Robert Hacker
15 min readJul 6, 2020
Credit: Pexels

Complexity science explains all natural and manmade systems from slime molds and ants to commodity markets and cities. One noteworthy characteristic of complex systems is emergence, where the whole is greater than the sum of the parts. An example of emergence is when heated water turns to gas. The properties of water do not explain the appearance of gas. The physicist explains the transition from water to gas as a phase transition. In each phase transition there is a period of near chaos. In the water example the gas and water are mixed before transitioning completely to gas. This “edge of chaos”[1] is present in every phase change and before emergence. Therefore, we should look for the edge of chaos before manmade systems transition to an emergent state.

Santa Fe Institute Professor Tim Koehler researches complexity and complex systems. His research shows:

“that sociopolitical development is dominated first by growth in polity scale, then by improvements in information processing and economic systems, and then by further increases in scale. We thus define a Scale Threshold for societies, beyond which growth in information processing becomes paramount, and an Information Threshold, which once crossed facilitates additional growth in scale.”[2]

Koehler’s two thresholds — Information and Scale — would be coincident with the chaos that marks a phase transition and emergence. The question one might ask is at which stage today is the United States or are we at the edge of chaos associated with a threshold.

I think we are at the edge of chaos before an Information Threshold. First, in this article, I would like to discuss my thinking for why we are at an Information Threshold, then describe the evidence for the edge of chaos and lastly voice my concerns about the future.

The United States experienced unprecedented economic growth and expansion of polity (government) from its founding through WWII. Then as Koehler predicts the U.S. went through a transition to updates its IT infrastructure to support future growth. This we now call the Computer Age which started in the late 1940s and early 1950s. By the 1960s Claude Shannon, John Von Neumann, Robert Shockley and Herbert Weiner had developed the know-how and technology to launch mainframe computing at scale and all of the fundamental concepts to bring us eventually to the cell phone computing of today. This convergence of technologies the seminal thinker Thomas Kuhn (philosophy of science) called a paradigm. Eventually we passed through the Information Threshold Koehler predicted to produce another period of unparalleled economic growth which perhaps lasted until March 2020 when the pandemic arrived. While the pandemic has deservedly captured worldwide attention, it may just be an indicator of the edge of chaos for another Information Threshold before a transition to a period of renewed economic growth. Kuhn’s writings would call Koehler’s Information Threshold the indicator of a paradigm, the coming together of multiple technologies that have the critical mass to markedly change or redefine human behavior. I think the current convergence of artificial intelligence (AI), big data, cloud computing and IOT (Internet of Things) is a Kuhnian paradigm that marks an Information Threshold. Following a consolidation period which would include the economic fall out from the pandemic, we would pass through the next Scale Threshold to resume social and economic scaling.

My concern is that the current examples of the edge of chaos before the transition are so alarming. I am concerned that the chaos today may actually threaten the likelihood of the next Scale Threshold and the transition to another growth phase.

PESTEL Analysis

If one were to systematically examine the evidence of chaos, one must first recognize that chaos is tangible — atomic particles, chemical reactions, organisms, human agents — real things — and not metaphor and rhetoric. One systematic way to complete such an analysis is to analyze the parts of the human ecosystem, what Harvard Professor Francis Aguilar called PESTEL analysis. This analysis includes Political, Economic, Social, Technology, Environmental and Legal issues. There is some judgment required to classify the data in a category, but I am more focused on trying to be comprehensive than precise.

In preparing the PESTEL analysis that follows, I will make clear my bias. I am more concerned about the United States than I have been since the Vietnam War. Also, many of the Cuban and Venezuelan exiles in Miami where I live have started to draw comparisons between their countries and what we see today. Furthermore, history shows us that pandemics and wars mark every significant change in geopolitical power. For example, the Spanish Flu and WWI marked the decline of the British Empire. By their nature, geo-political changes of this magnitude flow through an entire PESTEL analysis of a country or larger ecosystem. Given the effect of geopolitical change, let’s begin the PESTEL analysis with Politics.

Politics, or more accurately government, can be understood in terms of network theory and information theory. Government emerges in part because it serves to process information and distribute it, even in dictatorships and monarchies. In small disorganized networks a large node appears, an example of which is government, that has the economies of scale to efficiently process information. Networks grow in terms of the number of nodes in large part because better information processing developed. Today almost all of us have access to processing power equal to the government (ignore the Oak Ridge supercomputer) thanks in part to Google Cloud Platform and Amazon Web Services. With this processing power we have less need for a large-scale government in the network. Perhaps divisive Washington, fake news about national events and foreign agent provocateurs is in part due to the greater access to information and the ease with which one can use the Internet to circulate their views on a subject. Perhaps the mismanagement of COVID-19, the bombastic President, the loss of integrity in the press is just more examples of current irresponsibility. Perhaps all of this “controversy” is an example of the chaos before the government goes through a phase transition to be better suited to the new, real-time information technologies and the next phase of Koehler’s growth in scale. Perhaps government needs to be downsized and those resources better deployed to ensure a fairer, less discriminatory form of continued prosperity. I anticipate the downsizing will eventually lead to cities taking on an increasing role in government. Cities are the only current form of government that can react in real-time — the speed that most people have come to expect for services. If you think this power shift to cities is far-fetched, the response to COVID-19 in the U.S. was led in large part by the cities, as described in this story — “How a national health crisis fell on the backs of local leaders”.

Economic analysis suggests at least two possible examples of edge of chaos before a phase transition. In contrast to full-time workers, today[3] before the pandemic over 50 million people were contract laborers, freelancers and part-time workers (the “gig-economy”). The pandemic triggered an unemployment increase of approximately 22 million[4], most of whom immediately became gig workers in an effort to maintain some lifestyle. Ignoring possible double-counting, today 70+ million gig workers self-organize on a daily basis to provide for their families. Therefore, over 40 percent[5] of the U.S. workforce is not in a full-time job. Whether before or after the pandemic, the current gig workers as a percentage are much higher than the approximately 17 percent in 1990. This number of workers in the gig economy, forgive me, looks like water beginning to boil. I just do not know if the result will be a traditional revolution before the phase change or some draconian government reaction to increased protest over the uncertainty of the gig worker lifestyle. Increasing worker replacement by AI and robots can only make it worse. If you are not concerned by this mass uncertainty in society, do you care about the other important example of economic chaos — wealth disparity?

Probably around 1995 the economy passed through a Scale Threshold and scaled in new ways. This event was preceded by the popularization of the Internet and Google search which changed dramatically the IT infrastructure. This transition also led to a redefinition of wealth creation from land-labor to information-capital. The result of this change in wealth creation was that fewer workers benefited from wealth creation. The capital efficiency of digital wealth creation (information) provided dramatically greater cashflow through better margins and efficiency. This capital financed the widespread move to offshore production in Asia and China in particular. This reduced the alternatives for workers at home and exacerbated the situation for full-time jobs and the related economic well-being.

The chart below of the Gini Coefficient for the U.S. shows the concerning trend in wealth inequality (the greater the number, the greater the inequality).

Figure 1

The Computer Age transformed the world, but the capital efficiency and productivity of the related business models did not require as much labor as in earlier business models. With the Gini Coefficient constantly increasing, how long will the working people tolerate an “unfair” system — the chaos. Will the reaction be a traditional revolution before the phase change or some appropriate government reaction that also triggers a phase change to restructure either the economy, government support payments, or both. In the worst case, the government initiates an intentional misdirection campaign to divert voter attention from their problems and the situation continues to get worse. Eventually, perhaps only a war will distract the disgruntled voters without economic opportunity.

Social context is always the hardest for me to interpret and I frequently look to the role of women for insight. We know that coincident with each of the four industrial revolutions, women benefit from social change, as shown below.

Figure 2

I anticipate that what we will see biology become the science to dominate the 21st century, as McKinsey makes clear in their excellent report — The Bio Revolution (2020). AI will increasingly convert this science to a type of engineering and women will be able to opt for artificial means of reproduction. Carrying babies to term will be a choice for women and more of them will opt for outsourcing. This trend will further pressure the concept of family and lead to a “redefinition” of household, which has been going on since 1960, as shown below.

Figure 3

Humans have lived in tribes, then communities and finally cities for at least 100,000 years, since the humans became the dominant “advanced” life form. Whether communities and cities were an advance over tribes depends on one’s view of scarcity and abundance. Communities and cities developed because the technology which fostered the abundance required the economies of scale provided by larger groups. Cities will survive because of their inherent efficiency. Communities may reemerge as important if government power shifts to cities as I predict. The concept of family is where I see the chaos that indicates a phase transition will emerge. The multiple forms of household, again, looks to me like water about to boil. Perhaps a majority of single woman households and nonfamily households will emerge.

The press is another example of potential chaos, which I touched on briefly in the Political analysis. The U.S. and much of the developed world was built on the premise of freedom of the press. The press served as the source of truth and integrity and was expected to be the whistleblower. In the early part of the 21st century, Internet usage increased dramatically, social media emerged and life has not been the same since. One result of this change is that people were offered many more choices for news and information. This increased competition for readers and viewers prompted many of the new entrants to focus on the sensational headline and story in order to get market share. Surprising to me, the traditional press — NY Times, CBS, NBC, leading city newspapers, Bloomberg et al — followed the newcomer strategy and opted for sensationalism. This “break the story” sensationalism replaced the traditional, more measured reporting. Foreign government agitators and other sources of misinformation only made the situation worse. Today I think everyone is challenged to find the truth about a story. Maybe ten to twenty percent of the population recognize this dilemma. This lack of integrity in public information is one of the most concerning examples of a possible edge of chaos and may be an indicator of the need to modernize again the IT infrastructure as Koehler would predict.

Technology has been displacing labor for 200 years. Productivity was originally measured in terms of manhours. Today labor accounts for less than 1% of work done globally and 99% of work is done by fossil fuel energy.[6] AI will further challenge manpower and labor as AI technologies such as robots develop to carry out increasingly complicated tasks. Some commentators believe that only the domain of design will remain with humans, but the design will be of the algorithms that control the AI. Even the discovery process of research will be increasingly done by AI. The Deep Mind group at Google, which does the leading-edge AI research, talks now about the algorithms having “intuition” as the only way to describe how the technology functions. This encroachment by AI on human activities is part of the chaos that indicates an imminent threshold and upcoming phase change.

The reader may be surprised by only one short paragraph to highlight the chaos in technology. Technology, even more than government, is a major factor behind human system phase transition. A big concern I have is whether federal governments can transition, change the status quo, and make good use of the emerging AI-related technology. If government fails to transition to embrace the new technology and balance of power, we might see the emergence of Google countries or a reemergence of city-states in Shanghai, Sao Paolo or Tokyo (with populations of 30–40 million, comparable to Peru today). Inefficient federal government may be an unwarranted burden beyond defense, but perhaps even that might be outsourced using a NATO-like model. One should never lose sight of the fact that democratic government has been sustainable for approximately 250 years, basically a weekend experiment in a 100,000-year history of dictators and monarchies. To close this brief technology analysis, I describe the potential change from the emerging technologies as the 2nd Renaissance, a period in which we cannot imagine the scope and scale of change. For the World Economic Forum to call this period the Fourth Industrial Revolution (4IR) may be an understatement.

Environmental concern is my major concern in the 21st century, even more than wealth inequality. I teach my students that experiment and iteration are acceptable provided you do not run out of cash or kill yourself (or others). Wealth inequality may be “running out of cash”, but the environmental situation is “kill yourself”. We are on the edge of the apocalypse. Perhaps exploring space for minerals is not driven by economics or environmental concerns, but rather as a fallback strategy if we do not manage an environmental reversal here on earth. The alarming CO2 levels, the related warming and sea-level rise, the threats to the drinking water supply, this is the evidence of chaos that precedes a phase change. Remember, the phase change could be a return to a world with no “intelligent” life. Such human life is an experiment of only 100,000, or some now say 200,000 years, an inconsequential period in the 4.5 billion year history of the earth.

To explain the problem in another way, I turn to The Proceedings of the National Academy of Science[7].

“We show that for thousands of years, humans have concentrated in a surprisingly narrow subset of Earth’s available climates, characterized by mean annual temperatures around ∼13 °C. This distribution likely reflects a human temperature niche related to fundamental constraints. We demonstrate that depending on scenarios of population growth and warming, over the coming 50 [years], 1 to 3 billion people are projected to be left outside the climate conditions that have served humanity well over the past 6,000 [years]. Absent climate mitigation or migration, a substantial part of humanity will be exposed to mean annual temperatures warmer than nearly anywhere today.”

Perhaps I have exaggerated that some are considering evacuating to the moon or a planet. Perhaps only 1–3 billion people face uninhabitable conditions and will not be welcome in a remaining city-state. Not to worry, pick your city-state now. Learn to design algorithms so you will be an attractive citizen.

Law and regulation are the last part of the analysis. I recently worked on a project to design a law school course at the Masters level — Law and Technology. I think such a course should be an undergraduate degree requirement for every student. The impact of artificial intelligence technology and its derivatives, such as robotics, Blockchain, cyber-physical systems and cloud computing, will require a careful and thoughtful re-examination of the law. The problem is few lawyers, judges or government officials understand the AI technology or applications well enough to make informed decisions. Perhaps lawyers can appreciate being replaced as document preparers by natural language processing (NLP) software, perhaps a judge can understand the privacy issues of social media, but maybe not where to place liability — software developer, cloud service provider, platform operator or payment processing agent. When we get to genetic technology — anything to do with understanding, making or adapting genetic material[8] — we might need to develop a special class of judges with PhDs in biology or computational biology or systems biology or mechanistic modeling and a law degree. Given how badly we have done with the environment, I am even more terrified by lawyering and government regulation around genetic technology. My conclusion would probably be to limit genetic technology to disease therapy and not cross the border into the custom genetic design of children.

Take note, probably for the first time in history most government officials at all levels have little or no knowledge of the new technologies and their potential impact. The 1st, 2nd and 3rd industrial revolutions were comparatively tame, focused on productivity improvement and new information-sharing technology. We largely ignored the harmful consequences of each new energy source that accompanied a particular industrial revolution (see Figure 2 above). Today we need multidisciplinary leaders who are able to address the environmental issues, properly regulate all the new technology especially around biology and address the continuing trend toward less and less required human labor and the related economic consequences.


The strength of the PESTEL analysis is that it is comprehensive. The weakness is that such analysis is not holistic and focuses at the component level. Much if not all of the problems marked by chaos today are caused by the lack of holistic thinking. Since the late 1700s, much of the world has prioritized manmade systems at the expense of natural systems. This approach worked relatively well until Rachel Carson (1937), the Club of Rome (1968) and a few other visionaries called attention to the need for a holistic approach that included the environment. Many years have passed since that first call for attention to the environment, and we have made little real progress in addressing the environment. The abundance of economic success has trained us to prioritize shareholder returns at the expense of the environment and a more fair distribution of the wealth.

In my opinion, the edge of chaos signals a phase transition to a world where we recognize the urgency of the environmental problems and prioritize natural systems accordingly. W. Brian Arthur, the noted complexity economist, believes that technologies appear to solve the then-current problems. Perhaps the technology paradigm built around AI has appeared because we humans need more tools to address the environmental and wealth inequality problems. I believe we have the tools to address these challenges and the time to do it. I am increasingly worried about whether we have the will. This quote[9] from Georgetown Professor Charles King sums up the situation well.

“A better way to think about political cleavages was to observe which portions of society are most threatened by change and which ones seek to hasten it — and then to imagine how states might manage the differences between the two. Bureaucrats and politicians want to keep their jobs. Workers want a better standard of living. Intellectuals question old verities of national identity. These divides can create a survival problem for the institutions of state power. Self-preservation is clearly the dominant drive. “The only thing [the government] wants is for everything to go on as before.” Foreign Affairs June 2020

Notice: The views expressed herein are my personal views and do not reflect the views and opinions of any organization with whom I may be affiliated.






[5] U.S. Department of Labor







Robert Hacker

Director StartUP FIU-commercializing research. Entrepreneurship Professor FIU, Ex IAP Instructor MIT. Ex CFO One Laptop per Child. Built billion dollar company