Saturday, June 23, 2018

Shakespeare on tyranny


Stephen Greenblatt is a literary critic and historian whose insights into philosophy and the contemporary world are genuinely and consistently profound. His most recent book returns to his primary expertise, the corpus of Shakespeare's plays. But it is -- by intention or otherwise -- an  important reflection on the presidency of Donald Trump as well. The book is Tyrant: Shakespeare on Politics, and it traces in fascinating detail the evolution and fates of tyrants through Shakespeare's plays. Richard III gets a great deal of attention, as do Lear and Macbeth. Greenblatt makes it clear that Shakespeare was interested both in the institutions of governance within which tyrants seized power, and the psychology of the tyrant. The parallels with the behavior and psychology of the current US President are striking.

Here is how Greenblatt frames his book.
“A king rules over willing subjects,” wrote the influential sixteenth-century Scottish scholar George Buchanan, “a tyrant over unwilling.” The institutions of a free society are designed to ward off those who would govern, as Buchanan put it, “not for their country but for themselves, who take account not of the public interest but of their own pleasure.” Under what circumstances, Shakespeare asked himself, do such cherished institutions, seemingly deep-rooted and impregnable, suddenly prove fragile? Why do large numbers of people knowingly accept being lied to? How does a figure like Richard III or Macbeth ascend to the throne? (1)
So who is the tyrant? What is his typical psychology?
Shakespeare's Richard III brilliantly develops the personality features of the aspiring tyrant already sketched in the Henry VI trilogy: the limitless self-regard, the lawbreaking, the pleasure in inflicting pain, the compulsive desire to dominate. He is pathologically narcissistic and supremely arrogant. He has a grotesque sense of entitlement, never doubting that he can do whatever he chooses. He loves to bark orders and to watch underlings scurry to carry them out. He expects absolute loyalty, but he is incapable of gratitude. The feelings of others mean nothing to him. He has no natural grace, no sense of shared humanity, no decency. He is not merely indifferent to the law; he hates it and takes pleasure in breaking it. He hates it because it gets in his way and because it stands for a notion of the public good that he holds in contempt. He divides the world into winners and losers. The winners arouse his regard insofar as he can use them for his own ends; the losers arouse only his scorn. The public good is something only losers like to talk about. What he likes to talk about is winning. (53)
One of Richard’s uncanny skills—and, in Shakespeare’s view, one of the tyrant’s most characteristic qualities—is the ability to force his way into the minds of those around him, whether they wish him there or not. (64)
Greenblatt has a lot to say about the enablers of the tyrant -- those who facilitate and those who silently consent.
Another group is composed of those who do not quite forget that Richard is a miserable piece of work but who nonetheless trust that everything will continue in a normal way. They persuade themselves that there will always be enough adults in the room, as it were, to ensure that promises will be kept, alliances honored, and core institutions respected. Richard is so obviously and grotesquely unqualified for the supreme position of power that they dismiss him from their minds. Their focus is always on someone else, until it is too late. They fail to realize quickly enough that what seemed impossible is actually happening. They have relied on a structure that proves unexpectedly fragile. (67)
One of the topics that appears in Shakespeare's corpus is a class-based populism from the under-classes. Consider Jack Cade, the lying and violent foil to The Duke of York.
Cade himself, for all we know, may think that what he is so obviously making up as he goes along will actually come to pass. Drawing on an indifference to the truth, shamelessness, and hyperinflated self-confidence, the loudmouthed demagogue is entering a fantasyland—“ When I am king, as king I will be”—and he invites his listeners to enter the same magical space with him. In that space, two and two do not have to equal four, and the most recent assertion need not remember the contradictory assertion that was made a few seconds earlier. (37)
And what about the fascination tyrants have with secret alliances with hostile foreign powers?
Third, the political party determined to seize power at any cost makes secret contact with the country’s traditional enemy. England’s enmity with the nation across the Channel—constantly fanned by all the overheated patriotic talk of recovering its territories there, and fueled by all the treasure and blood spilled in the attempt to do so—suddenly vanishes. The Yorkists—who, in the person of Cade, had pretended to consider it an act of treason even to speak French—enter into a set of secret negotiations with France. Nominally, the negotiations aim to end hostilities between the two countries by arranging a dynastic marriage, but they actually spring, as Queen Margaret cynically observes, “from deceit, bred by necessity” (3 Henry VI 3.3.68).
How does the tyrant rule? In a word, badly.
The tyrant’s triumph is based on lies and fraudulent promises braided around the violent elimination of rivals. The cunning strategy that brings him to the throne hardly constitutes a vision for the realm; nor has he assembled counselors who can help him formulate one. He can count—for the moment, at least—on the acquiescence of such suggestible officials as the London mayor and frightened clerks like the scribe. But the new ruler possesses neither administrative ability nor diplomatic skill, and no one in his entourage can supply what he manifestly lacks. His own mother despises him. His wife, Anne, fears and hates him. (84)
Several things seem apparent, both from Greenblatt's reading of Shakespeare and from the recent American experience. One is that freedom and the rule of law are inextricably entangled. It is not an exaggeration to say that freedom simply is the situation of living in a society in which the rule of law is respected (and laws establish individual rights and impersonal procedures). When strongmen are able to use the organs of the state or their private henchmen to enact their personal will, the freedom and liberties of the whole of society are compromised.

Second, the rule of law is a normative commitment; but it is also an institutional reality. Institutions like the Constitution, the division of powers, the independence of the judiciary, and the codification of government ethics are preventive checks against arbitrary power by individuals with power. But as Greenblatt's examples show, the critical positions within the institutions of law and government are occupied by ordinary men and women. And when they are venal, timid, and bent to the will of the sovereign, they present no barrier against tyranny. This is why fidelity to the rule of law and the independence of the justice system is the most fundamental and irreplaceable ethical commitment we must demand of officials. Conversely, when am elected official demonstrates lack of commitment to the principles, we must be very anxious for the fate of our democracy.

Greenblatt's book is fascinating for the historical context it provides for Shakespeare's plays. But it is even more interesting for the critical light it sheds on our current politics. And it makes clear that the moral choices posed by politicians determined to undermine the institutions of democracy are perennial, whether in Shakespeare's time or our own.

Tuesday, May 22, 2018

Social generativity and complexity


The idea of generativity in the realm of the social world expresses the notion that social phenomena are generated by the actions and thoughts of the individuals who constitute them, and nothing else (link, link). More specifically, the principle of generativity postulates that the properties and dynamic characteristics of social entities like structures, ideologies, knowledge systems, institutions, and economic systems are produced by the actions, thoughts, and dispositions of the set of individuals who make them up. There is no other kind of influence that contributes to the causal and dynamic properties of social entities. Begin with a population of individuals with such-and-so mental and behavioral characteristics; allow them to interact with each other over time; and the structures we observe emerge as a determinate consequence of these interactions.

This view of the social world lends great ontological support to the methods associated with agent-based models (link). Here is how Joshua Epstein puts the idea in Generative Social Science: Studies in Agent-Based Computational Modeling):
Agent-based models provide computational demonstrations that a given microspecification is in fact sufficient to generate a macrostructure of interest.... Rather, the generativist wants an account of the configuration's attainment by a decentralized system of heterogeneous autonomous agents. Thus, the motto of generative social science, if you will, is: If you didn't grow it, you didn't explain its emergence. (42)
Consider an analogy with cooking. The properties of the cake are generated by the properties of the ingredients, their chemical properties, and the sequence of steps that are applied to the assemblage of the mixture from the mixing bowl to the oven to the cooling board. The final characteristics of the cake are simply the consequence of the chemistry of the ingredients and the series of physical influences that were applied in a given sequence.

Now consider the concept of a complex system. A complex system is one in which there is a multiplicity of causal factors contributing to the dynamics of the system, in which there are causal interactions among the underlying causal factors, and in which causal interactions are often non-linear. Non-linearity is important here, because it implies that a small change in one or more factors may lead to very large changes in the outcome. We like to think of causal systems as consisting of causal factors whose effects are independent of each other and whose influence is linear and additive.

A gardener is justified in thinking of growing tomatoes in this way: a little more fertilizer, a little more water, and a little more sunlight each lead to a little more tomato growth. But imagine a garden in which the effect of fertilizer on tomato growth is dependent on the recent gradient of water provision, and the effects of both positive influencers depend substantially on the recent amount of sunlight available. Under these circumstances it is difficult to predict the aggregate size of the tomato given information about the quantities of the inputs.

One of the key insights of complexity science is that generativity is fully compatible with a wicked level of complexity. The tomato's size is generated by its history of growth, determined by the sequence of inputs over time. But for the reason just mentioned, the complexity of interactions between water, sunlight, and fertilizer in their effects on growth mean that the overall dynamics of tomato growth are difficult to reconstruct.

Now consider the idea of strong emergence -- the idea that some aggregates possess properties that cannot in principle be explained by reference to the causal properties of the constituents of the aggregate. This means that the properties of the aggregate are not generated by the workings of the constituents; otherwise we would be able in principle to explain the properties of the aggregate by demonstrating how they derive from the (complex) pathways leading from the constituents to the aggregate. This version of the absolute autonomy of some higher-level properties is inherently mysterious. It implies that the aggregate does not supervene upon the properties of the constituents; there could be different aggregate properties with identical constituent properties. And this seems ontological untenable.

The idea of ontological individualism captures this intuition in the setting of social phenomena: social entities are ultimately composed of and constituted by the properties of the individuals who make them up, and nothing else. This does not imply methodological individualism; for reasons of complexity or computational limitations it may be practically impossible to reconstruct the pathways through which the social entity is generated out of the properties of individuals. But ontological individualism places an ontological constraint on the way that we conceptualize the social world. And it gives a concrete meaning to the idea of the microfoundations for a social entity. The microfoundations of a social entity are the pathways and mechanisms, known or unknown, through which the social entity is generated by the actions and intentionality of the individuals who constitute it.

Monday, May 7, 2018

What the boss wants to hear ...


According to David Halberstam in his outstanding history of the war in Vietnam, The Best and the Brightest, a prime cause of disastrous decision-making by Presidents Kennedy and Johnson was an institutional imperative in the Defense Department to come up with a set of facts that conformed to what the President wanted to hear. Robert McNamara and McGeorge Bundy were among the highest-level miscreants in Halberstam's account; they were determined to craft an assessment of the situation on the ground in Vietnam that conformed best with their strategic advice to the President.

Ironically, a very similar dynamic led to one of modern China's greatest disasters, the Great Leap Forward famine in 1959. The Great Helmsman was certain that collective agriculture would be vastly more productive than private agriculture; and following the collectivization of agriculture, party officials in many provinces obliged this assumption by reporting inflated grain statistics throughout 1958 and 1959. The result was a famine that led to at least twenty million excess deaths during a two-year period as the central state shifted resources away from agriculture (Frank DikötterMao's Great Famine: The History of China's Most Devastating Catastrophe, 1958-62).

More mundane examples are available as well. When information about possible sexual harassment in a given department is suppressed because "it won't look good for the organization" and "the boss will be unhappy", the organization is on a collision course with serious problems. When concerns about product safety or reliability are suppressed within the organization for similar reasons, the results can be equally damaging, to consumers and to the corporation itself. General Motors, Volkswagen, and Michigan State University all seem to have suffered from these deficiencies of organizational behavior. This is a serious cause of organizational mistakes and failures. It is impossible to make wise decisions -- individual or collective -- without accurate and truthful information from the field. And yet the knowledge of higher-level executives depends upon the truthful and full reporting of subordinates, who sometimes have career incentives that work against honesty.

So how can this unhappy situation be avoided? Part of the answer has to do with the behavior of the leaders themselves. It is important for leaders to explicitly and implicitly invite the truth -- whether it is good news or bad news. Subordinates must be encouraged to be forthcoming and truthful; and bearers of bad news must not be subject to retaliation. Boards of directors, both private and public, need to make clear their own expectations on this score as well: that they expect leading executives to invite and welcome truthful reporting, and that they expect individuals throughout the organization to provide truthful reporting. A culture of honesty and transparency is a powerful antidote to the disease of fabrications to please the boss.

Anonymous hotlines and formal protection of whistle-blowers are other institutional arrangements that lead to greater honesty and transparency within an organization. These avenues have the advantage of being largely outside the control of the upper executives, and therefore can serve as a somewhat independent check on dishonest reporting.

A reliable practice of accountability is also a deterrent to dishonest or partial reporting within an organization. The truth eventually comes out -- whether about sexual harassment, about hidden defects in a product, or about workplace safety failures. When boards of directors and organizational policies make it clear that there will be negative consequences for dishonest behavior, this gives an ongoing incentive of prudence for individuals to honor their duties of honesty within the organization.

This topic falls within the broader question of how individual behavior throughout an organization has the potential for giving rise to important failures that harm the public and harm the organization itself.


Monday, April 23, 2018

Regulatory failure


When we think of the issues of health and safety that exist in a modern complex economy, it is impossible to imagine that these social goods will be produced in sufficient quantity and quality by market forces alone. Safety and health hazards are typically regarded as "externalities" by private companies -- if they can be "dumped" on the public without cost, this is good for the profitability of the company. And state regulation is the appropriate remedy for this tendency of a market-based economy to chronically produce hazards and harms, whether in the form of environmental pollution, unsafe foods and drugs, or unsafe industrial processes. David Moss and John Cisternino's New Perspectives on Regulation provides some genuinely important perspectives on the role and effectiveness of government regulation in an epoch which has been shaped by virulent efforts to reduce or eliminate regulations on private activity. This volume is a report from the Tobin Project.

It is poignant to read the optimism that the editors and contributors have -- in 2009 -- about the resurgence of support for government regulation. The financial crisis of 2008 had stimulated a vigorous round of regulation of financial institutions, and most of the contributors took this as a harbinger of a fresh public support for regulation more generally. Of course events have shown this confidence to be sadly mistaken; the dismantling of Federal regulatory regimes by the Trump administration threatens to take the country back to the period described by Upton Sinclair in the early part of the prior century. But what this demonstrates is the great importance of the Tobin Project. We need to build a public understanding and consensus around the unavoidable necessity of effective and pervasive regulatory regimes in environment, health, product safety, and industrial safety.

Here is how Mitchell Weiss, Executive Director of the Tobin Project, describes the project culminating in this volume:
To this end, in the fall of 2008 the Tobin Project approached leading scholars in the social sciences with an unusual request: we asked them to think about the topic of economic regulation and share key insights from their fields in a manner that would be accessible to both policymakers and the public. Because we were concerned that a conventional literature survey might obscure as much as it revealed, we asked instead that the writers provide a broad sketch of the most promising research in their fields pertaining to regulation; that they identify guiding principles for policymakers wherever possible; that they animate these principles with concrete policy proposals; and, in general, that they keep academic language and footnotes to a minimum. (5)
The lead essay is provided by Joseph Stiglitz, who looks more closely than previous decades of economists had done at the real consequences of market failure. Stiglitz puts the point about market failure very crisply:
Only under certain ideal circumstances may individuals, acting on their own, obtain “pareto efficient” outcomes, that is, situations in which no one can be made better off without making another worse off. These individuals involved must be rational and well informed, and must operate in competitive market- places that encompass a full range of insurance and credit markets. In the absence of these ideal circumstances, there exist government interventions that can potentially increase societal efficiency and/or equity. (11)
And regulation is unpopular -- with the businesses, landowners, and other powerful agents whose actions are constrained.
By its nature, a regulation restricts an individual or firm from doing what it otherwise would have done. Those whose behavior is so restricted may complain about, say, their loss of profits and potential adverse effects on innovation. But the purpose of government intervention is to address potential consequences that go beyond the parties directly involved, in situations in which private profit is not a good measure of social impact. Appropriate regulation may even advance welfare-enhancing innovations. (13)
Stiglitz pays attention to the pervasive problem of "regulatory capture":
The current system has made regulatory capture too easy. The voices of those who have benefited from lax regulation are strong; the perspectives of the investment community have been well represented. Among those whose perspectives need to be better represented are the laborers whose jobs would be lost by macro-mismanagement, and the pension holders whose pension funds would be eviscerated by excessive risk taking.

One of the arguments for a financial products safety commission, which would assess the efficacy and risks of new products and ascertain appropriate usage, is that it would have a clear mandate, and be staffed by people whose only concern would be protecting the safety and efficacy of the products being sold. It would be focused on the interests of the ordinary consumer and investors, not the interests of the financial institutions selling the products. (18)
It is very interesting to read Stiglitz's essay with attention to the economic focus he offers. His examples all come from the financial industry -- the risk at hand in 2008-2009. But the arguments apply equally profoundly to manufacturing, the pharmaceutical and food industries, energy industries, farming and ranching, and the for-profit education sector. At the same time the institutional details are different, and an essay on this subject with a focus on nuclear or chemical plants would probably identify a different set of institutional barriers to effective regulation.

Also particularly interesting is the contribution by Michael Barr, Eldar Shafir, and Sendhil Mullainathan on how behavioral perspectives on "rational action" can lead to more effective regulatory regimes. This essay pays close attention to the findings of experimental economics and behavioral economics, and the deviations from "pure economic rationality" that are pervasive in ordinary economic decision making. These features of decision-making are likely to be relevant to the effectiveness of a regulatory regime as well. Further, it suggests important areas of consumer behavior that are particularly subject to exploitative practices by financial companies -- creating a new need for regulation of these kinds of practices. Here is how they summarize their approach:
We propose a different approach to regulation. Whereas the classical perspective assumes that people generally know what is important and knowable, plan with insight and patience, and carry out their plans with wisdom and self-control, the central gist of the behavioral perspective is that people often fail to know and understand things that matter; that they misperceive, misallocate, and fail to carry out their intended plans; and that the context in which people function has great impact on their behavior, and, consequently, merits careful attention and constructive work. In our framework, successful regulation requires integrating this richer view of human behavior with our understanding of markets. Firms will operate on the contour de ned by this psychology and will respond strategically to regulations. As we describe above, because firms have a great deal of latitude in issue framing, product design, and so on, they have the capacity to a affect behavior and circumvent or pervert regulatory constraints. Ironically, firms’ capacity to do so is enhanced by their interaction with “behavioral” consumers (as opposed to the hypothetically rational actors of neoclassical economic theory), since so many of the things a regulator would find very hard to control (for example, frames, design, complexity, etc.) can greatly influence consumers’ behavior. e challenge of behaviorally informed regulation, therefore, is to be well designed and insightful both about human behavior and about the behaviors that firms are likely to exhibit in response to both consumer behavior and regulation. (55)
The contributions to this volume are very suggestive with regard to the issues of product safety, manufacturing safety, food and drug safety, and the like which constitute the larger core of the need for regulatory regimes. And the challenges faced in the areas of financial regulation discussed here are likely to be found to be illuminating in other sectors as well.

Thursday, April 5, 2018

Empowering the safety officer?


How can industries involving processes that create large risks of harm for individuals or populations be modified so they are more capable of detecting and eliminating the precursors of harmful accidents? How can nuclear accidents, aviation crashes, chemical plant explosions, and medical errors be reduced, given that each of these activities involves large bureaucratic organizations conducting complex operations and with substantial inter-system linkages? How can organizations be reformed to enhance safety and to minimize the likelihood of harmful accidents?

One of the lessons learned from the Challenger space shuttle disaster is the importance of a strongly empowered safety officer in organizations that deal in high-risk activities. This means the creation of a position dedicated to ensuring safe operations that falls outside the normal chain of command. The idea is that the normal decision-making hierarchy of a large organization has a built-in tendency to maintain production schedules and avoid costly delays. In other words, there is a built-in incentive to treat safety issues with lower priority than most people would expect.

If there had been an empowered safety officer in the launch hierarchy for the Challenger launch in 1986, there is a good chance this officer would have listened more carefully to the Morton-Thiokol engineering team's concerns about low temperature damage to O-rings and would have ordered a halt to the launch sequence until temperatures in Florida raised to the critical value. The Rogers Commission faulted the decision-making process leading to the launch decision in its final report on the accident (The Report of the Presidential Commission on the Space Shuttle Challenger Accident - The Tragedy of Mission 51-L in 1986 - Volume One, Volume Two, Volume Three).

This approach is productive because empowering a safety officer creates a different set of interests in the management of a risky process. The safety officer's interest is in safety, whereas other decision makers are concerned about revenues and costs, public relations, reputation, and other instrumental goods. So a dedicated safety officer is empowered to raise safety concerns that other officers might be hesitant to raise. Ordinary bureaucratic incentives may lead to underestimating risks or concealing faults; so lowering the accident rate requires giving some individuals the incentive and power to act effectively to reduce risks.

Similar findings have emerged in the study of medical and hospital errors. It has been recognized that high-risk activities are made less risky by empowering all members of the team to call a halt in an activity when they perceive a safety issue. When all members of the surgical team are empowered to halt a procedure when they note an apparent error, serious operating-room errors are reduced. (Here is a report from the American College of Obstetricians and Gynecologists on surgical patient safety; link. And here is a 1999 National Academy report on medical error; link.)

The effectiveness of a team-based approach to safety depends on one central fact. There is a high level of expertise embodied in the staff operating a surgical suite, an engineering laboratory, or a drug manufacturing facility. By empowering these individuals to stop a procedure when they judge there is an unrecognized error in play, this greatly extend the amount of embodied knowledge involved in a process. The surgeon, the commanding officer, or the lab director is no longer the sole expert whose judgments count.

But it also seems clear that these innovations don't work equally well in all circumstances. Take nuclear power plant operations. In Atomic Accidents: A History of Nuclear Meltdowns and Disasters: From the Ozark Mountains to Fukushima James Mahaffey documents multiple examples of nuclear accidents that resulted from the efforts of mid-level workers to address an emerging problem in an improvised way. In the case of nuclear power plant safety, it appears that the best prescription for safety is to insist on rigid adherence to pre-established protocols. In this case the function of a safety officer is to monitor operations to ensure protocol conformance -- not to exercise independent judgment about the best way to respond to an unfavorable reactor event.

It is in fact an interesting exercise to try to identify the kinds of operations in which these innovations are likely to be effective.

Here is a fascinating interview in Slate with Jim Bagian, a former astronaut, one-time director of the Veteran Administration's National Center for Patient Safety, and distinguished safety expert; link. Bagian emphasizes the importance of taking a system-based approach to safety. Rather than focusing on finding blame for specific individuals whose actions led to an accident, Bagian emphasizes the importance of tracing back to the institutional, organizational, or logistic background of the accident. What can be changed in the process -- of delivering medications to patients, of fueling a rocket, or of moving nuclear solutions around in a laboratory -- that make the likelihood of an accident substantially lower? (Here is a co-authored piece by Bagian and others on the topic of team-based patient safety in the operating room; link.)

The safety principles involved here seem fairly simple: cultivate a culture in which errors and near-misses are reported and investigated without blame; empower individuals within risky processes to halt the process if their expertise and experience indicates the possibility of a significant risky error; create individuals within organizations whose interests are defined in terms of the identification and resolution of unsafe practices or conditions; and share information about safety within the industry and with the public.

Sunday, March 25, 2018

Mechanisms, singular and general


Let's think again about the semantics of causal ascriptions. Suppose that we want to know what  caused a building crane to collapse during a windstorm. We might arrive at an account something like this:
  • An unusually heavy gust of wind at 3:20 pm, in the presence of this crane's specific material and structural properties, with the occurrence of the operator's effort to adjust the crane's extension at 3:21 pm, brought about cascading failures of structural elements of the crane, leading to collapse at 3:25 pm.
The process described here proceeds from the "gust of wind striking the crane" through an account of the material and structural properties of the device, incorporating the untimely effort by the operator to readjust the device's extension, leading to a cascade from small failures to a large failure. And we can identify the features of causal necessity that were operative at the several links of the chain.

Notice that there are few causal regularities or necessary and constant conjunctions in this account. Wind does not usually bring about the collapse of cranes; if the operator's intervention had occurred a few minutes earlier or later, perhaps the failure would not have occurred; and small failures do not always lead to large failures. Nonetheless, in the circumstances described here there is causal necessity extending from the antecedent situation at 3:15 pm to the full catastrophic collapse at 3:25 pm.

Does this narrative identify a causal mechanism? Are we better off describing this as a sequences of cause-effect sequences, none of which represents a causal mechanism per se? Or, on the contrary, can we look at the whole sequence as a single causal mechanism -- though one that is never to be repeated? Does a causal mechanism need to be a recurring and robust chain of events, or can it be a highly unique and contingent chain?

Most mechanisms theorists insist on a degree of repeatability in the sequences that they describe as "mechanisms". A causal mechanism is the triggering pathway through which one event leads to the production of another event in a range of circumstances in an environment. Fundamentally a causal mechanism is a "molecule" of causal process which can recur in a range of different social settings.

For example:
  • X typically brings about O.
Whenever this sequence of events occurs, in the appropriate timing, the outcome O is produced. This ensemble of events {X, O} is a single mechanism.

And here is the crucial point: to call this a mechanism requires that this sequence recurs in multiple instances across a range of background conditions.

This suggests an answer to the question about the collapsing crane: the sequence from gust to operator error to crane collapse is not a mechanism, but is rather a unique causal sequence. Each part of the sequence has a causal explanation available; each conveys a form of causal necessity in the circumstances. But the aggregation of these cause-effect connections falls short of constituting a causal mechanism because the circumstances in which it works are all but unique. A satisfactory causal explanation of the internal cause-effect pairs will refer to real repeatable mechanisms -- for example, "twisting a steel frame leads to a loss of support strength". But the concatenation does not add up to another, more complex, mechanism.

Contrast this with "stuck valve" accidents in nuclear power reactors. Valves control the flow of cooling fluids around the critical fuel. If the fuel is deprived of coolant it rapidly overheats and melts. A "stuck valve-loss of fluid-critical overheating" sequence is a recognized mechanism of nuclear meltdown, and has been observed in a range of nuclear-plant crises. It is therefore appropriate to describe this sequence as a genuine causal mechanism in the creation of a nuclear plant failure.

(Stuart Glennan takes up a similar question in "Singular and General Causal Relations: A Mechanist Perspective"; link.)

Friday, March 23, 2018

Machine learning


The Center for the Study of Complex Systems at the University of Michigan hosted an intensive day-long training on some of the basics of machine learning for graduate students and interested faculty and staff. Jake Hofman, a Microsoft researcher who also teaches this subject at Columbia University, was the instructor, and the session was both rigorous and accessible (link). Participants were asked to load a copy of R, a software package designed for the computations involved in machine learning and applied statistics, and numerous data sets were used as examples throughout the day. (Here is a brief description of R; link.) Thanks, Jake, for an exceptionally stimulating workshop.

So what is machine learning? Most crudely, it is a handful of methods through which researchers can sift through a large collection of events or objects, each of which has a very large number of properties, in order to arrive at a predictive sorting of the events or objects into a set of categories. The objects may be email texts or hand-printed numerals (the examples offered in the workshop), the properties may be the presence/absence of a long list of words or the presence of a mark in a bitmap grid, and the categories may be "spam/not spam" or the numerals between 0 and 9. But equally, the objects may be Facebook users, the properties "likes/dislikes" for a very large list of webpages, and the categories "Trump voter/Clinton voter". There is certainly a lot more to machine learning -- for example, these techniques don't shed light on the ways that AI Go systems improve their play. But it's good to start with the basics. (Here is a simple presentation of the basics of machine learning; link.)

Two intuitive techniques form the core of basic machine learning theory. The first makes use of the measurement of conditional probabilities in conjunction with Bayes' theorem to assign probabilities of the object being a Phi given the presence of properties xi. The second uses massively multi-factor regressions to calculate a probability for the event being Phi given regression coefficients ci.

Another basic technique is to treat the classification problem spatially. Use the large number of variables to define an n-dimensional space; then classify the object according to the average or majority value of its m-closest neighbors. (The neighbor number m might range from 1 to some manageable number such as 10.)


There are many issues of methodology and computational technique raised by this approach to knowledge. But these are matters of technique, and smart data science researchers have made great progress on them. More interesting here are epistemological issues: how good and how reliable are the findings produced by these approaches to the algorithmic treatment of large data sets? How good is the spam filter or the Trump voter detector when applied to novel data sets? What kind of errors would we anticipate this approach to be vulnerable to?

One important observation is that these methods are explicitly anti-theoretical. There is no place for discovery of causal mechanisms or underlying explanatory processes in these calculations. The researcher is not expected to provide a theoretical hypothesis about how this system of phenomena works. Rather, the techniques are entirely devoted to the discovery of persistent statistical associations among variables and the categories of the desired sorting. This is as close to Baconian induction as we get in the sciences (link). The approach is concerned about classification and prediction, not explanation. (Here is an interesting essay where Jake Hofman addresses the issues of prediction versus explanation of social data; link.)

A more specific epistemic concern that arises is the possibility that the training set of data may have had characteristics that are importantly different from comparable future data sets. This is the familiar problem of induction: will the future resemble the past sufficiently to support predictions based on past data? Spam filters developed in one email community may work poorly in an email community in another region or profession. We can label this as the problem of robustness.

Another limitation of this approach has to do with problems where our primary concern is with a singular event or object rather than a population. If we want to know whether NSA employee John Doe is a Russian mole, it isn't especially useful to know that his nearest neighbors in a multi-dimensional space of characteristics are moles; we need to know more specifically whether Doe himself has been corrupted by the Russians. If we want to know whether North Korea will explode a nuclear weapon against a neighbor in the next six months the techniques of machine learning seem to be irrelevant.

The statistical and computational tools of machine learning are indeed powerful, and seem to lead to results that are both useful and sometimes surprising. One should not imagine, however, that machine learning is a replacement for all other forms of research methodology in the social and behavioral sciences.

(Here is a brief introduction to a handful of the algorithms currently in use in machine-learning applications; link.)

Saturday, March 10, 2018

Technology lock-in accidents

image: diagram of molten salt reactor

Organizational and regulatory features are sometimes part of the causal background of important technology failures. This is particularly true in the history of nuclear power generation. The promise of peaceful uses of atomic energy was enormously attractive at the end of World War II. In abstract terms the possibility of generating useable power from atomic reactions was quite simple. What was needed was a controllable fission reaction in which the heat produced by fission could be captured to run a steam-powered electrical generator.

The technical challenges presented by harnessing nuclear fission in a power plant were large. Fissionable material needed to be produced as useable fuel sources. A control system needed to be designed to maintain the level of fission at a desired level. And, most critically, a system for removing heat from the fissioning fuel needed to be designed so that the reactor core would not overheat and melt down, releasing energy and radioactive materials into the environment.

Early reactor designs took different approaches to the heat-removal problem. Liquid metal reactors used a metal like sodium as the fluid that would run through the core removing heat to a heat sink for dispersal; and water reactors used pressurized water to serve that function. The sodium breeder reactor design appeared to be a viable approach, but incidents like the Fermi 1 disaster near Detroit cast doubt on the wisdom of using this approach. The reactor design that emerged as the dominant choice in civilian power production was the light water reactor. But light water reactors presented their own technological challenges, including most especially the risk of a massive steam explosion in the event of a power interruption to the cooling plant. In order to obviate this risk reactor designs involved multiple levels of redundancy to ensure that no such power interruption would occur. And much of the cost of construction of a modern light water power plant is dedicated to these systems -- containment vessels, redundant power supplies, etc. In spite of these design efforts, however, light water reactors at Three Mile Island and Fukushima did in fact melt down under unusual circumstances -- with particularly devastating results in Fukushima. The nuclear power industry in the United States essentially died as a result of public fears of the possibility of meltdown of nuclear reactors near populated areas -- fears that were validated by several large nuclear disasters.

What is interesting about this story is that there was an alternative reactor design that was developed by US nuclear scientists and engineers in the 1950s that involved a significantly different solution to the problem of harnessing the heat of a nuclear reaction and that posed a dramatically lower level of risk of meltdown and radioactive release. This is the molten salt reactor, first developed at the Oak Ridge National Laboratory facility in the 1950s. This was developed as part of the loopy idea of creating an atomic-powered aircraft that could remain aloft for months. This reactor design operates at atmospheric pressure, and the technological challenges of maintaining a molten salt cooling system are readily solved. The fact that there is no water involved in the cooling system means that the greatest danger in a nuclear power plant, a violent steam explosion, is eliminated entirely. Molten salt will not turn to steam, and the risk of a steam-based explosion is removed completely. Chinese nuclear energy researchers are currently developing a next generation of molten salt reactors, and there is a likelihood that they will be successful in designing a reactor system that is both more efficient in terms of cost and dramatically safer in terms of low-probability, high-cost accidents (link). This technology also has the advantage of making much more efficient use of the nuclear fuel, leaving a dramatically smaller amount of radioactive waste to dispose of.

So why did the US nuclear industry abandon the molten-salt reactor design? This seems to be a situation of lock-in by an industry and a regulatory system. Once the industry settled on the light water reactor design, it was implemented by the Nuclear Regulatory Commission in terms of the regulations and licensing requirements for new nuclear reactors. It was subsequently extremely difficult for a utility company or a private energy corporation to invest in the research and development and construction costs that would be associated with a radical change of design. There is currently an effort by an American company to develop a new-generation molten salt reactor, and the process is inhibited by the knowledge that it will take a minimum of ten years to gain certification and licensing for a possible commercial plant to be based on the new design (link).

This story illustrates the possibility that a process of technology development may get locked into a particular approach that embodies substantial public risk, and it may be all but impossible to subsequently adopt a different approach. In another context Thomas Hughes refers to this as technological momentum, and it is clear that there are commercial, institutional, and regulatory reasons for this "stickiness" of a major technology once it is designed and adopted. In the case of nuclear power the inertia associated with light water reactors is particularly unfortunate, given that it blocked other solutions that were both safer and more economical.

(Here is a valuable review of safety issues in the nuclear power industry; link. Also relevant is Robin Cowan, "Nuclear Power Reactors: A Study in Technological Lock-in"; link -- thanks, Özgür, for the reference.)

Saturday, March 3, 2018

Consensus and mutual understanding


Groups make decisions through processes of discussion aimed at framing a given problem, outlining the group's objectives, and arriving at a plan for how to achieve the objectives in an intelligent way. This is true at multiple levels, from neighborhood block associations to corporate executive teams to the President's cabinet meetings. However, collective decision-making through extended discussion faces more challenges than is generally recognized. Processes of collective deliberation are often haphazard, incomplete, and indeterminate.

What is collective deliberation about? It is often the case that a collaborative group or team has a generally agreed-upon set of goals -- let's say reducing the high school dropout rate in a city or improving morale on the plant floor or deterring North Korean nuclear expansion. The group comes together to develop a strategy and a plan for achieving the goal. Comments are offered about how to think about the problem, what factors may be relevant to bringing the problem about, what interventions might have a positive effect on the problem. After a reasonable range of conversation the group arrives at a strategy for how to proceed.

An idealized version of group problem-solving makes this process both simple and logical. The group canvases the primary facts available about the problem and its causes. The group recognized that there may be multiple goods involved in the situation, so the primary objective needs to be considered in the context of the other valuable goods that are part of the same bundle of activity. The group canvases these various goods as well. The group then canvases the range of interventions that are feasible in the existing situation, along with the costs and benefits of each strategy. Finally, the group arrives at a consensus about which strategy is best, given everything we know about the dynamics of the situation.

But anyone who has been part of a strategy-oriented discussion asking diverse parties to think carefully about a problem that all participants care about will realize that the process is rarely so amenable to simple logical development. Instead, almost every statement offered in the discussion is both ambiguous to some extent and factually contestable. Outcomes are sensitive to differences in the levels of assertiveness of various participants. Opinions are advanced as facts, and there is insufficient effort expended to validate the assumptions that are being made. Outcomes are also sensitive to the order and structure of the agenda for discussion. And finally, discussions need to be summarized; but there are always interpretive choices that need to be made in summarizing a complex discussion. Points need to be assigned priority and cogency; and different scribes will have different judgments about these matters.

Here is a problem of group decision-making that is rarely recognized but seems pervasive in the real world. This is the problem of recurring misunderstandings and ambiguities within the group of the various statements and observations that are made. The parties proceed on the basis of frameworks of assumptions that differ substantially from one person to the next but are never fully exposed. One person asserts that the school day should be lengthened, imagining a Japanese model of high school. Another thinks back to her own high school experience and agrees, thinking that five hours of instruction may well be more effective for learning than four hours. They agree about the statement but they are thinking of very different changes.

The bandwidth of a collective conversation about a complicated problem is simply too narrow to permit ambiguities and factually errors to be tracked down and sorted out. The conversation is invariably incomplete, and often takes shape because of entirely irrelevant factors like who speaks first or most forcefully. It is as if the space of the discussion is in two dimensions, whereas the complexity of the problem under review is in three dimensions.

The problem is exacerbated by the fact that participants sometimes have their own agendas and hobby horses that they continually re-inject into the discussion under varying pretexts. As the group fumbles towards possible consensus these fixed points coming from a few participants either need to be ruled out or incorporated -- and neither is a fully satisfactory result. If the point is ruled out some participants will believe their inputs are not respected, but if it is incorporated then the consensus has been deformed from a more balanced view of the issue.

A common solution to the problems of group deliberation mentioned here is to assign an expert facilitator or "muse" for the group who is tasked to build up a synthesis of the discussion as it proceeds. But it is evident that the synthesis is underdetermined by the discussion. Some points will be given emphasis over others, and a very different story line could have been reached that leads to different outcomes. This is the Rashomon effect applied to group discussions.

A different solution is to think of group discussion as simply an aid to a single decision maker -- a chief executive who listens to the various points of view and then arrives at her own formulation of the problem and a solution strategy. But of course this approach abandons the idea of reaching a group consensus in favor of the simpler problem of an individual reaching his or her own interpretation of the problem and possible solutions based on input from others.

This is a problem for organizations, both formal and informal, because every organization attempts to decide what to do through some kind of exploratory discussion. It is also a problem for the theory of deliberative democracy (link, link).

This suggests that there is an important problem of collective rationality that has not been addressed either by philosophy or management studies: the problem of aggregating beliefs, perceptions, and values held by diverse members of a group onto a coherent statement of the problem, causes, and solutions for the issue under deliberation. We would like to be able to establish processes that lead to rational and effective solutions to problems that incorporate available facts and judgments. Further we would like the outcomes to be non-arbitrary -- that is, given an antecedent set of factual and normative beliefs by the participants, we would like to imagine that there is a relatively narrow band of policy solutions that will emerge as the consensus or decision. We have theories of social choice -- aggregation of fixed preferences. And we have theories of rational decision-making and planning. But a deliberative group discussion of an important problem is substantially more complex. We need a philosophy of the meeting!

Tuesday, February 27, 2018

Computational social science


Is it possible to elucidate complex social outcomes using computational tools? Can we overcome some of the issues for social explanation posed by the fact of heterogeneous actors and changing social environments by making use of increasingly powerful computational tools for modeling the social world? Ken Kollman, John Miller, and Scott Page make the affirmative case to this question in their 2003 volume, Computational Models in Political Economy. The book focuses on computational approaches to political economy and social choice. Their introduction provides an excellent overview of the methodological and philosophical issues that arise in computational social science.
The subject of this book, political economy, naturally lends itself to a computational methodology. Much of political economy concerns institutions that aggregate the behavior of multiple actors, such as voters, politicians, organizations, consumers, and firms. Even when the interactions within and rules of a political or economic institution tion are relatively simple, the aggregate patterns that emerge can be difficult to predict and understand, particularly when there is no equilibrium. It is even more difficult to understand overlapping and interdependent institutions.... Computational methods hold the promise of enabling scholars to integrate aspects of both political and economic institutions without compromising fundamental features of either. (kl 27)
The most interesting of the approaches that they describe is the method of agent-based models (linklink, link). They summarize the approach in these terms:
The models typically have four characteristics, or methodological primitives: agents are diverse, agents interact with each other in a decentralized manner, agents are boundedly rational and adaptive, and the resulting patterns of outcomes comes often do not settle into equilibria.... The purpose of using computer programs in this second role is to study the aggregate patterns that emerge from the "bottom up." (kl 51)
Here is how the editors summarize the strengths of computational approaches to social science.
First, computational models are flexible in their ability to encode a wide range of behaviors and institutions. Any set of assumptions about agent behavior or institutional constraints that can be encoded can be analyzed. 
Second, as stated, computational models are rigorous in that conclusions follow from computer code that forces researchers to be explicit about assumptions. 
Third, while most mathematical models include assumptions so that an equilibrium exists, a system of interacting political actors need not settle into an equilibrium point. It can also cycle, or it can traverse an unpredictable path of outcomes. 
The great strength of computational models is their ability to uncover dynamic patterns. (kl 116)
And they offer a set of criteria of adequacy for ABM models. The model should explain the results; the researcher should check robustness; the model should build upon the past; the researcher should justify the use of the computer; and the researcher should question assumptions (kl 131).
To summarize, models should be evaluated based on their ability to give insight and understanding into old and new phenomena in the simplest way possible. Good, simple models, such as the Prisoner's Dilemma or Nash bargaining, with their ability to frame and shed light on important questions, outlast any particular tool or technique. (kl 139)
A good illustration of a computational approach to problems of political economy is the editors' own contribution to the volume, "Political institutions and sorting in a Tiebout model". A Tiebout configuration is a construct within public choice theory where citizens are permitted to choose among jurisdictions providing different bundles of goods.
In a Tiebout model, local jurisdictions compete for citizens by offering bundles of public goods. Citizens then sort themselves among jurisdictions according to their preferences. Charles M. Tiebout's (1956) original hypothesis challenged Paul Samuelson's (1954) conjecture that public goods could not be allocated efficiently. The Tiebout hypothesis has since been extended to include additional propositions. (kl 2012)
Using an agent-based model they compare different sets of political institutions at the jurisdiction level through which policy choices are made; and they find that there are unexpected outcomes at the population level that derive from differences in the institutions embodied at the jurisdiction level.
Our model departs from previous approaches in several important respects. First, with a few exceptions, our primary interest in comparing paring the performance of political institutions has been largely neglected in the Tiebout literature. A typical Tiebout model takes the political institution, usually majority rule, as constant. Here we vary institutions and measure performance, an approach more consistent with the literature on mechanism design. Second, aside from an example used to demonstrate the annealing phenomenon, we do not explicitly compare equilibria. (kl 2210)
And they find significant differences in collective behavior in different institutional settings.

ABM methodology is well suited to the kind of research problem the authors have posed here. The computational method permits intuitive illustration of the ways that individual preferences in specific settings aggregate to distinctive collective behaviors at the group level. But the approach is not so suitable to the analysis of social behavior that involves a higher degree of hierarchical coordination of individual behavior -- for example, in an army, a religious institution, or a business firm. Furthermore, the advantage of abstractness in ABM formulations is also a disadvantage, in that it leads researchers to ignore some of the complexity and nuance of local circumstances of action that lead to significant differences in outcome.


Saturday, February 24, 2018

Nuclear accidents


diagrams: Chernobyl reactor before and after

Nuclear fission is one of the world-changing discoveries of the mid-twentieth century. The atomic bomb projects of the United States led to the atomic bombing of Japan in August 1945, and the hope for limitless electricity brought about the proliferation of a variety of nuclear reactors around the world in the decades following World War II. And, of course, nuclear weapons proliferated to other countries beyond the original circle of atomic powers.

Given the enormous energies associated with fission and the dangerous and toxic properties of radioactive components of fission processes, the possibility of a nuclear accident is a particularly frightening one for the modern public. The world has seen the results of several massive nuclear accidents -- Chernobyl and Fukushima in particular -- and the devastating results they have had on human populations and the social and economic wellbeing of the regions in which they occurred.

Safety is therefore a paramount priority in the nuclear industry, both in research labs and military and civilian applications. So what is the situation of safety in the nuclear sector? Jim Mahaffey's Atomic Accidents: A History of Nuclear Meltdowns and Disasters: From the Ozark Mountains to Fukushima is a detailed and carefully researched attempt to answer this question. And the information he provides is not reassuring. Beyond the celebrated and well-known disasters at nuclear power plants (Three Mile Island, Chernobyl, Fukushima), Mahaffey refers to hundreds of accidents involving reactors, research laboratories, weapons plants, and deployed nuclear weapons that have had less public awareness. These accidents resulted in a very low number of lives lost, but their frequency is alarming. They are indeed "normal accidents" (Perrow, Normal Accidents: Living with High-Risk Technologies. For example:
  • a Japanese fishing boat is contaminated by fallout from Castle Bravo test of hydrogen bomb; lots of radioactive fish at the markets in Japan (March 1, 1954) (kl 1706)
  • one MK-6 atomic bomb is dropped on Mars Bluff, South Carolina, after a crew member accidentally pulled the emergency bomb release handle (February 5, 1958) (kl 5774)
  • Fermi 1 liquid sodium plutonium breeder reactor experiences fuel meltdown during startup trials near Detroit (October 4, 1966) (kl 4127)
Mahaffey also provides detailed accounts of the most serious nuclear accidents and meltdowns during the past forty years, Three Mile Island, Chernobyl, and Fukushima.

The safety and control of nuclear weapons is of particular interest. Here is Mahaffey's summary of "Broken Arrow" events -- the loss of atomic and fusion weapons:
Did the Air Force ever lose an A-bomb, or did they just misplace a few of them for a short time? Did they ever drop anything that could be picked up by someone else and used against us? Is humanity going to perish because of poisonous plutonium spread that was snapped up by the wrong people after being somehow misplaced? Several examples will follow. You be the judge. 
Chuck Hansen [U.S. Nuclear Weapons - The Secret History] was wrong about one thing. He counted thirty-two “Broken Arrow” accidents. There are now sixty-five documented incidents in which nuclear weapons owned by the United States were lost, destroyed, or damaged between 1945 and 1989. These bombs and warheads, which contain hundreds of pounds of high explosive, have been abused in a wide range of unfortunate events. They have been accidentally dropped from high altitude, dropped from low altitude, crashed through the bomb bay doors while standing on the runway, tumbled off a fork lift, escaped from a chain hoist, and rolled off an aircraft carrier into the ocean. Bombs have been abandoned at the bottom of a test shaft, left buried in a crater, and lost in the mud off the coast of Georgia. Nuclear devices have been pounded with artillery of a foreign nature, struck by lightning, smashed to pieces, scorched, toasted, and burned beyond recognition. Incredibly, in all this mayhem, not a single nuclear weapon has gone off accidentally, anywhere in the world. If it had, the public would know about it. That type of accident would be almost impossible to conceal. (kl 5527)
There are a few common threads in the stories of accident and malfunction that Mahaffey provides. First, there are failures of training and knowledge on the part of front-line workers. The physics of nuclear fission are often counter-intuitive, and the idea of critical mass does not fully capture the danger of a quantity of fissionable material. The geometry of the storage of the material makes a critical difference in going critical. Fissionable material is often transported and manipulated in liquid solution; and the shape and configuration of the vessel in which the solution is held makes a difference to the probability of exponential growth of neutron emission -- leading to runaway fission of the material. Mahaffey documents accidents that occurred in nuclear materials processing plants that resulted from plant workers applying what they knew from industrial plumbing to their efforts to solve basic shop-floor problems. All too often the result was a flash of blue light and the release of a great deal of heat and radioactive material.

Second, there is a fault at the opposite end of the knowledge spectrum -- the tendency of expert engineers and scientists to believe that they can solve complicated reactor problems on the fly. This turned out to be a critical problem at Chernobyl (kl 6859).
The most difficult problem to handle is that the reactor operator, highly trained and educated with an active and disciplined mind, is liable to think beyond the rote procedures and carefully scheduled tasks. The operator is not a computer, and he or she cannot think like a machine. When the operator at NRX saw some untidy valve handles in the basement, he stepped outside the procedures and straightened them out, so that they were all facing the same way. (kl 2057)
There are also clear examples of inappropriate supervision in the accounts shared by Mahaffey. Here is an example from Chernobyl.
[Deputy chief engineer] Dyatlov was enraged. He paced up and down the control panel, berating the operators, cursing, spitting, threatening, and waving his arms. He demanded that the power be brought back up to 1,500 megawatts, where it was supposed to be for the test. The operators, Toptunov and Akimov, refused on grounds that it was against the rules to do so, even if they were not sure why. 
Dyatlov turned on Toptunov. “You lying idiot! If you don’t increase power, Tregub will!”  
Tregub, the Shift Foreman from the previous shift, was officially off the clock, but he had stayed around just to see the test. He tried to stay out of it. 
Toptunov, in fear of losing his job, started pulling rods. By the time he had wrestled it back to 200 megawatts, 205 of the 211 control rods were all the way out. In this unusual condition, there was danger of an emergency shutdown causing prompt supercriticality and a resulting steam explosion. At 1: 22: 30 a.m., a read-out from the operations computer advised that the reserve reactivity was too low for controlling the reactor, and it should be shut down immediately. Dyatlov was not worried. “Another two or three minutes, and it will be all over. Get moving, boys! (kl 6887)
This was the turning point in the disaster.

A related fault is the intrusion of political and business interests into the design and conduct of high-risk nuclear actions. Leaders want a given outcome without understanding the technical details of the processes they are demanding; subordinates like Toptunov are eventually cajoled or coerced into taking the problematic actions. The persistence of advocates for liquid sodium breeder reactors represents a higher-level example of the same fault. Associated with this role of political and business interests is an impulse towards secrecy and concealment when accidents occur and deliberate understatement of the public dangers created by an accident -- a fault amply demonstrated in the Fukushima disaster.

Atomic Accidents provides a fascinating history of events of which most of us are unaware. The book is not primarily intended to offer an account of the causes of these accidents, but rather the ways in which they unfolded and the consequences they had for human welfare. (Generally speaking his view is that nuclear accidents in North America and Western Europe have had remarkably few human casualties.) And many of the accidents he describes are exactly the sorts of failures that are common in all largescale industrial and military processes.

(Largescale technology failure has come up frequently here. See these posts for analysis of some of the organizational causes of technology failure (link, link, link).)

Sunday, February 11, 2018

Folk psychology and Alexa


Paul Churchland made a large splash in the philosophy of mind and cognitive science several decades ago when he cast doubt on the categories of "folk psychology" -- the ordinary and commonsensical concepts we use to describe and understand each other's mental lives. In Paul Churchland and Patricia Churchland, On the Contrary: Critical Essays, 1987-1997, Paul Churchland writes:
"Folk psychology" denotes the prescientific, commonsense conceptual framework that all normally socialized humans deploy in order to comprehend, predict, explain, and manipulate the behavior of . humans and the higher animals. This framework includes concepts such as belief, desire, pain pleasure, love, hate, joy, fear, suspicion, memory, recognition, anger, sympathy, intention, and so forth.... Considered as a whole, it constitutes our conception of what a person is. (3)
Churchland does not doubt that we ordinary human beings make use of these concepts in everyday life, and that we could not dispense with them. But he is not convinced that they have a scientifically useful role to play in scientific psychology or cognitive science.

In our ordinary dealings with other human beings it is both important and plausible that the framework of folk psychology is approximately true. Our fellow human beings really do have beliefs, desires, fears, and other mental capacities, and these capacities are in fact the correct explanation of their behavior. How these capacities are realized in the central nervous system is largely unknown, though as materialists we are committed to the belief that there are such underlying neurological functionings. But eliminative materialism doesn't have a lot of credibility, and the treatment of mental states as epiphenoma to the neurological machinery isn't convincing either.

These issues had the effect of creating a great deal of discussion in the philosophy of psychology since the 1980s (link). But the topic seems all the more interesting now that tens of millions of people are interacting with Alexa, Siri, and the Google Assistant, and are often led to treat the voice as emanating from an intelligent (if not very intelligent) entity. I presume that it is clear that Alexa and her counterparts are currently "question bots" with fairly simple algorithms underlying their capabilities. But how will we think about the AI agent when the algorithms are not simple; when the agents can sustain lengthy conversations; and when the interactions give the appearance of novelty and creativity?

It turns out that this is a topic that AI researchers have thought about quite a bit. Here is the abstract of "Understanding Socially Intelligent Agents—A Multilayered Phenomenon", a fascinating 2001 article in IEEE by Perrson, Laaksolahti, and Lonnqvist (link):
The ultimate purpose with socially intelligent agent (SIA) technology is not to simulate social intelligence per se, but to let an agent give an impression of social intelligence. Such user-centred SIA technology, must consider the everyday knowledge and expectations by which users make sense of real, fictive, or artificial social beings. This folk-theoretical understanding of other social beings involves several, rather independent levels such as expectations on behavior, expectations on primitive psychology, models of folk-psychology, understanding of traits, social roles, and empathy. The framework presented here allows one to analyze and reconstruct users' understanding of existing and future SIAs, as well as specifying the levels SIA technology models in order to achieve an impression of social intelligence.
The emphasis here is clearly on the semblance of intelligence in interaction with the AI agent, not the construction of a genuinely intelligent system capable of intentionality and desire. Early in the article they write:
As agents get more complex, they will land in the twilight zone between mechanistic and living, between dead objects and live beings. In their understanding of the system, users will be tempted to employ an intentional stance, rather than a mechanistic one.. Computer scientists may choose system designs that encourage or discourage such anthropomorphism. Irrespective of which, we need to understand how and under what conditions it works.
But the key point here is that the authors favor an approach in which the user is strongly led to apply the concepts of folk psychology to the AI agent; and yet in which the underlying mechanisms generating the AI's behavior completely invalidate the application of these concepts. (This approach brings to mind Searle's Chinese room example concerning "intelligent" behavior; link.) This is clearly the approach taken by current designs of AI agents like Siri; the design of the program emphasizes ordinary language interaction in ways that lead the user to interact with the agent as an intentional "person".

The authors directly confront the likelihood of "folk-psychology" interactions elicited in users by the behavior of AI agents:
When people are trying to understand the behaviors of others, they often use the framework of folk-psychology. Moreover, people expect others to act according to it. If a person’s behavior blatantly falls out of this framework, the person would probably be judged “other” in some, e.g., children, “crazies,” “psychopaths,” and “foreigners.” In order for SIAs to appear socially intelligent, it is important that their behavior is understandable in term of the folk-psychological framework. People will project these expectations on SIA technology and will try to attribute mental states and processes according to it. (354)
And the authors make reference to several AI constructs that are specifically designed to elicit a folk-psychological response from the users:
In all of these cases, the autonomous agents have some model of the world, mind, emotions, and of their present internal state. This does not mean that users automatically infer the “correct” mental state of the agent or attribute the same emotion that the system wants to convey. However, with these background models regulating the agent’s behavior the system will support and encourage the user to employ her faculty of folk-psychology reasoning onto the agent. Hopefully, the models generate consistently enough behavior to make folk-psychology a framework within which to understand and act upon the interactive characters. (355)
The authors emphasize the instrumentalism of their recommended approach to SIA capacities from beginning to end:
In order to develop believable SIAs we do not have to know how beliefs-desires and intentions actually relate to each other in the real minds of real people. If we want to create the impression of an artificial social agent driven by beliefs and desires, it is enough to draw on investigations on how people in different cultures develop and use theories of mind to understand the behaviors of others. SIAs need to model the folk-theory reasoning, not the real thing. To a shallow AI approach, a model of mind based on folk-psychology is as valid as one based on cognitive theory. (349)
This way of approaching the design of AI agents suggests that the "folk psychology" interpretation of Alexa's more capable successors will be fundamentally wrong. The agent will not be conscious, intentional, or mental; but it will behave in ways that make it almost impossible not to fall into the trap of anthropomorphism. And this in turn brings us back to Churchland and the critique of folk psychology in the human-human cases. If computer-assisted AI agents can be completely persuasive as mentally structured actors, then why are we so confident that this is not the case for fellow humans as well?

Friday, February 9, 2018

Cold war history from an IR perspective


Odd Arne Westad's The Cold War: A World History is a fascinating counterpoint to Tony Judt's Postwar: A History of Europe Since 1945. There are some obvious differences -- notably, Westad takes a global approach to the Cold War, with substantial attention to the dynamics of Cold War competition in Asia, Africa, Latin America, and the Middle East, as well as Europe, whereas Judt's book is primarily focused on the politics and bi-polar competition of Communism and liberal democratic capitalism in Europe. Westad is a real expert on East Asia, so his global perspectives on the period are very well informed. Both books provide closely reasoned and authoritative interpretations of the large events of the 1950s through the 1990s. So it is very interesting to compare them from an historiographic point of view.

The feature that I'd like to focus on here is Westad's perspective on these historical developments from the point of view of an international-relations conceptual framework. Westad pays attention to the economic and social developments that were underway in the West and the Eastern bloc; but his most frequent analytical question is, what were the intentions, beliefs, and strategies of the nations which were involved in competition throughout the world in this crucial period of world history? Ideology and social philosophy play a large role in his treatment. Judt too offers interpretations of what leaders like Truman, Gorbachev, or Thatcher were trying to accomplish; but the focus of his historiographical thinking is more on the circumstances of ordinary life and the social, economic, and political changes through which ordinary people shaped their political identities across Europe. In Westad's framework there is an underlying emphasis on strategic rationality -- and failures of rationality -- by leaders and national governments that is more muted in Judt's analysis. The two perspectives are not incompatible; but they are significantly different.

Here are a few illustrative passages from Westad's book revealing the orientation of his interpretation around interest and ideology:
The Cold War originated in two processes that took place around the turn of the twentieth century. One was the transformation of the United States and Russia into two supercharged empires with a growing sense of international mission. The other was the sharpening of the ideological divide between capitalism and its critics. These came together with the American entry into World War I and with the Russian Revolution of 1917, and the creation of a Soviet state as an alternative vision to capitalism. (19)
The contest between the US and the USSR over the future of Germany is a good example.
The reasons why Stalin wanted a united Germany were exactly the same reasons why the United States, by 1947, did not. A functional German state would have to be integrated with western Europe in order to succeed, Washington found. And that could not be achieved if Soviet influence grew throughout the country. This was not only a point about security. It was also about economic progress. The Marshall Plan was intended to stimulate western European growth through market integration, and the western occupation zones in Germany were crucial for this project to succeed. Better, then, to keep the eastern zone (and thereby Soviet pressure) out of the equation. After two meetings of the allied foreign ministers in 1947 had failed to agree on the principles for a peace treaty with Germany (and thereby German reunification), the Americans called a conference in London in February 1948 to which the Soviets were not invited.(109)
And the use of development aid during reconstruction was equally strategic:
For Americans and western European governments alike, a major part of the Marshall Plan was combatting local Communist parties. Some of it was done directly, through propaganda. Other effects on the political balance were secondary or even coincidental. A main reason why Soviet-style Communism lost out in France or Italy was simply that their working classes began to have a better life, at first more through government social schemes than through salary increases. The political miscalculations of the Communist parties and the pressure they were under from Moscow to disregard the local political situation in order to support the Soviet Union also contributed. When even the self-inflicted damage was not enough, such as in Italy, the United States experimented with covert operations to break Communist influence. (112)
Soviet miscalculations were critical in the development of east-west power relations. Westad treats the Berlin blockade in these terms:
The Berlin blockade, which lasted for almost a year, was a Soviet political failure from start to finish. It failed to make west Berlin destitute; a US and British air-bridge provided enough supplies to keep the western sectors going. On some days aircraft landed at Tempelhof Airport at three minute intervals. Moscow did not take the risk of ordering them to be shot down. But worse for Stalin: the long-drawn-out standoff confirmed even to those Germans who had previously been in doubt that the Soviet Union could not be a vehicle for their betterment. The perception was that Stalin was trying to starve the Berliners, while the Americans were trying to save them. On the streets of Berlin more than half a million protested Soviet policies. (116)
I don't want to give the impression that Westad's book ignores non-strategic aspects of the period. His treatment of McCarthyism, for example, is quite astute:
The series of hearings and investigations, which accusations such as McCarthy’s gave rise to, destroyed people’s lives and careers. Even for those who were cleared, such as the famous central Asia scholar Owen Lattimore, some of the accusations stuck and made it difficult to find employment. It was, as Lattimore said in his book title from 1950, Ordeal by Slander. For many of the lesser known who were targeted—workers, actors, teachers, lawyers—it was a Kafkaesque world, where their words were twisted and used against them during public hearings by people who had no knowledge of the victims or their activities. Behind all of it was the political purpose of harming the Administration, though even some Democrats were caught up in the frenzy and the president himself straddled the issue instead of publicly confronting McCarthy. McCarthyism, as it was soon called, reduced the US standing in the world and greatly helped Soviet propaganda, especially in western Europe. (120)
It is interesting too to find areas of disagreement between the two historians. Westad's treatment of Leonid Brezhnev is sympathetic:
Brezhnev and his colleagues’ mandate was therefore quite clear. Those who had helped put them in power wanted more emphasis on planning, productivity growth, and welfare. They wanted a leadership that avoided unnecessary crises with the West, but also stood up for Soviet gains and those of Communism globally. Brezhnev was the ideal man for the purpose. As a leader, he liked to consult with others, even if only to bring them onboard with decisions already taken. After the menacing Stalin and the volatile Khrushchev, Brezhnev was likeable and “comradely”; he remembered colleagues’ birthdays and the names of their wives and children. His favorite phrases were “normal development” and “according to plan.” And the new leader was easily forgiven a certain vagueness in terms of overall reform plans as long as he emphasized stability and year-on-year growth in the Soviet economy.... Contrary to what is often believed, the Soviet economy was not a disaster zone during the long reign of Leonid Brezhnev and the leadership cohort who came into power with him. The evidence points to slow and limited but continuous growth, within the framework provided by the planned economy system. The best estimates that we have is that the Soviet economy as a whole grew on average 2.5 to 3 percent per year during the 1960s and ’70s. (367)
By contrast, Judt treats Brezhnev less sympathetically and as a more minor figure:
The economic reforms of the fifties and sixties were from the start a fitful attempt to patch up a structurally dysfunctional system. To the extent that they implied a half-hearted willingness to decentralize economic decisions or authorize de facto private production, they were offensive to hardliners among the old guard. But otherwise the liberalizations undertaken by Khrushchev, and after him Brezhnev, presented no immediate threat to the network of power and patronage on which the Soviet system depended. Indeed, it was just because economic improvements in the Soviet bloc were always subordinate to political priorities that they achieved so very little. (Judt, 424)
Perhaps the most striking contrast between these two books is the scope that each provides. Judt is focused on the development of postwar Europe, and he does an unparalleled job of providing both detail and interpretation of the developments over these decades in well over a dozen countries. Westad is interested in providing a global history of the Cold War, and his expertise on Asian history and politics during this period, as well as his wide-ranging knowledge of developments in Africa, the Middle East, and Latin America, permits him to succeed in this goal. His representation of this history is nuanced and insightful at every turn. The Cold War unavoidably involves a focus on the USSR and the US and their blocs as central players; but Westad's account is by no means eurocentric. His treatments of India, China, and Southeast Asia are particularly excellent, and his account of turbulence and faulty diplomacy in the Middle East is particularly timely for the challenges we face today.

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Here are a couple of interesting video lectures by Westad and Judt.