1 April 2019 – I typically pick as a subject for my weekly post some topic of general interest, such as politics or the interaction between technology and society (which is actually the avowed focus of this blog). This week, however, I’ve decided to look at something else that commands an inordinate share of my mental attention: fictional literature. Specifically, a mystery novel I just read entitled Restorations by Charles Strickler.
To be honest, novels aren’t that far afield for this blog. This space’s avowed focus is, as I said above, the interaction between technology and society. Novels, being works of fiction, provide one of the most fertile fields for exploring abstract ideas like the interaction between technology and society. Actually, the most fertile field for exploring that topic is the narrow genre of grounded (or “hard”) science fiction mystery writing. It allows the writer the widest scope for evoking the reader’s willing suspension of disbelief while exploring how evolving technology interacts with existing social mores.
That’s not exactly the genre of the particular novel I’ve just finished reading, however. Restorations is more like a conventional mystery story. Unlike a typical grounded-science-fiction mystery, in which the action generally inhabits the temporal space extending from the present through the near future, Restorations inhabits the temporal space from the historically recent past through the present. Specifically, the novel’s plot is driven by one man’s efforts to unearth the story of one artifact (a 1928 Stutz Black-Hawk Boattail Roadster) and how those efforts embroil him in the fate of a modern-day crime family.
The title takes the plural form because the author interweaves multiple stories of restoration into his narrative. There is, of course, the physical restoration of the Stutz sports car his protagonist (Miles West) almost accidentally acquires at an estate auction. On a more symbolic level, however, there is the restoration of West’s joie de vivre, which took a nosedive after a series of personal disasters spiraled him into the depths of depression. A third restoraton story is that of the fractured Bello family, one half devoted to organized crime while the other half is devoted to philanthropy and civic order. Finally, there is restoration of the treasure amassed by the car’s first owner, the notorious bandit “Lefty” Webber, to the heirs of the people he robbed. There are additional restorations chronicled – more than the four the author promises on his website – but I’m going to leave them for you to discover by reading the book.
I must, however, mention the restoration story of West’s love interest, Bramley Ann Fairchild, whose love of historical investigation had been submerged in the day-to-day tedium of an underling in a large auction house. A tedium that was spectacularly relieved by the danger of competing with the Bello Crime Family in a transcontinental race to secure Webber’s long hidden treasure, the clues to which were hidden in secret compartments a custom coach builder had incorporated into the Stutz’ body work.
One negative note, however: I too often found myself thinking, “Oh no. Don’t drag out that old chestnut!” when one of Strickler’s descriptions or plot devices looked oh-so-familiar from previous literature. I generally want to be wowed by greater creativity from a mystery author.
But, then again, I’ve always said: “My best ideas are stolen!”
Someone once asked if that meant “My best ideas were stolen by someone else, or that I had stolen them from someone else?”
I simply answered: “Yes.”
I also detected several minor editing gaffes: places where clumsy or inaccurate wording got into print, or just out-and-out typos. Again, I should be careful about making that criticism. Every time I re-read one of my own previously published novels, I’m embarrassed to find similar mistakes that made it into print.
Altogether, Restorations is a well-written novel with compelling characters, a plot sufficiently complex to induce page turning, and lots of clear description to keep it all interesting. Unlike most of the first-time novels I get to read, Strickler’s prose is clear, unambiguous and largely hangs together logically.
I’d like to see him expand on some of the episodes that make up the plot, but there’s nothing actually missing from his narrative, just some turns down dark alleys that left me wondering what he might have found at the other end, even if it made no difference to the story.
Perhaps he’ll choose to follow such leads more in his next “Miles and Bramley” mystery! He and the book’s publisher, Koehler Books, promises that Restorations is but the first book in a series. I look forward to reading the next!
24 April 2019 – Pundits supporting the Democratic Party would have you believe that a vote for anyone other than whomever their party nominates for President in 2020 will be a vote for a second term for Donald Trump. I have been arguing that this is an extremely short sighted view that only serves the Democratic National Committee’s long-term purpose of maintaining the status quo.
Americans need a third party to break the political polarization gripping our national government under the two-party system and, at minimum, keep the existing parties focused on what matters to the American People right now instead of on partisan bickering.
The following is an invited guest post by Honor (Mimi) Robson, chair of the Libertarian Party of California that makes the case that the Libertarian Party is poised to provide that third alternative. Nearly all she says with reference to her home state of California can be said verbatim about politics in the rest of our country.
The Republican Party is finally realizing what the Libertarian Party has known for decades: California is best when the voters have options. Jessica Millan Patterson, Chair of the California Republican Party, recently wrote, “Republicans have both an opportunity and a responsibility to stand up and offer a viable alternative to the Democrats and give voters a real choice.”
However, other Republican leaders feel that the GOP isn’t the option Californians are looking for.
Soon after last year’s general election, Kristin Olsen, former Assembly Republican leader and current Stanislaus County Supervisor, wrote “the California Republican Party isn’t salvageable at this time. The Grand Old Party is dead.” So which is it?
What has been the cause of the Republican Party’s apparent demise in the state?
Perhaps it is because they concentrate on issues that are either irrelevant for or antithetical to Californians.
Perhaps it is because the party seems to have abandoned its former regard for limited government in order to appease a president that is wildly unpopular in this state.
Perhaps it is because they also seem to be doing a good job of identifying problems in the state but aren’t coming up with solutions.
The middle class is struggling in the state as they are burdened with the highest taxes and most stringent regulations in the country.
As a result businesses are fleeing the state and taking with them high paying jobs that could benefit many Californians.
In addition to jobs leaving the state, living here has become more expensive; we have a huge shortage of affordable housing.
And last, but certainly not least, we have an out of control public employee pension system; these pension liabilities are unsustainable and will ultimately bankrupt local municipalities and the state itself.
To solve the problems of California, we need to stop the unsustainable spending.
California legislators need to learn to spend within the state’s means rather than raising taxes on the top income earners who will continue to leave the state and take with them their tax dollars.
The Libertarian Party believes the first step is to reduce the many regulations that have forced so many businesses to find a more business-friendly environment.
The housing crisis could be alleviated by reducing the hurdles in place to build affordable housing.
A few simple steps we can take could help millions of people in the state.
And finally, the first step to handling the state’s pension debt is to renegotiate the contracts with the public employee unions.
As an example, when Jeff Hewitt was mayor of Calimesa, his city withdrew from their contract with CalFire and instead created their own fire department whose employees are enrolled in a traditional 401(k) retirement system; this simple step will keep the city from ultimate bankruptcy. This approach needs to be taken throughout the state.
In the last election season California Republicans lost seats in both state houses as well as representation in Washington. Between January 2018 and February 2019 the number of registered Republicans decreased by 2.5 percent while registered Libertarians increased 9.5 percent. Libertarians had a huge win in Riverside County when Jeff Hewitt was elected 5th District Supervisor over the Republican candidate, Russ Bogh, a former state assembly person with the deep pockets of the public employee unions behind him.
The Libertarian Party also ran candidates for state assembly seats in districts where Republicans didn’t even field a candidate. I was one of those candidates; in the 70th Assembly District I was the first Libertarian candidate to progress to the general election in a contested primary coming in ahead of Democratic and Green Party candidates to face off against the Democratic incumbent.
All of the Libertarian candidates running against incumbents in those seats were able to garner a significant percentage of the vote, with one of our candidates receiving approximately 40 percent of the vote in some of the counties in his district.
What does this mean? It means that Californians are looking for real change in the state. I think that the Libertarian Party offers much of this change, but I also believe in working with others when there’s common ground.
When I ran for office I said the beauty of electing a Libertarian is there are often times we can work with people on both sides of the traditional “aisle,” and I believe this more now than ever.
Honor (Mimi) Robson Bio
Honor (Mimi) Robson has been a registered Libertarian for over 3 decades and ran as the Libertarian Candidate for the 33rd District California State Senate in the 2016 General Election. In that election, with very little time or campaign funds she was able to attract support from her community, ultimately garnering almost 50,000 votes (22%). During the election cycle she became more involved in the California Libertarian Party, becoming Secretary for the party in February 2017 when the previous Secretary Resigned. She was unanimously elected secretary at the 2017 state convention; was elected chair at the 2018 state convention; and re-elected chair in April 2019. Honor ran as the Libertarian State Assembly candidate (70th District) in the top-two run-off election in November 2018.
Honor grew up in Southern California and has been a resident of Long Beach for the past 28 years. She is a Licensed Professional Civil Engineer and has worked at a small Structural Engineering Consulting firm since 1994 until recently resigning that position to become an independent engineering consultant, which will afford her more time to devote to the Libertarian Party of California. She has been involved with many charitable organizations such as AIDS Walk LA, The Alzheimer’s Association and the Juvenile Diabetes Research Foundation however Honor’s main passion is animal rescue and has been involved at every level for many years.
Sorry about failing to post to this blog last week. I took sick and just couldn’t manage it. This is the entry I started for 10 April, but couldn’t finish until now.
17 April 2019 – I had a whole raft of things to talk about in this week’s blog posting, some of which I really wanted to cover for various reasons, but I couldn’t resist an excuse to bang this old “environmental pollution” drum once again.
A Zoë Schlanger-authored article published on 2 April 2019 by World Economic Forum in collaboration with Quartz entitled “The average person in Europe loses two years of their life due to air pollution” crossed my desk this morning (8 April 2019). It was important to me because environmental pollution is an issue I’ve been obsessed with since the 1950s.
One of my earliest memories is of my father taking delivery of a even-then-ancient 26-foot lifeboat (I think it was from an ocean liner, though I never really knew where it came from), which he planned to convert to a small cabin cruiser. I was amazed when, with no warning to me, this great, whacking flatbed trailer backed over our front lawn, and deposited this thing that looked like a miniature version of Noah’s Ark.
It was double-ended – meaning it had a prow-shape at both ends – and was pretty much empty inside. That is, it had benches for survivors to sit on and fittings for oarlocks (I vaguely remember oarlocks actually being in place, but my memory from over sixty years ago is a bit hazy.) but little else. No decks. No superstructure. Maybe some grates in the bottom to keep people’s feet out of the bilge, but that’s about it.
My father spent year or so installing lower decks, upper decks, a cabin with bunks, head and a small galley, and a straight-six gasoline engine for propulsion. I sorta remember the keel already having been fitted for a propeller shaft and rudder, which would class the boat as a “launch” rather than a simple lifeboat, but I never heard it called that.
Finally, after multiple-years’ reconstruction, the thing was ready to dump into the water to see if it would float. (Wooden boats never float when you first put them in the water. The planks have to absorb water and swell up to tighten the joints. Until then, they leak like sieves.)
The water my father chose to dump this boat into was the Seekonk River in nearby Providence, Rhode Island. It was a momentous day in our family, so my mother shepherded my big sister and me around while my father stressed out about getting the deed done.
We won’t talk about the day(s) the thing spent on the tiny shipway off Gano Street where the last patches of bottom paint were applied over where the boat’s cradle had supported its hull while under construction, and the last little forgotten bits were fitted and checked out before it was launched.
While that was going on, I spent the time playing around the docks and frightening my mother with my antics.
That was when I noticed the beautiful rainbow sheen covering the water.
Somebody told me it was called “iridescence” and was caused by the whole Seekonk River being covered by an oil slick. The oil came from the constant movement of oil-tank ships delivering liquid dreck to the oil refinery and tank farm upstream. The stuff was getting dumped into the water and flowing down to help turn Narragansett Bay, which takes up half the state to the south, into one vast combination open sewer and toxic-waste dump.
That was my introduction to pollution.
It made my socks rot every time I accidentally or reluctantly-on-purpose dipped any part of my body into that cesspool.
It was enough to gag a maggot!
So when, in the late 1960s, folks started yammering on about pollution, my heartfelt reaction was: “About f***ing time!”
I did not join the “Earth Day” protests that started in 1970, though. Previously, I’d observed the bizarre antics surrounding the anti-war protests of the middle-to-late 1960s, and saw the kind of reactions they incited. My friends and I had been a safe distance away leaning on an embankment blowing weed and laughing as less-wise classmates set themselves up as targets for reactionary authoritarians’ ire.
We’d already learned that the best place to be when policemen suit up for riot patrol is someplace a safe distance away.
We also knew the protest organizers – they were, after all, our classmates in college – and smiled indulgently as they worked up their resumes for lucrative careers in activist management. There’s more than one way to make a buck!
Bohemians, beatniks, hippies, or whatever term du jour you wanted to call us just weren’t into the whole money-and-power trip. We had better, mellower things to do than march around carrying signs, shouting slogans, and getting our heads beaten in for our efforts. So, when our former friends, the Earth-Day organizers, wanted us to line up, we didn’t even bother to say “no.” We just turned and walked away.
I, for one, was in the midst of changing tracks from English to science. I’d already tried my hand at writing, but found that, while I was pretty good at putting sentences together in English, then stringing them into paragraphs and stories, I really had nothing worthwhile to write about. I’d just not had enough life experience.
Since physics was basic to all the other stuff I’d been interested in – for decades – I decided to follow that passion and get a good grounding in the hard sciences, starting with physics. By the late seventies, I had learned whereof science was all about, and had developed a feel for how it was done, and what the results looked like. Especially, I was deep into astrophysics in general and solar physics in particular.
As time went on, the public noises I heard about environmental concerns began to sound more like political posturing and less like scientific discourse. Especially as they chose to ignore variability of the Sun that we astronomers knew was what made everything work.
By the turn of the millennium, scholarly reports generally showed no observations that backed up the global-warming rhetoric. Instead, they featured ambiguous results that showed chaotic evolution of climate with no real long-term trends.
Those of us interested in the history of science also realized that warm periods coincided with generally good conditions for humans, while cool periods could be pretty rough. So, what was wrong with a little global warming when you needed it?
A disturbing trend, however, was that these reports began to feature a boilerplate final paragraph saying, roughly: “climate change is a real danger and caused by human activity.” They all featured this paragraph, suspiciously almost word for word, despite there being little or nothing in the research results to support such a conclusion.
Since nothing in the rest of the report provided any basis for that final paragraph, it was clearly non-sequitur and added for non-science reasons. Clearly something was terribly wrong with climate research.
The penny finally dropped in 2006 when emeritus Vice President Albert Gore (already infamous for having attempted to take credit for developing the Internet) produced his hysteria-inducing movie An Inconvenient Truth along with the splashing about of Jerry Mahlman’s laughable “hockey-stick graph.” The graph, in particular, was based on a stitching together of historical data for proxies of global temperature with a speculative projection of a future exponential rise in global temperatures. That is something respectable scientists are specifically trained not to do, although it’s a favorite tactic of psycho-ceramics.
By that time, however, so much rhetoric had been invested in promoting climate-change fear and convincing the media that it was human-induced, that concerns about plain old pollution (which anyone could see) seemed dowdy and uninteresting by comparison.
One of the reasons pollution seemed then (and still does now) old news is that in civilized countries (generally those run as democracies) great strides had already been made beating it down. A case in point is the image at right
. This image, which is a political map overlaid by a false-color map with colors indicating air-pollution levels, shows relatively mild pollution in Western Europe and much more severe levels in the more-authoritarian-leaning countries of Eastern Europe.
While this map makes an important point about how poorly communist and other authoritarian-leaning regimes take care of the “soup” in which their citizens have to live, it doesn’t say a lot about the environmental state of the art more generally in Europe. We leave that for Zoë Schlanger’s WEF article, which begins:
“The average person living in Europe loses two years of their life to the health effects of breathing polluted air, according to a report published in the European Heart Journal on March 12.
“The report also estimates about 800,000 people die prematurely in Europe per year due to air pollution, or roughly 17% of the 5 million deaths in Europe annually. Many of those deaths, between 40 and 80% of the total, are due to air pollution effects that have nothing to do with the respiratory system but rather are attributable to heart disease and strokes caused by air pollutants in the bloodstream, the researchers write.
“‘Chronic exposure to enhanced levels of fine particle matter impairs vascular function, which can lead to myocardial infarction, arterial hypertension, stroke, and heart failure,’ the researchers write.”
The point is, while American politicians debate the merits of climate change legislation, and European politicians seem to have knuckled under to IPCC climate-change rhetoric by wholeheartedly endorsing the 2015 Paris Agreement, the bigger and far more salient problem of environmental pollution is largely being ignored. This despite the visible and immediate deleterious affects on human health, and the demonstrated effectiveness of government efforts to ameliorate it.
By the way, in the two decades between the time I first observed iridescence atop the waters of the Seekonk River and when I launched my own first boat in the 1970s, Narragansett Bay went from a potential Superfund site to a beautiful, clean playground for recreational boaters. That was largely due to the efforts of the Save the Bay volunteer organization. While their job is not (and never will be) completely finished, they can serve as a model for effective grassroots activism.
3 April 2019 – On 29 October 2018, Lion Air flight 610 crashed soon after takeoff from Soekarno–Hatta International Airport in Jakarta, Indonesia. This is not the sort of thing we report in this blog. It’s straight news and we leave that to straight-news media, but I’m diving into it because it involves technology I’m quite familiar with and I might be able to help readers make sense of what happened and judge the often-uninformed reactions to it.
I claim to have the background to understand what happened because I’ve been flying light planes since the 1990s. I also put two years into a post-graduate Aerospace Engineering Program at Arizona State University concentrating on fluid dynamics. That’s enough background to make some educated guesses at what happened to Lion Air 610 as well as in the almost identical crash of an Ethiopian Airlines Boeing 737 MAX in Addis Ababa, , Ethiopia on 10 March 2019.
First, both airliners were recently commissioned Boeing 737 MAX aircraft using standard-equipment installations of Boeing’s new Maneuvering Characteristics Augmentation System (MCAS).
How to Stall an Aircraft
In aerodynamics the word “stall” means something quite unlike what most people expect. Most people encounter the word in an automobile context, where it refers to “stalling the engine.” That happens when you overload an internal-combustion engine. That is pull more power out than the engine can produce at its current operating speed. When that happens, the engine simply stops.
It turns from a power-producing machine to a boat anchor in a heartbeat. Your car stops with a lurch and everyone behind you starts swearing and blowing their horns in an effort to make you feel even worse than you already do.
That’s not what happens when an airplane stalls. It’s not the aircraft’s engine that stalls, but it’s wings. There are similarities in that, like engines, wings stall when they’re overloaded and when stalled they start producing drag like a boat anchor, but that’s about where the similarities end.
When an aircraft stalls, nobody swears and blows their horn. Instead, they scream and die.
Why? Well, wings are supposed to lift the aircraft and support it in the air. If you’ve ever tried to carry a sheet of plywood on a windy day you’ve experience both lift and drag. If you let the sheet tip up a little bit so the wind catches it underneath, it tries to fly up out of your hands. That’s the lift an airplane gets by tipping its wings up into the air stream as it moves forward into the air.
The more you tip the sheet up, the more lift you get for the same airspeed. That is, until you reach a certain attack angle (the angle between the sheet and the wind). Stalling begins suddenly at an attack angle of about 15°. Then, all of a sudden, the force lifting the sheet changes from up and a little back to no up, and a lot of back!
The aircraft stops imitating a bird, and starts imitating a rock.
You suddenly get a visceral sense of the concept “down.”
‘Cause that’s where you go in a hurry!
At that point, all you can do is point the nose down (so the wing’s forward edge starts pointing in the direction you’re moving: down!
If you’ve got enough space underneath your aircraft so the wing starts flying again before you hit the ground, you can gently pull the aircraft’s nose back up to resume straight and level flight. If not, that’s when the screaming starts.
Wings stall when they’re going too slowly to generate the required lift at an angle of attack of 15°. At higher speeds, the wing can generate the needed lift with less angle of attack, and worries about stalling never come up.
So, now you know all you need to know (or want to know) about stalling an aircraft.
Boeing’s MCAS is an anti-stall system. It’s beating heart is a bit of software running on the flight-control computer that monitors a number of sensor inputs, like airspeed and angle of attack. Basically, in simple terms, it knows exactly how much attack angle the wings can stand before stalling out. If it sees that for some reason, the attack angle is getting too high, it assumes the pilot has screwed up. It takes control and pushes the nose down.
It doesn’t have to actually “take control” because modern commercial aircraft are “fly by wire,” which means it’s the computer that actually moves the control surfaces to fly the plane. The pilot’s “yoke” (the little wheel he or she gets to twist and turn and move forward and back) and the rudder pedals he pushes to steer (push right, go right) just sends signals to the computer to tell it what he wants to have happen. In a sense, the pilot negotiates with the computer about what the airplane should do.
The pilot makes suggestions (through the yoke, pedals and throttle control – collectively called the “cockpit flight controls”); the computer then takes that information, combines it with all the other information provided by a plethora (Do you like that word? I do!) of additional sensors; thinks about it for a microsecond; then, finally, the computer tells the aircraft’s control surfaces to move smoothly to a position that it (the computer) thinks will make the aircraft do what it wants it to do.
That’s all well and good when the reason the attack angle got too high is just that something happened that broke the pilot’s concentration, and he (or she) actually screwed up. What about when the pilot actually wants to stall the aircraft?
For example, on landing.
To land a plane, you slow it way down, so the wing’s almost stalled. Then, you fly it really close to the ground so the wheels almost touch the runway. Then you stall the wing so the wheels touch the ground just as the wings lose lift. You hear a satisfying “squeak” as the wheels momentarily skid while spinning up to match the relative speed of the runway. Finally, the wheels gently settle down, taking up the weight of the aircraft. The flight crew (and a few passengers who’ve been paying attention) cheer the pilot for a job well done, and the pilot starts breathing again.
Anti-stall systems don’t do much good during a landing, when you’re trying to intentionally stall the wings at just the right time.
Similarly, the don’t do much good when you’re taking off, and the pilot’s just trying to get the wings unstalled to get the aircraft into the air in the first place.
For those times, you want the MCAS turned off! So you’ve gotta be able to do that, too. Or, if your pilot is too absent minded to shut it off when its not needed, you need it to shut off automatically.
When Things Go Wrong
So, what happened in those two airliner crashes?
Remember that the main input into the MCAS is an attack angle sensor? Attack angle sensors, like any other piece of technology can go bad, especially if it’s exposed to weather. And, airliners are exposed to weather 24/7 except when they’re brought into a hangar for repair.
The working hypothesis for what happened to both airliners is that the attack-angle sensors failed. They jammed in a position where they erroneously reported a high angle-of-attack to the MCAS, which jumped to the conclusion “pilot error,” and pushed the nose down. When the pilot(s) tried to pull the nose back up (because their windshield filled up with things that looked a lot like ground instead of sky), the MCAS said: “Nope! You’re going down, Jack!”
By the time the pilots figured out what was wrong and looked up how to shut the MCAS off, they’d actually hit the things that looked too much like ground.
Why didn’t the MCAS figure out there was something wrong with the sensor?
How’s it supposed to know?
The sensor says the nose is pointed up, so the computer takes it at it’s word. Computers aren’t really very smart, and tend to be quite literal. The sensor says the nose is pointed up, so the computer thinks the nose is pointed up, and tries to point it down (or at least less up). End of story. And, in the real world, it’s “end of aircraft” as well.
If the pilot(s) try to tell the computer to pull the nose up (by desperately pulling back on the yoke), it figures they’re screw-ups, anyway, and won’t listen.
Every try to argue with a computer? Been there, done that. It doesn’t work.
When I learned about the hypothesis of attack-angle-sensor failure causing the crashes that took nearly four hundred lives, I got this awful sick feeling that was a mixture of embarrassment and guilt. You see, a decade and a half ago my research project at ASU was an effort to develop a different style of attack-angle sensor. Several events and circumstances combined to make me abandon that research project and, in fact, the whole PhD. program it was a part of. In my defense, it was the start of a ten-year period in which I couldn’t get anything right!
But, if I’d stuck it out and developed that sensor it might have been installed on those airliners and might not have failed at all. Of course, it could have been installed and failed in some other spectacular way.
You see, the attack angle sensor that apparently was installed consisted of a little vane attached to one side of the aircraft’s nose. Just like the wind sock traditionally hung outside airports the world over, wind pressure makes the vane line up downstream of the wind direction. A little angle sensor attached to the vane reports the wind direction relative to the nose: the attack angle.
I got involved in trying to develop an alternative attack-angle sensor because I have a horror of relying on sensors that depend on mechanical movement to work. If you’re relying on mechanical movement, it means you’re relying on bearings, and bearings can corrode and wear out and fail. The sensor I was working on relied on differences in air pressure that depended on the direction the wind hit the sensor.
In actual fact, there were two attack-angle sensors attached to the doomed aircraft – one on each side of the nose – but the Boeing MCAS was paying attention to only one of them. That was Boeing’s second mistake (the first being not using the sensor I hadn’t developed, so I guess they can’t be blamed for it). If the MCAS had been paying attention to both sensors, it would have known something in its touchy-feely universe was wrong. It might have been a little more reluctant to override the pilots’ input.
The third mistake (I believe) Boeing made was to downplay the differences between the new “Max” version of the aircraft and the older version. They’d changed the engines, which (as any aerospace engineer knows) necessitates changes in everything else. Aircraft are so intricately balanced machines that every time you change one thing, everything else has to change – or at least has to be looked at to see if it needs to be changed.
The new engines had improved performance, which affects just about everything involving the aircraft’s handling characteristics. Boeing had apparently tried to make the more-powerful yet more fuel efficient aircraft handle like the old aircraft. There, of course, were differences, which the company tried to pretend would make no difference to the pilots. The MCAS was one of those things that was supposed to make the “Max” version handle just like the non-Max version.
So, when something went wrong in “Max” land, it caught the pilots, who had thousands of hours experience with non-Max aircraft, by surprise.
The latest reports are that Boeing, the FAA, and the airlines have realized what the problems are that caused these issues (I hope they understand them a lot better than I do, because, after all, it’s their job to!), and have worked out a number of fixes.
First, the MCAS will pay attention to two attack-angle sensors. At least then the flight-control computer will have an indication that something is wrong and tell the MCAS to go back in its corner and shut up ‘til the issue is sorted out.
Second, they’ll install a little blinking light that effectively tells the pilots “there’s something wrong, so don’t expect any help from the MCAS ‘til it gets sorted out.”
Third, they’ll make sure the pilots have a good, positive way of emphatically shut the MCAS off if it starts to argue with them in an emergency. And, they’ll make sure the pilots are trained to know when and how to use it.
My understanding is that these fixes are already part of the options that American commercial airlines have generally installed, which is supposedly why the FAA, the airlines and the pilots’ union have been dragging their feet about grounding Boeing’s 737 Max fleet. Let’s hope they’re not just blowing smoke (again)!
I’m not going to get into the tangled web of potential copyright infringement that Shaw’s posting of Hazlitt’s entire text opens up, I’ve just linked to the most convenient-to-read posting of that particular chapter. If you follow the link and want to buy the book, I’ve given you the appropriate link as well.
The chapter is of immense value apropos the question of whether automation generally reduces the need for human labor, or creates more opportunities for humans to gain useful employment. Specifically, it looks at the results of a number of historic events where Luddites excoriated technology developers for taking away jobs from humans only to have subsequent developments prove them spectacularly wrong.
Hazlitt’s classic book is, not surprisingly for a classic, well documented, authoritative, and extremely readable. I’m not going to pretend to provide an alternative here, but to summarize some of the chapter’s examples in the hope that you’ll be intrigued enough to seek out the original.
Before getting on to the examples, let’s start by looking at the history of Luddism. It’s not a new story, really. It probably dates back to just after cave guys first thought of specialization of labor.
That is, sometime in the prehistoric past, some blokes were found to be especially good at doing some things, and the rest of the tribe came up with the idea of letting, say, the best potters make pots for the whole tribe, and everyone else rewarding them for a job well done by, say, giving them choice caribou parts for dinner.
Eventually, they had the best flint knappers make the arrowheads, the best fletchers put the arrowheads on the arrows, the best bowmakers make the bows, and so on. Division of labor into different jobs turned out to be so spectacularly successful that very few of us rugged individualists, who pretend to do everything for ourselves, are few and far between (and are largely kidding ourselves, anyway).
Since then, anyone who comes up with a great way to do anything more efficiently runs the risk of having the folks who spent years learning to do it the old way land on him (or her) like a ton of bricks.
It’s generally a lot easier to throw rocks to drive the innovator away than to adapt to the innovation.
Luddites in the early nineteenth century were organized bands of workers who violently resisted mechanization of factories during the late Industrial Revolution. Named for an imaginary character, Ned Ludd, who was supposedly an apprentice who smashed two stocking frames in 1779 and whose name had become emblematic of machine destroyers. The term “Luddite” has come to mean anyone fanatically opposed to deploying advanced technology.
Of course, like religious fundamentalists, they have to pick a point in time to separate “good” technology from the “bad.” Unlike religious fanatics, who generally pick publication of a certain text to be the dividing line, Luddites divide between the technology of their immediate past (with which they are familiar) and anything new or unfamiliar. Thus, it’s a continually moving target.
In either case, the dividing line is fundamentally arbitrary, so the emotion of their response is irrational. Irrationality typically carries a warranty of being entirely contrary to facts.
What Happens Next
Hazlitt points out, “The belief that machines cause unemployment, when held with any logical consistency, leads to preposterous conclusions.” He points out that on the second page of the first chapter of Adam Smith’s seminal book Wealth of Nations, Smith tells us that a workman unacquainted with the use of machinery employed in sewing-pin-making “could scarce make one pin a day, and certainly could not make twenty,” but with the use of the machinery he can make 4,800 pins a day. So, zero-sum game theory would indicate an immediate 99.98 percent unemployment rate in the pin-making industry of 1776.
Did that happen? No, because economics is not a zero-sum game. Sewing pins went from dear to cheap. Since they were now cheap, folks prized them less and discarded them more (when was the last time you bothered to straighten a bent pin?), and more folks could afford to buy them in the first place. That led to an increase in sewing-pin sales as well as sales of things like sewing-patterns and bulk fine fabric sold to amateur sewers, and more employment, not less.
Similar results obtained in the stocking industry when new stocking frames (the original having been invented William Lee in 1589, but denied a patent by Elizabeth I who feared its effects on employment in hand-knitting industries) were protested by Luddites as fast as they could be introduced. Before the end of the nineteenth century the stocking industry was employing at least a hundred men for every man it employed at the beginning of the century.
Another example Hazlitt presents from the Industrial Revolution happened in the cotton-spinning industry. He says: “Arkwright invented his cotton-spinning machinery in 1760. At that time it was estimated that there were in England 5,200 spinners using spinning wheels, and 2,700 weavers—in all, 7,900 persons engaged in the production of cotton textiles. The introduction of Arkwright’s invention was opposed on the ground that it threatened the livelihood of the workers, and the opposition had to be put down by force. Yet in 1787—twenty-seven years after the invention appeared—a parliamentary inquiry showed that the number of persons actually engaged in the spinning and weaving of cotton had risen from 7,900 to 320,000, an increase of 4,400 percent.”
As these examples indicate, improvements in manufacturing efficiency generally lead to reductions in manufacturing cost, which, when passed along to customers, reduces prices with concommitent increases in unit sales. This is the price elasticity of demand curve from Microeconomics 101. It is the reason economics is decidedly not a zero-sum game.
If we accept economics as not a zero-sum game, predicting what happens when automation makes it possible to produce more stuff with fewer workers becomes a chancy proposition. For example, many economists today blame flat productivity (the amount of stuff produced divided by the number of workers needed to produce it) for lack of wage gains in the face of low unemployment. If that is true, then anything that would help raise productivity (such as automation) should be welcome.
Long experience has taught us that economics is a positive-sum game. In the face of technological advancement, it behooves us to expect positive outcomes while taking measures to ensure that the concomitant economic gains get distributed fairly (whatever that means) throughout society. That is the take-home lesson from the social dislocations that accompanied the technological advancements of the Early Industrial Revolution.
20 March 2019 – The image at right visualizes something described in Douglas Adams’ Hitchiker’s Guide to the Galaxy. At one point, the main characters of that six-part “trilogy” found a big red button on the dashboard of a spaceship they were trying to steal that was marked “DO NOT PRESS THIS BUTTON!” Naturally, they pressed the button, and a new label popped up that said “DO NOT PRESS THIS BUTTON AGAIN!”
Eventually, they got the autopilot engaged only to find it was a stunt ship programmed to crash headlong into the nearest Sun as part of the light show for an interstellar rock band. The moral of this story is “Never push buttons marked ‘DO NOT PUSH THIS BUTTON.’”
Per the author: “It is said that despite its many glaring (and occasionally fatal) inaccuracies, the Hitchhiker’s Guide to the Galaxy itself has outsold the Encyclopedia Galactica because it is slightly cheaper, and because it has the words ‘DON’T PANIC’ in large, friendly letters on the cover.”
Despite these references to the Hitchhiker’s Guide to the Galaxy, this posting has nothing to do with that book, the series, or the guide it describes, except that I’ve borrowed the words from the Guide’s cover as a title. I did that because those words perfectly express the take-home lesson of Bill Snyder’s 11 March 2019 article in The Robot Report entitled “Fears of job-stealing robots are misplaced, say experts.”
Snyder’s article reports opinions expressed at the the Conference on the Future of Work at Stanford University last month. It’s a topic I’ve shot my word processor off about on numerous occasions in this space, so I thought it would be appropriate to report others’ views as well. First, I’ll present material from Snyder’s article, then I’ll wrap up with my take on the subject.
“Robots aren’t coming for your job,” Snyder says, “but it’s easy to make misleading assumptions about the kinds of jobs that are in danger of becoming obsolete.”
“Most jobs are more complex than [many people] realize,” said Hal Varian, Google’s chief economist.
David Autor, professor of economics at the Massachusetts Institute of Technology points out that education is a big determinant of how developing trends affect workers: “It’s a great time to be young and educated, but there’s no clear land of opportunity for adults who haven’t been to college.”
“When predicting future labor market outcomes, it is important to consider both sides of the supply-and-demand equation,” said Varian, “demographic trends that point to a substantial decrease in the supply of labor are potentially larger in magnitude.”
His research indicates that shrinkage of the labor supply due to demographic trends is 53% greater than shrinkage of demand for labor due to automation. That means, while relatively fewer jobs are available, there are a lot fewer workers available to do them. The result is the prospect of a continued labor shortage.
At the same time, Snyder reports that “[The] most popular discussion around technology focuses on factors that decrease demand for labor by replacing workers with machines.”
In other words, fears that robots will displace humans for existing jobs miss the point. Robots, instead, are taking over jobs for which there aren’t enough humans to do them.
Another effect is the fact that what people think of as “jobs” are actually made up of many “tasks,” and it’s tasks that get automated, not entire jobs. Some tasks are amenable to automation while others aren’t.
“Consider the job of a gardener,” Snyder suggests as an example. “Gardeners have to mow and water a lawn, prune rose bushes, rake leaves, eradicate pests, and perform a variety of other chores.”
Some of these tasks, like mowing and watering, can easily be automated. Pruning rose bushes, not so much!
Snyder points to news reports of a hotel in Nagasaki, Japan being forced to “fire” robot receptionists and room attendants that proved to be incompetent.
There’s a scene in the 1997 film The Fifth Element where a supporting character tries to converse with a robot bartender about another character. He says: “She’s so vulnerable – so human. Do you you know what I mean?” The robot shakes its head, “No.”
Sometimes people, even misanthropes, would prefer to interact with another human than with a drink-dispensing machine.
“Jobs,” Varian points out, “unlike repetitive tasks, tend not to disappear. In 1950, the U.S. Census Bureau listed 250 separate jobs. Since then, the only one to be completely eliminated is that of elevator operator.”
“Excessive automation at Tesla was a mistake,” founder Elon Muskmea culpa-ed last year “Humans are underrated.”
Another trend Snyder points out is that automation-ready jobs, such as assembly-line factory workers, have already largely disappeared from America. “The 10 most common occupations in the U.S.,” he says, “include such jobs as retail salespersons, nurses, waiters, and other service-focused work. Notably, traditional occupations, such as factory and other blue-collar work, no longer even make the list.
Again, robots are mainly taking over tasks that humans are not available to do.
The final trend that Snyder presents, is the stark fact that birthrates in developed nations are declining – in some cases precipitously. “The aging of the baby boom generation creates demand for service jobs,” Varian points out, “but leaves fewer workers actively contributing labor to the economy.”
Those “service jobs” are just the ones that require a human touch, so they’re much harder to automate successfully.
My Inexpert Opinion
I’ve been trying, not entirely successfully, to figure out what role robots will actually have vis-a-vis humans in the future. I think there will be a few macroscopic trends. And, the macroscopic trends should be the easiest to spot ‘cause they’re, well, macroscopic. That means bigger. So, there easier to see. See?
As early as 2010, I worked out one important difference between robots and humans that I expounded in my novel Vengeance is Mine! Specifically, humans have a wider view of the Universe and have more of an emotional stake in it.
“For example,” I had one of my main characters pontificate at a cocktail party, “that tall blonde over there is an archaeologist. She uses ROVs – remotely operated vehicles – to map underwater shipwreck sites. So, she cares about what she sees and finds. We program the ROVs with sophisticated navigational software that allows her to concentrate on what she’s looking at, rather than the details of piloting the vehicle, but she’s in constant communication with it because she cares what it does. It doesn’t.”
More recently, I got a clearer image of this relationship and it’s so obvious that we tend to overlook it. I certainly missed it for decades.
It hit me like a brick when I saw a video of an autonomous robot marine-trash collector. This device is a small autonomous surface vessel with a big “mouth” that glides around seeking out and gobbling up discarded water bottles, plastic bags, bits of styrofoam, and other unwanted jetsam clogging up waterways.
The first question that popped into my mind was “who’s going to own the thing?” I mean, somebody has to want it, then buy it, then put it to work. I’m sure it could be made to automatically regurgitate the junk it collects into trash bags that it drops off at some collection point, but some human or humans have to make sure the trash bags get collected and disposed of. Somebody has to ensure that the robot has a charging system to keep its batteries recharged. Somebody has to fix it when parts wear out, and somebody has to take responsibility if it becomes a navigation hazard. Should that happen, the Coast Guard is going to want to scoop it up and hand its bedraggled carcass to some human owner along with a citation.
So, on a very important level, the biggest thing robots need from humans is ownership. Humans own robots, not the other way around. Without a human owner, an orphan robot is a pile of junk left by the side of the road!
That said, I want to inject a note of caution for anyone considering her advice about being a rebel. There’s an old saying: “The nail that sticks up the most is the first to get hammered down.” It’s true in carpentry and in life. Being a rebel is lonely, dangerous, and is no guarantee of success, financial or otherwise.
I speak from experience, having broken every rule available for as long as I can remember. When I was a child in the 1950s, I wanted to grow up to be a beatnik. I’ve always felt most comfortable amongst bohemians. My wife once complained (while we were sitting in a muscle car stopped by the highway waiting for the cop to give me a speeding ticket) about my “always living on the edge.” And, yes, I’ve been thrown out of more than one bar.
On the other hand, I’ve lived a long and eventful life. Most of the items on my bucket list were checked off long ago.
As I expected, the book’s theme is best summed up by a line from the blurb on its dust jacket: “ … the most successful among us break the rules.”
The book description goes on to say, “Rebels have a bad reputation. We think of them as trouble-makers. outcasts, contrarians: those colleagues, friends, and family members who complicate seemingly straight-forward decisions, create chaos, and disagree when everyone else is in agreement. But in truth, rebels are also those among us who change the world for the better with their unconventional outlooks. Instead of clinging to what is safe and familiar, and falling back on routines and tradition, rebels defy the status quo. They are masters of innovation and reinvention, and they have a lot to teach us.”
Considering the third paragraph above, I hope she’s right!
The 283-page (including notes and index) volume summarizes Gino’s decade-long study of rebels at organizations around the world, from high-end boutiques in Italy’s fashion capital (Milan), to the world’s best restaurant (Three-Michelin-star-rated Osteria Francescana), to a thriving fast-food chain (Pal’s), and an award-winning computer animation studio (Pixar).
Francesca Gino is a behavioral scientist and professor at Harvard Business School. She is the Tandon Family Professor of Business Administration in the school’s Negotiation, Organizations & Markets Unit. No slouch professionally, she has been honored as one of the world’s top 40 business professors under 40 by Poets & Quants and one of the world’s 50 most influential management thinkers by Thinkers50.
Enough with the “In Praise Of” stuff, though. Let’s look inside the book. It’s divided into eight chapters, starting with “Napoleon and the Hoodie: The Paradox of Rebel Status,” and ending with “Blackbeard, ‘Flatness,’ and the 8 Principles of Rebel Leadership.” Gino then adds a “Conclusion” telling the story of Risotto Cacio e Pepe (a rice-in-Parmigiano-Reggiano dish invented by Chef Massimo Bottura), and an “Epilogue: Rebel Action” giving advice on releasing your inner rebel.
Stylistically, the narrative uses the classic “Harvard Case Study” approach. That is, it’s basically a pile of stories, each of which makes a point about how rebel leaders Gino has known approach their work. In summary, the take-home lesson is that those leaders encourage their employees to unleash their “inner rebel,” thereby unlocking creativity, enthusiasm, and productivity that more traditional management styles suppress.
The downside of this style is that it sometimes is difficult for the reader to get their brain around the points that Gino is making. Luckily, her narrative style is interesting, easy to follow and compelling. Like all well-written prose she keeps the reader wondering “What happens next?” The episodes she presents are invariably unusual and interesting themselves. She regularly brings in her own exploits and keeps, as much as possible, to first-person active voice.
That is unusual for academic writers, who find it all too easy to slip into a pedantic third-person, passive-voice best reserved for works intended as sleep aids.
To give you a feel for what reading an HCS-style volume is like, I’ll describe what it’s like to study Quantum Dynamics. While the differences outnumber the similarities, the overall “feel” is similar.
The first impression students get of QD is that the subject is entirely anti-intuitive. That is, before you can learn anything about QD, you have to discard any lingering intuition about how the Universe works. That’s probably easier for someone who never learned Classical Physics in the first place. Ideas like “you can’t be in two places at the same time” simply do not apply in the quantum world.
Basically, to learn QD, you have to start with a generous dose of “willing suspension of disbelief.” You do that by studying stories about experiments performed in the late nineteenth century that simply didn’t work. At that time, the best minds in Physics spent careers banging their heads into walls as Mommy Nature refused to return results that Classical Physics imagined she had to. Things like the Michelson-Moreley experiment (and many other then-state-of-the-art experiments) gave results at odds with Classical Physics. There were enough of these screwy results that physicists began to doubt that what they believed to be true, was actually how the Universe worked. After listening to enough of these stories, you begins to doubt your own intuition.
Then, you learn to trust the mathematics that will be your only guide in QD Wonderland.
Finally, you spend a couple of years learning about a new set of ideas based on Through the Looking Glass concepts that stand normal intuition on its head. Piling up stories about all these counter-intuitive ideas helps you build up a new intuition about what happens in the quantum world. About that time, you start feeling confident that this new intuition helps you predict what will happen next.
The HCS style of learning does something similar, although usually not as extreme. Reading story after story about what hasn’t and what has worked for others in the business world, you begin to develop an intuition for applying the new ideas. You gain confidence that, in any given situation, you can predict what happens next.
What happens next is that when you apply the methods Gino advocates, you start building a more diverse corporate culture that attracts and retains the kinds of folks that make your company a leader in its field.
There’s an old one-line joke:
“I want to be different – like everybody else.”
We can’t all be different because then there wouldn’t be any sameness to be different from, but we can all be rebels. We can all follow the
6 March 2019 – While surfing the Internet this morning, in a valiant effort to put off actually getting down to business grading that pile of lab reports that I should have graded a couple of days ago, I ran across this posting I wrote in 2013 for Packaging Digest.
Surprisingly, it still seems relevant today, and on a subject that I haven’t treated in this blog, yet. It being that I’m planning to devote most of next week to preparing my 2018 tax return, I decided to save some writing time by dusting it off and presenting it as this week’s posting to Tech Trends. I hope the folks at Packaging Digest won’t get their noses too far out of joint about my encroaching on their five-year-old copyright without asking permission.
By the way, this piece is way shorter than the usual Tech Trends essay because of the specifications for that Packaging Digest blog, which was entitled “New Metropolis” in homage to Fritz Lang’s 1927 feature film entitled Metropolis, which told the story of a futuristic mechanized culture and an anthropomorphic robot that a mad scientist creates to bring it down. The “New Metropolis” postings were specified to be approximately 500 words long, whereas Tech Trends postings are planned to be 1,000-1,500 words long.
Anyway, I hope you enjoy this little slice of recent history.
11 November 2013 – I thought it might be fun—and maybe even useful—to catalog the classifications of these things we call “robots.”
Let’s start with the word “robot.” The idea behind the word “robot” grows from the ancient concept of the golem. A golem was an artificial person created by people.
Frankly, the idea of a golem scared the bejeezus out of the ancients because the golem stands at the interface between living and non-living things. In our “enlightened” age, it still scares the bejeezus out of people!
If we restricted the field to golems—strictly humanoid robots, or androids—we wouldn’t have a lot to talk about, and practically nothing to do. The things haven’t proved particularly useful. So, I submit that we should expand the “robot” definition to include all kinds of human-made artificial critters.
This has, of course, already been done by everyone working in the field. The SCARA (selective compliance assembly robot arm) machines from companies like Kuka, and the delta robots from Adept Technologies clearly insist on this expanded definition. Mobile robots, such as the Roomba from iRobot push the boundary in another direction. Weird little things like the robotic insects and worms so popular with academics these days push in a third direction.
Considering the foregoing, the first observation is that the line between robot and non-robot is fuzzy. The old 50s-era dumb thermostats probably shouldn’t be considered robots, but a smart, computer-controlled house moving in the direction of the Jarvis character in the Ironman series probably should. Things in between are – in between. Let’s bite the bullet and admit we’re dealing with fuzzy-logic categories, and then move on.
Okay, so what are the main characteristics symptomatic of this fuzzy category “robot?”
First, it’s gotta be artificial. A cloned sheep is not a robot. Even designer germs are non-robots.
Second, it’s gotta be automated. A fly-by-wire fighter jet is not a robot. A drone linked at the hip to a human pilot is not a robot. A driverless car, on the other hand, is a robot. (Either that, or it’s a traffic accident waiting to happen.)
Third, it’s gotta interact with the environment. A general-purpose computer sitting there thinking computer-like thoughts is not a robot. A SCARA unit assembling a car is. I submit that an automated bill-paying system arguing through the telephone with my wife over how much to take out of her checkbook this month is a robot.
More problematic is a fourth direction—embedded systems, like automated houses—that beg to be admitted into the robotic fold. I vote for letting them in, along with artificial intelligence (AI) systems, like the robot bill paying systems my wife is so fond of arguing with.
Finally (maybe), it’s gotta be independent. To be a robot, the thing has to take basic instruction from a human, then go off on its onesies to do the deed. Ideally, you should be able to do something like say, “Go wash the car,” and it’ll run off as fast as its little robotic legs can carry it to wash the car. More chronistically, you should be able to program it to vacuum the living room at 4:00 a.m., then be able to wake up at 6:00 a.m. to a freshly vacuumed living room.
27 February 2019 – Some ideas are just so beautiful that we try to hang on to them even after failure after failure shows them to be unrealizable. Especially for the naive, these ideas hold such fascination that they persist long after cooler inspection consigns them to the dust bin of fantasy. This essay looks at two such ideas that display features in common: the ancient Greek myth of the flying horse, Pegasus, and the modern myth of the socialist state.
The ancient myth of the flying horse Pegasus is an obvious example. There’s no physical reason for such a creature to be impossible. Actual horses are built far too robustly to take to the air on their own power, but a delicately built version of Equus ferus fitted with properly functioning wings could certainly be able to fly.
That’s not the objection. Certainly, other robust land animals have developed flying forms. Birds, of course, developed from what our ancestors believed to be great lumbering theropod dinosaurs. Bats belong to the same mammalian class as horses, and they fly very well, indeed.
The objection to the existence of Pegasus-like creatures comes from evolutionary history. Specifically, the history of land-based vertebrates.
You see, all land-based vertebrates on Earth evolved from a limited number of ray-finned fish species. In fact, the number of fish species contributing DNA to land-vertebrate animals is likely limited to one.
All land vertebrates have exactly the same basic body form – with modifications – that developed from features common to ray-finned fishes. Basically, they have:
One spine that extends into a tail,
One head appended to the forward (opposite the tail) end of the spine,
Two front appendages that developed from the fish’s pectoral fins, and
Two rear appendages that developed from the fish’s pelvic fins.
Not all land-based vertebrates have all these features. Some originally extant features (like the human tail and cetacean rear legs) atrophied nearly to non-existence. But, the listed features are the only ones land-based vertebrates have ever had. Of course, I’m also including such creatures as birds and dolphins that developed from land-based critters as they moved on to other habitats or back to the sea.
The reason I suggest that all land vertebrates likely hail from one fish species is that no land vertebrates have ever had anal, caudal or adipose appendages, thus we all seem to have developed from some fish species that lacked these fins.
“Aha!” you say, “cetaceans like dolphins and whales have tail fins!”
“Nope,” I rebut. “Notice that cetacean tail flukes are fleshy appendages extending horizontally from the tip of the animals’ tails, not bony appendages oriented vertically like a fish’s caudal fins.”
Okay, so we’ve discovered what’s wrong with Pegasus that is not wrong with bats, pterodactyls, and birds. All the real land-based vertebrate forms have four limbs, whereas the fanciful Pegasus has six (four legs and two wings). Six-limbed Pegasus can’t exist because there aren’t any similar prior forms for it to have evolved from.
So, Pegasus is a beautiful idea that simply can’t be existent on Earth.
Well, you could have some sort of flying-horse-like creature that evolved on some other planet, then caught a convenient flying saucer to pop over to Earth, but they wouldn’t be native, and likely wouldn’t look at all earthlike.
So, what has all this got to do with socialism?
Well, as I’ve intimated, both are beautiful ideas that people are pretty fond of. Notwithstanding its popularity, Pegasus is not possible (as a native Earth creature) for a very good reason. Socialism is also a beautiful idea that people (at least great swaths of the population) are pretty fond of. Socialism is, however, also not possible as a stable form of society for a very good reason.
The reason socialism is not possible as a stable form of society goes back to our old friend, the Tragedy of the Commons. If you aren’t intimately familiar with this concept, follow the link to a well-written article by Margaret E. Banyan, Adjunct Assistant Professor in the Southwest Florida Center for Public and Social Policy at Florida Gulf Coast University, which explains the Tragedy, its origins, and ways that have been proposed to ameliorate its effects.
Anyway, economist Milton Friedman summarized the Tragedy of the Commons with the phrase: “When everybody owns something, nobody owns it … .”
The Tragedy of the Commons speaks directly to why true socialism is impossible, or at least not tenable as a stable, permanent system. Let’s start with what the word “socialism” actually means. According to Merriam-Webster, socialism is:
“any of various economic and political theories advocating collective or governmental ownership and administration of the means of production and distribution of goods.”
Other dictionaries largely agree, so we’ll work with this definition.
So, you can see where the Tragedy of the Commons connects to socialism. The beautiful idea relates to the word “collective.”
We know that human beings evolved as territorial animals, but we’d like to imagine a utopia where we’ve gotten past this primitive urge. Without territoriality, one could imagine a world where conflict would cease to exist. Folks would just get along because nobody’d say “Hey, that’s mine. Keep your mitts off!”
The problem with such a world is the Tragedy of the Commons as described by Friedman: if everybody owns the means of production, then nobody owns it.
There are two potential outcomes
Scenario 1 is the utter destruction of whatever resource is held in common as described at the start of Banyan’s essay.
Scenario 2 is what happened to the first recorded experiment with democracy in ancient Athens: somebody steps up to the plate and takes over management of the resource for everybody. For Athens it was a series of dictator kings ending with Alexander the Great. In effect, to save the resource from destruction, some individual moves in to “own” it.
In scenario 1, the resource is destroyed along with the socialist society that collectively owns it.Everyone either starves or leaves. Result: no more socialism.
In scenario 2, the resource is saved by being claimed by some individual. That individual sets up rules for how to apportion use of the resource, which is, in effect, no longer collectively owned. Result: dictatorship and, no more socialism.
Generally, all socialist states eventually degenerate into dictatorships via scenario 2. They invariably keep the designation “socialist,” but their governments are de facto authoritarian, not socialist. This is why I say socialism is a beautiful idea that is, in the long term, impossible. Socialist states can be created, but they very quickly come under authoritarian rule.
The Democracy Option
The Merriam-Webster definition admits of one more scenario, and that’s what we use in democratically governed nations, which are generally not considered socialist states: government ownership of some (but not all) resources.
If we have a democracy, there are all kinds of great things we can have governmentally owned, but not collectively owned. Things that everybody needs and everybody uses and everybody has to share, like roads, airspace, forests, electricity grids, and national parks. These are prime candidates for government ownership.
Things like wives, husbands, houses, and bicycles (note there’s been a big bicycle-sharing SNAFU recently reported in China) have historically been shown best to not be shared!
So, in a democracy, lots of stuff can be owned by the government, rather than by individuals or “everybody.”
A prime example is airspace. I don’t mean the air itself. I mean airspace! That is the space in the air over anyplace in the United States, or virtually the entire world. One might think it’s owned by everybody, but that just ain’t so.
You just try floating off at over 500 feet above ground level (AGL) in any type of aircraft and see where it gets you. Ya just can’t do it legally. You have to get permission from the Federal Government (in the form of a pilot’s license), which involves a great whacking pile of training, examinations, and even background checks. That’s because everybody does NOT own airspace above 500 feet AGL (and great, whacking swaths of the stuff lower down, too), the government does. You, personally, individually or collectively, don’t own a bit of it and have no rights to even be there without permission from its real owner, the Federal Government.
Another one is the Interstate Highway System. Try walking down Interstate 75 in, say, Florida. Assuming you survive long enough without getting punted off the roadway by a passing Chevy, you’ll soon find yourself explaining what the heck you think you’re doing to the nearest representative (spelled C-O-P) of whatever division of government takes ownership of that particular stretch of roadway. Unless you’ve got a really good excuse (e.g., “I gotta pee real bad!”) they’ll immediately escort you off the premises via the nearest exit ramp.
Ultimately, the only viable model of socialism is a limited one that combines individual ownership of some resources that are not shared, with government ownership of other resources that are shared. Democracy provides a mechanism for determining which is what.
13 February 2019 – Most mentally adult human beings recognize that binary thinking seldom proves useful in real-world situations. Our institutions, however, seem to be set up to promote binary thinking. And, that accounts for most of today’s societal dysfunction.
Lets start with what binary thinking really is. We’ve all heard disparaging remarks about “seeing things in black and white.” Simplistic thinking tends to categorize things into two starkly divided categories: good vs. evil, left vs. right, and, of course, dark vs. light. That latter category gives rise to the “black and white” metaphor.
“Binary thinking” refers to this simplistic strategy of dividing whatever we’re thinking about into two (hence the word “binary”) categories.
In many situations, binary thinking makes sense. For example, in team sports it makes sense to divide outcomes of contests into Team 1 wins and Team 2 loses.
Ultimately, every decision process degenerates into a selection between two choices. We do one and not the other. Even with multiple choices, we make the ultimate decision to pick one of the options to win after relegating all the others into the “loser” category.
If you think about it, however, those are always (or almost always) artificial situations. Mommy Nature seldom presents us with clear options. You aren’t presented with a clear choice between painting your house red or blue. House paint comes in a wide variety of hues that are blends of five primary colors: red, blue, yellow, black and white.
Even people aren’t really strictly divided into men and women. It’s a multidimensional mix of male-associated and female-associated traits that each blend from one extreme to another. The strict division into male and female is a dichotomy that we, as a society, impose on the world. Even existence or absence of a penis is a situation where there are numerous examples of intermediate forms.
The fact that we see binary choices everywhere is a fiction we impose on the Universe for our own convenience. That is, it’s easier and often more satisfying to create artificial dichotomies just so we don’t have to think about the middle.
But, the middle is where most of what goes on happens.
More than once I’ve depicted the expected distribution of folks holding views along the conservative/liberal spectrum by an image like that below, with those holding conservative views in red on the right and those with liberal views in blue to the left. That’s what I mean by my oft-repeated metaphor of the Red Team and Blue Team. It’s an extreme example of what statisticians call a “bimodal distribution.” That is a graph of numbers of examples plotted along a vertical axis with some linearly varying characteristic on a one-dimensional horizontal axis, that has two peaks.
The actual distribution we should expect from basic statistics is a single-mode distribution with a broad peak in the middle.
The two main political parties, however, act as if they imagine the distribution of political views to be bimodal, with one narrow peak ‘way over on the (liberal) left, and another narrow peak ‘way over on the (conservative) right. That picture leads to a binary view where you (the voter) are expected to be either on the left or the right.
With that view, campaigning becomes a two-team contest where the Democratic Party (Blue Team) hopes to attract voters over to their liberal view, making the blue peak larger than the red peak. The Republican Party, in turn, hopes to attract voters to their conservative agenda, making the red peak larger than the blue one.
What voters want, of course, is for the politicians to reflect the preferences they actually have. Since voters’ views can be expected to have a standard distribution with one (admittedly quite broad) peak more or less centered in the middle, Congress should be made up of folks with views falling in a broad peak more-or-less centered in the middle, with the vast majority advocating a moderate agenda. That would work out well because with that kind of distribution, compromise would be relatively easy to come by and laws would be passed that most people could find palatable, things would get done, and so forth.
Why don’t we have a situation like that? Why do we have this epidemic of binary thinking?
I believe that the answer comes from the two major parties becoming mesmerized in the 1980s by the principles of Marketing 101. The first thing they teach you in Marketing 101 is how to segment your customers. Translated into the one-dimensional left/right view so common in political thinking, that leads to imagining the bimodal distribution I’ve presented.
The actual information space characterizing voter preferences, however, is multidimensional. It’s not one single characteristic that can be represented on a one-dimensional spectrum. Every issue that comes up in political discourse represents a separate dimension, and any voter’s views appear as a point floating somewhere in that multidimensional space.
Nobody talks about this multidimensional space because it’s too complicated a picture to present in the evening news. Most political reporters don’t have the mathematical background to imagine it, let alone explain it. They’re lucky to get the basic one-dimensional spectrum picture across.
The second thing they teach you in Marketing 101 is product differentiation. Once you’ve got your customer base segmented, you pick a segment with the biggest population group, and say things to convince individuals in that group that your product (in this case, your candidate) matches the characteristics desired by that group, while the competition’s characteristics don’t.
If you think your chosen segment likes candidates wearing red T-shirts, you dress your candidate in a red T-shirt and point out that the competitor wears blue. In fact, you say things aimed at convincing voters that candidates wearing red T-shirts are somehow better (more likeable) than those awful bums wearing those ugly, nasty blue T-shirts. That way you try to attract voters to the imaginary red peak from the imaginary blue peak. If you’re successful, you win the election.
Of course, since voters actually expect your candidate to run the government after the election, what color T-shirt he or she wears is then immaterial. Since they were elected based on the color of their T-shirt, however, you end up with a legislature sitting around cheering for “Red!” or “Blue!” when voters want them to pass purple legislation.
An example of rabid binary thinking is the recent Democratic Party decision to have “zero tolerance” on race and gender issues. That thinking assumes that the blue peak on the left is filled with saintly heaven-bound creatures devoted to women’s and minorities’ rights, while the red peak on the right is full of mysogynistic racist bullies, and that there’s nobody in the middle.
That’s what “zero tolerance” means.
Liberals tried a similar stunt in the 1980s with “Political Correctness.” That fiasco worked for approximately zero time. It worked only until people realized that hardly anyone agreed with everything the PC folks liked. Since it was a binary choice – you were either politically correct or not – most folks opted for “not.” Very soon the jokes started, then folks started voting anti-PC.
What started out as a ploy by the left to bully everyone into joining their political base had the opposite effect. Most Americans don’t react well to bullying. They tend to turn on the bullies.
Instead of a cadre of Americans cowed into spouting politically correct rhetoric, we got a generation proudly claiming politically incorrect views.
You don’t hear much about political correctness, any more.
It’s quickly becoming clear that the binary thinking of the “zero tolerance” agenda will, like the PC cultural revolution, quickly lead to a “zero support” result.
Perhaps the Democratic Party should go back to school and learn Marketing 102. The first thing they teach you in Marketing 102 is “the customer is always right.”