Building an Upgraded Model
As with any new subject of interest, I build a set of questions and look for the answers from people already writing about the subject. By learning more, the questions begin to shift, and the answers become more difficult to find. I either encounter the Law of Diminishing Returns and set the topic aside, or I explore new avenues to learn more. In the case of human nature and public policy, the cumulative collection of thoughts have roots so vast and so deep, I had to organize them and write them down just to stop thinking them.
When considering the topic, the biggest hurdle was uncovering the gap I was feeling. Some forty years ago, roboticists coined the term Uncanny Valley to describe the innate feeling that you were not interacting with another human. While the phrase is meant to describe artificial life, this really seems like a modern extension of the internal feelings triggered by any deception. When a con man attempts to sell you something too good to be true, complex emotions with terms like price anchoring create internal confusion that all too often results in a costly lapse in judgement. Politicians provoke a similar responses for me (and I am sure others). When they engage in persuasion, the language rarely aligns to the policies proposed invoking disingenuous feelings- and nausea.
Recognizing that politics is typically just a form of sales, there must be more complex machinery that actually makes things move. The task of actually developing laws and regulations falls to a vast network of actors. From staffers in a congressional office to investigators testing water samples, policy details are influenced by an array of professionals. Some exist as specialists in a field- such as public health while others focus more on the function of government. The range of topics, occupations, and opinions at play make the development of a model or framework crucial.
A conceptual model is built to describe observed patterns improve understanding and hopefully even predict outcomes. Models exist in most academic disciplines- from Rutherford’s Model of the Atom to the deterrence model of crime prevention or the Jungian model of the psyche. Even the pantheon of Greek gods could be seen as a model of explanation with each assigned interrelated responsibilities and tales of impact. The drive for a more holistic and organized view of knowledge is irresistible. Even simple models can be powerful and important. Understanding gravity as an attraction between two masses was revolutionary long before we had any ability to measure or test.
Models of the atom began with discussions between the Stoic and Epicurean schools of philosophy. The Stoics imagined everything to be composed of very small (or atomic, from the Greek atomos “uncut, unhewn; indivisible”) billiard balls whose numerous collisions produced every outcome in life. Epicureans countered with “free will”. Disagreement between deterministic and expressive thinking in developing explanatory models has deep roots in the evolutionary tree. Over time, thought experiments were augmented by real experiments that could be replicated. As reported results were either confirmed or refuted, theories were adopted or discarded. New models replaced the old.
Even in areas with objective measures, conflict still exists. New science is often met by not merely skepticism but derision and even hostility. However, once the evidence is compelling and reinforcing experiments validate the new theories, skeptics are forced to evolve or simply be left behind. Recent flat earth discussions aside, no one still argues the “plum pudding” model of the atom rivals quantum mechanics. Psychology, economics, anthropology, and other areas of human study on the other hand will continue with generally discredited notions often well beyond the passing of the key proponents. Instead of continually seeking a superior understanding of the nature of humanity, even informed people sink into comfortable beliefs.
Does that mean no objective tools exist in the social sciences? Of course not, but they have been incredibly slow to evolve, and reliance on evidence to develop policy remains controversial. Improved understanding of the brain has led to new theories of economics and human development, but corresponding changes in public policy have stalled even in the face of overwhelming evidence. Mechanical factors like building political support for legislation help to explain this, but often explanations are less satisfying. In a scientific discipline, research and evidence is required to build consensus around a theory. Substantially changing how criminal justice should be meted out only requires a compelling essay.
Gathering a number of humans tabula rasa for observation poses logistical and ethical challenges not faced by scientists observing atoms, but even truly odious pseudoscientific ideas can still take hold in policy circles without need of a factual foundation. Conversely, the advance of knowledge requires an injection of humanity. Many supposedly purely scientific endeavors (such as the creation of nominally dispassionate models of artificial intelligence) fail to recognize their own limitations until ethical standards are applied.
What then could be the roots of a model of public policy supportive of the advance of knowledge by constrained by our common humanity?
My proposal is an improved understanding of motivation and risk. Much of the advance in physical sciences came about for reasons of profit or the improvement of strategic advantage (i.e. better weaponry). When such a frame is suggested; some scientists would be offended, some would accede to the reality of maintaining funding, and many would simply have never given the topic much consideration. As with any human pursuit, becoming a scientist has many motivations, and being a scientist comes with many risks.
Through the next few essays, I will attempt to build a model of public policy based on categories of motivation, social structures that shape those motivations, and methods to better evaluate the impacts of those policies.
