14 December 2019 – The following essay is a verbatim copy of one I recently posted to a Global Business discussion site in response to a link emailed to me by Dr. Tiffany Jordan of Keiser University.
Thank you, TJ, for sending along a link to Steve Sjuggerud’s documentary on Chinese development. History teaches us that 5,000 years ago, China was one of two (maybe three, if you count Central America) population centers (the other was Egypt) where folks independently invented civilization. You can’t go far wrong by betting on people that smart!
The second factor in this story is that one out of six human beings on this planet is Chinese. With that many really smart people let loose to work together, they’re bound to push the limits of economic development. The last time that happened anywhere was in the 18th century when steam technology was let loose among the newly liberated populations of England, North America, and Europe. The resulting Industrial Revolution was a similar game changer. People from the countryside flocked to the cities to make the most of revolutionary technology, and made vast piles of wealth in the process. Sound familiar?
So, what could go wrong? The known preference of the Chinese people for long power distance is what could go wrong (Hofstede, 1993). Since Qin Shi Huang patched together the Chinese Empire in 221 BCE (Shi, 2014), the country has had a nearly unbroken record of authoritarian rule, which is why, after all this time, they’re still stuck with “emerging nation” status. The latest period of lax central control started in the mid-1970s, when Mao Zedong lost control of his Marxist People’s Republic (PRC), and good things started happening in China.
China is home to two philosophies at opposing ends of the power-distance spectrum: Taoist egalitarianism and Confucian formality (Carnogurská, 2014). Taoists insist (among other things) on individual self-rule. Confucionists insist on respect for authority (Zhou, 2011). You can guess which philosophy Xi Jinping’s power-grabbing PRC favors! It is no accident that the slowing of China’s economic expansion immediately followed Xi’s re-institution of central authority. The stark contrast can be seen in the difference between the miracle on the Chinese mainland and the even-bigger miracle that has been playing out in Hong Kong.
I’m always ambivalent, however, about investing in the Chinese “miracle.” Back in the early 1990s I was asked to duplicate my success helping expand an American electronics publication into Europe by doing the same thing in China. With images from Tiananmen-Square events fresh in my mind, I declined. Unlike my corporate bosses, I just didn’t trust the PRC leadership to play nice. That corporation is now out of the publishing business! I’d done the same thing in the 1970s when I declined the last Shah of Iran’s invitation to take our Boston-based Physics Department to Tehran University–just before theirrevolution broke out. (Whew!)
China is not Iran, and Xi Jinping is not Mohammad Reza Shah. Pres. Xi likes leading the fastest-growing economy on the planet, but is facing his big test with current events in Hong Kong. Will he figure a way to defuse that uprising, or will his unenlightened cronies in Beijing push him into a disasterous reprise of Tiananmen-Square? I’m not jumping onto the Chinese bandwagon until I see the result.
Carnogurská, M. (2014). Xunzi, an ingeniously critical synthesist of Chinese philosophy of the pre-Qin period. Journal of Sino – Western Communications, 6(1), 3-25.
Hofstede, G. (1993). Cultural constraints in management theories. Executive, 7(1), 81–94.
Shi, J. (2014). Incorporating all for one: The first emperor’s tomb mound. Early China, 37(1), 359-391.
Zhou, H. (2011). Confucianism and the legalism: A model of the national strategy of governance in ancient China. Frontiers of Economics in China, 6(4), 616-637.
4 September 2019 – I’m in the early stages of a long-term research project for my Doctor of Business Administration (DBA) degree. Hopefully, this research will provide me with a dissertation project, but I don’t have to decide that for about a year. And, in the chaotic Universe in which we live a lot can, and will, happen in a year.
I might even learn something!
And, after learning something, I might end up changing the direction of my research. Then again, I might not. To again (as I did last week ) quote Winnie the Pooh: “You never can tell with bees!”
No, this is not an appropriate forum for publishing academic research results. For that we need peer-reviewed scholarly journals. There are lots of them out there, and I plan on using them. Actually, if I’m gonna get the degree, I’m gonna have to use them!
This is, however, an appropriate forum for summarizing some of my research results for a wider audience, who might just have some passing interest in them. The questions I’m asking affect a whole lot of people. In fact, I dare say that they affect almost everyone. They certainly can affect everyone’s thinking as they approach teamwork at home and at work, as well as how they consider political candidates asking for their votes.
For example, a little over a year from now, you’re going to have the opportunity to vote for who you want running the United States Government’s Executive Branch as well as a few of the people you’ll hire (or re-hire) to run the Legislative Branch. Altogether, those guys form a fairly important decision-making team. A lot of folks have voiced disapprobation with how the people we’ve hired in the past have been doing those jobs. My research has implications for what questions you ask of the bozos who are going to be asking for your votes in the 2020 elections.
One of the likely candidates for President has shown in words and deeds over the past two years (actually over the past few decades, if you care to look that far into his past) that he likes to make decisions all by his lonesome. In other words, he likes to have a decision team numbering exactly one member: himself.
Those who have paid attention to this column (specifically the posting of 17 July) can easily compute the diversity score for a team like that. It’s exactly zero.
When looking at candidates for the Legislative Branch, you’ll likely encounter candidates who’re excessively proud to promise that they’ll consult that Presidential candidate’s whims regarding anything, and support whatever he tells them he wants. Folks who paid attention to that 17 July posting will recognize that attitude as one of the toxic group-dynamics phenomena that destroy a decision team’s diversity score. If we elect too many of them to Congress and we vote Bozo #1 back into the Presidency, we’ll end up with another four years of the effective diversity of the U.S. Government decision team being close to or exactly equal to zero.
Preliminary results from my research – looking at results published by other folks asking what diversity or lack thereof does to the results of projects they make decisions for – indicates that decision teams with zero effective diversity are dumber than a box of rocks. Nobody’s done the research needed to make that statement look anything like Universal Truth, but several researchers have looked at outcomes of a lot of projects. They’ve all found that more diverse teams do better.
Anyway, what this research project is all about is studying the effect of team-member diversity on decision-team success. For that to make sense, it’s important to define two things: diversity and success. Even more important is to make them measurable.
I’ve already posted about how to make both diversity and success measurable. On 17 July I posted a summary of how to quantify diversity. On 7 August I posted a summary of my research (so far) into quantifying project success as well. This week I’m posting a summary of how I plan to put it all together and finally get some answers about how diversity really affects project-development teams.
What I’m hoping to do with this research is to validate three hypotheses. The main hypothesis is that diversity (as measured by the Gini-Simpson index outlined in the 17 July posting) correlates positively with project success (as measured by the critical success index outlined in the 7 August posting). A secondary hypothesis is that four toxic group-dynamic phenomena reduce a team’s ability to maximize project success. A third hypothesis is that there are additional unknown or unknowable factors that affect project success. The ultimate goal of this research is to estimate the relative importance of these factors as determinants of project success.
Understanding the methodology I plan to use begins with a description of the information flows within an archetypal development project. I then plan on conducting an online survey to gather data on real world projects in order to test the hypothesis that it is possible to determine a mathematical function that describes the relationship between diversity and project success, and to elucidate the shape of such a function if it exists. Finally, the data can help gauge the importance of group dynamics to team-decision quality.
The figure above schematically shows the information flows through a development project. External factors determine project attributes. Personal attributes, such as race, gender, and age combine with professional attributes, such as technical discipline (e.g., electronics or mechanical engineering) and work experience to determine raw team diversity. Those attributes combine with group dynamics to produce an effective team diversity. Effective diversity affects both project planning and project execution. Additional inputs from stakeholder goals and goals of the sponsoring enterprise also affect the project plans. Those plans, executed by the team, determine the results of project execution.
The proposed research will gather empirical data through an online survey of experienced project managers. Following the example of researchers van Riel, Semeijn, Hammedi, & Henseler (2011), I plan to invite members of the Project Management Institute (PMI) to complete an online survey form. Participants will be asked to provide information about two projects that they have been involved with in the past – one they consider to be successful and one that they consider less successful. This is to ensure that data collected includes a range of project outcomes.
There will be four parts to the survey. The first part will ask about the respondent and the organization sponsoring the project. The second will ask about the project team and especially probe the various dimensions of team diversity. The third will ask about goals expressed for the project both by stakeholders and the organization, and how well those goals were met. Finally, respondents will provide information about group dynamics that played out during project team meetings. Questions will be asked in a form similar to that used by van Riel, Semeijn, Hammedi, & Henseler (2011): Respondents will rate their agreement with statements on a five- or seven-step Likert scale.
The portions of the survey that will be of most importance will be the second and third parts. Those will provide data that can be aggregated into diversity and success indices. While privacy concerns will make masking identities of individuals, companies and projects important, it will be critical to preserve links between individual projects and data describing those project results.
This will allow creating a two-dimensional scatter plot with indices of team diversity and project success as independent and dependent variables respectively. Regression analysis of the scatter plot will reveal to what extent the data bear out the hypothesis that team diversity positively correlates with project success. Assuming this hypothesis is correct, analysis of deviations from the regression curve (n-way ANOVA) will reveal the importance of different group dynamics effects in reducing the quality of team decision making. Finally, I’ll need to do a residual analysis to gauge the importance of unknown factors and stochastic noise in the data.
Altogether this research will validate the three hypotheses listed above. It will also provide a standard methodology for researchers who wish to replicate the work in order to verify or extend it. Of course, validating the link between team diversity and decision-making success has broad implications for designing organizations for best performance in all arenas of human endeavor.
de Rond, M., & Miller, A. N. (2005). Publish or perish: Bane or boon of academic life? Journal of Management Inquiry, 14(4), 321-329.
van Riel, A., Semeijn, J., Hammedi, W., & Henseler, J. (2011). Technology-based service proposal screening and decision-making effectiveness. Management Decision, 49(5), 762-783.
28 August 2019 – The short answer is, to quote Pooh Bear in A.A. Milne’s Winnie-the-Pooh, “You never can tell with bees!” Or, with advancing technology, for that matter. Last week, however, the Analytics Team at Autolist published results of a survey of 1,567 current car shoppers that might shed some light on the question of whether electric vehicles (EVs) can fully replace vehicles with internal combustion engines (ICEs).
The Analytics Team asked survey respondents what were their biggest reasons to not buy an electric vehicle. By looking at the results, we can project when, how, and if e-vehicle technology can ever surmount car-shoppers’ objections.
The survey results were spectacularly unsurprising. The top three barriers to purchasing an electric vehicle were:
Concerns about lack of adequate range;
E-vehicles’ relatively high cost compared to similar gas vehicles; and
Concerns about charging infrastructure.
Anybody following the development of electric vehicles already knew that. Most folks could even peg the order of concern. What was somewhat surprising, though, is how little folks’ trepidation dropped off for less significant concerns. Approximately 42% of respondents cited adequate range as a concern. The score dropped only to about 14% for the ninth-most-concerning worry: being unhappy with choices of body style.
What that means for development of electric-vehicle technology is that resolving the top three issues won’t do the job. Resolving the top three issues would just elevate the next three issues to top-concern status for 25-30% of potential customers. That’s still way too high to allow fully replacing ICE-powered vehicles with EVs, as nine European countries (so far) have announced they want to do between 2020 and 2050.
Looking at what may be technologically feasible could give a glimpse of how sane or insane such ICE bans might be. What we can do is go down the list and speculate on how tough it will be to overcome each obstacle to full adoption. The Pareto chart above will show the “floor” to folks’ resistance if any of these issues remains unmet.
Top Three Issues
By inspection the Pareto chart shows natural breaks into three groups of three. The top three concerns (range, cost, and charging) all concern roughly 40% of respondents. That’s approximately the size of the political base that elected Donald Trump to be President of the United States in 2016.
I mention Trump’s political base to give perspective for how important a 40% rating really is. Just as 40% acceptance got Trump over the top in a head-to-head competition with Hillary Clinton, a 40% non-acceptance is enough to doom electric vehicles in a head-to-head competition with ICE-powered vehicles. So, what are the chances of technologically fixing those problems?
Lack of Range is just a matter of how much energy you can backpack onto an electric vehicle. The inputs to that calculation are how far you can drive on every Joule of energy (for comparison, 3,600 Joules equal one Watt-hour of energy) and how many Joules can you pack into a battery that an electric vehicle can reasonably carry around. I don’t have time to research these data points today, since I have only a few hours left to draft this essay, so I’m just not going to do it.
There are two ways, however, that we can qualitatively guesstimate the result. First, note that EV makers have already introduced models that they claim can go as far on one “fill up” (i.e., recharge) as is typical for ICE vehicles. That’s in the range of 200 to 300 miles. I can report that my sportscar goes pretty close to 200 miles on a tankful of gas, and that’s adequate for most of the commuting I’ve done over my career.
The second way to guesstimate the result is to watch progress of the Formula E electric-vehicle races. Formula E has been around for nearly a decade now (the first race was run in 2011), so we have some history to help judge the pace of technological developments.
The salient point that Formula E history makes is that battery range is improving. In previous events batteries couldn’t last a reasonable race distance. Unlike other forms of motor racing, where refueling takes just a few seconds, it takes too darn long to charge up an electric vehicle to make pit stops for refueling viable.
The solution was to have two cars for each racer. About half way through the race, the first car’s batteries would run out of juice, and the driver would have to jump into the second car to complete the race. This uncomfortable situation lasted through the last racing season (2018).
This year, however, I’m told that the rules have been changed to require racers to complete the entire race in one car on one battery charge. That tells us that e-technology has advanced enough to allow racers to complete a reasonable race distance at a reasonable race speed on one charge from a reasonable battery pack. That means e-vehicle developers have made significant progress on the range-limitation issue. Projecting into the future, we can be confident that range limits will soon become a non-issue.
High e-vehicle cost will also soon become a non-issue. History plainly shows that if folks are serious about mass-marketing anything, purchase prices will come down to a sustainable level. While Elon Musk’s Tesla hasn’t yet shown a profit while the company struggles to produce enough cars to fill even today’s meager electric-vehicle demand, there are some very experienced and professional automobile manufacturers also in the electric-vehicle game. Anyone who thinks those guys won’t be able to solve the mass-production-at-a-reasonable-cost problem for electric vehicles just hasn’t been paying attention over the past century and a quarter. They’re gonna do it, and they’ll do it very soon!
Charging infrastructure is similarly just a matter of doing it. It didn’t take the retail-gasoline vendors long to build out infrastructure to feed ICE-powered cars. Solving the EV-charging problem is not much more difficult. You just plunk charging stations down on every corner to replace the gasoline filling stations you’re going to close down because you’ve made ICE vehicles illegal.
The top three issues don’t seem to pose any insurmountable obstacles, so we can move on to the second-tier issues of recharging time, insufficient public knowledge, and battery life. All of these concerned just under 30% of survey respondents.
Charging time is the Achilles heel for EV technology. Currently, it takes hours to recharge an electric-car’s batteries. Charging speed is a matter of power, and that’s a serious limitation. It’s the real charging-infrastructure problem!
It takes less than a minute to pump ten gallons of gasoline into my sportscar’s fuel tank. That ten gallons can deliver approximately 1.2x109 Joules of energy. That’s 1.2 billion Watt seconds!
To cram that much energy into a battery in one minute would take a power rate of 20 MW. That’s enough to power a medium-sized town of 26,000 people! Now, look at a typical gas station with eight gas pumps, and imagine each of those pumps pumping a medium-size-town’s worth of electric power into a waiting EV’s battery. Now, count the number of gas stations in your town.
That should give you some idea of the enormity of the charging-infrastructure problem that mass use of electric vehicles will create!
I’m not going to suggest any solutions to this issue. Luckily, since I don’t advocate for mass use of electric vehicles, I don’t have to solve this problem for people do. In the interest of addressing the rest of the issues, let’s pretend we’re liberal politicians and can wave our fairy wands to make the enormity of this issue magically disappear.
Inadequate public knowledge is a relative non-issue. Electric vehicles aren’t really difficult to understand. In fact, they should be simpler to operate than ICE vehicles. Especially since the prime mover EVs use is a motor rather than an engine.
Hardly anyone I know is conscious of the difference between a motor and an engine. Everyone knows it, but doesn’t think about it. Everyone knows that to run an ICE you have to crank it with a starter motor to get it running in the first place, and then you’ve got to constantly take care not to stall it. That knowledge becomes so ingrained by the time you get a driver’s license that you don’t even think about it.
Electric motors are not engines, though. They’re motors, which means they start all by themselves as soon as you feed them power. When you brake your electric car to a stop at a stop light, it just stops! You don’t have to then keep it chunking over at idle. Stopped is stopped.
When sitting at a stop light, or waiting for your spouse to load groceries into the boot, an EV uses no power ‘cause it’s stopped. When you’re ready to go, you push on the accelerator pedal, and it just goes. No more fiddling with clutch pedals or shifting gears or using any of the other mechanical skills manual-transmission cars force us to learn and automatic-transmission cars take care of for us automatically. The biggest thing we have to learn about driving EVs is how easy it is.
There isn’t much else to learn about EVs either. Gearheads will probably want to dig into things like regenerative braking and multipolar induction motors, but just folks won’t care. If the most important thing about your ICE-powered SUV is the number of cup holders, that will all be the same in your electric-powered SUV.
Overall battery life will be an issue for years going forward, but eventually that will become a non-issue, too. Overall battery life refers to the number of times your lithium-ion battery pack can be recharged before it swells up and bursts. Ten years from now we expect to have a better solution than lithium-ion batteries, but they aren’t all that bad a solution for now, anyway.
It was annoying when the relatively small lithium-ion battery pack in your Samsung smartphone burst into flames back in 2016, and you can imagine what’ll happen if the much larger battery pack in your Tesla does the same thing when sitting in the garage under your house. But, it’ll be less of a problem than when the battery packs in airliners started going up in smoke a few years ago. We got through that and we’ll get through this!
Third-rate issues concerned 15-20% of survey respondents. They include issues around electric-motor reliability, battery materials, and vehicle designs. While they concerned relatively fewer respondents, enough people said they worried about them that they have to be addressed before EVs can fully replace ICE-powered vehicles.
Reliability concerned 20% of survey respondents. It shouldn’t. Electric motors have been around since William Sturgeon built the first practical one in 1832. They’ve proved to be extremely reliable with only two parts to wear out: the commutator brushes and the bearings. Unlike ICE power units, they need practically no regular maintenance. With modern solid-state power electronics taking the place of the old commutators, the only things left to wear out are the bearings, which take less punishment than the load-carrying wheel bearings all cars have.
Battery materials are a concern, but when viewed in perspective they shouldn’t be. Yes, lithium burns vigorously when exposed to air, and is especially flammable when exposed to water. But, gasoline burns just as vigorously when ignited by even a spark.
A tankful of gasoline can be responsible for a horrendous fire if ignited in an accident. Lithium ion batteries can cause similar mayhem, but are no more likely to do so than any other energy-storage medium.
Body size/style should not, to my mind, even be on the list. Electric-powered vehicles present fewer design constraints to coach builders than those with ICE power plants. In fact, it’s possible to design an EV chassis such that you can put any body on it that you can think of. Especially if you design that chassis with individually driven wheels, there are no drive-shaft and power-train issues to deal with.
Looking at the nine EV issues that survey respondents said would give them pause when considering the purchase of an electric vehicle rather than an ICE-powered vehicle, the only one not inevitably amenable to technological solution is the scale of the charging infrastructure. All of the others we can expect to be disposed of in short order as soon as we collectively decide we want to do it.
That charging infrastructure issue poses two problems: recharging time and recharging cost. The ten-gallon fuel tank in my sportscar typically gets me through about a week. That’s because I do relatively little commuting. I drive a round trip of about 60 miles to teach classes in Fort Myers twice a week. The rest of my driving is short local trips that burn up more than their fair share of gasoline because they’re stop-and-go driving.
In the past, I’ve had more difficult commute schedules that would have burned up a tankful of gas a day. Commuting more than 200 miles a day is almost unheard of. So, having to sit at a recharging station for hoursto top up batteries in the middle of a commute would be an unusual concern for a commuter. They would top up the batteries at home overnight.
Road trips, however, are another story. On a typical road trip, most people plan to burn up two tankfuls of fuel a day in two 4-5-hour stints. That’s why most vehicles have fuel tanks capable of taking them 200-300 miles. That’s about how far you can drive in a 4-5-hour stint. So, you drive out the tank, then stop for a while, which includes spending a minute or so refilling the tank. Then you’re ready to go on the next stint.
With an electric vehicle, however, which has to sit still for hours to recharge, that just doesn’t work. Instead of taking two days to drive to Virginia to visit my daughter, the trip would take most of a week. Electric vehicles are simply not suitable for road trips unless and until we solve the problem of supplying enough electric power to an EV’s battery to supply a small town!
Then, there’s the expense. If you’re going to recharge your EV once a week (or top it off from your wall outlet every night), you’ve gotta pay for that energy at the going rate. That 1.2 billion Joules translates into 333 kiloWatt hours added to your light bill every week. At a typical U.S. electricity rate of $0.12/kWh, that’s about $40. That may not seem like much, but compare it to the $25 I typically pay for a tankful of gas.
In conclusion, it looks like EVs will eventually do fine as dedicated commuter vehicles. They’ll cost a little more to run, but not enough to break most budgets. For road trips, however, they won’t work out well.
Thus, the answer to the question: “Can electric vehicles fully replace gas guzzlers?” is probably “No.” They’re fine for intra-city commuting, or commuting out to the suburbs, but unless Americans want to entirely forgo the possibility of taking road trips, ICE-powered vehicles will be needed for the foreseeable future.
31 July 2019 – Over the millennia that philosophers have been doing their philosophizing, a recurring theme has been the quest to come up with some simple definition of what sets humans apart from so-called “lower” animals. This is not just idle curiosity. From Aristotle on, folks have realized that understanding what makes us human is key to making the most of our humanity. If we don’t know who we are, how can we figure out how to be better?
In recent decades, however, it’s become clear that this is a fool’s errand. Such a definition of humanity doesn’t exist. Instead, what sets humans apart is a suite of characteristics, such as two eyes in the front of a head that’s set up on a stalk over a main torso, with two legs down below and a couple of arms on each side ending with wiggly fingers and opposable thumbs; a brain able to use sophisticated language; and so forth. Not every human has all of them (for example, I had a friend in Arizona who’d managed to lose his right arm and shoulder without losing his humanity) and a lot of non-humans have some of them (for example, chimpanzees use tools a lot). What marks humans as humans is having most of these characteristics, and what marks non-humans as not human is lacking a lot of them.
On the other hand, there is one thing that most humans are capable of that most non-humans aren’t: humans are capable of doing the math.
Yeah, crows can count past two. I hear that pigeons are good at pattern recognition. But, I’m talking about mathematical reasoning more sophisticated than counting past seven. That’s something most humans can do, and most other animals can’t.
Everybody has their mathematical limitations.Experience indicates that one’s mathematical limitations are mostly an issue of motivation. At some point, just about everybody decides that it’s just not worth putting in the effort needed to learn any more math than they already know.
That’s because learning math is hard. It’s the biggest learning challenge most of us ever face. Most of us give up long before reaching the limits of our innate ability to puzzle it out.
Luckily, there are some who are willing to push the limits, and master mathematical puzzles that no human has solved before. That’s lucky because without people like them, human progress would quickly stop.
Even better, those people are often willing – even anxious – to explain what they’ve puzzled out to the rest of us. For example, we have geometry because a bunch of Egyptians puzzled out how to design pyramids, stone temples and other stuff they wanted to build, then proudly explained to their peers exactly how to do it. We have double-entry accounting because folks in the Near East wanted to keep track of what they had, figured out how to do it, and taught others to help. We’ve got calculus because Sir Isaac Newton and a bunch of his buddies figured out how to predict what the visible planets would do next, then taught it to a bunch of physics students.
It’s what we like to call “Applied Mathematics,” and it’s responsible for most of the progress people have made since the days of stone knives and bear skins. Throughout history, we’ve all stood around scratching our heads about things we couldn’t make sense of until some bright guy (or gal) worked out the right mathematics and applied it to the problem. Then, suddenly what had been unintelligible became understandable.
These days, what I think is the bleeding edge of applied mathematics is nonlinear dynamics and chaos. Maybe there’s some fuzzy logic thrown into the mix, too. Most of the math tools needed to understand (as in “make mathematical models using”) these things is pretty well in hand. What we need to do is apply such tools to the problems that today vex us.
A case in point is the Gini-Simpson Diversity Index I described in this blog two weeks ago. That is a small brick in the wall of a structure that I hope will someday help us avoid making so many dumb choices. Last week I ran across another brick in a paper written by a couple of computer science professors at my old alma materRensselaer Polytechnic Institute (aka RPI, or as we used to call it when I was there as a graduate student, “the Tute”). This bit of intellectual flotsam describes a mathematical model the authors use to predict how political polarization evolves in the U.S. Congress.
Polarization is one of four (at my last count) toxic group-dynamics phenomena that make collaborative decision making fail. Basically, the best decisions are made by groups that work together to reach a consensus. We get crappy decisions when the group’s dynamics break down.
The RPI model is a nonlinear differential equation describing an aspect of the dynamics of decision-making teams. Specifically, it quantifies conditions that determine whether decision teams evolve toward consensus or polarization. We see today what happens when Congress evolves toward polarization. The authors’ research shows that prior to about 1980 Congress evolved toward consensus. Seeing this dynamic at work mathematically gives us a leg up on figuring out why, and maybe doing something about it.
I’m not going to go into the mathematical model the RPI paper presents. The study of nonlinear dynamical systems is far outside the editorial focus of this column. At this point, I’m not going to talk about solutions the paper might suggest for toxic U.S. Government polarization, either. The theory is not well enough developed yet to provide meaningful suggestions.
The purpose of this posting is to point out that application of sophisticated mathematics is necessary for solving society’s most intractable problems. As I said above, not everybody is ready and willing to become expert in using such tools. That’s not necessary. What I hope you’ll walk away with today is an appreciation of applied mathematics’ importance for societal development, and a willingness to support STEM (science, technology, engineering and mathematics) education throughout our school system. Finally, I hope you’ll encourage students who show an interest to learn the techniques and follow STEM careers.
24 July 2019 – Abraham Harold Maslow (1908-1970) was a 20th century psychologist famous for describing human motivation as an hierarchy of needs in a 1943 paper entitled “A Theory of Human Motivation” published in Psychological Review. He was a central figure in the founding of Humanistic Psychology, which concentrates on studying mentally healthy humans.
You have to remember that Maslow did his most important work in the middle of the 20th century. At that time there was great popular interest in the works of Sigmund Freud, who worked with the mentally ill, and B.F. Skinner who mainly studied lower animals. Indeed, the entire arts-and-letters school of Surrealism explicitly drew inspiration from Andre Breton’s interpretation of Freud’s work. Despite (or perhaps because of) this interest in Freud and Skinner’s work, there had been little, if any, study of mentally healthy people.
Humanistic Psychologists felt these earlier studies were of limited value to understanding the healthy human mind. Maslow chose to study the workings of healthy human minds from all social strata, but he was especially interested in studying high achievers. For this reason those of us interested in organizational behavior find his humanists of particular interest. We kinda hope our organizations are populated with, and run by, mentally healthy humans, rather than Freud’s neurotics or Skinner’s lab rats!
Maslow’s emphasis on studying high achievers likely gave rise to the first misconception I want to talk about today: the idea that his work gives cover to elitist views. This elitist theory assumes that everyone strives to reach the self-actualization level at the top of the so-called “Pyramid of Needs” used to illustrate Maslow’s hierarchy, but that only an elite fraction of individuals reach it. Lesser individuals are doomed to wallowing in more squalid existences at lower levels.
The second misconception I want to treat today is a similar notion that people start out at the lower levels and climb slowly up to the top as their incomes rise. This theory substitutes a ladder for the pyramid image to visualize Maslow’s hierarchy. People are imagined to climb slowly up this ladder as both their income and social status increase. This, again, gives cover for elitist views as well as laissez-faire economics.
What Maslow’s Hierarchy really describes is a priority system that determines what people are motivated to do next. It has little to do with their talents, income or social status. To illustrate what I mean, I like to use the following thought experiment. This thought experiment involves Albert Einstein and it’s particularly appropriate because the Grizzled Genius loved thought experiments.
Albert Einstein’s greatest joy was becoming immersed in translating his imaginings about the physical universe into mathematical equations. This is an example of what Maslow called “peak experiences.” Maslow believed these were periods when self-actualized people (those engaged in satisfying their self-actualization need) are happiest and most productive.
Once in a while, however, Einstein would become hungry. Hunger is, however, one of those pesky physiological needs down at the bottom of Maslow’s Hierarchy. There’s nothing aspirational about hunger. It’s what Fredrick Herzberg called a “hygiene factor” or “demotivator.” Such needs are the opposite of aspirational.
If you’ve got an unsatisfied demotivator need, you become unhappy until you can satisfy it. If, for example, you’re hungry, or have a toothache, or need to pee, it becomes hard to concentrate on anything else. Your only thought is (depending on the nature of the unmet physiological need) to go to the bathroom, or the dentist, or, as in Einstein’s case, go find lunch.
The moral of this story is that people don’t sit somewhere for extended periods of time on a shelf labeled with one of Maslow’s categories. Rich people don’t float in a blissful self-actualizing state. Poor people don’t wallow in a miasma of permanently unmet physiological needs. People constantly move up and down the pyramid depending on what the most pressing unmet need of the moment is.
The hierarchy is therefore actually an inverted priority list. Physiological needs are more important than safety needs. When something frightens you – a safety need – the first thing that happens is you feel an urge to pee to take care of a physiological need to prepare your body for running like a scared rabbit. When you see a fast-moving Chevy bearing down on you, you immediately forget pride in that (esteem level) achievement award you just got.
A combination of confusion about how Maslow’s heirarchy works and his preference for studying high achievers has led many people to imagine his work gives cover for elitist views. If you’re predisposed to imagine that rich people, smart people, or those of high social status are somehow innately “better” than denizens of what 19th century novelist Edward Bulwer-Lytton called “the great unwashed,” then you’re an elitist. An elitist can derive great comfort by misinterpreting Maslow’s work. You can imagine there being a cadre of elite people destined to spend their lives in some ethereal existence where all lower needs are completely satisfied and life’s only pursuit is self actualization.
The poster child for elitism is 16th century theologian John Calvin. In Calvin’s version of Protestant theology everyone was tainted with original sin and doomed to an eternity in Hell. That was a pretty common view at the time of the Protestant Reformation. Calvin added an elitist element by hypothesizing that there was a limited number of individuals (the elect) whom God had chosen for salvation.
It’s called predestination and those folks got tickets into the elite ranks through no merit of their own. There was nothing anybody could do to beg, borrow, or steal their way in. God decided, while making the Universe in the first place, who was in and who was out based on nothing but His whimsey. (Sexist pronoun used specifically to make a point about Calvinism.)
Of course, the requirements of natural selection logically lead to everyone having a desire to be part of an elite. We all want to be different, like the Dada-esque avant garde group King Missile. That’s how DNA measures its success. Only elite DNA gets to have long-term survival.
So, elitism has a lot of natural appeal. This natural appeal accounts for all kinds of rampant racism and xenophobia. Misunderstanding Maslow’s heirarchy provides a pseudoscientific rationale for elitism. To the elitist, the fact that this view is completely mistaken makes no nevermind.
I hope that by now I have disposed of the elitist fallacy.
Economic Ladder Fallacy
Hoping that I’ve disposed of the idea that Maslow’s work gives cover to elitism, I’ll turn to the fallacy of imagining his hierarchy as an economic ladder. This puppy is a natural outgrowth of the Pyramid of Needs image. The top (self actualization) level of the pyramid is imagined as “higher” than the bottom (physiological) level.
This image actually works from the viewpoint that “lower” needs take precedence over “higher” needs in the same way that a building’s supporting foundation takes precedence over the walls and roof. Without a foundation, there’s nothing to support walls or a roof in the same way that without fulfilling physiological needs, there’s no motivation for, say, self actualization.
Think of it this way: dead people, whose physiological needs are all unmet, hardly ever want to run for President.
So, how do you reach something high? You use a ladder!
That’s the thinking that transforms the Pyramid of Needs into some kind of ladder.
If you’re a strict materialist (and way too many Americans are strict materialists) the “high” you care about reaching is wealth. Folks who haven’t understood last month’s posting entitled “The Fluidity of Money” often confuse income with wealth, so there’s some appeal to thinking about Maslow’s Hierarchy of Needs as a metaphor for income levels. That completes the economic-ladder fallacy.
With this fallacy, folks imagine that everyone starts out at the bottom of the ladder and, with time, hard work and luck, climbs their way to the top. There are obvious problems matching income levels with needs levels, but if you’re sufficiently intellectually lazy, you can unfocus your mind’s eye enough to render these problems invisible.
I especially get a kick out of efforts to use the idea of Engel curves (from economics) to make this ladder fallacy work. Engel curves map the desireability (measured as the demand side of the economics law of supply and demand) of a given good or product against a given consumer’s income level. If the good in question is, for example, a used Mazda Miata, the desirability may be high when the consumer has a low-to-moderate income, but low if that particular consumer has enough income to pay for a new Ferrari SF90 Stradale. If you want to, it is obvious you can somehow conflate Engel curves with the ladder idea of Maslow’s Heirarchy of Needs.
The problem with this thinking is, first, that the Ladder doesn’t make a lot of sense as a visualization for Maslow’s Heirarchy, since the latter is formost a priority-setting scheme; second, that Maslow’s Hierarchy has little connection to income; and, third, that Engel curves present an incomplete view of what makes a product desirable.
The elitist fallacy and the economic-ladder fallacy are not the only fallacies people, with their infinite capacity to generate cockamamie theories, can concoct in connection to Maslow’s work. They are just two that have come up recently in articles I’ve had occasion to read. I think analyzing them can also help clarify how the Hierarchy of Needs applies to understanding human behavior.
Besides, I’ve had a bit of fun knocking them around, and I hope you have, too.
17 July 2019 – It’s come to my attention that a whole lot of people don’t know how to calculate a diversity score, or even that such a thing exists! How can there be so much discussion of diversity and so little understanding of what the word means? In this post I hope to give you a peek behind the curtain, and maybe shed some light on what diversity actually is and how it is measured.
This topic is of particular interest to me at present because momentum is building to make a study of diversity in business-decision making the subject of my doctoral dissertation in Business Administration. Specifically, I’m looking at how decision-making teams (such as boards of directors) can benefit from membership diversity, and what can go wrong.
The dictionary definition of diversity is: “the condition of having or being composed of differing elements.”
So, before we can quantify the diversity of any group, we’ve got to identify what makes different elements different. This, by the way, is all basic set theory. In different contexts what we mean by “different” may vary. When we’re talking about group decision making in a business context, it gets pretty complicated.
A group may be subdivided, or “stratified” along various dimensions. For example, a team of ten people sitting around a table trying to figure out what to do next about, say, a new product could be subdivided in various ways. One way to stratify such a group is by age. You’d have so many individuals in their 20’s, so many might be in their 30’s, and so forth up to the oldest group being aged 50 or more. Another (perhaps more useful) way to subdivide them is by specialty. There may be so many software engineers, so many hardware engineers, so many marketers, and so forth. These days stratifying teams by gender, ethnicity, educational level or political persuasion could be important. What counts as diversity depends on what the team is trying to decide.
The moral of this story is that a team might score high in diversity along one dimension and very poorly along another. I’m not going to say any more about diversity’s multidimensional nature in this essay, however. We have other fish to fry today.
For now, let’s assume a one-dimensional diversity index. What we pick for a dimension makes little difference to the mathematics we use. Let’s just imagine a medium-sized group of, say, ten individuals and stratify them according to the color of tee-shirts they happen to be wearing at the moment.
What the color of their tee-shirts could possibly mean for the group’s decisions about new-product development I can’t imagine, and probably wouldn’t care anyway. It does, however, give us a way to stratify the sample. Let’s say their shirt colors fall out as in Table 1. So, we’ve got five categories of team members stratified by tee-shirt color.
NOTE: The next bit is mathematically rigorous enough to give most people nosebleeds. You can skip over it if you want to, as I’m going to follow it with a more useful quick-and-dirty estimation method.
The Gini–Simpson diversity index, which I consider to be the most appropriate for evaluating diversity of decision-making teams, has a range of zero to one, with zero being “everybody’s the same” and one being “everybody’s different.” We start by asking: “What is the probability that two members picked at random have the same color tee shirt?”
If you’ve taken my statistical analysis course, you’ll likely loathe remembering that the probability of picking two things from a stratified data set, and having them both fall into the same category is:
Where λ is the probability we want, N is the number of categories (in this case 5), and P is the probability that, given the first pick falling into a certain category (i) the second pick will be in the same category. The superscript 2 just indicates that we’re taking members two at a time. Basically P is the number of members in category i divided by the total number of members in all categories. Thus, if the first pick has a blue tee-shirt, then P is 3/10 = 0.3.
This probability is high when diversity is low, and low when diversity is high. The Gini-Simpson index makes more intuitive sense by simply subtracting that probability from unity (1.0) to get something that is low when diversity is low, and high when diversity is high.
NOTE: Here’s where we stop with the fancy math.
Veteran business managers (at least those not suffering from pathological levels of OCD) realize that the vast majority of business decisions – in fact most decisions in general – are not made after extensive detailed mathematical analysis like what I presented in the previous section. In fact, humans have an amazing capacity for making rapid decisions based on what’s called “fuzzy logic.”
Fuzzy logic recognizes that in many situations, precise details may be difficult or impossible to obtain, and may not make a significant difference to the decision outcome, anyway. For example, deciding whether to step out to cross a street could be based on calculations using precise measurements of an oncoming car’s speed, distance, braking capacity, and the probability that the driver will detect your presence in time to apply the brakes to avoid hitting you.
But, it’s usually not.
If we had to make the decision by the detailed mathematical analysis of physical measurements, we’d hardly ever get across the street. We can’t judge speed or distance accurately enough, and have no idea whether the driver is paying attention. We don’t, in general, make these measurements, then apply detailed calculations using Gallilean Transformations to decide if now is a safe time to cross.
No, we have, with experience over time, developed a “gut feel” for whether it’s safe. We use fuzzy categories of “far” and “near,” and “slow” or “fast.” Even the terms “safe” and “unsafe” have imprecise meanings, gradually shifting from one to the other as conditions change. For example “safe to cross” means something quite different on a dry, sunny day in summertime, than when the pavement has a slippery sheen of ice.
Group decision making has a similar fuzzy component. We know that the decision team we’ve got is the decision team we’re going to use. It makes no difference whether it’s diversity score is 4.9 or 5.2, what we’ve got is what we’re going to use. Maybe we could make a half-percent improvement in the odds of making the optimal decision by spending six months recruiting and training a blind Hispanic woman with an MBA to join the team, but are we going to do it? Nope!
We’ll take our chances with the possibly sub-optimal decision made by the team we already have in place.
Hopefully we’re not trying to work out laws affecting 175 million American women with a team consisting of 500 old white guys, but, historically, that’s the team we’ve had. No wonder we’ve got so many sub-optimal laws!
Anyway, we don’t usually need to do the detailed Gini-Simpson Diversity Index calculation to guesstimate how diverse our decision committee is. Let’s look at some examples whose diversity indexes are easy to calculate. That will help us develop a “gut feel” for diversity that’ll be useful in most situations.
So, let’s assume we look around our conference room and see six identical white guys and six identical white women. It’s pretty easy to work out that the team’s diversity index is 0.5. The only way to stratify that group is by gender, and the two strata are the same size. If our first pick happens to be a woman, then there’s a 50:50 chance that the second pick will be a woman, too. One minus that probability (0.5) equals 0.5.
Now, let’s assume we still have twelve team members, but eleven of them are men and there’s only one token woman. If your first pick is thewoman, the probability of picking a woman again is 1/12 = 0.8. (The Gini-Simpson formula lets you pick the same member twice.) If, on the other hand, your first pick is a man, the probability that the second pick will also be a man is 11/12 = 0.92. I plugged all this into an online Gini-Simpson-Index calculator (‘cause I’m lazy) and it returned a value of 26%. That’s a whole lot worse.
Let’s see what happens when we maximize diversity by making everyone different. That means we end up stratifying the members into twelve segments. After picking one member, the odds of the second pick being identical are 1/12 = 0.8 for every segment. The online calculator now gives us a diversity index of 91.7%. That’s a whole lot better!
What Could Possibly Go Wrong?
There are two main ways to screw up group diversity: group-think and group-toxicity. These are actually closely related group-dynamic phenomena. Both lower the effective diversity.
Group-think occurs when members are too accommodating. That is, when members strive too hard to reach consensus. They look around to see what other members want to do, and agree to it without trying to come up with their own alternatives. This produces sub-optimal decisions because the group fails to consider all possible alternatives.
Toxic group dynamics occurs when one or more members dominate the conversation either by being more vocal or more numerous. Members with more reticent personalities fail to speak up, thus denying the group their input. Whenever a member fails to speak up, they lower the group’s effective diversity.
A third phenomenon that messes up decision making for high-diversity teams is that when individual members are too insistent that their ideas are the best, groups often fail to reach consensus at all. At that point more diversity makes reaching consensus harder. That’s the problem facing both houses of the U.S. Congress at the time of this writing.
These phenomena are present to some extent in every group discussion. It’s up to group leadership to suppress them. In the end, creating an effective decision-making team requires two elements: diversity in team membership, and effective team leadership. Membership diversity provides the raw material for effective team decision making. Effective leadership mediates group dynamics to make it possible to maximize the team’s effective diversity.
10 July 2019 – ‘Way back in the late 1960s I spent an entire day as a news hawker. That is, I stood on street corners shouting things at passersby intended to induce them to by copies of a newspaper I was selling. The newspaper was something called The L.A. Free Press. It was produced and sold in Los Angeles, and the street corners I stood on had names like “West Hollywood Boulevard and Sunset.”
I’d recently transplanted from Boston, Massachusetts to the Los Angeles, California area and had never heard of The L.A. Free Press before. A small gang I’d been hanging out with that morning heard that I had a driver’s license on me, and knew that we could use it as collateral to get a great whacking stack of those newspapers to sell at a profit.
Seemed like a good idea at the time.
I initially thought the newspaper copies were somehow free for the taking (as so many local papers are today). I was quickly disabused of that idea because I got pretty decent money for buying copies of it at a low price, then selling them on street corners for a higher price. It clearly wasn’t that kind of free!
Then, I imagined that was (like so many thin publications of the time) some hippy-dippy propaganda rag full of free-love manifestos and ads for beatnik-poetry venues. Being a veteran hippy-beatnik-biker, that was okay with me. I didn’t care as long as there was coin to be had. I wasn’t one of Donovan Leitch’s “beatniks out to make it rich,” but I was interested in coming up with lunch money!
The main headline on the first page of the copies we got in exchange for a mortgage on my driver’s license sounded like a local-interest story that I was not embarrased to wave at potential newsprint buyers, so it didn’t seem to be some hippy-dippy propaganda rag, either. The papers actually sold pretty well!
I needed the money (being dead broke at the time), so I swallowed my pride and did the job. I kept the last copy from my stack, however, to read when I got back to wherever I was sleeping that night.
By the time I’d finished reading the thing I’d realized why the publication was called The L.A. Free Press. It was an independent newspaper founded by a small group dedicated to investigative journalism with nobody to answer to but their readers. I became proud to be working with them.
If I’d been smart and ambitious I would have tried to get a job with them writing copy. After all, part of my reason for relocating was to find some kind of writing gig. But, as is typical with homeless eighteen-year-olds living on the streets, I was more frightened and depressed than smart and ambitious. The next day I moved on to doing something that turned out to be another stupid career move.
Sometimes depression is not a sign of mental illness, but a rational response to the way your life is going.
What I learned from that episode of my misspent youth (What’s the point of misspending your youth if you’re not going to learn something from it?) was what intellectuals mean when they talk about “the Free Press.” It’s not just some empty slogan you hear once in a while on CNN. It’s how we, as citizens of a free country, keep track of what’s going on outside of our individual hovels.
The difference between we citizens of a free country and downtrodden medieval serfs slaving to feed their “betters,” is that we have some say in what goes on outside our hovels. We can’t affect things in a way that’s good for us and the people we care about unless we find out what’s actually going on out there. For that we hire independent journalists who have at least half a brain and make it their business to find out for us.
We pay them a living wage and (if we’ve got at least half a brain ourselves) listen to what they tell us is happening. The Free Press is not, as some dishonest demagogues try to tell us, “the enemy of the people,” but a necessary part of a free democratic society.
For this reason, the journalistic profession has been called “The Fourth Estate” since the Enlightenment. Originally, the term was meant to indicate that a Free Press was available – in addition to the three original estates of clergy, aristocracy and commoners – whose writ was to frame the debate upon which society made common decisions. Later political systems still had (usually) three competing authorities explicitly charged with governing, along with a Free Press implicitly charged with framing the debate about what to do next.
In the United States, our Constitution explicitly delineates a government made up of three co-equal branches: Legislature, Court System, and Executive. The Founding Fathers (If that’s not a sexist term, I don’t know what is!) realized they’d forgotten the Free Press in the original document when they couldn’t get anybody to ratify (agree to) the thing without immediately amending it to include a Free Press (as well as the rest of the Bill of Rights).
The Free Press was considered so important that it was included in the first amendment.
Before anybody gets the idea that I’m criticizing the Founding Fathers as incompetent, I want to point out that this error just goes to prove that those guys were human, and humans make mistakes. Specifically, they were exceedingly bright guys to whom the need for a vibrant Free Press was so obvious that they forgot to mention it. The first ten Amendments – the Bill of Rights – should be seen as an “Oh, Shit!” moment.
“How could we have left that out?”
Having a Free Press, and making good use of it, is the first thing you have to have to set up a democracy. In a sense, it’s not the “fourth” estate, but the first. All the rest is afterthought. It’s bells and whistles designed to be the mechanical parts of a democracy. They’re of no value whatsoever without a Free Press.
On the other hand, once you have a functioning Free Press and a society that makes good use of it, the rest of the bells and whistles will inevitably follow. In that sense, the Free Press is not an afterthought or a result of democracy. Instead, it’s the essence of democracy. That’s why the first thing would-be authoritarians seek to eliminate is the Free Press.
3 July 2019 – Long time readers of my columns will know that one of my favorite philosophical questions is: “How do we know what we think we know?” Along the way, my thoughts have gravitated toward constructivism, which is a theory in the epistemology branch of philosophy.
Jean Piaget has been credited with initiating the constructivist theory of learning through his studies of childhood development. His methods were to ask probing questions of his children and others, in an attempt to understand how they viewed the world. He also devised and administered reading tests to schoolchildren and became interested in the types of errors they made, leading him to explore the reasoning process in these young children.
From his studies, he worked out a model of childhood development that mapped several stages of world-view paradigms they seemed to use as they matured. This forced him to postulate that children actively participate in constructing their own ideas – their knowledge base – based on experience and prior knowledge. Hence, the term “constructivism.”
Imagine a house that represents everything the child “knows.” Mentally, they live in that house all the time, view the world in relation to it, and make decisions based on what’s there.
As they experience everything, including the experience of having someone tell them something verbally or through written words, they actively remodel the place. The operant concept here is that they constantly do the remodeling themselves by trying to fit new information into the structure that’s already there.
My own journey toward constructivism was based on introspective phenomenological studies. That is, I paid attention to how I gained new knowledge and compared my experiences with experiences reported by others studying the same material.
A paradigm example is the study of quantum mechanics. This subject is difficult for students familiar with classical physics because the principles and the phenomena on which they are based seem counterintuitive. Especially, the range of time and distance scales on which quantum principles act is not directly accessible to humans. Quantum mechanics works at submicroscopic distances and on nanosecond time scales.
Successful students of quantum mechanics start by studying human-scale phenomena that betray the presence of quantum principles. For example, the old “planetary model” of atoms as miniature solar systems in which electrons revolve in stable orbits around the atomic nucleus like planets around the Sun is a physical impossibility. Students realize this after studying Maxwellian Electrodynamics.
In 1864, James Clerk Maxwell succeeded in summarizing everything physicists of the time knew about electricity and magnetism in four concise (though definitely not simple) equations. Taken together, they implied the feasibility of radio and not only how light traveled, but even predicted its precise speed. Maxwell’s Equations were enormously successful in guiding the development of electrical technology in the late nineteenth century.
The problem for physicists studying atomic-scale phenomena, however, was that Maxwell’s Equations implied that electrons whizzing around nuclei would rapidly convert all their energy of motion into light, which would radiate away. With no energy of motion left to keep electrons orbiting, the atoms would quickly collapse – then, no more atoms! The Universe as we know it would rapidly cease to exist.
When I say rapidly, I mean on the time scale of trillionths of a second!
Not good for the Universe! Luckily for the Universe, what this really means that there’s something wrong with classical-electrodynamic theory (i.e., Maxwell’s Equations).
The student finds out about dozens of such paradoxes that show that classical physics is just flat out wrong! The student is then ready to entertain some outlandish ideas that form the core of quantum theory. The student proceeds to piece these ideas together into their own mental version of quantum mechanics.
Every physics student I’ve discussed this with has had the same experience learning this quantum-electrodynamical theory (QED). Even more telling, they all report initially learning the ideas by rote without really understanding them, then applying them for considerable time (months or years) before piecing them together into a mental pattern that eventually feels intuitive. At that point, when presented with some phenomenon (such as the sky being blue) they immediately seize on a QED-based explanation as the most obvious. Even doubting QED has become absurd for them!
To a constructivist, this process for learning quantum mechanics makes perfect sense. The student is presented with numerous paradoxes, which causes cognitive dissonance. This state motivates the student to seek alternative concepts and fit them into his or her world view. In a sense, they construct an extension onto the framework of their world view. This will likely require them to make some modifications to the original structure to accommodate the new knowledge.
This method of developing new knowledge dovetails quite nicely with the scientific method that’s been under development since Aristotle and Plato started toying around with it in the fourth century BCE. The new development is that Piaget showed that it is the normal way humans develop new knowledge. Even children can’t fully comprehend a new idea until they fit it into a modified version of their knowledge base.
This model also explains why humans’ normal initial reaction to novel ideas is to forcefully reject them. Accepting new ideas requires them to do a lot of work on their mental scaffolding. It takes a powerful mental event causing severe cognitive dissonance to motivate them to remodel a mental construction they’ve been piecing together for years.
It also explains why younger humans are so much quicker to take up new ideas. Their mental frameworks are still small, and rebuilding them to fit in new concepts is relatively easy. The reward for building out their mental framework is great. They are also more used to tinkering with their mental models than older humans, who have mental frameworks that have served them well for decades without modification.
Of course, once they reach the point of intolerable cognitive dissonance, older humans have more experience to draw on to do the remodeling job. They will be even quicker than youngsters to make whatever adjustments are necessary.
Older humans who have a lifelong habit of challenging themselves with new ideas have the easiest time adapting to change. They are more used to realigning their thinking to incorporate new concepts and have more practice in constructing knowledge frameworks.
Apologies to all the folks whose words I’ve expropriated for this piece with insufficient attribution – mostly from Wikipedia and ASEAN sources. It’s already taken three days to piece this essay together and I’m trying to get it published while the dateline is still good! Just ONE more editing pass.
26 June 2019 – This is an appropriate time to visit a little-known and -acknowledged regional international community being developed in Southeast Asia: ASEAN. Last Sunday (23 June 2019) marked the 34th meeting of the ASEAN Summit in Bangkok, Thailand
The creation of ASEAN was originally motivated by a common fear of communism among the original five founding member states. ASEAN achieved greater cohesion in the mid-1970s following a change in the international balance of power after the end of the Vietnam War in 1975. The region’s dynamic economic growth during the 1970s strengthened the organization, enabling ASEAN to adopt a unified response to Vietnam’s invasion of Cambodia in 1979.
ASEAN’s first summit meeting, held in Bali, Indonesia in 1976, resulted in an agreement on several industrial projects and the signing of a Treaty of Amity and Cooperation, and a Declaration of Concord.
The end of the Cold War between the West and the Soviet Union at the end of the 1980s allowed ASEAN countries to exercise greater political independence in the region, and in the 1990s ASEAN emerged as a leading voice on regional trade and security issues.
ASEAN has a total population of 642 million people, which is nearly double that of the United States (327 million), and twenty-five percent larger than that of the European Union (513 million). Its average annual income per person, however, is only $4,308.00, putting it between the Israeli-occupied West Bank and Mauritania in the Western Sahara as far as average wealth per person is concerned. That means its people still have a long way to go! Its GDP growth rate, however, is 5.3% per annum, which is comparable to that of Egypt or Pakistan and ahead of the average for even emerging and developing countries.
Why Do We Care?
Why should Americans care about ASEAN?
First, it has aspirations to be a regional intergovernmental organization similar to the European Union in an region where the United States has economic and political interests. Their charter specifically calls for adherence to basic principles in line with those of the United States and other Western democracies. Notably the ASEAN charter specifically calls for adherence to democratic principles and maintaining the region as a nuclear-free zone.
Second, as a large and (aspirationally) politically and economically cohesive regional intergovernmental organization, ASEAN can provide a large and (again aspirationally) economically powerful ally in Southeast Asia to counterbalance Chinese efforts to extend its hegemony in the region. Especially, their actions reveal a desire to cooperate with the United States and its allies. For example, the charter refers in numerous places to working with United Nations principles and protocols, and establishes English as the ASEAN working language.
The figure below shows ASEAN’s top organization levels. At the top is the ASEAN Summit, comprised of the heads of state or government of the member states. By charter, they meet together twice a year, hosted by the member state holding the ASEAN Chairmanship, which cycles through the member states. At present, that is Thailand (Prime Minister General Prayut Chan-o-cha), so the latest meeting was held on 23 June 2019 in the Thai capital, Bangkok.
At the next level, ASEAN is divided into three Community Councils that represent the three pillars of ASEAN activity:
The ASEAN Political-Security Community Council
The ASEAN Economic Community Council
The ASEAN Socio-Cultural Community Council
Each of the three Community Councils has their own makeup and sphere of activity. The ASEAN Coordinating Council, for example, comprises the Foreign Ministers of the ASEAN member states and meets at least twice a year, not only to prepare the meetings of the ASEAN Summit, but to undertake other tasks provided for in the Charter, or for such other functions as may be assigned by the ASEAN Summit. For example, the Coordinating Council coordinates implementation of agreements and decisions of the ASEAN Summit.
In order to realize the objectives of each of the three pillars of the ASEAN Community, each ASEAN Community Council ensures the implementation of the relevant decisions of the ASEAN Summit; coordinates the work of the different sectors under its purview; ensures implementation of Summit decisions on issues that cut across the other Community Councils; and submits reports and recommendations to the ASEAN Summit on matters under its purview.
Each member state designates its own national representatives for each ASEAN Community Council. In addition, each ASEAN member state establishes an ASEAN National Secretariat that serves as a national focal point, the repository of information on all ASEAN matters at the national level, coordinates the implementation of ASEAN decisions at the national level, coordinates and supports the national preparations of ASEAN meetings, promotes ASEAN identity and awareness at the national level, and contributes to ASEAN community building.
ASEAN member states pledge to rely exclusively on peaceful processes in the settlement of intra-regional differences and with regard to their security. They are fundamentally linked to one another and bound by geographic location, as well as by a common vision and objectives.
The ASEAN Political-Security Community (APSC) aims to ensure that countries in the region live at peace with one another and with the world in a just, democratic and harmonious environment. The APSC Blueprint envisages ASEAN to be a rules-based community of shared values and norms; a cohesive, peaceful, stable and resilient region with shared responsibility for comprehensive security; and a dynamic and outward-looking region in an increasingly integrated and interdependent world. The APSC’s normative activities include: political development; shaping and sharing of norms; conflict prevention; conflict resolution; post-conflict peace building; and implementing mechanisms.
The inaugural issue of the ASEAN Economic Integration Brief (AEIB) was released on 30 June 2017. The AEIB provides regular updates on ASEAN economic integration progress and outcomes, and is a demonstration of ASEAN’s commitment to strengthen communication and outreach to raise stakeholder awareness of the AEC.
The ASEAN Good Regulatory Practice (GRP) Core Principles was adopted at the 50th AEM Meeting in 29 August 2018 and subsequently endorsed by the AEC Council. It provides a practical, non-binding set of principles to assist ASEAN member states to improve their regulatory practice and foster ASEAN-wide regulatory cooperation.
At the heart of the ASEAN Socio-Cultural Community (ASCC) is the commitment to lift the quality of life of ASEAN peoples through cooperative activities that are people-oriented, people-centered, environmentally friendly, and geared toward the promotion of sustainable development through member states’ cooperation on a wide range of areas including: culture and information, education, youth and sports, health, social welfare and development, women and gender, rights of the women and children, labor, civil service, rural development and poverty eradication, environment, transboundary haze-pollution, disaster management and humanitarian assistance.
The AEC aims to “implement economic integration initiatives” to create a single market across ASEAN member states. Its blueprint, adopted during the 13th ASEAN Summit (2007) in Singapore, serves as a master plan guiding the establishment of the community. Its characteristics include a single market and production base, a highly competitive economic region, a region of fair economic development, and a region fully integrated into the global economy.
The areas of co-operation include human resources development; recognition of professional qualifications; closer consultation on macroeconomic and financial policies; trade financing measures; enhanced infrastructure and communications connectivity; development of electronic transactions through e-ASEAN; integrating industries across the region to promote regional sourcing; and enhancing private sector involvement.
The AEC is the embodiment of the ASEAN’s vision of “a stable, prosperous and highly competitive ASEAN economic region in which there is a free flow of goods, services, investment and a freer flow of capital, equitable economic development and reduced poverty and socio-economic disparities.”
The average economic growth of member states from 1989 to 2009 was between 3.8% and 7%. This was greater than the average growth of APEC, which was 2.8%. The ASEAN Free Trade Area (AFTA), established on 28 January 1992, includes a Common Effective Preferential Tariff (CEPT) to promote the free flow of goods between member states.
ASEAN member states have made significant progress in the lowering of intra-regional tariffs through the CEPT. More than 99 percent of the products in Brunei Darussalam, Indonesia, Malaysia, the Philippines, Singapore and Thailand, have been brought down to the 0-5 percent tariff range. ASEAN’s newer members, namely Cambodia, Laos, Myanmar and Viet Nam, are not far behind.
ASEAN member states have also resolved to work on the elimination of non-tariff barriers, which includes, among others, the process of verification and cross-notification; updating the working definition of Non-Tariff Measures (NTMs)/Non-Tariff Barriers (NTBs); the setting-up of a database on all NTMs maintained by member states; and the eventual elimination of unnecessary and unjustifiable non-tariff measures.
I led this essay off with the comment that ASEAN does not seem to get the attention it deserves, at least in U.S. national media. Certainly, U.S. President Donald Trump seems to feel it’s not worth a tweet. The closest I was able to find with a quick Internet search was a report that he insulted Philippines President Rodrigo Duterte before meeting him on the sidelines of the Winter 2017 ASEAN Summit meeting!
That said, I must report that I became interested in ASEAN through a segment in Fareed Zacharia’s GPS show on CNN. So, not everybody is completely ignoring what I’ve come to realize is potentially an important regional intergovernmental organization.
I encourage you to learn more about ASEAN by visiting the various links peppering this column. Maybe together we can generate more interest in what could be a powerful U.S. ally in the Eastern Pacific.
19 June 2016 – I’m supposed to have some passing understanding of economics and accounting. I have, after all, a Master’s degree in Business Administration, for which I had to study Macroeconomics and Microeconomics, as well as Cost and Financial Accounting.
Howsomever, while trying to make sense of what folks call “Modern Monetary Theory” it dawned on me that, not only didn’t I have a clear concept of what money actually is, but the people babbling on about money and monetary policy aren’t any clearer on the concept than I am. A review of the differences between neoclassical economics based on Keynsian ideas and so-called Modern Monetary Theory reveals an incomplete understanding of money.
We all think we know what money is, and spout long winded and erudite-sounding loads of gobbledygook that only serve to prove, beyond a shadow of a doubt, that none of us have a clue what the stuff actually is!
I find that situation intolerable, and have set out to change it by trying real hard to come up with a theory that makes sense of all the stupid things we do with and say about money.
Now, I’m not a financial wizard, or a prize-winning economist, or even a whiz-bang developer of computer models of the global economy. I’m just some schmuck with some basic math ability, a little time on my hands, and the desire to make sense of something that it seems the “experts” haven’t wrapped their brains around, yet. So, I’ve thought about this problem a bit, and have a hint of an answer that I want to run up the flagpole to see if anyone salutes.
If this essay triggers something in the brain of somebody smart that sets him, her or it thinking in a new direction about money, I’ll count it time well spent.
So, here goes … .
In science, we try to make sense of anything we don’t fully comprehend by developing some kind of conceptual model that helps us predict what will happen in any given situation. The fact that we currently haven’t a clue what will actually happen when, for example, the Federal Government runs up huge deficits for a very long time, indicates that we’re very far from knowing what we’re talking about with regard to money.
I generally try to model things poorly understood through analogy with things that are well understood. I’ve developed a two-fluid model of money by analogy to certain ideas in classical physics. It seems to work decently for the situations I’ve applied it to.
Analogy with Momentum
Specifically, the model draws an analogy with Newtonian momentum, which is a conserved vector quantity – meaning that the total momentum in a closed system cannot be changed, and that the quantity involves both a magnitude and a spatial direction.
For our analogy to be useful, we need to also use the idea of generalized coordinates, which allow the idea of “direction” to extend beyond strictly cartesian spatial coordinates (motion in straight lines). For example, a bicycle drive chain wraps around two sprockets and has flexible spans linking them, so its motion certainly does not follow along a single cartesian coordinate, yet there is a well-defined path along which any two points on the chain follow each other, maintaining their separation (measured along the path). That allows us to measure motion along the path by a generalized coordinate.
In Newtonian mechanics, momentum is exchanged between objects, which are thought of as components of a system, through the action of forces. Mathematically, the magnitude and direction of the force equals the rate of flow of momentum between the objects.
Newton’s third law, which states that every force is paired with an equal and opposite reaction force, is just an expression of conservation of momentum in that every force (representing a transfer of momentum from one object to another) is paired with an equal and opposite transfer of momentum from the second object to the first. This takes care of maintaining conservation of momentum.
Take, for example, a person stepping off a boat onto a dock. At first, everything is (as seen from the perspective of the dock) stationary. The momentum of an object is defined as the object’s mass (amount of material) times its velocity (a vector combining speed and direction). Since both the person and the boat are stationary (meaning they both have a velocity of zero), the total momentum of the system of person + boat is zero.
Then, the person applies a force to the boat in a direction away from the dock. The Newton’s-third-law reaction force is a push by the boat on the person toward the dock. That’s how the person actually gets to the dock. The boat pushes him/her toward it!
The boat moves away from the dock. The person moves toward the dock. So, the directions of the two momenta are opposite. The speeds of the person and boat automatically (or maybe you’d like to say “magically”) adjust to keep the total momentum of the system equal to zero at all times. That is, at every instant the momentum of the person is equal and opposite to the momentum of the boat.
In the theory of money that I’m proposing, money itself is analogous to momentum. Altogether, it’s conserved. That is, it cannot be created or destroyed. There’s always the same amount of “money” – zero!
What we’re used to thinking of as “money” is only half the story, which is why there’s so much confusion over it. Borrowing from double-entry bookkeeping, we’ll call what we usually think of as money as credit. Everyone who understands double-entry bookkeeping knows that for every credit, there is an equal (and opposite) entry called a debit. For our purposes, we’ll shorten that word to something we’re all familiar with: debt.
Debt is the other side of the analogy, which we tend to ignore and that accounts for all the confusion.
We’re going to visualize credit and debt as fluids because they’re measured as continuous, as opposed to quantized, variables. That means that they’re representable by real numbers as opposed to integers. So, nobody has a problem with dividing seven dollars ($7) into two portions each containing three and a half dollars ($3.50). Current usage is to round everything to the nearest cent, or hundredth of a dollar, but that’s for convenience and not wanting to be bothered with truly small change.
At one time, we had half-penny ($0.005) coins, but we don’t do that anymore.
Okay, so “money” actually represents credit and debt in equal amounts, which consequently always add up to zero. Whenever money is created, it’s created as equal amounts of credit and debt.
Money creation always requires activity by two cooperating entities: a creditor and a debtor. Credit is created and transferred from the creditor to the debtor. An equal quantity of debt is created and flows from the debtor to the creditor. “Money” consists of these paired fluids, which flow through the economy via paired interactions between creditors and debtors. Money is created by an interaction that creates equal amounts of credit and debt, and the words “creditor” and “debtor” simply indicate the direction of flow.
Once created, the money flows around in the economy through paired transactions in which credit flows one way and debt the other.
This visualization allows us to separate the concepts of “money” and “wealth.” Wealth refers to tangible and intangible assets, such as commodities and intellectual property. Wealth is very definitely not conserved. When a contractor builds a house, he or she creates wealth from, essentially, nothing. The contractor then sells the house to the new owner in a binary transaction that transfers credit to the contractor and debt to the owner.
We’ll leave out discussion of what happens to the wealth represented by the house, since this essay is about money, and money is not wealth.
The owner previously got the credit through a transaction with a lender in which money was created as a transfer of credit to the owner and debt to the lender. The lender can then, for example, package the debt up into something called a “collateralized debt obligation,” and exchange it with somebody else for an equivalent amount of credit. The lender then transfers that credit to another prospective home owner in exchange for an equivalent amount of debt, and the merry-go-round keeps turning.
Unlike wealth, which was created from nothing, the total of credit minus debt in the system remains zero at all times.
It is interesting to note that wealth appears through the creation of a pattern in the physical universe. For example, bricks used by a contractor to build a house start out as a less-organized pile. The contractor creates wealth by arranging those bricks in a house-like pattern. The owner has no use for the disorganized pile of bricks, but has a use for them when arranged as a house. Similarly, the contractor had no use for the raw clay that went into the bricks until the brick manufacturer rearranged it into the pattern we call “bricks.”
Historically, folks’ fascination with the credit side of money has led them to confuse “money” with “wealth.” They’re entirely different things. One is a medium of exchange related to entries in a bookkeeper’s ledger, the other is a real thing related to patterns in the physical world.
I hope this essay manages to help make sense of the money nonsense!