Category Archives: systems thinking

COVID-19 (Average) vs Other Causes of Death (Actual) in the U.S. – Animated Data Graph

Source: Covid vs. US Daily Average Cause of Death, Robert Martin on 8 Apr 2020

For those still saying influenza is a much bigger killer than COVID-19 (SARS-COV-2), the numbers don’t support that argument, especially considering there are many deaths that strongly appear to be due to COVID-19 that are not reported as such because the deceased are not tested. The animation conveys the speed with which an exponentially increasing infection rate overtakes other, relatively linear rates of expansion.

How the Black Death Radically Changed the Course of History

This article is relevant to our recent discussions and Zak Stein’s (see Edward’s recent post) suggestion that great destabilizing events open gaps in which new structures can supplant older, disintegrating systems–with the inherent risks and opportunities.

Living in the future’s past

I watched a good documentary last night titled, Living in the Future’s Past, a project organized, produced, and narrated by Jeff Bridges. It’s available through your Albuquerque Public Library account’s access to Hoopla Digital, Amazon Prime video, and other services. It lays out the modern dilemma of having a pre-neolithic brain in a Neolithic era and posits several questions that align closely with the theme of our current discussion . The film has commentary from diverse scientific experts, including Daniel Goldman (emotional and social intelligence and mindfulness). The upshot is a recurring suggestion our current brain functionality is capable of reframing our perspective and modulating our perceptions and behaviors around carefully constructed focal questions that get at what sort of future(s) we desire. I like this approach—so well in fact that I Had reserved some web domains months ago:,,, and These domains are not active yet. They will relate to the novel I’m writing and to a related non-fiction project. Edward is onto an important approach in looking to semantics (framing, etc.).

Also, on a short-term level, cultural evolution (including language and semantics) appears much more potent a driver than physiological evolution. Given that, I recently purchased a book by an author who goes into great depth on cultural evolution. The book is Cognitive Gadgets: The Cultural Evolution of Thinking, by Cecelia Heyes. I may put it forward for a future discussion.

The age of entanglement

It is superseding the Age of Enlightenment as the dominant paradigm. It also applies to our models, many of which still retain the apparent logical necessities of Enlightenment hierarchical categorization. Entanglement is much more hier(an)archically synplex. Yes, we are still in transition, retaining elements from the Enlightenment. And when we do see evidence of entanglement we try to fit that round peg into the old square hole. But it’s time begin to frame our evidence within that new paradigm where it makes the most sense.

From this  2016 piece that began framing it that way way back when. In the New Year and New Decade it’s time to play catch up.

“Unlike the Enlightenment, where progress was analytic and came from taking things apart, progress in the Age of Entanglement is synthetic and comes from putting things together. Instead of classifying organisms, we construct them. Instead of discovering new worlds, we create them. And our process of creation is very different. Think of the canonical image of collaboration during the Enlightenment: fifty-five white men in powdered wigs sitting in a Philadelphia room, writing the rules of the American Constitution. Contrast that with an image of the global collaboration that constructed the Wikipedia, an interconnected document that is too large and too rapidly changing for any single contributor to even read.”

“As we are becoming more entangled with our technologies, we are also becoming more entangled with each other. The power (physical, political, and social) has shifted from comprehensible hierarchies to less-intelligible networks. We can no longer understand how the world works by breaking it down into loosely-connected parts that reflect the hierarchy of physical space or deliberate design. Instead, we must watch the flows of information, ideas, energy and matter that connect us, and the networks of communication, trust, and distribution that enable these flows.”

More on Haidt

Continuing this previous post:

I’m looking at the section “conclusion and critique” of Haidt starting on p. 31. Gibbs appreciates that we should account for our earlier human history and more primitive brain centers in describing morality. But to limit it to these structures and history at the expense of later brain structures and evolutionary development is another thing.

“The negative skew in Haidt’s descriptive work discourages study in moral psychology of higher reaches of morality such as rational moral reflection, empathy for the plight of entire out-groups, moral courage, and the cultivation of responsible, mature moral agency —broadly, study of ‘the scope of human possibilities, of what people can do morally, if they are prepared, through development and education, to approach life’s important issues in a thoughtful way’” (34).

Several neuroscientific studies make clear which parts of the brain are emphasized in liberals and conservatives. The amygdala (indicative of fight or flight fear) is a much older evolutionary brain structure, while the anterior cingulate cortex (higher thinking functions) much newer. Hence there is neuroscientific brain evidence for the evolution of morality per Kohlberg. Haidt admits that conservative morality is rooted in these more evolutionary earlier brain structures, and liberal morality in the newer structures.

The newer neocortex then coordinates and integrates the older brain functions so that the latter do not dominate and send us backward in evolution. It’s not that liberals don’t have the conservative moral traits like Haidt claims; it’s that those earlier evolutionary traits are now modified under neocortex control. Yes, there is a value judgment involved here, but it’s supported by evolutionary science, not ideology.

The abstract from “Neural correlates or post-conventional moral reasoning”:

“Going back to Kohlberg, moral development research affirms that people progress through different stages of moral reasoning as cognitive abilities mature. Individuals at a lower level of moral reasoning judge moral issues mainly based on self-interest (personal interests schema) or based on adherence to laws and rules (maintaining norms schema), whereas individuals at the post-conventional level judge moral issues based on deeper principles and shared ideals. However, the extent to which moral development is reflected in structural brain architecture remains unknown. To investigate this question, we used voxel-based morphometry and examined the brain structure in a sample of 67 Master of Business Administration (MBA) students. Subjects completed the Defining Issues Test (DIT-2) which measures moral development in terms of cognitive schema preference. Results demonstrate that subjects at the post-conventional level of moral reasoning were characterized by increased gray matter volume in the ventromedial prefrontal cortex and subgenual anterior cingulate cortex, compared with subjects at a lower level of moral reasoning. Our findings support an important role for both cognitive and emotional processes in moral reasoning and provide first evidence for individual differences in brain structure according to the stages of moral reasoning first proposed by Kohlberg decades ago.”

From Mendez, M. (2017). “A neurology of the conservative-liberal dimension of political ideology.” The Journal of Neuropsychiatry and Clinical Neurosciences.

“Differences in political ideology are a major source of human disagreement and conflict. There is increasing evidence that neurobiological mechanisms mediate individual differences in political ideology through effects on a conservative-liberal axis. This review summarizes personality, evolutionary and genetic, cognitive, neuroimaging, and neurological studies of conservatism-liberalism and discusses how they might affect political ideology. What emerges from this highly variable literature is evidence for a normal right-sided cconservative-complex’ involving structures sensitive to negativity bias, threat, disgust, and avoidance.”

New scientific model can predict moral and political development

According to this study in Nature Human Behavior, in time frames about fairness and preventing harm triumph over those about loyalty, purity and authority. The latter might succeed temporarily, like now in the US, but the more the former frames are strongly and repeatedly reinforced the quicker the results. Let’s keep up our passionate frames, for this research supports that we will overcome the dark forces that have a temporary hold on our government. Also see Kohlberg‘s moral stages, showing that the former frames are more developed that the latter set.

“Their conclusion is that the key characteristic of opinions that gain ground is that they are supported by arguments about what is fair and what does not cause harm to others. […] Opinions based on other classical grounds used to determine right and wrong actions—loyalty, authority, purity, religion—can gain support temporarily, but over time, opinions based on these arguments lose support all over the political spectrum. The stronger the connection an opinion has to arguments about fairness and harm, the greater the probability that it will gain ground in public opinion. Also, the stronger the connection is, the faster the change will come.”

40 year update on memes

From this piece:

“There is not one, but at least four, hereditary systems recognized by biologists today. Eva Jablonka and Marion Lamb lay this out clearly in their 2006 book, Evolution in Four Dimensions, as they walk through the research literature on genetics, epigenetics, behavioral repertoires, and symbolic culture as four distinct pathways where traits are ‘heritable’ in appropriately defined fashion.”

“Specifically, I am thinking of three areas where significant progress has been made during the last forty years: the birth of complexity science in the early 1980’s, developments in the study of human conceptualization and cognitive linguistics since the mid-70’s, and the explosion of digital media in the age of personal computers and later via the internet.”

“Applied to meme theory, this body of tools and techniques [cognitive linguistics] demonstrates that researchers across many fields have found value in the perspective that culture can be studied as information patterns that arise in a variety of social settings routinely and with modular elements that are readily discernible in each new instance. The claim that information patterns do not replicate is contradicted by the evidence for image-schematic structures.”

The root of the power law religion

New draft paper by me. Update: Published here. The abstract:

A ‘power law’ refers specifically to a statistical relationship between quantities, such that a change in one quantity has a proportional change in another. One property of this law is scale invariance, otherwise known as ‘scale-free,’ meaning the same proportion repeats at every scale in a self-similar pattern. Mathematical fractals are an example of such a power law. Power laws are taken as universal and have been applied to any and all phenomena to prove the universality of this law.

However, a recent study (Broido and Clauset, 2019) claims that “scale free networks are rare.” They conducted an extensive review of one thousand social, biological, technological and information networks using state of the art statistical methods and concluded what the title of their article states. To the contrary, “log-normal distributions fit the data as well or better than power laws.” And that scale-free structure is “not an empirically universal pattern.” Hence it should not be used to model and analyze real world structures.

Decentralized collective intelligence

Jordan Hall of the Neurohacker Collective on decentralized collective intelligence. Sounds a lot how our group works, our collaborations creating something greater than our individual contributions, even though the latter are part and parcel of the process. What happens when we node thyself.

History of complexity science

Here’s an interesting infographic of the main concepts and thinkers in complexity science across time. Notice S. Kauffman is slated in the 1980s column, suggesting the graphic depicts when influential thinkers first make their marks.