All the Political Blaming Misses the Point

finger pointing

Disappointment and anger directed toward what are claimed to be the failures of government to solve persistent social problems is misdirected. Government is not the culprit; the ineffectiveness lies in the way we think. We are stuck in a modernist mindset that sees the world as a big machine. When the machine sputters and fails us, we turn to the engineers and technocrats, and charge them to fix it. This is true whether the problem is deemed to arise from the systems of the government, private sector, natural world, or elsewhere. We tried to fix the financial system that broke down in 2008 by tightening regulations, We think we can mitigate the impact of climate change by changing our energy mix away from carbon.

No, we can’t. The problems that have captured our attention are the result of complexity at work. To address these we have to change the basic frame of our thinking from one based on the Enlightenment ideas about a mechanistic universe that we can come to know and control to a post-modern acknowledgement that the world is complex and is, in terms of the standard scientific method, unknowable. The global social/economic/environmental system is so highly interconnected and full of non-linear relationships that it cannot be reduced to a set of conventional rules, laws, and formulas. At any moment, the next instant cannot be predicted. Outcomes defy our models. We alternate between boom and bust, drought and flood. Great problems, like global warming or growing inequality are inevitable, unintended consequences of our normal societal structure.

When we are dealing with complexity, we have to heed the law of unintended consequences because the models we use to design our institutions and technological structures are, except for the simplest situations, imperfect replicas of the real world out there. The great power of science and technology rests on a methodology that takes the world apart and looks at one piece at a time, but that is not how that world works. It’s not the parts that matter as much as how they are interconnected to form a system. The failure of the design models, based on scientific knowledge, to precisely represent the world produces unintended outcomes, sometimes insignificant, but occasionally large and threatening, as it the case for climate change.

If the source of the problems we face is the failure of our scientific knowledge and technology to match reality, then it should be obvious, that we cannot rely on these tools to alleviate or obviate these problems. Institutions, like governments or markets, cannot fix the problems by simply identifying unitary causes and applying fixes. A flat tax, for example, could reduce some serious distortions and quirks in the present system, but risks creating new and unpredictable problems because the system is complex. Almost any proposal to fix an existing problem offered by the political sphere would fit this picture. The same is true of economists, aiming to fix market imperfections, but using an imprecise model of human behavior.

Technology also exhibits the law of unintended consequences. Devices, designed to do one thing, produce additional outcomes, some good but, often, some bad. This happens because the knowledge used to design the devices fails to represent the complete real context into which the device is to be introduced. Sherry Turkle, an MIT technology scholar, in a recent book, argues that the ubiquitousness and persistent use of mobile devices has negatively affected the ability of young people to engage in meaningful conversations. Other similar examples abound. The explosion of technological devices and personal applications has deepened our centuries-old optimism that science and technology will always rise to solve our persistent societal problems and keep us on the progressive path to perfection. We should be extra cautious, warned by outcomes that are not so aligned.

Is there an alternate way to proceed that holds the possibilities of avoiding the pitfalls of matching reductionist thinking to complexity? Yes, we have a very good example of an alternate way of framing these serious problems and dealing with them in the response to the Great Depression by the Roosevelt administrations. The approach Roosevelt and his team used to understand and address the terrible devastation of the collapse of the socio-economic system was pragmatic in nature. Pragmatism, which some call the only American-bred philosophy, is ideally suited to cope with complexity. Pragmatism rests on a methodology to slowly and patiently understand complexity and develop effective solutions to problems arising from it.

Contrary to the abstractive methods of science which require the investigators to isolate the subject of their inquiry, pragmatists directly interact with the system in play, trying one approach after another until they begin to see positive results. Large problems demand large teams of concerned seekers. Different points of view are subjected to questioning to avoid getting stuck on some ideologically pure approach. John Dewey, perhaps the greatest American pragmatist, saw this way of thinking and acting as the heart of democracy. Progress would come by continuous inquiries into the nature of the barriers to fully realizing critical American values, and testing the solutions as they emerge from the murk of complexity.

Whether conservative or liberal or of any other political ilk, blaming any of the major institutions of our society is misplaced and ineffective. The failures lie deeper in the modernist ideas about how the world works. Neither pole of the political spectrum will be successful as long as they claim to have answers based on some technocratic ideology. The possibility of effective solutions will arise only by working together, under a pragmatic governance regime. The current practice of casting blame on individuals for all our messes may win points, but deepens the misunderstanding of the nature of our most serious problems and prevents us from seeking solutions that might really work.