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 OneVolume TwoVolume 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?

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.

The second American revolution

The first American Revolution broke the bonds of control exercised by a colonial power over the actions and aspirations of a relatively small number of people in North America in 1776 — about 2.5 million people. The second American Revolution promises to affect vastly larger numbers of Americans and their freedom, and it is not yet complete. (There were about 19 million African-Americans in the United States in 1960.)

This is the Civil Rights revolution, which has been underway since 1865 (the end of the Civil War); which took increased urgency in the 1930s through the 1950s (the period of Jim Crow laws and a coercive, violent form of white supremacy); and which came to fruition in the 1960s with collective action by thousands of ordinary people and the courageous, wise leadership of men and women like Dr. Martin Luther King, Jr. When we celebrate the life and legacy of MLK, it is this second American revolution that is the most important piece of his legacy.

And this is indeed a revolution. It requires a sustained and vigilant struggle against a powerful status quo; it requires gaining political power and exercising political power; and it promises to enhance the lives, dignity, and freedoms of millions of Americans.

This revolution is not complete. The assault on voting rights that we have seen in the past decade, the persistent gaps that exist in income, health, and education between white Americans and black Americans, the ever-more-blatant expressions of racist ideas at the highest level — all these unmistakeable social facts establish that the struggle for racial equality is not finished.

Dr. King’s genius was his understanding from early in his vocation that change would require courage and sacrifice, and that it would also require great political wisdom. It was Dr. King’s genius to realize that enduring social change requires changing the way that people think; it requires moral change as well as structural change. This is why Dr. King’s profoundly persuasive rhetoric was so important; he was able to express through his speeches and his teaching a set of moral values that almost all Americans could embrace. And by embracing these values they themselves changed.

The struggle in South Africa against apartheid combined both aspects of this story — anti-colonialism and anti-racism. The American civil rights movement focused on uprooting the system of racial oppression and discrimination this country had created since Reconstruction. It focused on creating the space necessary for African-American men and women, boys and girls, to engage in their own struggles for freedom and for personal growth. It insisted upon the same opportunities for black children that were enjoyed by the children of the majority population.

Will the values of racial equality and opportunity prevail? Will American democracy finally embrace and make real the values of equality, dignity, and opportunity that Dr. King expressed so eloquently? Will the second American revolution finally erase the institutions and behaviors of several centuries of oppression?

Dr. King had a fundamental optimism that was grounded in his faith: “the arc of the moral universe is long, but it bends toward justice.” But of course we understand that only long, sustained commitment to justice can bring about this arc of change. And the forces of reaction are particularly strong in the current epoch of political struggle. So it will require the courage and persistence of millions of Americans to these ideals if racial justice is finally to prevail.

Here is an impromptu example of King’s passionate commitment to social change through non-violence. This was recorded in Yazoo City, Mississippi in 1966, during James Meredith’s March against Fear.

Is history probabilistic?

Many of our intuitions about causality are driven by a background assumption of determinism: one cause, one effect, always. But it is evident in many realms — including especially the social world — that causation is probabilistic. A cause makes its effects more likely than they would be in the absence of the cause. Exposure to a Zika-infected mosquito makes it more likely that the individual will acquire the illness; but many people exposed to Zika mosquitoes do not develop the illness. Wesley Salmon formulated this idea in terms of the concept of causal relevance: C is causally relevant to O just in case the conditional probability of O given C is different from the probability of O. (Some causes reduce the probability of their outcomes.)

There is much more to say about this model — chiefly the point that causes rarely exercise their powers in isolation from other factors. So, as J.L. Mackie worked out in The Cement of the Universe: A Study of Causation, we need to be looking for conjunctions of factors that jointly affect the probability of the occurrence of O. Causation is generally conjunctural. But the essential fact remains: no matter how many additional factors we add to the analysis, we are still unlikely to arrive at deterministic causal statements: “whenever ABCDE occurs, O always occurs.”

But here is another kind of certainty that also arises in a probabilistic world. When sequences are governed by objective probabilities, we are uncertain about any single outcome. But we can be highly confident that a long series of trials will converge around the underlying probability. In an extended series of throws of a fair pair of dice the frequency of throwing a 7 will converge around 6/36, whereas the frequency of throwing a 12 will converge around 1/36. So we can be confident that the eventual set of outcomes will look like the histogram above.

Can we look at history as a vast series of stochastic events linked by relations of probabilistic causation? And does this permit us to make historical predictions after all?

Let’s explore that idea. Imagine that history is entirely the product of a set of stochastic events connected with each other by fixed objective probabilities. And suppose we are interested in a particular kind of historical outcome — say the emergence of central states involving dictatorship and democracy. We might represent this situation as a multi-level process of social-political complexification — a kind of primordial soup of political development by opportunistic agents within a connected population in a spatial region. Suppose we postulate a simple political theory of competition and cooperation driving patterns of alliance formation, institution formation, and the aggregation of power by emerging institutions. (This sounds somewhat similar to Tilly’s theory of state formation in Coercion, Capital and European States, A.D. 990 – 1992 and to Michael Mann’s treatment of civilizations in The Sources of Social Power: Volume 1, A History of Power from the Beginning to AD 1760.)

Finally we need to introduce some kind of mechanism of invention — of technologies, institutions, and values systems. This is roughly analogous to the mechanism of genetic mutation in the evolution of life.

Now we are ready to ask some large historical questions about state formation in numerous settings. What is the likelihood of the emergence of a stable system of self-governing communities? What is the likelihood that a given population will arrive at a group of inventions involving technology, institutions, and values systems that permit the emergence of central state capable of imposing its will over distance, collecting revenues to support its activities, and conducting warfare? And what is the likelihood of local failure, resulting in the extinction of the local population? We might look at the historical emergence of various political-economic forms such as plunder societies (Genghis Khan), varieties of feudalism, and medieval city states as different outcomes resulting from the throw of the dice in these different settings.

Self-governance seems like a fairly unlikely outcome within this set of assumptions. Empire and dictatorship seem like the more probable outcomes of the interplay of self-interest, power, and institutions. In order to get self-governance out of processes like these we need to identify a mechanism through which collective action by subordinate agents is possible. Such mechanisms are indeed familiar — the pressures by subordinate but powerful actors in England leading to the reform of absolutist monarchy, the overthrow of the French monarchy by revolutionary uprisings, the challenges to the Chinese emperor represented by a series of major rebellions in the nineteenth century. But such counter-hegemonic processes are often failures, and even when successful they are often coopted by powerful insiders. These possibilities lead us to estimate a low likelihood of stable self-governance.

So this line of thought suggests that a stochastic model of the emergence of central states is possible but discouraging. Assign probabilities to the various kinds of events that need to occur at each of the several stages of civilizational development; run the model a large number of times; and you have a Monte Carlo model of the emergence of dictatorship and democracy. And the discouraging likelihood is that democratic self-governance is a rare outcome.

However, there are several crucial flaws in this analysis. First, the picture is flawed by the fact that history is made by purposive agents, not algorithms or mechanical devices. These actors are not characterized by fixed objective probabilities. Historical actors have preferences and take actions to influence outcomes at crucial points. Second, agents are not fixed over time, but rather develop through learning. They are complex adaptive agents. They achieve innovations in their practices just as the engineers and bureaucrats do. They develop and refine repertoires of resistance (Tilly). So each play of the game of political history is novel in important respects. History is itself influenced by previous history.

Finally, there is the familiar shortcoming of simulations everywhere: a model along these lines unavoidably requires making simplifying assumptions about the causal factors in play. And these simplifications can be shown to have important consequences for the sensitivity of the model.

So it is important to understand that social causation is generally probabilistic; but this fact does not permit us to assign objective probabilities to the emergence of central states, dictatorships, or democracies.

(See earlier posts on more successful efforts to use Bayesian methods to assess the likelihood of the emergence of specific outcomes in constrained historical settings;
link, link.)

Organizational dysfunction

What is a dysfunction when it comes to the normal workings of an organization? In order to identify dysfunctions we need to have a prior conception of the “purpose” or “agreed upon goals” of an organization. Fiscal agencies collect taxes; child protection services work to ensure that foster children are placed in safe and nurturing environments; air travel safety regulators ensure that aircraft and air fields meet high standards of maintenance and operations; drug manufacturers produce safe, high-quality medications at a reasonable cost. A dysfunction might be defined as an outcome for an organization or institution that runs significantly contrary to the purpose of the organization. We can think of major failures in each of these examples.

But we need to make a distinction between failure and dysfunction. The latter concept is systemic, having to do with the design and culture of the organization. Failure can happen as a result of dysfunctional arrangements; but it can happen as a result of other kinds of factors as well. For example, the Tylenol crisis of 1982 resulted from malicious tampering by an external third party, not organizational dysfunction.

Here is an example from a Harvard Business Review article by Gill Corkindale indicating some of the kinds of dysfunction that can be identified in contemporary business organizations:

Poor organizational design and structure results in a bewildering morass of contradictions: confusion within roles, a lack of co-ordination among functions, failure to share ideas, and slow decision-making bring managers unnecessary complexity, stress, and conflict. Often those at the top of an organization are oblivious to these problems or, worse, pass them off as or challenges to overcome or opportunities to develop. (link)

And the result of failures like these is often poor performance and sometimes serious crisis for the organization or its stakeholders.

But — as in software development — it is sometimes difficult to distinguish between a feature and a bug. What is dysfunctional for the public may indeed be beneficial for other actors who are in a position to influence the design and workings of the organization. This is the key finding of researchers like Jack Knight, who argues in Institutions and Social Conflict for the prevalence of conflicting interests in the design and operations of many institutions and organizations; link. And it follows immediately from the approach to organizations encapsulated in the Fligstein and McAdam theory of strategic action fields (link).

There is an important related question to consider: why do recognized dysfunctional characteristics persist? When a piano is out of tune, the pianist and the audience insist on a professional tuning. When the Nuclear Regulatory Commission persistently fails to enforce its regulations through rigorous inspection protocols, nothing happens (Union of Concerned Scientists, link; Perrow, link). Is it that the individuals responsible for the day-to-day functioning of the organization are complacent or unmotivated? Is it that there are contrary pressures that arise to oppose corrective action? Or, sometimes, is it that the adjustments needed to correct one set of dysfunctions can be expected to create another, even more harmful, set of bad outcomes?

One intriguing hypothesis is that correction of dysfunctions requires observation, diagnosis, and incentive alignment. It is necessary that some influential actor or group should be able to observe the failure; it should be possible to trace the connection between the failure and the organizational features that lead to it; and there should be some way of aligning the incentives of the powerful actors within and around the organization so that their best interests are served by their taking the steps necessary to correct the dysfunction. If any of these steps is blocked, then a dysfunctional organization can persist indefinitely.

The failures of Soviet agriculture were observable and the links between organization and farm inefficiency were palpable; but the Soviet public had not real leverage with respect to the ministries and officials who ran the agricultural system. Therefore Soviet officials had no urgent incentive to reform agriculture. So the dysfunctions of collective farming were not corrected until the collapse of the USSR. A dysfunction in a corporation within a market economy that significantly impacts its revenues and profits will be noticed by shareholders, and pressure will be exerted to correct the dysfunction. The public has a strong interest in nuclear reactor safety; but its interests are weak and diffused when compared to the interests of the industry and its lobbyists; so Congressional opposition to reform of the agency remains strong. The same could be said with respect to the current crisis at the Consumer Financial Protection Bureau; the influence of the financial industry and its lobbyists can be concentrated in a way that the interests of the public cannot.

Charles Perrow has written extensively on the failures of the US regulatory sector (link). Here is his description of regulatory capture in the nuclear power industry:

Nuclear safety is problematic when nuclear plants are in private hands because private firms have the incentive and, often, the political and economic power to resist effective regulation. That resistance often results in regulators being captured in some way by the industry. In Japan and India, for example, the regulatory function concerned with safety is subservient to the ministry concerned with promoting nuclear power and, therefore, is not independent. The United States had a similar problem that was partially corrected in 1975 by putting nuclear safety into the hands of an independent agency, the Nuclear Regulatory Commission (NRC), and leaving the promotion of nuclear power in the hands of the Energy Department. Japan is now considering such a separation. It should make one. Since the accident at Fukushima, many observers have charged that there is a revolving door between industry and the nuclear regulatory agency in Japan — what the New York Times called a “nuclear power village” — compromising the regulatory function. (link)

Ten years of Understanding Society

 

This month marks the tenth anniversary of Understanding Society. The blog now includes 1,176 posts on topics in the philosophy of social science, the heterogeneity of the social world, current thinking about social problems, and occasional contributions on how we can envision a better future. Thanks to all of the readers who have visited during the past twelve months!

The blog continues to serve as a simulating outlet for intellectual work for me. Each post is roughly a thousand words, and my aim is to develop one idea or address one problem in the post. I’ve never tried for consistency or thematic coherence over time; the blog is more of a research notebook for me, allowing me to capture ideas and topics as they come up. Since the beginning I’ve looked at it as a kind of “open source philosophy,” allowing for the development of ideas and arguments in a piecemeal way. At the same time, it serves as a kind of seismograph for me, letting me recall the kind of topics that have come to the fore over time.

And, as I had hoped, the blog has created a platform for moving ideas from conception to academic publication for new ideas. My book New Directions in the Philosophy of Social Science appeared about a year ago, and it was wholly developed through the blog.

In the past year there have been a number of posts on familiar topics — critical realism, social mechanisms, and social inequality, for example. These are enduring topics in my research and writing. But a few new topics have arisen as well. One is the question of the dynamics and extent of hate-driven political movements, such as the populist-nationalist extremism of the Trump campaign and presidency (link). Another is completely unrelated — the fascinating history of fundamental physics during the early decades is the twentieth century, culminating in the development of the atomic bomb (link). And a third is an emerging area of interest for me — the nature and causes of organizational dysfunction in contemporary institutions (link). I’ve even had occasion to reflect on cephalopod intelligence (link).

The blog continues to enjoy increasing numbers of visitors. Google recorded over 140,000 page views on the blog in the past month, resulting in over 1.5 million page views over the past year. Part of that traffic comes from followers on Twitter (2,106), Facebook (7,786), Google+ (1,621), and Flipboard, and a great number of the visits are directed by Google searches on relevant topics.

So thank you, readers and visitors, and I hope you will keep reading and commenting!

Chinese modernization c. 1930

At the end of the nineteenth century — which was also of the end of the Qing Dynasty — China was not “modern”. Its political institutions had crumbled, it had not substantially incorporated new technologies and forms of economic organization, and its military was still equipped with mid-century weapons and tactics. And, of course, the conditions for peasants and landless workers were abysmal; here is J. R. Tawney’s description in a review of Chen Han-seng’s 1936 Agrarian Problems in Southermost China (link):

Not only the whole surplus, but a large part of the cultivator’s bare livelihood is skinned off by the landowner. As a result, the peasant falls increasingly into debt, and what the landowner and tax-collector leave, the usurer takes. “We close our survey, then,” writes Dr. Chen Han-seng, “upon a note of misery beyond which human experience can hardly go, except in times of catastrophe.” So much for the author’s account of the facts. No one not intimately acquainted with the region studied can say whether the picture is overdrawn, or not. If it is not–and the evidence presented suggests that it is not–then rural society in China, or in this part of China, is crumbling at the bottom. No stable state can be built on such foundations, and the case for some serious policy of land reform, already unanswerable, is once more reinforced. (346)

What avenues of purposeful social change were available to China’s leaders in the early part of the twentieth century? This broad question was addressed in strikingly relevant terms  in 1937 in a special issue of Pacific Affairs. This is a remarkable volume for anyone interested in China’s twentieth-century history, including contributions by Leonard Hsü, Edgar Snow, and R. H. Tawney. It is striking to read these reflections from the mid-1930s, from the perspective of the realities of China in the early twenty-first century.

The model of modernization that prevailed by mid-century in China was that of communist revolution, emphasizing class conflict, state ownership and management of the economy, and a substantial dose of ideological orthodoxy. This trajectory began in the 1920s in China, and led through a very tumultuous several decades before the final triumph of communism in China in 1949. Edgar Snow was a friendly observer of the left in China in the 1930s, and his 1937 Red Star over China represents his first-hand observations of the early stages of Mao’s movement and the Long March. Here is how Snow described the situation of communist activism in North China in the 1930s in his contribution to the Pacific Affairs volume, “Soviet Society in Northwest China”:

Practical considerations, however, denied the Reds the possibility of organizing much more than the political framework for the beginnings of socialist economy, of which naturally they could think only in terms of a future which might give them power in the great cities, where they could take over the industrial bases from foreign imperialism and thus lay the foundations for a true socialist society. Meanwhile, in the rural areas, their activity centered chiefly on the solution of the immediate problems of the peasants -land and taxes. This may sound like the reactionary program of the old Narodniks of Russia, but the great difference lies in that Chinese Communists regarded land distribution as only a phase in the building of a mass base, enabling them to develop the struggle toward the conquest of power and final realization of profound socialist changes-in which collectivization would be inevitable. In Fundamental Laws of the Chinese Soviet Republic’ the First All-China Soviet Congress in 1931 set forth in detail the “maximum program” of the Communist Party of China-and reference to it shows clearly that the ultimate aim of Chinese Communists is a true and complete socialist state of the Marx-Leninist conception. Meanwhile, however, it has to be remembered that the social, political and economic organization of the Red districts has all along been only a very provisional affair. Even in Kiangsi it was little more than that. Because the soviets have had to fight for an existence ever since they began, their main task has always been to build a military and political base for the extension of the revolution on a wider and deeper scale, rather than to “try out Communism in China,” which is what some people childishly imagine the Reds have been attempting in their little blockaded areas. (266-267)

Communism was one important strand of reform that China witnessed in the 1930s. But there were other efforts at modernization that offered a different view of what China needed in order to move forward. Many of these non-Communist directions fell within a broad coalition of individuals and groups under the label of “rural reconstruction,” which focused on social reforms, educational reforms, and governance reforms in the countryside. Leonard Hsü was an early American-educated sociologist in China. Hsü’s career is briefly described in Yung-chen Chiang’s Social Engineering and the Social Sciences in China, 1919-1949. Hsü describes the rural reconstruction movement in China in his 1937 article, “Rural reconstruction in China” in the Pacific Affairs volume (link). Here is Hsü’s brief description of the rural reconstruction movement:

The origin of the movement may be traced to three factors: China’s contact with the industrial powers of the West and the consequent decline of its rural economy; the proposals of Chinese thinkers and statesmen, beginning with Dr. Sun Yat-sen’s San Min Chu-I (Three Principles of the People) for a planned social development; and, finally, the series of incidents in 1931 and 1932 which brought about a national crisis unparalleled in the previous history of China. This crisis furnished an impulse toward national salvation through reconstruction. It included not only the Japanese military aggression in China, but a great flood in the Yangtze and Huai River valleys, the establishment of the Chinese Soviet Republic in the Yangtze provinces, and the spread of world economic depression to Chinas after the suspension of the gold standard in Great Britain and Japan, and later in the United States.

Within the rural reconstruction movement, which is itself the product of diverse social forces, three main objectives can be observed. One is increased production. China is only now awakening to the need for industrialization, and has not yet had freedom for unhampered growth, with the result that there has been insufficient urban industrial development to offset the rural decline. The estimated percentages of home production in 1935 of the following. (249)

Here is Hsü’s conclusion in the article:

I may, therefore, conclude by saying that rural reconstruction in China, as a social movement, is one phase of a correlated attack, on various technical fronts, on the problem of realizing a planned society. The movement presupposes that if China is to survive, it must modernize its social organization and vastly increase its work- ing efficiency. This in turn means the application of scientific knowledge to community reconstruction from the village unit up. Finally, the application must be a planned process, taking into consideration the social factors of population, resources and technical skill, and making use of the local unit of government as the medium of coordinating and correlating technical services.

The hard question to be considered now, eighty years later, is whether rural reconstruction and social reform could have brought about wide and deep processes of social change in China without the traumas associated with decades of revolutionary war. On the one hand, the logic of centralized one-party rebuilding of a large society like China is inherently risky. It poses the hazard of bad ideas prevailing at a certain time and being implemented on a vast and destructive scale. The Great Leap Forward and subsequent massive famine is one such example, and so is the Cultural Revolution. So centralized blueprints for longterm change carried out by an authoritarian regime seem inherently hazardous for a people. But at the same time, the problems that China faced in the 1930s, both in rural life and in urban life, were genuinely massive; and it isn’t entirely clear that a piecemeal, decentralized process of reform could have reached the scope necessary to bring about sustained social and economic progress in China. Hsü highlights the scope of the challenge in his summary of rural reconstruction:

When the total needs of China are considered, all these efforts are small indeed. There are still almost 220 million hectares that need to be afforested. How much can a million members of co-operatives help, when the farm population exceeds 340 million and the number of farm households exceeds 6o million? In spite of the interest in rural loans of the big banks, one study shows that peasants receive only 2.4 per cent of their financial assistance from the banks, and 97.6 per cent in loans at high interest from landlords and usurers.

Even smaller is the beginning that has been made in the social and cultural aspects of rural reconstruction. It is true that not until a physical and economic foundation has been laid can social and cultural work be developed on any considerable scale. It is not unreasonable to expect that in a few years the nation will take a more serious and systematic interest in such social fields as rural education, community recreation, rural health, social welfare, and local self-government. Present developments in these fields are inadequate to meet the needs of the rural population. How much help can hsien health centers and 144 rural health stations and clinics give to a rural population of 340 million? China has nearly 2,000 hsien, 100,000 villages and one to two million hamlets, for which in I932 there were only 477 rural normal schools, with 50,150 students. (261)

These points lead to a degree of uncertainty about the potential effectiveness and scope of cumulative small-scale reform programs. However, on balance the decentralized and pluralistic strategy is probably the most convincing pathway to long-term social and economic progress, given what we know about the alternatives. And there are good examples of such a pluralistic process leading to great social progress — greater democracy, improved quality of life, and increasing economic opportunities in all sectors of society. It would be very interesting to see a novelist of the stature of an André Malraux attempting to think through an alternative non-communist history for China. It might have the same gripping power as Malraux’s account of the early experience of the Chinese Revolution in Man’s Fate (La Condition Humaine).

* .    * .    *

Kate Merkel-Hess addresses China’s indigenous alternative to Communist modernization theory in her recent book, The Rural Modern: Reconstructing the Self and State in Republican China. The book is an important contribution to our understanding of how China might have developed differently into the twentieth century and beyond. Several earlier posts have focused on the question of the feasibility of largescale programs of social progress; linklinklink.

Cacophony of the social

Take a typical day in a major city — a busy street with a subway stop, a park, a coffee bar, and a large consumer financial office. There are several thousand people in view, mostly in ones and twos. Some people are rushing to an appointment with a doctor, a job interview, a drug dealer in the park. A group of young men and women are beginning to chant in a demonstration in the park against a particularly egregious announcement of government policy on contraception.

There is a blooming, buzzing confusion to the scene. And yet there are overlapping forms of order — pedestrians crossing streets at the crosswalks, surges of suits and ties at certain times of day, snatch and grab artists looking for an unguarded cell phone. The brokers in the financial office are more coordinated in their actions, tasked to generate sales with customers who walk in for service. The demonstrators have assembled from many parts of the city, arriving by subway in the previous hour. Their presence is, of course, coordinated; they were alerted to the demo by a group text from the activist organization they belong to. 

What are the opportunities for social science investigation here? What possibilities exist for explanation of some of the phenomena on display?

For one thing there is an interesting opportunity for ethnographic study presented here. A micro-sociologist or urban anthropologist may find it very interesting to look closely to see what details of dress and behavior are on display. This is the kind of work that sociologists inspired by Erving Goffmam have pursued.

Another interesting possibility is to see what coordinated patterns of behavior can be observed. Do people establish eye contact as they pass? Are the suits more visibly comfortable with other suits than with the street people and panhandlers with whom they cross paths? Is there a subtle racial etiquette at work among these urban strangers?

These considerations fall at the “micro” end of the spectrum. But it is clear enough that the snapshots we gain from a few hours on the street also illustrate a number of background features of social structure. There is differentiation among actors in these scenes that reflect various kinds of social inequalities. There are visible inequalities of income and quality of life that can be observed. These inequalities in turn can be associated with current activities — where the various actors work, how much education they have, what schools they attended, their overall state of health. There are spatial indicators of interest as well — what kinds of neighborhoods, in what parts of the city, did these various actors wake up in this morning?

And for all of these structural differentiators we can ask the question, what were the social mechanisms and processes that performed the sorting of new-borns into affluent/poor, healthy/sick, well educated/poorly educated, and so forth? In other words, how did social structure impose a stamp on this heterogeneous group of people through their own distinctive histories?

We can also ask a series of questions about social networks and social data about these actors. How large are their personal social networks? What are the characteristics of other individuals within various individual networks? How deep do we need to go before we begin to find overlap across the networks of individuals on the street? This is where big data comes in; Amazon, credit agencies, and Verizon know vastly more about these individuals, their habits, and their networks than a social science researcher is likely to discover through a few hundred interviews. 

I’d like to think this disorderly ensemble of purposive but uncoordinated action by several thousand people is highly representative of the realities of the social world. And this picture in turn gives support to the ontology of heterogeneity and contingency that is a core theme here. 

Organizational learning

 
I’ve posed the question of organizational learning several times in recent months: are there forces that push organizations towards changes leading to improvements in performance over time? Is there a process of organizational evolution in the social world? So where do we stand on this question?

There are only two general theories that would lead us to conclude affirmatively. One is a selection theory. According to this approach, organizations undergo random changes over time, and the environment of action favors those organizations whose changes are functional with respect to performance. The selection theory itself has two variants, depending on how we think about the unit of selection. It might be hypothesized that the firm itself is the unit of selection, so firms survive or fail based on their own fitness. Over time the average level of performance rises through the extinction of low-performance organizations. Or it might be maintained that the unit is at a lower level — the individual alternative arrangements for performing various kinds of work, which are evaluated and selected on the basis of some metric of performance. On this approach, individual innovations are the object of selection. 

The other large mechanism of organizational learning is quasi-intentional. We postulate that intelligent actors control various aspects of the functioning of an organization; these actors have a set of interests that drive their behavior; and actors fine-tune the arrangements of the organization so as to serve their interests. This is a process I describe as quasi-intentional to convey that the organization itself has no intentionality, but its behavior and arrangements are under the control of a loosely connected set of actors who are individually intentional and purposive. 

In a highly idealized representation of organizations at work, these quasi-intentional processes may indeed push the organization towards higher functioning. Governance processes — boards of directors, executives — have a degree of influence over the activities of other actors within and adjacent to the organization, and they are able to push some subordinate behavior in the direction of higher performance and innovation if they have an interest in doing so. And sometimes these governance actors do in fact have an interest in higher performance — more revenue, less environmental harm, greater safety, gender and racial equity. Under these circumstances it is reasonable to expect that arrangements will be modified to improve performance, and the organization will “evolve”.

However, two forms of counter-intentionality arise. The interests of the governing actors are not perfectly aligned with increasing performance. Substantial opportunities for conflict of interest exist at every level, including the executive level (e.g. Enron). So the actions of executives are not always in concert with the goal of improving performance. Second, other actors within the organization are often beyond control of executive actors and are motivated by interests that are quite separate from the goal of increasing performance. Their actions may often lead to status quo performance or even degradation of performance. 

So the question of whether a given organization will change in the direction of higher performance is highly sensitive to (i) the alignment of mission interest and personal interest for executive actors, (ii) the scope of control executive actors are able to exercise over subordinates, and (iii) the strength and pervasiveness of personal interests among subordinates within the organization and the capacity these subordinates have to select and maintain arrangements that favor their interests.

This represents a highly contingent and unpredictable situation for the question of organizational learning. We might regard the question as an ongoing struggle between local private interest and the embodiment of mission-defined interest. And there is no reason at all to believe that this struggle is biased in the direction of enhancement of performance. Some organizations will progress, others will be static, and yet others will decline over time. There is no process of evolution, guided or invisible, that leads inexorably towards improvement of arrangements and performance.

So we might formulate this conclusion in a fairly stark way. If organizations improve in capacity and performance over time in a changing environment, this is entirely the result of intelligent actors undertaking to implement innovations that will lead to these outcomes, at a variety of levels of action within the organization. There is no hidden process that can be expected to generate an evolutionary tendency towards higher organizational performance. 

(The images above are of NASA headquarters and Enron headquarters — two organizations whose histories reflect the kinds of dysfunctions mentioned here.)

Social change and leadership


Historians pay a lot of attention to important periods of social change — the emergence of new political movements, the development of a great city, the end of Jim Crow segregation. There is an inclination to give a lot of weight to the importance of leaders, visionaries, and change-makers in driving these processes to successful outcomes. And, indeed, history correctly records the impact of charismatic and visionary leaders. But consider the larger question: are large social changes amenable to design by a small number of actors?

My inclination is to think that the capacity of calculated design for large, complex social changes is very much more limited than we often imagine. Instead, change more often emerges from the independent strategies and actions of numerous actors, only loosely coordinated with others, and proceeding from their own interests and framing assumptions. The large outcome — the emergence of Chicago as the major metropolis of the Midwest, the forging of the EU and the monetary union, the coalescence of nationalist movements in France and Germany — are the resultant of multiple actors and causes. Big outcomes are contingent outcomes of multiple streams of action, mobilization, business decisions, political parties, etc.

There are exceptions, of course. Italy’s political history would have been radically different without Mussolini, and the American Civil War would probably have had a different course if Douglas had won the 1860 presidential election. 

But these are exceptions, I believe. More common is the history of Chicago, the surge of right-wing nationalism, or the collapse of the USSR. These are all multi-causal and multi-actor outcomes, and there is no single, unified process of development. And there is no author, no architect, of the outcome. 

So what does this imply about individual leaders and organizations who want to change the social and political environment facing them? Are their aspirations for creating change simply illusions? I don’t think so. To deny that single visionaries cannot write the future does not imply they cannot nudge it in a desirable direction. And these effects can indeed alter the future, sometimes in the desired direction. An anti-racist politician can influence voters and institutions in ways that inflect the arc of his or her society in a less racist way. This doesn’t permanently solve the problem, but it helps. And with good fortune, other actors will have made similar efforts, and gradually the situation of racism changes. 

This framework for thinking about large social change raises large questions about how we should think about improving the world around us. It seems to imply the importance of local and decentralized social change. We should perhaps adjust our aspirations for social progress around the idea of slow, incremental change through many actors, organizations, and coalitions. As Marx once wrote, “men make their own history, but not in circumstances of their own choosing.” And we can add a qualification Marx would not have appreciated: change makers are best advised to construct their plans around long, slow, and incremental change instead of blueprints for unified, utopian change. 

Is there a new capitalism?

 

An earlier post considered Dave Elder-Vass’s very interesting treatment of the contemporary digital economy. In Profit and Gift in the Digital Economy Elder-Vass argues that the vast economic significance of companies like Google, FaceBook, and Amazon in today’s economy is difficult to assimilate within the conceptual framework of Marx’s foundational ideas about capitalism, constructed as they were around manufacturing, labor, and ownership of capital, and that we need some new conceptual tools in order to make sense of the economic system we now confront. (Elder-Vass responded to my earlier post here.)

A new book by Nick Srnicek looks at this problem from a different point of view. In Platform Capitalism Srnicek proposes to understand the realities of our current “digital economy” according to traditional ideas about capitalism and profit. Here is a preliminary statement of his approach:

The simple wager of the book is that we can learn a lot about major tech companies by taking them to be economic actors within a capitalist mode of production. This means abstracting from them as cultural actors defined by the values of the Californian ideology, or as political actors seeking to wield power. By contrast, these actors are compelled to seek out profits in order to fend off competition. This places strict limits on what constitutes possible and predictable expectations of what is likely to occur. Most notably, capitalism demands that firms constantly seek out new avenues for profit, new markets, new commodities, and new means of exploitation. For some, this focus on capital rather than labour may suggest a vulgar econo-mism; but, in a world where the labour movement has been significantly weakened, giving capital a priority of agency seems only to reflect reality. (Kindle Locations 156-162)

In other words, there is not a major break from General Motors, with its assembly lines, corporate management, and vehicles, to IBM, with its products, software, and innovations, to Google, with its purely abstract and information-intensive products. All are similar in their basic corporate navigation systems: make decisions today that will support or increase profits tomorrow. In fact, each of these companies falls within the orbit of the new digital economy, according to Srnicek:

As a preliminary definition, we can say that the digital economy refers to those businesses that increasingly rely upon information technology, data, and the internet for their business models. This is an area that cuts across traditional sectors – including manufacturing, services, transportation, mining, and telecommunications – and is in fact becoming essential to much of the economy today. (Kindle Locations 175-177).

What has changed, according to the economic history constructed by Srnicek, is that the creation and control of data has suddenly become a vast and dynamic source of potential profit, and capitalist firms have adapted quickly to capture these profits.

The restructuring associated with the rise of information-intensive economic activity has greatly changed the nature of work:

Simultaneously, the generalised deindustrialisation of the high-income economies means that the product of work becomes immaterial: cultural content, knowledge, affects, and services. This includes media content like YouTube and blogs, as well as broader contributions in the form of creating websites, participating in online forums, and producing software. (Kindle Locations 556-559)

But equally it takes the form of specialized data-intensive work within traditional companies: design experts, marketing analysis of “big data” on consumer trends, the use of large simulations to guide business decision-making, the use of automatically generated data from vehicles to guide future engineering changes.

In order to capture the profit opportunities associated with the availability of big data, something else was needed: an organizational basis for aggregating and monetizing the data that exist around us. This is the innovation that comes in for Srnicek’s greatest focus of attention: the platform.

This chapter argues that the new business model that eventually emerged is a powerful new type of firm: the 

platform

. Often arising out of internal needs to handle data, platforms became an efficient way to monopolise, extract, analyse, and use the increasingly large amounts of data that were being recorded. Now this model has come to expand across the economy, as numerous companies incorporate platforms: powerful technology companies (Google, Facebook, and Amazon), dynamic start-ups (Uber, Airbnb), industrial leaders (GE, Siemens), and agricultural powerhouses (John Deere, Monsanto), to name just a few. (Kindle Locations 602-607).

What are platforms? At the most general level, platforms are digital infrastructures that enable two or more groups to interact. They therefore position themselves as intermediaries that bring together different users: customers, advertisers, service providers, producers, suppliers, and even physical objects. More often than not, these platforms also come with a series of tools that enable their users to build their own products, services, and marketplaces. Microsoft’s Windows operating system enables software developers to create applications for it and sell them to consumers; Apple’s App Store and its associated ecosystem (XCode and the iOS SDK) enable developers to build and sell new apps to users; Google’s search engine provides a platform for advertisers and content providers to target people searching for information; and Uber’s taxi app enables drivers and passengers to exchange rides for cash. (Kindle Locations 607-616)

Srnicek distinguishes five large types of digital data platforms that have been built out as business models: advertising, cloud, industrial, product, and “lean” platforms (the latter exemplified by Uber).

Srnicek believes that firms organized around digital platforms are subject to several important dynamics and tendencies: “expansion of extraction, positioning as a gatekeeper, convergence of markets, and enclosure of ecosystems” (kl 1298). These tendencies are created by the imperative by the platform-based firm to generate profits. Profits depend upon monetizing data; and data has little value in small volume. So the most fundamental imperative is — mass collection of data from individual consumers.

If data collection is a key task of platforms, analysis is the necessary correlate. The proliferation of data-generating devices creates a vast new repository of data, which requires increasingly large and sophisticated storage and analysis tools, further driving the centralisation of these platforms. (kl 1337-1339)

So privacy threats emerging from the new digital economy are not a bug; they are an inherent feature of design.

This appears to lead us to Srnicek’s most basic conclusion: the new digital economy is just like the old industrial economy in one important respect. Firms are wholly focused on generating profits, and they design intelligent strategies to permit themselves to appropriate ever-larger profits from the raw materials they process. In the case of the digital economy the raw material is data, and the profits come from centralizing and monopolizing access to data, and deploying data to generate profits for other firms (who in turn pay for access to the data). And revenues and profits have no correspondence to the size of the firm’s workforce:

Tech companies are notoriously small. Google has around 60,000 direct employees, Facebook has 12,000, while WhatsApp had 55 employees when it was sold to Facebook for $ 19 billion and Instagram had 13 when it was purchased for $ 1 billion. By comparison, in 1962 the most significant companies employed far larger numbers of workers: AT& T had 564,000 employees, Exxon had 150,000 workers, and GM had 605,000 employees. Thus, when we discuss the digital economy, we should bear in mind that it is something broader than just the tech sector defined according to standard classifications. (Kindle Locations 169-174)

Marx’s theory of capitalism fundamentally originates in a theory of conflict of interest and a theory of exploitation. In Capital that conflict exists between capitalists and workers, and consumers are essentially ignored (except when Marx sometimes refers to the deleterious effects of competition on public health; link). But in Srnicek’s reading of the contemporary digital economy (and Elder-Vass’s as well) the focus shifts away from labor and towards the consumer. The primary conflict in the digital economy is between the platform firm that seeks to acquire our data and the consumers who want the digital services but who are poorly aware of the cost to their privacy. And here it is more difficult to make an argument about exploitation. Are consumers being exploited in this exchange? Or are they getting fair value through extensive and valuable digital services, for the surrender of their privacy in the form of data collection of clicks, purchases, travel, phone usage, and the countless other ways in which individual data winds up in the aggregation engines?

In an unexpected way, this analysis leads us back to a question that seems to belong in the nineteenth century: what after all is the source of value and wealth? And who has a valid claim on a share? What principles of justice should govern the distribution of the wealth of society? The labor theory of value had an answer to the question, but it is an answer that didn’t have a lot of validity in 1850 and has none today. But in that case we need to address the question again. The soaring inequalities of income and wealth that capitalism has produced since 1980 suggest that our economy has lost its control mechanisms for equity; and perhaps this has something to do with the fact that a great deal of the money being generated in capitalism today comes from control of data rather than the adding of value to products through labor. Oddly enough, perhaps Marx’s other big idea is relevant here: social ownership of the means of production. If there were a substantial slice of public-sector ownership of big data firms, including financial institutions, the resulting flow of income and wealth might be expected to begin to correct the hyper-inequalities our economy is currently generating.

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