of some obscure spectrum of theory differentiation, their account also seems to rub shoulders with rational-choice theory, where both actions and rules are subject to deliberation and change by prudential actors.


There are several features of this approach that seem promising to me. One is the fact that it directly challenges the tendency towards reification that sometimes blocks sociological thinking — the idea that social “things” like states persist largely independently from the individuals who make them up. This new approach leads to a way of thinking about the social world that emphasizes contingency and plasticity (linklink) rather than rigid and homogeneous social structures. It also seems consistent with the thinking that leads to the idea of “methodological localism” — the idea that social phenomena rest upon “molecules” of socially constructed, socially situated individuals (link). I also like the fact that their analysis is explicitly couched at the meso level — neither macro nor micro.

One concern this approach raises, however, is suggested by the point mentioned above about its apparent proximity to some versions of rational choice theory — the view that all social outcomes and processes are ultimately the consequence of prudential actors pursuing their interests. But this assumption — which McAdam certainly does not share elsewhere in his writing (e.g. Dynamics of Contention) — threatens to push out of consideration social realities like normative systems, social identities, and distributed systems of power that somehow or other seem to demand inclusion in our understanding of social processes.

Finally, we can ask whether this innovation provides a basis for more fruitful empirical research into concrete phenomena like how corporations and revolutionary parties function, how demonstrations against Islamophobia take shape, and how resistance to racial discrimination emerges.  If the theoretical innovation doesn’t lead to richer empirical research, then it is reasonable to be skeptical about why we should adopt the new theoretical tools.

Value-free economics?


A recent volume by Vivian Walsh and Hilary Putnam,  The End of Value-Free Economics, brings to a fine point a line of argument that has been brewing for fifteen years: is the logical positivist insistence on separating “fact-based” science from “value-based” ethics any longer a tenable one? Most particularly, are there now compelling reasons for declaring that mainstream economics needs to recognize that the distinction is wholly untenable? Is the zeal for insisting on “positive” economics now unsupportable? Should economists at last recognize that Lionel Robbins’ strong exclusion of normative language from the science of economics both unjustified and unwise?  Walsh and Putnam argue that the answers to each of these questions is definitive: the strict dichotomy between fact and value in economics can no longer be supported.

The issue of facts and values has a number of sources within the empiricist tradition.  There is Hume’s view that we can’t derive “ought” from “is”; or in other words, that moral judgments are logically independent from empirical beliefs.  There is the positivists’ criterion of significance, according to which the meaning of an utterance reduces to the empirical experiences that would demonstrate its truth or falsity.  (The two propositions together imply that moral sentences are meaningless or “non-cognitive”, since the first proposition concedes that no empirical experience can demonstrate the truth or falsity of a normative statement.) And there is the positivists’ idea that science is exclusively concerned with “facts”; but the first two propositions consign moral statements to the category of “value” rather than “fact”, so science cannot contain normative vocabulary.  Another source was internal to debates within neoclassical economics itself: Lionel Robbins’s arguments against interpersonal comparisons of utilities, based on the idea that making such comparisons unavoidably involves taking an evaluative stance towards the individuals in question.

The key idea advanced in The End of Value-Free Economics is that none of these philosophical ideas have survived the critique of positivism that was offered within philosophy of science and philosophy of language over the past fifty years.  The attempt to draw a sharp line between “fact” and “value” turns out to be impossible.  And this is equally so in economics.

Consider an example.  The concept of Pareto efficiency is defined in value-neutral terms: a distribution is Pareto-efficient if there is no other distribution that improves some individuals without harming at least one individual.  The concept of distributive justice is not value-neutral; it invokes the idea that some distributions are better because they are more fair or more just than others.  The positive economist holds that the latter set of distinctions are legitimate to make — in some other arena.  But within economics, the language of justice and equity has no place.  The economist, according to this view, can work out the technical characteristics of various economic arrangements; but it is up to the political process or the policy decision-maker to arrive at a governing set of normative standards.  Walsh and Putnam (as well as Amartya Sen) dispute this view on logical grounds; and this leaves the discipline free to have a rational and reasoned discussion of the pros and cons of various principles of distributive justice.

Raising the issue of value-neutrality for economics is a frontal assault on the uncritical positivism that neoclassical economics incorporated from the 1930s and forward. But it is also an attack on something else–the no-longer acceptable idea that economists can only tell us how things are, not how they should be. Is famine worse than food sufficiency? Is literacy better than illiteracy? Is good health an improvement in wellbeing? If we take the view that “positive economics” cannot contain normative judgments, then none of these questions could be answered by an economist. “It depends on what you value.” What Walsh, Putnam, Sen, and other contributors to this volume want to say is that this response is idiotic, and there is no basis in logic, science, or methodology that would support it. Of course economics, and economists, can find that starvation is a bad thing. Instead, they maintain that the best philosophy of language and philosophy of science supports the idea that value concepts and descriptive concepts are intermingled or “entangled”, and that we can offer good reasons and evidence for evaluating claims involving both.

Why, some readers will ask, has Hilary Putnam become a central figure in this emerging debate? Putnam is known as a technically astute philosopher of mathematics, logic, and physics, and a philosopher of language; he is known for a sometimes wavering adherence to several versions of scientific realism; and he has made contributions of the greatest importance to each of these fields. But how did he come to get deeply immersed in the issue of the role of values in economics?

Vivian Walsh is one important part of the answer. Walsh undertook a series of articles in the 1980s and 1990s that were critical of the logical positivist assumptions that have lingered within the methodology of neoclassical economics. He took encouragement from the writings of Amartya Sen on welfare economics that confidently dismissed these positivist assumptions — for example, the idea that science could not incorporate values or that statements about values were meaningless. (Lionel Robbins is offered as a particularly clear advocate of these views.) And Putnam worked up his reactions to these ideas into a novel book in 2002, The Collapse of the Fact/Value Dichotomy and Other Essays.

A key construct in the collaborative thinking that Putnam and Walsh have done together is the idea of the “second phase of classical theory.” (Harvey Gram discusses this construction in detail in his contribution.) Walsh introduces the idea and Putnam follows up in his essay. What this refers to is the fact that classical political economy, as expressed by Smith and Ricardo, underwent a major intellectual revival in the 1960s when thinkers like Pierro Sraffa proposed reappropriating some of their key analytical ideas. Sraffa’s Production of Commodities by Means of Commodities : Prelude to a Critique of Economic Theorywas a key product of this rethinking. The rethinking itself came about because of an uneasiness about the premises of neoclassical economics, and it stayed close to the core logical ideas. The first revival focused on Ricardo, but the second phase, Walsh argues, has given a much more nuanced interpretation of Smith himself.  Walsh finds that this reconsideration has been led by Amartya Sen and is more wide-ranging. Here is why Walsh thinks this reconsideration of Smith is important:

This is because Smith embedded a remarkable understanding of the core concepts of a political economy whose implications for moral philosophy he understood and explored.  The Smith texts as a whole offer a rich tapestry, interweaving threads of classical analysis, moral philosophy, jurisprudence, and history. (7)

And here is how Putnam summarizes Sen’s contribution to this reconsideration of classical political economy:

If we are to understand Sen’s place in history, the reintroduction of ethical concerns and concepts into economic discourse must not be thought of as an abandonment of “classical economics”; rather it is a reintroduction of something that was everywhere present in the writings of Adam Smith, and that went hand-inhand with Smith’s technical analyses. This is something that Sen himself stresses. (quoted by Walsh, 29)

Amartya Sen has argued throughout his career for the robust possibility of reasoning about value issues — in economics and elsewhere. (A very early place where Sen takes up this topic is in “The Nature and Classes of Prescriptive Judgements”; link.) Much of what Sen brings to this debate within economics, according to Walsh and Putnam, is found in his capabilities theory as a foundation for a theory of welfare or wellbeing. This theory is based on the idea of human functionings; and there is a plain intermingling of factual and evaluative ideas associated with this notion.  We need to know what human beings can and want to do, before we can say how well off they are. And this means bringing in orienting human values at the foundations. Putnam draws attention to Martha Nussbaum’s list of core human capabilities. Anyone reading these descriptions would agree that they presuppose human values. And Nussbaum (as well as Sen and Putnam) believes that we can rationally discuss and evaluate these. But if welfare economics is to incorporate a substantive notion of human wellbeing, then it plainly cannot be maintained that it is “value-free”.

Another important locus for Sen’s reintroduction of ethical concepts into economics is his critique of the narrow conception of individual economic rationality.  As Sen puts the point in “Rational Fools” (link),

A person thus described may be “rational”in the limited sense of revealing no inconsistencies in his choice behavior, but if he has no use for these distinctions between quite different concepts, he must be a bit of a fool. The purely economic man is indeed close to being a social moron. Economic theory has been much preoccupied with this rational fool decked in the glory of his one all-purpose preference ordering. To make room for the different concepts related to his behavior we need a more elaborate structure. (336)

Sen introduces the idea of “commitments” directly into the concept of economic rationality.  Individuals choose among preference rankings based on their commitments — to each other, to political ideas, to groups with whom they have decided to affiliate.  And this brings normative ideas directly into economic decision-making — and therefore into the domain of economics.

Walsh and Putnam insist on a point that seems very important to me as well: it is the dichotomy between facts and values, or between positive and normative analysis, that they reject. They do not reject the idea that there are facts and there are values. But they believe in important respects these categories are intertwined and inseparable. They argue for “entanglement” and “rich description.” They believe that it is fully possible and acceptable to engage in rational debates over the best theory of justice, or human nature, or human freedom; and to do so within economics as well as outside of economics.  And they believe that science can handle its goals without this sharp dichotomy.

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