#321 Using AI for Profiling – Birds of a Feather Flock Together

Readers: this blog is set in the future (sometime after the year 2020). Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution. More about the Revenge Revolution and author, How the 5th US Revolution Begins and About the Author.  Many entries are formatted as conversations. Characters appear in a number of entries, with many entries building on previous conversations.  

Occasionally I do a “sense check” about the likelihood of a Revenge Revolution.  Entry #318 is the most recent “sense check.”  One more note — sometimes I write about another topic that does not quite fit the theme of the blog.  Those comments are available on the page titled “JRD Thoughts and Comments.” 

This series is about the coming “Technology Tsunami.”  The series addresses what might be involved and some suggestions for mitigating and even capitalizing on the opportunity.  Entries #321 and #322 are intended to describe AI in more understandable terms, using personal experiences as examples.  

A widespread use of AI today is what is called “profiling.” Ever notice after you’ve searched something on Google, an ad appears for the product? How does the computer know?

This entry discusses how AI was used to create “profiles” and how those profiles were used in a commercial application. The examples in this entry and the next (Entry #322) are “early stage” and intentionally selected to demonstrate: (i) applications that are easy to understand: (ii) AI-based applications have been around for a number of years; (iii) how AI can be used to increase the effectiveness of “gut-feel” profiling.

The concept of profiling is simple. Profiles are based on the assumption that “birds of a feather flock together.” That is, people with similar profiles have similar behavior.

Of course, not everyone in the flock, or profile group, behaves the same way.   But to the user, profiling is not about individuals but about probabilities of member in the group. What percentage of the people in the profile group will behave a certain way? The goal is to create a group, or profile, where there is a high likelihood that members will have a specific desired behavior.

Profiling is not a new idea. Profiles existed for eons before being formalized with computer programs. Further, virtually everyone creates profiles. Most all of us put strangers into categories based on such factors as geographic location, appearance – skin color, hair color, hair style, clothing, etc. – age, education and a host of other criteria. Think back to someone you met, then after you got to know the person much better, said to yourself, “Gee, that person is a lot different from I first imagined.”

As for this entry, the first example seems rather crude by today’s standards. At the time the profiling technique described was considered “state-of-the-art.” Remember an abacus was considered state-of-the-art when introduced.

The time period for this entry is the mid-1980’s, at Buick Motor Division of General Motors, where I’m director of marketing. As described previously, Buick has used AI-programs to improve the accuracy of its sales forecast and to start allowing dealers more discretion when ordering cars. (Reading Entry #320 will provide more context.)

The next logical step to try to continue building market share was helping dealers refine how to order the appropriate number and mix/models of cars. For example, dealers in the Northeast knew smaller cars were preferred, but which ones were likely to sell more rapidly in a dealer’s particular sales area? Same problem with dealers throughout the country.

I do not remember who or how the introduction was made – could have been one of the “crazy phone calls” the staff often accused me of taking – but Buick was introduced to a company called Claritas. At the time Claritas had combined zip code and general demographic data. The results were “clustered” into 40 groups, or profiles. Each profile had general buying information for products ranging from food to wine to vehicles to many other items. Claritas also assigned a descriptive and memorable to each group. Some examples of names of group – “Pools & Patios,” “Furs & Station Wagons,” “Hard Scrabble,” “Down-Home Gentry,” “Blue Blood Estates,” etc.

As I recall Buick was the first auto company to use the Claritas profiling. We introduced the concept at the annual dealer announcement meeting. And then not much happened for several months. Finally I got a call from a dealer who purchased a store in Florida that had gone bankrupt and was in the process of converting to a Buick store.

The call went something like this, “You remember that program you told us about at the announcement meeting? I’ve forgotten the name of the program but do you think it might help me order the cars more effectively for this new store?” We asked for the zip codes he thought most likely to consider shopping buy at his store. Based on the zip codes we suggested a mix of cars he should consider ordering.

About six months later, my wife and I were hosts on an incentive trip for dealers. During cocktail hour one night, the dealer said, “I owe you a drink. You’ve made me a ton of money.” As he told the story, the profiling program had been a major contributor to helping him turn what had been an unprofitable dealership into one that was very profitable. And, yes, I let him buy me a drink…even though drinks were already paid for.

He told his success story to many other Buick dealers and the use of the program became more widespread. What seems like standard marketing procedure now was anything but standard then.

Within a couple of years starting to work with Claritas, Buick developed a variation of an existing car that designed to appeal to a very small audience. Because introducing such a “niche” car in the traditional way would be too expensive – major national tv and print campaign that could eat all the potential profits – we decided on a targeted campaign using the information from Claritas. What was the result of promoting the niche car to selected profiles – “Pools & Patios,” “Blue Blood Estates” and a few others? A very successful, and profitable, introduction.

What’s the status of profiling today? Profiling has migrated from projecting buying patterns based on zip code (5 digit) to neighborhood profiles (9-digit zip codes) to profiles by families to profiles for individuals within the same household. The same philosophy applies – birds of a feather flock together. However, the flock is no longer defined by geography but by attitudes and behavior gathered from information on search engines, websites, on-line purchases and social media platforms. Profiling is still about probabilities – and not individuals – even though the clusters can include specific information about individuals within the group.

What does this migration portend for the future? One of the unintended consequences of profiling seems to be the diminished value of small geographic social groups. When one had more face-to-face interaction with neighbors, it was difficult to simply walk away from people with different opinions. While you might not always agree with your neighbor, one at least tried to be civil because that neighbor would be there the next morning and you might need to rely on him or her for something.   Amazon, on-line buying, delivery services, etc. have reduced the reliance for many activities. No longer does longer does one even need to talk face-to-face with neighbors. One can replace face-to-face chats by going on-line and finding a chat room of like-minded people, thereby avoiding having to listen to the neighbor with whom one might disagree.

In the future are we going to continue only to seek others in our profile and therefore become more isolated? Maybe for a few more years…then I’m hopeful the tide will turn. The underlying premise of my blog (www.usrevolution5.com): the US is headed for a 5th revolution sometime after 2020. I’ve labeled revolution as the Revenge Revolution. One societal change that I think will result is a return to neighborhoods. Some groups and communities have maintained active neighborhoods, but far too few. What I’m hoping evolves from the Revenge Revolution is a sense of cohesion among neighbors.

Yes, post Revenge Revolution you’ll still be able to use your smart phone and order on-line. At the same time, people will become more aware of and concerned about others, especially those in their neighborhoods. Maybe naively, this awareness will help neighborhoods begin to have the feel more like the 1950’s – not quite like Wally and the Beaver but a lot closer than today. And, no, in my view fences do not make good neighbors.

(In the next entry, a discussion about how AI-developed personality profiles can be extremely useful in dealing with others. Of course, women have used this approach for centuries. Men are still in the learning phase.)

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#320 Personal Experience Developing AI and Implications for Skills and Employment

Readers: this blog is set in the future (sometime after the year 2020). Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution. More about the Revenge Revolution and author, How the 5th US Revolution Begins and About the Author.  Many entries are formatted as conversations. Characters appear in a number of entries, with many entries building on previous conversations.  

Occasionally I do a “sense check” about the likelihood of a Revenge Revolution.  Entry #318 is the most recent “sense check.”  One more note — sometimes I write about another topic that does not quite fit the theme of the blog.  Those comments are available on the page titled “JRD Thoughts and Comments” as well as “Tech Tsunami”, which has more articles about how technology might affect US…and add a dimension to the Revenge Revolution.

Background to Technology Tsunami series focuses on how implementation of technology may change the family earnings structure in the US.

In “Technology Tsunami” (Entry #319) I noted that with the increased use of artificial intelligence, many current workers will need to increase skills in order to remain employed. But just what is artificial intelligence? And how can it be used? To make AI more concrete and less abstract, thought it might be interesting to allocate the next couple of entries to describing some personal experience developing AI and what happened as a result.today

First, let’s go back to define just what constitutes artificial intelligence, or AI? (Readers, please keep in mind this is not an article for an academic journal. The article is aimed at trying to help the general populace understand more about what AI is and how it might affect the workforce.)

The term “artificial intelligence,” which was first used in the 1950’s, seems to be applied to an ever-increasing range of computer-based applications.  Much of AI we hear about today has been developed by applying to very large data bases sophisticated multiple regressions (regressions look for an association between one action/word and another). The algorithms that result become the foundation for software to support an AI application. What has expanded the use of AI is the availability of very large databases and much more computing power.  However, as demonstrated by this example, a useful and effective AI program can be developed without an overly large database and/or staff.

A question associated with AI, “When AI is implemented, will people be replaced?” Yes, but people have always been replaced with the introduction of new technology. Farm hands were replaced by tractors and mechanical harvesting equipment. The printing press replaced scribes. The telegraph replaced the Pony Express. Trains replaced stage coaches. Cars replaced buggies…and endless other examples.

In the current wave of AI, the jobs that seem most vulnerable in the near-term are ones that involve repetition. Jobs where running a software program or using robot could perform most or all of the task. Such jobs might be assembling parts, loading/unloading shelves, providing certain types of information (clerks, including law clerks could be replaced by a more sophisticated Siri, for example), completing forms or completing some basic analysis (proof reading, financial analysis, etc.), steering vehicles and similar jobs.

The list of vulnerable jobs is quite lengthy and includes a considerable number of white-collar positions. For example, when General Motors announced in fall 2018 the intent to close five plants in the US/Canada, more white-collar workers were affected than assembly workers.

OK, how about a real-world example. In 1980…yes, that was many moons ago…I transferred to headquarters of Buick Division of General Motors. One of the staffs I managed was responsible for forecasting sales – short and long-term. The short-term forecast – 180 days – was used to set production schedules at assembly plants and suppliers.

When I arrived, the accuracy of the forecast was abysmal. Even though Buick had been in business about 75 years, it was not uncommon for forecast sales for the current month to miss actual sales by 30-40%…sometimes 50%. Such a variance made it extremely difficult to manage inventory. The forecast/actual discrepancies also caused frustrations with Buick dealers because arrival dates for cars ordered varied widely from the original schedule, which in turn frustrated customers.

To increase the accuracy of the forecast, we developed an application of AI. The AI-based forecast consisted of three key estimates: (i) industry sales; (ii) mix of sales by category – % small cars, % mid-size cars, % full-size, % SUV’s, etc. – within the industry; (iii) Buick % share within the general categories.

Unlike today, at the time most assembly plants were limited to a few models with little variation in size. Further, changing the production mix at an assembly plant could be time consuming and costly.

Buick’s solution to this dilemma (and common in the industry) was to “force” the dealers to take the mix of cars produced. Further, there was little recognition of differences in consumer preference by region of the country. Dealers in New England, where smaller cars were preferred, would end up with mix of small/large cars very similar to the dealers in say Texas, where larger cars were preferred. “Encouraging” dealers to take the production mix required the field staff to spend considerable time with the dealer and often involved some type of costly incentive – free financing, extra cash per car, etc. Dealers would then have to try to steer customers to these “unwanted” cars.

The solution to fixing the problem was conceptually simple: (i) a more accurate forecast; (ii) allowing dealers to order what cars they wanted. Improving the accuracy of the forecast was the critical first step. Doing so required building a math model that would predict more accurately upcoming changes in demand.

Previous sales forecasts had been based on changes in the rate of actual sales. Basing the forecast on “lagging indicators” – sales the past few months – is akin to trying to drive a car by looking only in the rearview mirror. Doing so reduces one’s speed and increases the chance of making a serious error. The previous method of forecasting was always “catching up” to changes in demand rather than being ahead of the curve.

Developing the AI model was remarkably easy – or so it seems now. We ran regressions of historical sales data for the industry as well as Buick. Fortunately, the auto companies had been reporting monthly sales for many years, so the data base was credible. The results of the regressions yielded useful, seasonal patterns. We also analyzed the shift in mix of sales over time. This helped determine if sales of smaller cars were increasing faster or slower than say mid-size or luxury cars. Another task was estimating how many people were switching from cars to what were then early-version SUV’s.

Finally, we had to determine Buick’s likely share of each category. At the time the overall car market was shifting to smaller cars. While Buick had competitive smaller car entries, it was more successful in larger cars. The effect of the shift in consumer preference was profound. Even though in a given month Buick could gain in market share in every major industry category compared to the previous year, that same month could show Buick’s overall share had declined compared to a year ago.   That phenomenon was always fun to try to explain. “Yes, we gained market share in every category…but, no we lost market share overall.”

Within about one year of starting the AI model, the US industry experienced a major economic downturn and vehicle sales took a nosedive. The AI model helped Buick management begin to make more informed decisions about setting production schedules and marketing plans. With the implementation of the AI-model, the accuracy of the forecast improved markedly. Rather than a variance of 30-40% between actual and forecast for a given month, the variance fell to less than 5%. The improvement helped smooth production schedules, reduce short-term layoffs and/or overtime at Buick and suppliers and made lead-times for deliveries to dealers much more accurate.

The increased forecast accuracy allowed Buick to migrate to what is called a “free-expression” forecast and production schedule. Dealers were allowed much more freedom to order the number and model of cars they wanted.

The decision to migrate to “free-expression” forecast/production caused great angst among staff members tied to the old “dealers-will-order-what-we-tell-them” system. In the end, however, most everyone became a convert because the overall production volume and mix were about what the dealers wanted.

Other benefits of the AI forecast model? The field staff was able to spend more time helping dealers with marketing programs, working on customer satisfaction and finding ways to improve profitability. The dealers then started to order more cars from Buick because the turnover rate improved. In the three-year period following implementation of the AI model, Buick increased market share more than any other manufacturer, domestic or foreign. While not all the gain in market share can be attributed to the AI model, the number of new products Buick introduced during the same period was limited, so most of the gain in market share came from “non-product” activities.

What happened to employment? Buick reduced the number of field offices from 26 to 20. Buick also started a call center to increase contact with dealers located outside urban areas. The non-urban dealers still received some personal visits, but less frequently.

Use of AI also changed the skills required of the office staff. To be effective in the new environment, staff members needed more skills in math, statistics, economics and marketing. If today’s computing power were available then, we could have cut the staff in half, possibly more. Even skills of and the number of senior managers would have been affected. At the retirement party of a key sales executive, who’d grown up in the days of gut-feel and seat-of-the-pants forecasts, the retiring executive told me – after several drinks – “I never understood what you were talking about, but I trusted you.” I appreciated the compliment but was a bit taken aback by the admission.

Does this example help us look ahead for what might happen when more AI is implemented? I think so. What did this rather simple application of artificial intelligence help Buick accomplish?

  • + Increased sales
  • + Increased market share
  • + Increased profits
  • + Increased customer satisfaction (dealer and buyer)
  • – Reduced employment
  • – Higher skills required of employees

If you’re a shareholder and/or your compensation is tied to profits, you will view the results of implementing the AI program as positive. If you’re an employee whose job was eliminated and/or you were unable to learn the additional skills required, you will view the AI program as negative.  The inherent conflict between perspectives, unless we quickly start to manage more effectively, will likely be another contributing factor to the Revenge Revolution.

(In the next entry, another real-world example of using AI – an early application of consumer profiling. While the profiling was not as sophisticated as done today by Google, Facebook, Amazon and many others, the effort allowed Buick to spend marketing dollars more effectively.  We’ll also address why it is important that the output of AI programs is understood and trusted. )

#319 Technology Tsunami Headed toward US Shores

Readers: this blog is set in the future (sometime after the year 2020). Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution. More about the Revenge Revolution and author, How the 5th US Revolution Begins and About the Author.  Many entries are formatted as conversations. Characters appear in a number of entries, with many entries building on previous conversations.  

Occasionally I do a “sense check” about the likelihood of a Revenge Revolution.  Entry #318 is the most recent “sense check.”  One more note — sometimes I write about another topic that does not quite fit the theme of the blog.  Those comments are available on the page titled “JRD Thoughts and Comments” as well as “Tech Tsunami”, which has more articles about how technology might affect US…and add a dimension to the Revenge Revolution.

Background to Technology Tsunami series. Thought it might be worthwhile to take a break from all the craziness in Washington and discuss other issues that likely will contribute to the Revenge Revolution. A key issue that seems to be getting less attention than it deserves….maybe because of all the noise emanating from the Trump White House…is how the implementation of technology will change the family earnings structure in the US.

We’ve seen some of the changes already, with the reduction in manufacturing jobs and the stagnation of wages for a large segment of the population. In my view the changes so far are just a small taste of what is to come. The next several blog entries…and I don’t know how many at this point…will focus on what I’m labeling the coming “technology tsunami.” The first of the entries, which follows, is a bit long but tries to set the stage.

There are already numerous early warning signs of the tsunami. An example – the announcement by General Motors in November 2018 of its intent to close five (5) plants in North America. Another warning sign is a story in the New York Times about a robotic arm playing the piano. While a robot playing a piano may seem like a bit of a novelty, think about the implications. The more dexterous robots become, the more robots can perform tasks of people who are highly skilled. Robots in warehouses and welding or painting in cars/trucks are commonplace. Those tasks are fairly straight forward compared to cooking or performing surgery or a host of other tasks.

As noted in this entry, over the centuries societies have coped with implementation of new technologies. Some societies have adopted well and succeeded; other did not adopt well and fell behind.  An example — in 1910, GDP per capita in Argentina was about 80% of US GDP per capita.  By 2010, 100 years later, GDP per capita in Argentina had fallen to about 30% of US GDP per capita.

Adopting successfully is very difficult. There are a couple of interesting books about adopting new technologies that we’ll discuss in a later entry. For now let’s get started. As you read, keep in mind how the disruption caused by adopting the new technologies might compound the societal problems currently facing the US. Numerous factors point to another revolution in the US – the technology tsunami could accelerate the revolution and make it worse. And, yes, Mrs. Lincoln, enjoy the play.

Entry Begins

After General Motors announced plans to close five (5) plants in North America (November 2018), I was asked by several friends and colleagues for my opinion of the merits of the decision. While I had no inside information, based on my experience at GM and additional analysis, I concluded GM made the correct decision and should be congratulated.

To explain my logic in more detail, I wrote a couple of informal articles and published links on Facebook. The articles included the term “technology tsunami,” which I thought might help explain some of GM’s rationale for closing the plants…and why GM’s decision might portend what’s ahead for other companies. (GM had additional reasons for the closings. Links to articles on Tech Tsunami page.)

Reaction to the term “technology tsunami” seemed to beg for more explanation. So, here goes. I selected the term “technology tsunami” because the characteristics of a tsunami seemed to a good proxy for how the wave of artificial intelligence (AI), increased use of robots, implementation of the blockchain, and other technologies will affect employment in the US. The effect will not be limited to the manufacturing and some service sectors but include many white-collar professionals (GM, for example, laid off more salaried  white-collar staff, than hourly manufacturing workers.)

First let’s look at the sequence of a tsunami. The start is often an earthquake or volcanic eruption deep in the ocean. The energy from that quake is transferred in the form of a series of powerful ocean waves. In the open ocean, the change in the wave pattern caused by the earthquake is not necessarily apparent. To the naked eye, tsunami waves appear relatively normal.

The strength of the waves becomes more apparent as waves move closer to shore. As the waves start to come ashore, the waves are compressed. The more gradual the slope of the shoreline, the more compression.

And there is not just one wave that is compressed and hits the shore, but a series of waves. The waves are powerful and of such height that virtually everything at or near the shoreline is completely destroyed. The waves continue inland, causing significant damage. A tsunami usually is more powerful and destructive than the surge associated with a hurricane.

An usual characteristic of a tsunami is how it affects the waterline preceding its arrival. As the tsunami gets closer to shore, the water at shore’s edge recedes. The shoreline looks as if there is an exaggerated low tide. This phenomenon might last several minutes. Then, the waterline changes quickly and drastically as repeated high and powerful waves come ashore, destroying virtually everything.

With that picture in mind, let’s examine how a technology tsunami might affect employment in the US. In my view, the earthquake has already occurred that will cause the technology tsunami. The energy from that quake has been transferred to form of a series of large and destructive waves. And those waves are headed toward the US shore. Warning signs of the tsunami are becoming more evident at the shoreline as the waterline has begun receding.

The US shoreline is filled with people. Many at the shore still work in manufacturing and service industries. However, few at the shore seem to understand the implication of the receding water line and even fewer take action to avoid the pending disaster. As the waves roll closer to shore, the beach remains filled with people.

In the next few moments – for this analysis consider next “few moments” as next “few years” – the pending disaster becomes apparent. The waterline begins moving ashore rapidly as the first of a series of giant waves becomes visible. The people at the shore – those with limited education and skills – try to escape, but it is too late and waves overwhelm them.

The powerful waves continue inland, destroying many long-standing structures, once thought invincible. Much is lost and chaos ensues for those who survive.

Am I overreacting to the potential impact of a technology tsunami? Is a technology tsunami even possible? Or, as a couple of people have suggested, am I being like “Chicken Little”?

My concern about a technology tsunami has less to do with whether AI will become smarter than humans and more to do with the potential impact on the stability of society. How many lower-skilled, semi-skilled and even skilled blue and white-collar jobs will technology replace?

Trying to stop implementation of technology is foolhardy. Depending on when such a stop-technology approach was implemented, today we might be travelling by horse and buggy and living without electricity, telephones, tv/radio, computers, internet, etc.

And yes, I agree that societies have survived major technology disruptions in the past. But the transitions to new technologies have rarely, if ever, been smooth. Even worse, countries that did not transition to new technologies successfully became also-rans.

During the technology tsunami, what is likely to happen to societal stability in the US? How will people react who are replaced by technology? As middle-class jobs continue to be eliminated…and many new jobs are at lower pay, if available at all…will people sit idly by? (When formulating your answer don’t be misled by the unemployment rates in recent months. Look at constant-dollar median incomes over time compared to GDP per capital. Income has not kept up with productivity. Also significant wealth has transferred toward the very top. The longer-term trend is a much smaller middle class with less wealth accumulation.)

If a technology tsunami seems possible, then what are we…societal we…doing to prevent a likely social upheaval that follows the tsunami? As best I can tell, we are doing nothing of substance. Policies of the Trump Administration seem to be focused on preventing adoption and even overturning technology rather than planning how to manage the transition.

In a way, the logic for why we should prepare for a technology tsunami is similar to the logic of why we should make efforts to prevent further global warming. Who’s right about the cause of accelerated global warming does not matter. If global-warming deniers are correct and man has contributed virtually nothing to global warming, the consequences are the same…and the consequences are not good. By doing something, then there’s a chance to reduce the negative effects.

Since we have a good idea of the effect of a technology tsunami, how do we start preparing? Maybe the first step should be to look at the 1930’s. In response to widespread unemployment (at least 25%), reduced net worth among most families, and no clear prospect for an economic turnaround, FDR and Congress implemented programs to create jobs. Creating jobs had a twofold effect: (i) putting money into people’s pockets so they could begin buying again; (ii) allowing families to regain self-respect.

One can argue about the efficacy of specific New Deal programs. However, there should be little argument that these programs helped bring stability back to US society.

Part of the New Deal not often discussed is the effort to increase participation in public education. During the 1930’s, many grammar and high schools were built and students encouraged to complete high school.

The efforts resulted in a sharp increase in the percentage of the population graduating from high school. The increase in percent graduating from high school continued until the 1970’s when the rates plateaued.[1]

Emphasis on education continued after WWII with the GI Bill of Rights and then with availability of low-cost loans encouraging more students from lower- and middle-income families to attend college.

The lesson of these programs for today? Existing and emerging technologies require more math/analytical skills to utilize capabilities. With the need for more math/analytic skills…and the risk of becoming an also-ran country by not adopting the technologies…what actions do we take? How does US society get more people educated, especially those on the shore unaware of the pending technology tsunami?

Following are some ideas. You’ll likely look at the list and say, “What’s so innovative about the list? I’ve heard these ideas before.” And, you’re right. The ideas are not new…but you know what? We’re not implementing them, and in some cases we seem to be regressing.

The list is intended to start the discussion:

  1. Help society understand that expenses for public education are investments, not merely costs. Investments may take time to payback but result in a benefit that spans generations.
  2. Increase pay for…and respect for teachers. Make the qualifications and salaries for teachers competitive with, and possibly slightly above, the private sector.
  3. Reinstitute more technical training in high schools. Almost everyone agrees not everyone is suited for college. Not attending college does not mean one does not have valuable skills. Far from it. The public schools should provide everyone an opportunity for training in how to use, leverage and maintain technology skills. At one time “technical training” was common in high schools. Time for it to return.
  4. Make loans for college affordable with a provision to “earn-out” the loan over a reasonable period. Unlike today, make compliance for the earn-out provision easy to understand and execute. Provide assistance to the participant – not everyone is an expert at filling out government paperwork. Encourage people to become teachers. Don’t discourage them with onerous penalties for slight mistakes in completing paperwork.
  5. Cut back, or eliminate private charter schools. Yes, all organizations need fixing over time. Public education is no exception. But charter schools are not necessary to fix problems in public education. Charter schools destroy the very foundation of public education…and operate with far less accountability. The trend toward charters needs to stop and charters eliminated.
  6. Create meaningful education programs for older workers. The claim by some that “I’m too old to learn” is an excuse, not a reason. My experience has been many older people are embarrassed to ask for help. When assistance is framed the right way, it is rare that someone turns down the opportunity to learn. We…again societal we…need to be flexible in how we approach teaching students, whether the student prospect is in grammar school or a grandparent.
  7. Implement meaningful education programs and works-skills programs in prisons. Incarceration is incredibly expensive. While different studies include different amounts for overhead and other costs, the least amount of cost per year to incarcerate someone is roughly the same as tuition, room and board at a state university. In many studies, the cost is multiples higher than tuition, room and board. Incarceration without rehabilitation is wasted money. Educating prisoners and having prisoners do meaningful work while incarcerated seems to be “common sense.”

How do we implement some of these ideas? More in the next article. Stay tuned.

[1] 120 Years of American Education: a Statistical Portrait, US Department of Education, 1993.

Links to articles re GM Plant Closings

#318 Tipping Point on the Donald: Fingernails Are Too Long

Readers: this blog is set in the future (sometime after the year 2020). Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution. More about the Revenge Revolution and author, Entry #1.  Many entries are formatted as conversations. Characters appear in a number of entries, with many entries building on previous conversations.  

Occasionally I do a “sense check” about the likelihood of a Revenge Revolution.  Entry #318 is a “sense check.”  One more note — sometimes I write about another topic that does not quite fit the theme of the blog.  Those comments are in the page titled “JRD Thoughts and Comments.

When I started this blog more than five (5) years ago, two guidelines I set were key: (i) avoid spending too much time on political or economic events occurring in the previous week or two; (ii) avoid overreacting to such events. Throughout writing the blog I’ve tried to keep such events in proper perspective and also tried to frame the events in the context of the underlying premise of the blog – sometime after 2020 the US would experience a 5th revolution, which I labeled the “Revenge Revolution.”

Trying to avoid overreacting is borne out by history. Revolutions seem to be caused by events over time. However, a few events during a short period of time, or even one event, can tip the scales, triggering the populace to say, “Enough, already. Throw the bum(s) out. Time for a change!”

Although we rarely think about it, such trigger points happen in our everyday lives. A simple example is one day you look at your fingernails and think they’re too long. And with that realization, most of us feel an urgent need to take action and file the nails. Obviously the fingernails didn’t grow all at once. The fingernails grew a little bit every day and then, suddenly, the fingernails seemed too long.

This phenomenon is described by the Theory of Just Noticeable Difference, (JND). While JND is usually applied to more physical measures – e.g., length of fingernails – the theory seems to apply to less tangible measures as well. For many people, Trump’s behavior the past couple of weeks has been akin to a “fingernails-too-long” moment.

Just why would people think that way? Let’s take a quick review of events of the past couple of weeks. The list is not necessarily in chronological order.

  1. Michael Cohen, long-time Trump lawyer and “fixer” of problems, was sentenced to three (3) years in prison for what the judge called a “veritable smorgasbord of criminal conduct.” Earlier in 2018 Cohen’s offices were raided by the FBI. Cohen eventually became a cooperating witness against Trump in investigations by Mueller and the Southern District of NY. A partial list of crimes by Cohen has been disclosed. One crime of public interest, although one that eventually might prove to be a “lesser” crime, was for payments made immediately preceding the election to two women with whom Trump had affairs. The payments were a violation of campaign laws.
  2. National Enquirer, owned by American Media, Inc. CEO, David Pecker, admitted working with Cohen to help squash negative news about Trump immediately preceding the election. AMI was funneling money to cover a payment to at least one of the women. AMI’s involvement violated campaign finance laws.
  3. Michael Flynn, former Marine Corps general and former National Security Advisor to Trump, was anticipating no jail time at his sentencing. The judge chose to ignore the recommendations of the Special Counsel and dressed down the general in the court proceeding, indicating Flynn would be smart to ask for a delay in sentencing and agree to continue cooperating with Special Counsel for the next six (6) months. Even then the judge told Flynn he was subject to incarceration. Flynn was selected by Trump over widespread objections of the intelligence community.
  4. Matthew Whittaker, Acting Attorney General, refused to recuse himself from any involvement in the Mueller probe. Whittaker, who had been a regular on Fox News criticizing the investigation before being appointed by Trump, was strongly encouraged by the Ethics Office to recuse himself. Whittaker ignored the advice. In addition, there is some question whether his appointment was legal and whether certain actions taken by Justice Department under his appointment would be legal. The nominee to become the permanent head of Justice has been equally critical of the Mueller investigation and appears to have been chosen for that reason.
  5. Ryan Zinke, head of Dep’t of Interior, resigned. Zinke is subject of at least five ongoing investigations for various crimes.
  6. Trump Foundation agreed to dissolve after a lawsuit by the State of New York Attorney General claiming “…shocking pattern of illegality.” Based on claims presented by the State AG, it appears Trump and several members of the Trump family could face significant civil fines and possible criminal indictments.
  7. John Kelly, Trump’s chief of staff and former Marine Corps general, was fired by Trump. Kelly’s replacement – Mick Mulvaney. Mulvaney, a former representative from South Carolina, is currently Director of Office of Management and Budget. Mulvaney supposedly will function as chief of staff and run OMB. The practical effect is Trump has no chief of staff to manage schedules or try to coordinate legislation with Congress. How long will Mulvaney last? Mulvaney once called Trump’s views on a border wall and immigration “simplistic” and “absurd and almost childish.” Mulvaney added a physical barrier would not stop undocumented immigrants from crossing the Mexican border and ranchers at the border say they don’t need a fence.
  8. James Mattis, former Marine Corps 4-star, resigned as head of Dep’t of Defense. For Mattis the “fingernails-too-long” moment was Trump not seeking advice of the military and intelligence community before announcing, via Twitter, that the US would withdraw troops from Syria and probably withdraw half the forces from Afghanistan. The arbitrary decision on Syria shocked people in the US military, Congress and US allies. Since DOD was established in 1947, Mattis is the first head to resign in protest. If you have not read the letter of resignation, please do so.     18 12 21 Mattis Letter of Resignation NYT
  9. Trump Administration lifted sanctions on a Russian oligarch, Oleg V. Deripaska, who has close ties to Putin and Manafort.
  10. Putin publically praised Trump for his decisions re Syria and lifting sanctions on the Russian oligarch. (Sort of makes you wonder whose camp Trump is in, doesn’t it?)
  11. Trump, in a highly unusual public meeting in the White House, attempted to negotiate with Senator Charles Schumer of NY (top Democrat in Senate) and Representative Nancy Pelosi (incoming Speaker of the House) about a budget resolution that would continue to fund the Federal government. During the negotiations, Trump demanded that $5.0 billion be included for part of Trump’s Mexican border wall. If the $5.0 billion were not included, Trump declared in front of rolling cameras that he would be “”proud to shut down the government for border security.” The Senate passed a bill that included additional funding for border security but not a wall. The House, still under Paul Ryan, passed a bill that included funding for a wall. The House bill then forced the bill back to the Senate which refused to fund the wall. Trump then flip-flopped and tried to blame Democrats for the subsequent shutdown what he claimed he would be “proud” to do.
  12. Trump, after claiming that he was responsible for gains in the stock market, then blamed the Federal Reserve chairman for causing the largest percentage loss in value in any December since 1931. To “correct the problem,” Trump indicated he would fire Federal Reserve Chairman Jerome Powell, whom Trump appointed earlier in 2018 after firing Janet Yeltin.

There are probably more events but these are the ones that came to mind…with no further research. Yikes!! Any one of these events would have been a major scandal in a “normal” administration.

What do these events mean for the likelihood of a Revenge Revolution? If we were living during the era of the Wild West, I’d say, “Add another notch to your gun.”

I’ve not conducted a survey that would be considered scientifically valid. However, after listening to a number of people on the left, center and right, I get the sense that many have reached a “fingernails-too-long” moment…and some corrective action needs to be taken. Interesting, even some on the far right seem frustrated, but maybe for a different reason. They might sense that adults could start taking back Washington.

One far-right person that I deal with (data points of one are dangerous except in Washington), suggested he would use armed force to defend his property against any government action. I had limited time and did not dig deeper into what he considered intrusive government action. Nor did I take time to remind him the only reason he can claim ownership of property is…well, because of the legal structure established by the government. I’ll explain that role of government to him on another day.

So where are we? Many people seem to think Trump is so out of control that he needs to be removed from office. And what does that attitude mean for the likelihood of a Revenge Revolution? When I started the blog in 2013, the chances of a Revenge Revolution by the early 2020’s were at the very most 50 (yes):50 (no). Over time the odds seemed to have increased gradually. Now the odds have increased to 75 (yes): 25 (no) – at a minimum. And, without much effort, I could be talked into raising the odds to 90 (yes): 10 (no). It is truly a scary time.

If you’d like to read more about how a Revenge Revolution might get started, take a look at Entries #1-#8. (E-book version of the entries, How the 5th US Revolution Begins and About the Author).  These were my initial blog entries. I recently reread and the entries seem OK. If you are interested in how Trump might be “taken out” – impeached or physically removed from office – try Entries #244-#257. For a PDF e-book, DOWNLOAD Who Took Out the Donald #244-#257. These entries were written in summer 2017. The general content still seems plausible.

Thanks for your time. Comments welcome.

   

#317 How Technology-Induced Disruptions Impact Societies (#6 of 6)

Readers: this blog is set in the future (sometime after the year 2020). Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution. More about the Revenge Revolution and author, Entry #1.  Most entries are formatted as conversations. Characters appear in a number of entries, with many entries building on previous conversations.  

Occasionally I do a “sense check.”  Auditing one’s own work is problematic but I try to be objective.  Entries #300 and #301 are the most recent standard “sense checks.”   Entries (#310-#313) broke from conversation format.  One more note — sometimes I write about another topic that does not quite fit the theme of the blog.  Those comments are in the page titled “JRD Thoughts and Comments.”   

Scene: Jordan’s office, Washington, DC.  Continuing conversation with Gelly, Jordan’s assistant.  Conversation began Entry #308.

092615_2031_Characters7.gifGelly:  “Seems to me we have two open topics – (i) if the invention of the automobile changed society; (ii) to what extent do product life cycles influence societal change.  But I need to get out of the office soon, so no blabbering on, please.”

Jordan:  “So diplomatic.  OK, I’ll try to keep it short…”

Gelly:  “…and simple.”

Jordan:  “Let’s start with autos.  Recall I said the iPhone…really the smartphone…seemed to be more integration of existing components than an invention.  Without question, since introduction the iPhone has had a major impact on societies worldwide.  But, to me the iPhone should not be categorized as a major technology breakthrough.”

iPhone3Gelly:  “Your analysis surprised me before the break and still surprises me.  I always thought the iPhone was some big invention.  Invention or not, what does the iPhone have to do with the automobile?”

Jordan:  “The introduction of the automobile, in many ways, fits in the same category as the iPhone – more integration than invention.”

Gelly:  “Your comment just seems to counter-intuitive.  Why do you say the automobile was more integration?”

Jordan:  “What was the nickname that most people called early automobiles?”

1903 OldsGelly:  “Horseless carriage, right?”

Jordan:  “Yes.  And what did the early automobiles look like?”

Gelly:  “A carriage without horses.”

Jordan:  “Now, think about the key components of an early automobile.  Obviously horse-carriage components were around.  If fact, for the early years, automobiles used wooden frames and wooden wheels – wheels, not tires.  The engine for the automobile had been around for a while, too.  Both the steam engines and the gas engine had been used in farm tractors.”

Model T AssemblyGelly:  “What about the assembly line.  Didn’t Henry Ford invent that?”

Jordan:  “Not really.  An assembly line required parts to be standardized so each part fit the same way on every car.  While Ford was probably the first auto company to use an assembly line, rifle manufacturers had been making standardized parts for decades.  Ford was smart and adopted the same assembly-line technique to increase production and reduce cost of the Model A.”

Gelly:  “Gee, I always thought automobiles were a technological breakthrough.  Now you’re saying autos were more like an iPhone.”

Jordan:  “True, but I also have a confession.  Always knew that Henry Ford borrowed the idea of an assembly line but until this conversation, I never really thought about the development of the automobile as being more integration than invention.”

Gelly:  “Well, well.  Jordan makes a confession.  Now, next topic – how do product life cycles affect societal change?”

Jordan:  “Stick with autos to start.  The automobile life cycle has been very long…and still going strong.  While lots of things on cars have changed – design, interior, engine Baker Electricperformance, emissions, creature comforts – the fundamental technology in cars and trucks is the same as the early 1900’s.  I know that might sound odd, but it’s true.  Most people forget there were steam-powered cars and battery-powered electric cars in 1910.  See that picture on my desk.  That’s a Baker Electric.”

Gelly:  “You mean Elon Musk didn’t invent the electric car?  Yikes!  What will all those Millennials think?”

Jordan:  “Now, now, be nice.”

Gelly:  “I know what you mean.  If you see a car that was built around 1910, even earlier, everyone still knows it’s a car.  That’s not true for some major products from 40-50 years ago, or even 25-30 years ago.”

WhyJordan:  “So has the automobile life cycle affected societal behavior?  Yes, but has society been affected by the life-cycle of the automobile manufacturers?”

Gelly:  “Not sure what you mean.”

Jordan:  “The answer is no, society has not.  Let me tell you why.  And give me some leeway on the numbers.  They’re about right.  In the US in 1910 there were 200 or more companies making cars.  By 1920 that number had dropped to about 20.”

Gelly:  “Is that drop like one of those order-of-magnitudes you were talking about before the break?”

Declining ChartJordan:  “Yes.  Very good.  Then between about 1920 and the mid-1960’s, the number of manufacturers dropped from 20 to 4-5, depends on the timing.  However, did the decline in the number of manufacturers affect how societal behavior was affected by the automobile?”

Gelly:  “No.  Car sales kept increasing.  So the relative short life-cycle of most of the early manufacturers had no affect at all on the number of cars being produced.  In fact, even though the number of car manufacturers declined sharply, the number of cars sold increased sharply.”

Jordan:  “So now we’ve separated the influence of the technology from the influence of individual companies involved with the technology.”

Gelly:  “The number of auto companies in the US declined but then it increased again.  Right now there are a bunch of foreign companies selling cars in the US.  And many of those companies have assembly plants here.  Let’s see, there’s Toyota, Honda, Mazda, Mercedes, BMW…let me think some more.”

TurtleneckJordan:  “You’ve made your point.  There are at least 10 different auto companies with assembly plants in North America. They got here, in part, because in the late 1960’s and 1970’s and even in the 1980’s, the US companies were slow to respond to changing consumer tastes and the increased demand for more fuel-efficient cars.  Even if the Big 3 auto companies had responded more quickly, they probably could not have stopped all the imports.”

Gelly:  “So in the 1970’s the foreign-based companies start selling in the US…and have taken a big chunk of the US market.  But what I don’t understand is why did they build assembly plants in the US?  If Trump’s MAGA claim – Make America Great Again – had any validity, then why wouldn’t the various foreign manufacturers take the same approach?  Just build cars in say Germany or Japan and ship to the US.  Why not?

Trump DunceJordan:  “The foreign-based manufacturers built plants in North America to save money and respond to market demands more quickly.  What Trump seemed to overlook…more likely never understood…is the real cost and the long lead-times involved with building overseas and then shipping to the country where the cars are sold.  What he also probably never understood was that before 1920, the US auto companies set up assembly plants in a number of foreign countries for the very same reasons the foreign companies built assembly plants in the US.”

Gelly:  “Another example of dodo-bird reasoning in the Trump Oval Office.  Boy, am I glad Trump’s gone.”

Jordan:  “Speaking of gone, before you leave let me try to wrap us what we’ve been talking about.”

Gelly:  “Let me try instead, please.  Societies may experience major changes in behavior as a result of a new product.  There does not seem to be consistent pattern whether the product that precipitated the change was an invention, a spin-off of an invention or an integration of other products, like the iPhone or the automobile.  We also concluded it doesn’t really matter…other than to maybe a few academics…whether the primary product was the invention, a spin-off or some integration.”

Jordan:  “OK so far.”

Gelly:  “In addition, although we didn’t talk about it a lot, some products have a very long life cycle that continues to affect societal behavior – automobiles, for example.  Other products have shorter cycles that affect societal behavior – mainframe computers, for example.  Some version of the Question Animatedshorter life-cycle product might still be around but the period of influence – its life cycle – is over.  I think I understand…but the answer seems so messy.”

Jordan:  “Agreed.  There doesn’t seem to be a clear-cut answer whether a technology per se, products based on that technology, or some product which integrated that technology precipitated societal change…let alone did the societal change contribute to a societal revolution.”

Gelly:  “One thing is clear, I need to get out of here.  Good-bye, Jordan.”

Jordan:  “Good-bye, Gelly.”

(Topic over for now.  Will likely revisit reasonably soon.)

#316 How Technology-Induced Disruptions Impact Societies (#5 in Series)

Readers: this blog is set in the future (sometime after the year 2020). Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution. More about the Revenge Revolution and author, Entry #1.  Most entries are formatted as conversations. Characters appear in a number of entries, with many entries building on previous conversations.  

Occasionally I do a “sense check.”  Auditing one’s own work is problematic but I try to be objective.  Entries #300 and #301 are the most recent standard “sense checks.”   Entries (#310-#313) broke from conversation format.  One more note — sometimes I write about another topic that does not quite fit the theme of the blog.  Those comments are in the page titled “JRD Thoughts and Comments.”   

Scene: Jordan’s office, Washington, DC.  Continuing conversation with Gelly, Jordan’s assistant.  Conversation began Entry #308.

Jordan: “OK, Gelly, I’m back. On the break I thought more how to keep this discussion simple.”

Gelly: “Good. So where do we start?”

Jordan: “First step is to decide what’s a disruptive technology for society compared to a disruptive technology for a company or industry.”

Coffee cup StarbucksGelly: “Just looking at your coffee cup, I suspect the introduction of a paper coffee cup was a major disruption to the pottery coffee-cup makers.  However, it’s hard to imagine the paper coffee cup had a major societal impact. Is that what you mean?”

Jordan: “Exactly. Same logic applies to causes of the various revolutions in the US. The Great Depression in the 1930’s caused a major economic disruption for much of the population but there was no societal upheaval as there was with the other revolutions.  In fact, one might argue that during the Great Depression most of the US population came closer together rather growing than farther apart.”

Gelly: “Think I understand the difference. Now, how about looking at some technologies. Before the break I asked if computers and automobiles were technologies that caused disruptions to society.”

Jordan: “Computers seem to be easier to analyze…but be prepared because the discussion might get a bit messy.”

Gelly: “OK. If computers really started to change society, then when did the change start?”

IBM MainframeJordan: “In the 1960’s when IBM introduced what were called mainframe computers. Granted, by today’s standards, the mainframes were big and slow. There were special air-conditioned rooms to handle all the extra heat from the computers. Plus, for a lot of applications, you had to transfer information to punch cards before you could use the computer. While those computers were clunky and dumb by today’s standards, the machines were breakthroughs for the time — offering at least a couple of orders of magnitude better data management and analysis.”

Gelly: “I said to keep the discussion simple, please. What’s an order of magnitude?”

Chart RisingJordan: “Each order of magnitude represents a tenfold increase. One order of magnitude would be 10x higher than the previous number. Two orders would be 100x higher – 10x the previous number which also was 10x higher. Three orders would be 10x10x10 or 1,000x higher.  Look at this chart and then imagine the line going up faster than what’s shown.”

Gelly: “So you think the computer increased data management and analysis by say 100 times, maybe 1,000 times? Wow.”

Jordan: “Wow is right. The gains didn’t apply to everything but they did to a lot of analysis. However…and this problem still exists today…you had to make sure input data was good. Otherwise, it was GIGO — garbage in, garbage out.”

092615_2031_Characters7.gifGelly: “Did IBM just one day decide to invent the computer or was something else invented that allowed the mainframe to be developed?”

Jordan: “Very perceptive question. The first so-called computers were even larger than the ones I described. The early computers used vacuum tubes and were not very practical. Have you ever seen a vacuum tube?”

Gelly: “Think so.  My grandmother kept a radio from her childhood. She took the back off one time and all I saw was a bunch of tubes. What I remember most is one time I touched a tube and it was really hot.”

Semi-ConductorJordan: “What changed to allow IBM…and a few others…to make practical mainframes was a way to eliminate vacuum tubes. The invention was the semi-conductor. Think of a semi-conductor as a computer chip or the SIM card in your phone. The early chips were not nearly as powerful as today.”

Gelly: “So getting rid of vacuum tubes was the breakthrough?”

Jordan: “Yes along with being able to store data on magnetic tape.”

Gelly: “With semi-conductors, IBM could make machines more powerful but smaller and cheaper, right?”

Jordan: “Yes. And now back to the question, ‘Does a certain technology become the driving force for societal change or merely a catalyst for societal change?’”

Know NothingsGelly: “If I understand correctly, the invention of the semi-conductor did not cause societal change per se. The societal change occurred only after products were developed using the semi-conductor. So, in deciding how a society adapts or manages technology-induced disruption, does it really matter whether the invention is the driver or the catalyst for the change? Deciding which might be a good academic exercise but does anyone else care?”

Jordan: “You’re right, it probably does not matter whether the technology is the driver or the catalyst. The semi-conductor could have been invented but then put on the shelf and never used. That’s happened to who knows how many inventions.  And some of those shelf sitters might be as important for society as the semi-conductor.”

HorseGelly: “Jordan, are we looking at the issue from the wrong end? We’re trying to find the cause of the societal disruptions. Would a better approach be to ignore the cause and analyze how the  technology disrupted society…and, if so, what kind of disruption?”

Jordan: “Mmm, you might be on to something. Keep talking.”

Gelly: “Say if some company like IBM had not used the semi-conductor, we might not have laptops, internet, or smartphones.”

Jordan: “Good point. Let’s not get hung up on who or what technology caused the disruption. Let’s look at the change that resulted.”

Gelly: “Go back to IBM. My uncle used to work there. If family stories are anywhere near correct, IBM quickly became a behemoth company, making lots money for many people, including my uncle.”

Jordan: “So how long do you think the IBM growth spurt was? Just for fun, let me do a quick download of IBM sales over time.”

Gelly: “OK.”

18 11 24 IBM Growth Yr-to-Yr 1007214-13999302201478128-Peter-E--Greulich_origin_LIJordan: “Take a look at sales after WWII and the hand-drawn blue line.  The company had positive sales growth virtually every year from right after WWII to almost 1990 – 45 years.”

Gelly: “Some of those year-to-year gains don’t look like much.”

Jordan: “Take another look at the scale on the left side. There were a lot of years when sales increased 15% or more over the prior year. That kind of gain for one year is good. To achieve that kind of gain year after year after year is phenomenal.”

Gelly: “So what happened in the early 1990’s? Sales declined for several years…and doesn’t look like they’ve really bounced back since.”

Laptop 1990Jordan: “What IBM missed was the shift to the personal computer – desktops first, then laptops. Even though the PC was not as powerful as the mainframe, it was easier to use.”

Gelly: “I’m beginning to appreciate what you mean by the analysis being complicated. The semi-conductor gets invented, then voila, a bunch of new electronic products are introduced – mainframe computers to portable radios – and society begins to change behavior.”

Jordan: “As semi-conductors become more powerful, more products are introduced – personal computers, e.g. – and a new set of players dominates the scene – Apple, Microsoft and Dell. IBM’s still around but no longer the really big dog.”

Gelly: “Then the internet comes along and we have another set of players. By the way, wasn’t the internet some kind of Defense Department project?”

Jordan: “It was.  DoD worked with a small number of universities to set up a commutations network to make it easier to exchange data between computers. I’ll bet that in their wildest dreams these guys never thought how the internet would grow and be used today. Who could have imagined the likes of Google, Facebook and Amazon?”

Gelly: “So, if I step back and try to decide if society was changed by electronic products…and the answer is ‘yes’…then the base technology that allowed the change as the semi-conductor. But without products that used the semi-conductor – mainframes, laptops, portable radios, cell phones…and who knows what else – the semi-conductor would not have been a game changer.”

TurtleneckJordan: “Now you can see why trying to figure out how much society was changed by a specific technology is a messy exercise. Some products that influence societal behavior, at least in my estimation, don’t even qualify as technology breakthroughs. Others are breakthroughs but don’t get credit.”

Gelly:  “OK, Jordan, cut the gibberish and tell me what you mean.”

Jordan:  “Some so-called breakthrough products are really integration of existing components, albeit very sophisticated component integration but still integration.”

Gelly: “By integration you mean like picking and choosing parts from other products and then creating a new product? Sorta like Italian food. Spaghetti, linguine, angel hair have essentially the same base ingredients but are configured differently.”

iPhone3Jordan: “That’s a different way of looking at it but a good example. Let me give you one of my favorites. Not sure everyone on the original development team would agree, but I think the iPhone was a very clever and sophisticated integration of components from cell phones and laptops.”

Gelly: “Alright, but even if some products are integrations, so what? Can’t these products change society?”

Jordan: “Absolutely. And there’s another yet aspect of how a technology can change societal behavior – that is the life cycle of a product.

Gelly: “We can talk about life cycle.  But before we do I have a question for you.”

Jordan: “Which is?”

Miracle on 34th StreetGelly: “Near the end of the movie ‘Miracle on 34th Street’ when they’re driving down some the suburban street, Natalie Wood shouts something. Remember what she shouted”

Jordan: “You mean, ‘Stop Uncle Fred, stop!’”

Gelly: “That’s what we’re going to do now – stop.”

(Continued)

#315 How Technology-Induced Disruptions Impact Societies (#4 in Series)

Readers: this blog is set in the future (sometime after the year 2020). Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution. More about the Revenge Revolution and author, Entry #1.  Most entries are formatted as conversations. Characters appear in a number of entries, with many entries building on previous conversations.

Occasionally I do a “sense check.”  Auditing one’s own work is problematic but I try to be objective.  Entries #300 and #301 are the most recent standard “sense checks.”   Entries (#310-#313) broke from conversation format.  

Scene: Jordan’s office, Washington, DC.  Continuing conversation with Gelly, Jordan’s assistant.  Conversation began Entry #308.

Jordan: “OK, Gelly, got my coffee refill. Ready to talk more about how societies cope with technology-induced disruptions?”

Gelly: “Yes, but as a reminder, keep it simple, please. I’m just trying to understand the basics. Not trying to become a PhD candidate.”

Jordan: “Not to worry. Besides, I’m not a PhD.”

092615_2031_Characters7.gifGelly: “Maybe not but you have lots of study time…and a bunch of experience in the real world using economics stuff. Remember, KISS, okay?”

Jordan: “Let’s go back and look at how artificial intelligence (AI) is being used. Another example is your iPhone. Ask Siri a question.”

Gelly: “Siri has artificial intelligence?  And I thought she lived in my iPhone. OK, ‘Hey, Siri, what was the score of last week’s Michigan-Indiana football game?’”

MichiganJordan: “When Siri tells you Michigan beat Indiana, that’s a form of AI.”

Gelly: “I understand that part…I think. Siri hears the question, does a quick search of available databases, finds the answer, and then repeats the score. That easy enough to understand. Not saying easy to make happen, just easy to understand.”

Jordan: “You’re right, not easy to make happen. Now ask Siri to tell you a joke.”

Confused Clip ArtGelly: “How does she do that?”

Jordan: “When the question is more abstract, like ‘Tell me a joke,’ it’s the same procedure as looking for the score of the football game. However, for more abstract questions, sometimes the answer is reasonable and sometimes the answer is off the wall. Remember that AI is more effective when parameters of the task are defined. The Michigan-Indiana score is quite specific. So is picking up boxes, which we talked about earlier. Accuracy of AI also improves as more information is added to the database and algorithms refined.”

PhoneGelly: “So for Siri, Alexa and their siblings, they’re best at providing quick access to available information. At the same time, the working stiffs most affected by Siri and siblings are people employed to provide information. The example might seem a bit  dated but as a kid I remember being able to pick up the phone and have the operator get someone’s number, right?”

Jordan: “Right. Another example is society’s need for newspapers. For a couple of centuries newspapers were a primary source of information for all kinds of activities. People used to buy a paper for say just the sports section. That need has changed. Siri just told you the score of the Michigan-Indiana game. And, if you wanted, you could get real-time updates on your smart phone. Even if the game is not broadcast in your viewing area, you can ge an app on your phone to watch the highlights of the game and a bunch of other games as well.”

Legal ClerkGelly: “What about AI replacing some functions of what lawyers do, or at least law clerks do? Same with some portion of information gathered when visiting a doctor. Seems as if a lot of people could be replaced, or maybe have been replaced already by some form of Siri and siblings. What about using AI for tasks that are a lot more complicated than say picking up boxes or searching a database?”

Jordan: “You mean like people who used to paint cars or weld frames or even lay bricks being replaced by robots?”

Gelly: “Yes, but also tasks that seems even more complicated…like sewing clothes. You might not appreciate it but there are lots of steps in sewing. Lots of turning fabric and moving it back-and-forth. Making even simple clothes requires a lot of steps and precise hand-eye coordination. It’s not easy.”

Sewing MachineJordan: “Well, some clothes are already being made 100% or nearly 100% by machines. And over time, machines will make clothes that require more steps.”

Gelly: “That’s what I still don’t understand. What does happen to all those people in low-cost countries that are making clothes? If they lose their jobs, what happens? By the way, has anyone ever studies what happened to all those telephone operators, or guys that were painting cars?”

Jordan: “Your concern is spot on. What does happen? Unfortunately, the people who are most negatively affected by a disruptive technology, AI or otherwise, have little or no recourse when their job is eliminated. If they’re lucky, some get a handshake and severance pay but in developing countries, these people are SOL.”

Poor PersonGelly: “Another case of the working stiff getting screwed?”

Jordan: “The key for the country is whether the leadership begins adopting new technology and creating new jobs. If not, the country will continue to fall behind.”

Gelly: “How often do these technology disruptions happen? Seems like much faster today.”

Jordan: “Faster today…maybe. But we forget some of the objects or equipment we consider mundane today were really technology disruptions when introduced.”

Gelly: “You mean like the printing press, telegraph, the tractor and combine?”

Jordan: “Think about what was introduced between say 1850-1950. Electricity, cars, planes, trains, repeating rifles, motion pictures, radio, television…and that list doesn’t include any medical advances. So whether change is faster now is debatable. But the same problem exists – what do you do with people replaced by technology?”

Gelly: “OK, what does happen to society? I remember you talking one time about Argentina and the US having roughly the same GDP per capita in 1900. Then 100 or so years later GDP per capita in the US was almost 4x Argentina.  Argentina fell way behind.”

TurtleneckJordan: “Excellent example. I’m impressed you remembered.”

Gelly: “Thank you. Now, what happens in these countries?”

Jordan: “Remember when we first started to talk about the patterns of revolutions in the US?”

Gelly: “You found that there was a pattern of a revolution roughly every 50 years.”

Jordan: “The word ‘roughly’ is the key. Major changes in societal behavior do not follow some precise timeline. People who want to develop a more predictive model are always disappointed in how squishy the approach is.”

Gelly: “There seems to be a reasonable pattern for revolutions. Is there some kind of pattern or technology disruptions?”

Jordan: “There seems to be but the problem is trying to figure out if and how other factors affect the cycle.”

dude-with-questionGelly: “Now I’m starting to get even more confused.  What happened to KISS…keep it simple, stupid?”

Jordan: “Let me say after technology moves out of the lab and first becomes commercially viable, there’s a period of very rapid growth in companies and countries that use the technology. After a while the growth associated with the technology slows and, eventually, the technology and companies mature and decline.”

Gelly: “OK, a new technology is introduced, companies grows fast, and then decline. How long is the cycle?”

Jordan: “Without any of these other interruptions, 50 years more or less like a reasonable number. Keep in mind, if the data about revolutions are squishy, data for technology cycles are really squishy. I think there’s a pattern but the timeline for that pattern likely varies.”

Gelly: “Have you got a couple of examples. What about the auto industry? You know a lot about that? What about computers?”

Jordan: “What about another break, then we’ll talk more. I promise to try to keep it simple. As I said, the data and cycles are a bit messy.”

(Continued)

#314 What’s Artificial Intelligence? What’s Going to Happen to Working Stiffs? (#3 in Series)

Readers: this blog is set in the future (sometime after the year 2020). Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution. More about the Revenge Revolution and author, Entry #1.  Most entries are formatted as conversations. Characters appear in a number of entries, with many entries building on previous conversations.

Occasionally I do a “sense check.”  Auditing one’s own work is problematic but I try to be objective.  Entries #300 and #301 are the most recent standard “sense checks.”   The previous four entries (#310-#313) broke from conversation format.  Characters return with this entry.

Scene: Jordan’s office, Washington, DC.  Continuing conversation with Gelly, Jordan’s assistant.  Conversation began Entry #308.

092615_2031_Characters7.gifGelly: “The last lesson we had on economics, professor, was about how tariffs usually don’t work. As a result, when tariffs are imposed it’s often the working stiff that ends up…well, getting screwed.”

Jordan: “Where’s this conversation headed? And, please, no more of the ’professor’ stuff.”

Gelly: “Alright, no more name calling. But I would like to learn more about AI.”

Jordan: “For AI, you talking about ‘artificial intelligence’ or ‘artificial insemination’?”

Gelly: “You know which one – artificial intelligence.”

Trump DunceJordan: “You mean artificial intelligence…like Donald Trump’s intelligence — artificial?”

Gelly: “Get serious, please. A lot of people are talking about AI and I really don’t know what it means or how it works.”

Jordan: “First, I’m not an expert on AI and don’t know exactly where it’s headed. But I’m not sure anyone does. What’s even more confusing is the term ‘artificial intelligence’ gets applied to a broad range of what seem to be not overly sophisticated software applications.”

dude-with-questionGelly: “I’m also confused about what I hear people calling ‘machine learning.’ Is machine learning the same as artificial intelligence or part of artificial intelligence?”

Jordan: “Let’s try to simplify the entire category. I know some techies would probably go apoplectic if they heard this explanation but we’re not trying to prepare you to write a thesis at MIT. To get started, think about AI as using more advanced software. And there are a lot of applications. At the same time, the software is designed for…”

Gelly: “Let me try, please. Rather than software for say Excel or Word, the software for AI is a designed so some kind of machine can learn to do things?”

Jordan: “That’s a good way to think about it.”

Gelly: “But does the machine end up writing its own software program? How does it learn?”

Hammer NailJordan: “Think about how you learn to do some task. Could be learning to use a computer. Maybe something easier like hammering a nail. What’s the first step?”

Gelly: “Usually you watch somebody do it.”

Jordan: “Then what?”

Gelly: “When you first try you’re usually not very good at it.  So you have to practice and practice. If you’re lucky there’s a teacher around to help correct your mistakes. Eventually you get better and do whatever it is on your own.”

Jordan: “You just described how a machine learns.”

Boxes in WarehouseGelly: “So, if somebody shows the machine how to say pick a box off a shelf and load it on a cart, then the machine can learn to do that?”

Jordan: “Basically, yes. The person demonstrates to the machine how to find the box, pick up the box and load it on the cart. The machine records the movements — say with some kind of camera.  Then the machine tries to repeat the movements.”

Gelly: “What if the machine makes a mistake?”

albert-einsteinJordan: “Good question. That’s what different about today’s machine learning and attempts in the past.  In the past, the limitations were software and computer processing. To get the machine…a robot…to do something required a lot of very precise programming. Plus the capacity of machine ‘memory chips’ was limited…intellectually challenged…so the robot couldn’t really do much.  Today’s chips are like Albert Einstein compared to earlier chips.”

Gelly: “I know computer chips have gotten more powerful. But can a machine learn a more complicated task right away?  How would it do that?”

Jordan: “The power of the computer chips is a key.  Let’s say the machine response is not quite right.  The person can do another demonstration and the machine can correct itself.  But let’s say the task is a lot more complicated.  The demonstration can be broken into smaller steps.  The machine then learns each step.”

SuccessGelly: “If I understand correctly, by learning a set of small steps, the machine can adapt  if some part of the task changes.  For example, if the first box is small and the next box is larger, the machine could pick-up either size box and load on the cart.  I understand there’s some range of sizes but, as long as the machine has been taught to pick up a bunch of different size boxes, the machine can pick up any size box within that range.  Right?”

Jordan: “You got it.”

Gelly: “What else can these machines be taught to do?”

drone-manJordan: “That’s the question that seems to be scaring a lot of people. As computer chips continue to be more powerful, the capabilities of the machines will continue to increase.”

Gelly: “Guess the machines are like children. As they get older, they can learn to do more things. But people seem to reach a limit as to what they can learn and do. What about machines? Will they reach a limit or will they keep on learning…and maybe outsmart humans?”

Jordan: “No one knows for sure. When I hear that question, I go back to a fundamental of learning, whether learning for humans or machines, but especially machines.”

Gelly: “You mean GIGO – garbage in, garbage out?”

Jordan: “Exactly. People need to think about what machines are being trained to do. And then think about what happens if the machines turn against the trainers.”

Gelly: “If we go back to machines picking boxes in a warehouse, what kind of bad things can the little robot do? At most, some people lose their jobs. Not nice for the people but not a societal crisis. If we talk about some sort of robot war machine that seems like a lot more risk.”

TurtleneckJordan: “That’s the point. War machines are a different story. While it seems like a bit of science fiction, very sophisticated war robots could decide to turn around and attack.”

Gelly: “Now, that does seem scary.”

Jordan: “A rogue war robot…or even worse an army of rogue robots…is still an abstract idea. Because the idea of a rogue war machine is still abstract and not yet a reality is why we need to start thinking through what we’re training machines to do…and start now.”

Gelly: “Back to the more mundane. Seems as if machines can replace lots of people, even some who are considered highly skilled.”

Jordan: “Yes these robots can and probably should replace some of these people.”

Gelly: “What does society do with all the people who end up losing their jobs to machines? If a bunch of people lose jobs, won’t that negatively affect the economy?”

Steam Engine Old RenderingJordan: “Yes, but countries having to manage the transition from an existing to a disruptive technology is not something new. Countries worldwide have faced this very problem for centuries — what about the introduction of steam engines, planes, cars, telephones, internet…and the list goes on. Some countries have managed the transitions well, other not so well.”

Gelly: “Seems to me the United States has managed well so far. But I’m not so sure going forward. Trump’s whole theme seemed to be attracting people who had been or likely to be negatively affected by new technology. Then after Trump, we had another upheaval with the Revenge Revolution. How do we manage going forward? Now, I’m getting nervous.”

Jordan: “Hold on, Gelly. Let me go get a coffee refill, then we’ll talk. Or maybe that coffee robot could get a coffee refill for me.”

Gelly: “Funny, Jordan. But I really am concerned.”

 

#313 “I’m So Proud of My Son. He Lies, Cheats, Steals and Discriminates.”

Readers: this blog is set in the future (sometime after the year 2020). Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution. More about the Revenge Revolution and author, Entry #1.  Most entries are formatted as conversations. Characters appear in a number of entries, with many entries building on previous conversations.

Occasionally I do a “sense check.”  Auditing one’s own work is problematic but I try to be objective.  Entries #300 and #301 are the most recent standard “sense checks.”   The last four entries, including this one, break from the conversation format.  Characters will return soon.

What a proud moment for any parent. Being able to proclaim, “I’m so proud of my son. He lies cheats, steals, and discriminates. Exactly what I wanted him to be.”

Proud FatherIf you’re a parent, or have a brother or sister, wouldn’t you be proud to be able to make such a proclamation? Well, you can make such a proclamation if you support Donald Trump and his Republican enablers.

Put aside your political party and look at the behavior. Do you want your child or sibling to be known for lying, cheating, stealing and discriminating?

If you said “yes” unequivocally or said “yes” but included a list of caveats in your answer – such as “You need to look at what Trump has accomplished” – then read no farther. You are someone who is willing to let the ends justify the means, no matter how unethical the means and no matter how questionable the ends.

Ten CommandmentsIf you’re religious…if not pretend you are for a few minutes…then show me where in your religion is a list of basic tenets indicating acceptable behavior includes lying, cheating, stealing, discriminating. Even if your religion “forgives” such behavior, doesn’t the person being forgiven need to stop such behavior first?

Trump has not stopped lying, cheating, stealing or discriminating. So why do you support him? (If you think Trump doesn’t steal, dig deeper into how Trump and family have repeatedly cheated on income taxes due. His cheating, by the way, means you are paying more in taxes.)

ConstitutionLet’s put religion aside and talk instead about the oath of office taken by the president. The oath, which is part of the US Constitution, reads, “I do solemnly swear (or affirm) that I will faithfully execute the Office of President of the United States, and will to the best of my Ability, preserve, protect, and defend the Constitution of the United States.”

Notice the oath includes “…preserve, protect and defend the Constitution of the United States.” So, why do you support someone who thinks he has the power to change the Constitution at will — such as the 14th Amendment?

We know Trump didn’t attend civics classes and certainly has never read the Constitution. But if you’re a Trump supporters who made it past 6th grade, then you should know the way to modify the Constitution is not some half-assed Executive Order but ratification by 2/3 (67%) of the House and Senate, then ratification by 3/4 (75%) of the states.

Gee, you say, don’t be so picky. Its election time. Everyone distorts the truth. Quit being such an elitist liberal.

PinocchioNo, I won’t get over it…and neither should you. By latest count, Trump has been lying at least 30 times a day with the rate of lies increasing with each day closer to the mid-term elections. And those 30 lies per day are the ones known to the public. How many more lies does he tell inside the White House? Trump supporters – would you tolerate your child lying 30 times a day?

Fellow Americans, like it or not, the president’s words and actions matter. The president’s words and actions help set the tone of behavior and dialogue for the country. Think of the president having the same type influence on many people as a parent’s behavior influences a child.

If you think behavior does not matter, look at families where one or both parents is abusive and/or lies constantly and/or steals and/or discriminates. How does such a toxic atmosphere affect the behavior of children? Compare the long-term behavior and success of children raised in such a toxic environment to children raised in more stable environment where parental behavior is open, honest and encouraging. Which atmosphere do you want your children or grandchildren to be raised in?

Trumpsters, forget brining up examples of people who end up thriving despite a toxic home environment as a child. Such individuals should be praised for their success…but they are outliers, the exceptions. For every one who has been able to overcome the effects of a toxic environment, there are probably 100 who, unfortunately, have not.

Voting LineMaking a choice about what type behavior you want from the president and other political leaders is not difficult. Do you want someone leading the country and/or representing you who lies, cheats, steals, and discriminates? If you would be proud of such behavior by your child or sibling, then Trump and his gang of enablers are for you.

Just keep in mind continuing to support such unethical behavior by Trump is a sure-fire path to having the Revenge Revolution sooner than later…and a sure-fire path to making the Revenge Revolution more intense. Trumpsters, it’s your call.

 

#312 Republicans Have Given Away Their Soul…and the Country’s Soul. How Do We Get It Back?

Readers: this blog is set in the future (sometime after the year 2020). Each entry assumes there has been a 5th revolution in the US — the Revenge Revolution. More about the Revenge Revolution and author, Entry #1.  Most entries are formatted as conversations. Characters appear in a number of entries, with many entries building on previous conversations.

Occasionally I do a “sense check.”  Auditing one’s own work is problematic but I try to be objective.  Entries #300 and #301 are the most recent standard “sense checks.”   The last three entries, including this one break from the conversation format.  Characters will return soon.

Ever notice how many adults seem to take statements at face value, never asking, “Why do you make that statement?” or “What’s the source of your data?” The lack of curiosity seems particularly prevalent around elections and among those who quit reading newspapers regularly and rely primarily on the internet and/or specific cable channels for what is often opinion disguised as news..

Hear Speak See No EvilHow many people do you know have joined a “political tribe”?  And as a member of that tribe, no longer question even the most outlandish statements of tribal leaders?  Think about how passive these tribal members have become.  Do you know of any self-respecting four year-old who would take your statements as gospel and quit asking “why?” Chances are you’ll have a hard time finding a four year-old who fits that category.

dunce capsI know some blog readers think that lately I’ve been beating up the Republicans too much.  Maybe so, but given the behavior of the so-called leaders of the Republican Party, such criticism seems more than justified.

For starters, has anyone in the Republican Party asked “Why do we so ardently support a president whose actions are seemingly contrary to everything the Party has promoted the past decades?”  Maybe the Republicans should start to act like that self-respecting four year-old and ask some questions.  Here’s a start on a list of questions:

  • Why are we…yes, we Republicans…supporting a guy who coddles known enemies, starting with the Russians but including a host of other bad characters?Putin
  • Why are we no longer supporting free trade, a bedrock of the Republican Party for decades?
  • Why are we trashing our best allies in favor of known enemies?  (Ever think about the implications of alienating countries that we might need later?  Do you behave this way toward your friends?)
  • Why did we knowingly and enthusiastically pass tax legislation that transfers more money to the wealthy, takes away money from the middle class and is already resulting in ever-larger and unsustainable budget deficits?
  • Why are we following Trump and effectively promoting violence against certain groups within the US?
  • Why are we ignoring a basic tenet of most religions to treat thy neighbor as thyself?
  • Why are we barring refugees from entering this country legally?  (Yes, refugees have a right to enter.)
  • Why are we cutting funding for public education, which has been the bedrock of economic growth for decades?School Bldg
  • Why are we encouraging companies and people to pollute when there are numerous directives in the Bible to leave the earth a better place?
  • Why are we encouraging discrimination against people who are gay?  (Look folks, nearly every family has someone who is gay.  Get over it.)
  • Why are we ignoring a key provision of the Constitution by not letting citizens vote or making it extremely hard for citizens to vote?  (The Republican Party has produced no evidence in any location in the US of voter fraud.)
  • Why are we ignoring the 1st Amendment right to a free press?  (Yes, a free press is protected by the 1st Amendment.)NYT Logo
  • Why are we supporting claims that a free press is the “enemy of the people” when such claims are used by dictators?  (Need some evidence aside from Trump’s outright statements that the media are the enemy?  Start with the killing of Jamal Khashoggi by the Saudi government…and the tepid, if not bizarre, response by Trump.  If that’s not chilling enough, please read some history about how Hitler and others claimed the media was the enemy as part of their plan to help create dictatorships.)
  • Why are we accepting and even cheering “trash talk” and “name calling” by the Duncepresident when such talk from your children would result in punishment?
  • Why are we going to great lengths to support someone for the Supreme Court who lied under oath to Congress?
  • Why are we supporting a president who, after a mass shooting in a synagogue, says the synagogue should have armed guards?  (And, who was wounded at the synagogue — a mere four police officers who were heavily armed.  Do you think all religious institutions should have armed guards? )
  • Why are we trying to take away individual rights of women (Roe v Wade) yet insist on individual rights for gun owners?  (The gun-owner argument is based on a wild exaggeration about rights granted the 2nd Amendment.)    pants-on-fire
  • Why do we support a president who is a serial liar and lying more frequently each day?
  • Why do we support a president who cheats on taxes and then appoints someone to head the IRS who will minimize the likelihood of any serious audit of Trump’s taxes?
  • And the list goes on and on and on.

The questions are not political questions.  No one is challenging whether an individual has the right to be a Republican and/or conservative and/or fundamentalist Christian.  The questions are ethical and directed at making sure Republicans understand the core values of a democracy.

ScreamWhy have Republicans decided to abdicate truth in favor of Trump?  Why have Republicans decided to abdicate core values of a democracy for a guy who openly courts leaders hostile to the US?  Why have Republicans given up having America be the shining light worldwide for fairness and moral standards?

I am baffled why Republicans support such behavior.  I have no clue other than thinking the  Republicans have been brainwashed.  Whatever the cause of the brainwashing, giving away one’s core values, as have Republicans, is like giving away one’s soul.  And what did all but a handful of Republicans get in return?  Think hard because the answer is “You got nothing.”  Even if you got a bunch of money, whatever amount you got likely wasn’t worth your soul.  Further, once the trade for your soul has been made, getting back the soul will be very difficult, if not impossible.

fife-drum%201 (Just to be clear, Democrats are not completely clean…but the behavior by the Republicans in supporting Trump overwhelms any bad behavior by Democrats  Claiming the behavior is equal is a false equivalency.)

So what’s the consequence of Republicans selling the country’s soul to Trump and his cronies?  Unfortunately, so many Republicans seem to have sold their soul, the only way the country can likely start to get back on the right course is with a revolution — aka the Revenge Revolution.  And, even with a revolution, the road back will be very long and very bumpy.  Not a pleasant thought, I know, but one all of us should be thinking about.