The Democratic Quality Vector and
the New Social Agreement

The Democratic Quality Vector

Including the value of natural resources and our social capital in national accounting is a vital step to achieve economic growth that is equitable and sustainable.”

In a sense, this chapter is the heart of the book. What we have learned on our journey to arrive here is that the facts are not what they always seem. While we know that good decisions rely on sound data, there appears to be a gap in our knowledge that results in sub-optimal decision-making. In other words, there is much valuable information that remains inaccessible to us because we have not found a way to tap into our intuitive knowledge. We have new tools like big data, data analytics, and AI to help us navigate an increasingly complex world. However, none of these address the issue of inaccessibility of intuition, and other intangibles, and as a result end up with sub-optimal results. In this chapter, we propose a new way to tap into this intuition by creating a metric that can quantify intuition. In this way, we create a numerical proxy that transfers intuitive information from the inaccessible domain over to the mathematical realm that is the basis for much of decision-making in the modern world.

A brief glimpse back can help summarize and set the tone for the rest of this chapter. We began by realizing that modernity is confronted with a data problem, both in quantity and perhaps, more importantly, quality. To understand what data quality means we took a closer look at how science, primarily since the Enlightenment, has defined what facts are. However, a closer look at science, the discipline we turn to for truth, reveals something uncomfortable. Science itself is in constant flux and in a strange sense, all “facts” can be interpreted to be false. This is because, science is in continual flux and never stands still. An idea that fits in a model that is peer accepted today may be outdated tomorrow in light of new discoveries. Hence, what we consider truth today is false tomorrow. We can validate this and build confidence in this recursive pattern of the scientific process itself through studying the history of science. We are led to the inescapable conclusion that scientific truth is impermanent and that it is possible that all such scientific knowledge has a shelf life. All experimental models may eventually turn out to be false, to be succeeded by a more accurate model.

A further way knowledge may have been inadvertently distorted is due to human civilizations ongoing romance with psychoactive compounds. It seems plausible that the sheer volume of historical Euro-centric psychoactive drug consumption may have altered the course of human knowledge in some significant and sophisticated way, contributing to ideas that are now ingrained and normalized into our cultural institutions today. From an epistemological perspective, drugs can both degrade and enhance cognitive function. Under many conditions, cognitive impairment results, but in some cases, and with specific types of compounds taken by particular types of drug users, it can stimulate the emergence of novel ideas. Indeed, the significant consumption of Laudanum before the Enlightenment period may have influenced its outcome, through its many cognitive impairments, as well as stimulation of new ideas. The success of the Enlightenment has placed a heavy emphasis on rational, analytic thinking over intuitive thinking. As a result of the success of the Enlightenment, modern scientists’ frown upon fields of science which cannot quantify their key variables of study, subjecting them to rigorous, mathematical analysis.

However, more and more, researchers are discovering that intuition is only vague because it has been vaguely understood. Indeed, modern research suggests that intuitive thinking is highly evolved for increasing fitness and emerges from a predictive brain model. If appropriately used, intuition is an integral part of reasoning. Researchers like Daniel Kahnaman have demonstrated that the limitations of intuition are often in making common cognitive bias mistakes and in drawing from a sparse set of experiences. The best intuitions are the result of a rich experiential set of data. Hence experienced workers have much more accurate intuitions than green employees. In Kahnaman’s theory, intuition makes up the fast reasoning system 1, while slow, analytic reasoning makes up system 2.

Research is also beginning to reveal the mechanics of inner feelings, which are the distinguishing qualia of what we call intuition. Scientists label these feelings as interoceptive signals. They emerge from internal organs and send internal messages which we can sense. They are evolved out of millions of years of evolution to warn us of such things as an impending danger so as to increase our fitness for survival. All in all, current research into intuition is slowly shedding light on the mysteries of intuition and revealing its true predictive nature.

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