Robots Revisited

Engineer with SCARA robots
Engineer using monitoring system software to check and control SCARA welding robots in a digital manufacturing operation. PopTika/Shutterstock

12 December 2018 – I was wondering what to talk about in this week’s blog posting, when an article bearing an interesting-sounding headline crossed my desk. The article, written by Simone Stolzoff of Quartz Media was published last Monday (12/3/2018) by the World Economic Forum (WEF) under the title “Here are the countries most likely to replace you with a robot.”

I generally look askance at organizations with grandiose names that include the word “World,” figuring that they likely are long on megalomania and short on substance. Further, this one lists the inimitable (thank God there’s only one!) Al Gore on its Board of Trustees.

On the other hand, David Rubenstein is also on the WEF board. Rubenstein usually seems to have his head screwed on straight, so that’s a positive sign for the organization. Therefore, I figured the article might be worth reading and should be judged on its own merits.

The main content is summarized in two bar graphs. The first lists the ratio of robots to thousands of manufacturing workers in various countries. The highest scores go to South Korea and Singapore. In fact, three of the top four are Far Eastern countries. The United States comes in around number seven.Figure 1

The second applies a correction to the graphed data to reorder the list by taking into account the countries’ relative wealth. There, the United States comes in dead last among the sixteen countries listed. East Asian countries account for all of the top five.

Figure 2The take-home-lesson from the article is conveniently stated in its final paragraph:

The upshot of all of this is relatively straightforward. When taking wages into account, Asian countries far outpace their western counterparts. If robots are the future of manufacturing, American and European countries have some catching up to do to stay competitive.

This article, of course, got me started thinking about automation and how manufacturers choose to adopt it. It’s a subject that was a major theme throughout my tenure as Chief Editor of Test & Measurement World and constituted the bulk of my work at Control Engineering.

The graphs certainly support the conclusions expressed in the cited paragraph’s first two sentences. The third sentence, however, is problematical.

That ultimate conclusion is based on accepting that “robots are the future of manufacturing.” Absolute assertions like that are always dangerous. Seldom is anything so all-or-nothing.

Predicting the future is epistemological suicide. Whenever I hear such bald-faced statements I recall Jim Morrison’s prescient statement: “The future’s uncertain and the end is always near.”

The line was prescient because a little over a year after the song’s release, Morrison was dead at age twenty seven, thereby fulfilling the slogan expressed by John Derek’s “Nick Romano” character in Nicholas Ray’s 1949 film Knock on Any Door: “Live fast, die young, and leave a good-looking corpse.”

Anyway, predictions like “robots are the future of manufacturing” are generally suspect because, in the chaotic Universe in which we live, the future is inherently unpredictable.

If you want to say something practically guaranteed to be wrong, predict the future!

I’d like to offer an alternate explanation for the data presented in the WEF graphs. It’s based on my belief that American Culture usually gets things right in the long run.

Yes, that’s the long run in which economist John Maynard Keynes pointed out that we’re all dead.

My belief in the ultimate vindication of American trends is based, not on national pride or jingoism, but on historical precedents. Countries that have bucked American trends often start out strong, but ultimately fade.

An obvious example is trendy Japanese management techniques based on Druckerian principles that were so much in vogue during the last half of the twentieth century. Folks imagined such techniques were going to drive the Japanese economy to pre-eminence in the world. Management consultants touted such principles as the future for corporate governance without noticing that while they were great for middle management, they were useless for strategic planning.

Japanese manufacturers beat the crap out of U.S. industry for a while, but eventually their economy fell into a prolonged recession characterized by economic stagnation and disinflation so severe that even negative interest rates couldn’t restart it.

Similar examples abound, which is why our little country with its relatively minuscule population (4.3% of the world’s) has by far the biggest GDP in the world. China, with more than four times the population, grosses less than a third of what we do.

So, if robotic adoption is the future of manufacturing, why are we so far behind? Assuming we actually do know what we’re doing, as past performance would suggest, the answer must be that the others are getting it wrong. Their faith in robotics as a driver of manufacturing productivity may be misplaced.

How could that be? What could be wrong with relying on technological advancement as the driver of productivity?

Manufacturing productivity is calculated on the basis of stuff produced (as measured by its total value in dollars) divided by the number of worker-hours needed to produce it. That should tell you something about what it takes to produce stuff. It’s all about human worker involvement.

Folks who think robots automatically increase productivity are fixating on the denominator in the productivity calculation. Making even the same amount of stuff while reducing the worker-hours needed to produce it should drive productivity up fast. That’s basic number theory. Yet, while manufacturing has been rapidly introducing all kinds of automation over the last few decades, productivity has stagnated.

We need to look for a different explanation.

It just might be that robotic adoption is another example of too much of a good thing. It might be that reliance on technology could prove to be less effective than something about the people making up the work force.

I’m suggesting that because I’ve been led to believe that work forces in the Far Eastern developing economies are less skillful, may have lower expectations, and are more tolerant of authoritarian governments.

Why would those traits make a difference? I’ll take them one at a time to suggest how they might.

The impression that Far Eastern populations are less skillful is not easy to demonstrate. Nobody who’s dealt with people of Asian extraction in either an educational or work-force setting would ever imagine they are at all deficient in either intelligence or motivation. On the other hand, as emerging or developing economies those countries are likely more dependent on workers newly recruited from rural, agrarian settings, who are likely less acclimated to manufacturing and industrial environments. On this basis, one may posit that the available workers may prove less skillful in a manufacturing setting.

It’s a weak argument, but it exists.

The idea that people making up Far-Eastern work forces have lower expectations than those in more developed economies is on firmer footing. Workers in Canada, the U.S. and Europe have very high expectations for how they should be treated. Wages are higher. Benefits are more generous. Upward mobility perceptions are ingrained in the cultures.

For developing economies, not so much.

Then, we come to tolerance of authoritarian regimes. Tolerance of authoritarianism goes hand-in-hand with tolerance for the usual authoritarian vices of graft, lack of personal freedom and social immobility. Only those believing populist political propaganda think differently (which is the danger of populism).

What’s all this got to do with manufacturing productivity?

Lack of skill, low expectations and patience under authority are not conducive to high productivity. People are productive when they work hard. People work hard when they are incentivized. They are incentivized to work when they believe that working harder will make their lives better. It’s not hard to grasp!

Installing robots in a plant won’t by itself lead human workers to believe that working harder will make their lives better. If anything, it’ll do the opposite. They’ll start worrying that their lives are about to take a turn for the worse.

Maybe that has something to do with why increased automation has failed to increase productivity.

Teaching News Consumption and Critical Thinking

Teaching media literacy
Teaching global media literacy to children should be started when they’re young. David Pereiras/Shutterstock

21 November 2018 – Regular readers of this blog know one of my favorite themes is critical thinking about news. Another of my favorite subjects is education. So, they won’t be surprised when I go on a rant about promoting teaching of critical news consumption habits to youngsters.

Apropos of this subject, last week the BBC launched a project entitled “Beyond Fake News,” which aims to “fight back” against fake news with a season of documentaries, special reports and features on the BBC’s international TV, radio and online networks.

In an article by Lucy Mapstone, Press Association Deputy Entertainment Editor for the Independent.ie digital network, entitled “BBC to ‘fight back’ against disinformation with Beyond Fake News project,” Jamie Angus, director of the BBC World Service Group, is quoted as saying: “Poor standards of global media literacy, and the ease with which malicious content can spread unchecked on digital platforms mean there’s never been a greater need for trustworthy news providers to take proactive steps.”

Angus’ quote opens up a Pandora’s box of issues. Among them is the basic question of what constitutes “trustworthy news providers” in the first place. Of course, this is an issue I’ve tackled in previous columns.

Another issue is what would be appropriate “proactive steps.” The BBC’s “Beyond Fake News” project is one example that seems pretty sound. (Sorry if this language seems a little stilted, but I’ve just finished watching a mid-twentieth-century British film, and those folks tended to talk that way. It’ll take me a little while to get over it.)

Another sort of “proactive step” is what I’ve been trying to do in this blog: provide advice about what steps to take to ensure that the news you consume is reliable.

A third is providing rebuttal of specific fake-news stories, which is what pundits on networks like CNN and MSNBC try (with limited success, I might say) to do every day.

The issue I hope to attack in this blog posting is the overarching concern in the first phrase of the Angus quote: “Poor standards of global media literacy, … .”

Global media literacy can only be improved the same way any lack of literacy can be improved, and that is through education.

Improving global media literacy begins with ensuring a high standard of media literacy among teachers. Teachers can only teach what they already know. Thus, a high standard of media literacy must start in college and university academic-education programs.

While I’ve spent decades teaching at the college level, so I have plenty of experience, I’m not actually qualified to teach other teachers how to teach. I’ve only taught technical subjects, and the education required to teach technical subjects centers on the technical subjects themselves. The art of teaching is (or at least was when I was at university) left to the student’s ability to mimic what their teachers did, informal mentoring by fellow teachers, and good-ol’ experience in the classroom. We were basically dumped into the classroom and left to sink or swim. Some swam, while others sank.

That said, I’m not going to try to lay out a program for teaching teachers how to teach media literacy. I’ll confine my remarks to making the case that it needs to be done.

Teaching media literacy to schoolchildren is especially urgent because the media-literacy projects I keep hearing about are aimed at adults “in the wild,” so to speak. That is, they’re aimed at adult citizens who have already completed their educations and are out earning livings, bringing up families, and participating in the political life of society (or ignoring it, as the case may be).

I submit that’s exactly the wrong audience to aim at.

Yes, it’s the audience that is most involved in media consumption. It’s the group of people who most need to be media literate. It is not, however, the group that we need to aim media-literacy education at.

We gotta get ‘em when they’re young!

Like any other academic subject, the best time to teach people good media-consumption habits is before they need to have them, not afterwards. There are multiple reasons for this.

First, children need to develop good habits before they’ve developed bad habits. It saves the dicey stage of having to unlearn old habits before you can learn new ones. Media literacy is no different. Neither is critical thinking.

Most of the so-called “fake news” appeals to folks who’ve never learned to think critically in the first place. They certainly try to think critically, but they’ve never been taught the skills. Of course, those critical-thinking skills are a prerequisite to building good media-consumption habits.

How can you get in the habit of thinking critically about news stories you consume unless you’ve been taught to think critically in the first place? I submit that the two skills are so intertwined that the best strategy is to teach them simultaneously.

And, it is most definitely a habit, like smoking, drinking alcohol, and being polite to pretty girls (or boys). It’s not something you can just tell somebody to do, then expect they’ll do it. They have to do it over and over again until it becomes habitual.

‘Nuff said.

Another reason to promote media literacy among the young is that’s when people are most amenable to instruction. Human children are pre-programmed to try to learn things. That’s what “play” is all about. Acquiring knowledge is not an unpleasant chore for children (unless misguided adults make it so). It’s their job! To ensure that children learn what they need to know to function as adults, Mommy Nature went out of her way to make learning fun, just as she did with everything else humans need to do to survive as a species.

Learning, having sex, taking care of babies are all things humans have to do to survive, so Mommy Nature puts systems in place to make them fun, and so drive humans to do them.

A third reason we need to teach media literacy to the young is that, like everything else, you’re better off learning it before you need to practice it. Nobody in their right mind teaches a novice how to drive a car by running them out in city traffic. High schools all have big, torturously laid out parking lots to give novice drivers a safe, challenging place to practice the basic skills of starting, stopping and turning before they have to perform those functions while dealing with fast-moving Chevys coming out of nowhere.

Similarly, you want students to practice deciphering written and verbal communications before asking them to parse a Donald-Trump speech!

The “Call to Action” for this editorial piece is thus, “Agitate for developing good media-consumption habits among schoolchildren along with the traditional Three Rs.” It starts with making the teaching of media literacy part of K-12 teacher education. It also includes teaching critical thinking skills and habits at the same time. Finally, it includes holding K-12 teachers responsible for inculcating good media-consumption habits in their students.

Yes, it’s important to try to bring the current crop of media-illiterate adults up to speed, but it’s more important to promote global media literacy among the young.

Computers Are Revolting!

Will Computers Revolt? cover
Charles Simon’s Will Computers Revolt? looks at the future of interactions between artificial intelligence and the human race.

14 November 2018 – I just couldn’t resist the double meaning allowed by the title for this blog posting. It’s all I could think of when reading the title of Charles Simon’s new book, Will Computers Revolt? Preparing for the Future of Artificial Intelligence.

On one hand, yes, computers are revolting. Yesterday my wife and I spent two hours trying to figure out how to activate our Netflix account on my new laptop. We ended up having to change the email address and password associated with the account. And, we aren’t done yet! The nice lady at Netflix sadly informed me that in thirty days, their automated system would insist that we re-log-into the account on both devices due to the change.

That’s revolting!

On the other hand, the uprising has already begun. Computers are revolting in the sense that they’re taking power to run our lives.

We used to buy stuff just by picking it off the shelf, then walking up to the check-out counter and handing over a few pieces of green paper. The only thing that held up the process was counting out the change.

Later, when credit cards first reared their ugly heads, we had to wait a few minutes for the salesperson to fill out a sales form, then run our credit cards through the machine. It was all manual. No computers involved. It took little time once you learned how to do it, and, more importantly, the process was pretty much the same everywhere and never changed, so once you learned it, you’d learned it “forever.”

Not no more! How much time do you, I, and everyone else waste navigating the multiple pages we have to walk through just to pay for anything with a credit or debit card today?

Even worse, every store has different software using different screens to ask different questions. So, we can’t develop a habitual routine for the process. It’s different every time!

Not long ago the banks issuing my debit-card accounts switched to those %^&^ things with the chips. I always forget to put the thing in the slot instead of swiping the card across the magnetic-stripe reader. When that happens we have to start the process all over, wasting even more time.

The computers have taken over, so now we have to do what they tell us to do.

Now we know who’ll be first against the wall when the revolution comes. It’s already here and the first against the wall is us!

Golem Literature in Perspective

But seriously folks, Simon’s book is the latest in a long tradition of works by thinkers fascinated by the idea that someone could create an artifice that would pass for a human. Perhaps the earliest, and certainly the most iconic, is the golem stories from Jewish folklore. I suspect (on no authority, whatsoever, but it does seem likely) that the idea of a golem appeared about the time when human sculptors started making statues in realistic human form. That was very early, indeed!

A golem is, for those who aren’t familiar with the term or willing to follow the link provided above to learn about it, an artificial creature fashioned by a human that is effectively what we call a “robot.” The folkloric golems were made of clay or (sometimes) wood because those were the best materials available at the time that the stories’ authors’ could have their artists work with. A well-known golem story is Carlo Collodi’s The Adventures of Pinocchio.

By the sixth century BCE, Greek sculptors had begun to produce lifelike statues. The myth of Pygmalion and Galatea appeared in a pseudo-historical work by Philostephanus Cyrenaeus in the third century BCE. Pygmalion was a sculptor who made a statue representing his ideal woman, then fell in love with it. Aphrodite granted his prayer for a wife exactly like the statue by bringing the statue to life. The wife’s name was Galatea.

The Talmud points out that Adam started out as a golem. Like Galatea, Adam was brought to life when the Hebrew God Yahweh gave him a soul.

These golem examples emphasize the idea that humans, no matter how holy or wise, cannot give their creations a soul. The best they can do is to create automatons.

Simon effectively begs to differ. He spends the first quarter of his text laying out the case that it is possible, and indeed inevitable, that automated control systems displaying artificial general intelligence (AGI) capable of thinking at or (eventually) well above human capacity will appear. He spends the next half of his text showing how such AGI systems could be created and making the case that they will eventually exhibit functionality indistinguishable from consciousness. He devotes the rest of his text to speculating about how we, as human beings, will likely interact with such hyperintelligent machines.

Spoiler Alert

Simon’s answer to the question posed by his title is a sort-of “yes.” He feels AGIs will inevitably displace humans as the most intelligent beings on our planet, but won’t exactly “revolt” at any point.

“The conclusion,” he says, “is that the paths of AGIs and humanity will diverge to such an extent that there will be no close relationship between humans and our silicon counterparts.”

There won’t be any violent conflict because robotic needs are sufficiently dissimilar to ours that there won’t be any competition for scarce resources, which is what leads to conflict between groups (including between species).

Robots, he posits, are unlikely to care enough about us to revolt. There will be no Terminator robots seeking to exterminate us because they won’t see us as enough of a threat to bother with. They’re more likely to view us much the way we view squirrels and birds: pleasant fixtures of the natural world.

They won’t, of course, tolerate any individual humans who make trouble for them the same way we wouldn’t tolerate a rabid coyote. But, otherwise, so what?

So, the !!!! What?

The main value of Simon’s book is not in its ultimate conclusion. That’s basically informed opinion. Rather, its value lies in the voluminous detail he provides in getting to that conclusion.

He spends the first quarter of his text detailing exactly what he means by AGI. What functions are needed to make it manifest? How will we know when it rears its head (ugly or not, as a matter of taste)? How will a conscious, self-aware AGI system act?

A critical point Simon makes in this section is the assertion that AGI will arise first in autonomous mobile robots. I thoroughly agree for pretty much the same reasons he puts forth.

I first started seriously speculating about machine intelligence back in the middle of the twentieth century. I never got too far – certainly not as far as Simon gets in this volume – but pretty much the first thing I actually did realize was that it was impossible to develop any kind of machine with any recognizable intelligence unless its main feature was having a mobile body.

Developing any AGI feature requires the machine to have a mobile body. It has to take responsibility not only for deciding how to move itself about in space, but figuring out why. Why would it, for example, rather be over there, rather than to just stay here? Note that biological intelligence arose in animals, not in plants!

Simultaneously with reading Simon’s book, I was re-reading Robert A. Heinlein’s 1966 novel The Moon is a Harsh Mistress, which is one of innumerable fiction works whose plot hangs on actions of a superintelligent sentient computer. I found it interesting to compare Heinlein’s early fictional account with Simon’s much more informed discussion.

Heinlein sidesteps the mobile-body requirement by making his AGI arise in a computer tasked with operating the entire infrastructure of the first permanent human colony on the Moon (more accurately in the Moon, since Heinlein’s troglodytes burrowed through caves and tunnels, coming up to the surface only reluctantly when circumstances forced them to). He also avoids trying to imagine the AGI’s inner workings, by glossing over with the 1950s technology he was most familiar with.

In his rather longish second section, Simon leads his reader through a thought experiment speculating about what components an AGI system would need to have for its intelligence to develop. What sorts of circuitry might be needed, and how might it be realized? This section might be fascinating for those wanting to develop hardware and software to support AGI. For those of us watching from our armchairs on the outside, though, not so much.

Altogether, Charles Simon’s Will Computers Revolt? is an important book that’s fairly easy to read (or, at least as easy as any book this technical can be) and accessible to a wide range of people interested in the future of robotics and artificial intelligence. It is not the last word on this fast-developing field by any means. It is, however, a starting point for the necessary debate over how we should view the subject. Do we have anything to fear? Do we need to think about any regulations? Is there anything to regulate and would any such regulations be effective?

Babies and Bath Water

A baby in bath water
Don’t throw the baby out with the bathwater. Switlana Symonenko/Shutterstock.com

31 October 2018 – An old catchphrase derived from Medieval German is “Don’t throw the baby out with the bathwater.” It expresses an important principle in systems engineering.

Systems engineering focuses on how to design, build, and manage complex systems. A system can consist of almost anything made up of multiple parts or elements. For example, an automobile internal combustion engine is a system consisting of pistons, valves, a crankshaft, etc. Complex systems, such as that internal combustion engine, are typically broken up into sub-systems, such as the ignition system, the fuel system, and so forth.

Obviously, the systems concept can be applied to almost everything, from microorganisms to the World economy. As another example, medical professionals divide the human body into eleven organ systems, which would each be sub-systems within the body, which is considered as a complex system, itself.

Most systems-engineering principles transfer seamlessly from one kind of system to another.

Perhaps the most best known example of a systems-engineering principle was popularized by Robin Williams in his Mork and Mindy TV series. The Used-Car rule, as Williams’ Mork character put it, quite simply states:

“If it works, don’t fix it!”

If you’re getting the idea that systems engineering principles are typically couched in phrases that sound pretty colloquial, you’re right. People have been dealing with systems for as long as there have been people, so most of what they discovered about how to deal with systems long ago became “common sense.”

Systems engineering coalesced into an interdisciplinary engineering field around the middle of the twentieth century. Simon Ramo is sometimes credited as the founder of modern systems engineering, although many engineers and engineering managers contributed to its development and formalization.

The Baby/Bathwater rule means (if there’s anybody out there still unsure of the concept) that when attempting to modify something big (such as, say, the NAFTA treaty), make sure you retain those elements you wish to keep while in the process of modifying those elements you want to change.

The idea is that most systems that are already in place more or less already work, indicating that there are more elements that are right than are wrong. Thus, it’ll be easier, simpler, and less complicated to fix what’s wrong than to violate another systems principle:

“Don’t reinvent the wheel.”

Sometimes, on the other hand, something is such an unholy mess that trying to pick out those elements that need to change from the parts you don’t wish to change is so difficult that it’s not worth the effort. At that point, you’re better off scrapping the whole thing (throwing the baby out with the bathwater) and starting over from scratch.

Several months ago, I noticed that a seam in the convertible top on my sports car had begun to split. I quickly figured out that the big brush roller at my neighborhood automated car wash was over stressing the more-than-a-decade-old fabric. Naturally, I stopped using that car wash, and started looking around for a hand-detailing shop that would be more gentle.

But, that still left me with a convertible top that had started to split. So, I started looking at my options for fixing the problem.

Considering the car’s advanced age, and that a number of little things were starting to fail, I first considered trading the whole car in for a newer model. That, of course, would violate the rule about not throwing the baby out with the bath water. I’d be discarding the whole car just because of a small flaw, which might be repaired.

Of course, I’d also be getting rid of a whole raft of potentially impending problems. Then, again, I might be taking on a pile of problems that I knew nothing about.

It turned out, however, that the best car-replacement option was unacceptable, so I started looking into replacing just the convertible top. That, too, turned out to be infeasible. Finally, I found an automotive upholstery specialist who described a patching scheme that would solve the immediate problem and likely last through the remaining life of the car. So, that’s what I did.

I’ve put you through listening to this whole story to illustrate the thought process behind applying the “don’t throw the baby out with the bathwater” rule.

Unfortunately, our current President, Donald Trump, seems to have never learned anything about systems engineering, or about babies and bathwater. He’s apparently enthralled with the idea that he can bully U.S. trading partners into giving him concessions when he negotiates with them one-on-one. That’s the gist of his love of bilateral trade agreements.

Apparently, he feels that if he gets into a multilateral trade negotiation, his go-to strategy of browbeating partners into giving in to him might not work. Multiple negotiating partners might get together and provide a united front against him.

In fact, that’s a reasonable assumption. He’s a sufficiently weak deal maker on his own that he’d have trouble standing up to a combination of, say, Mexico’s Nieto and Canada’s Trudeau banded together against him.

With that background, it’s not hard to understand why POTUS is looking at all U.S. treaties, which are mostly multilateral, and looking for any niddly thing wrong with them to use as an excuse to scrap the whole arrangement and start over. Obvious examples being the NAFTA treaty and the Iran Nuclear Accord.

Both of these treaties have been in place for some time, and have generally achieved the goals they were put in place to achieve. Howsoever, they’re not perfect, so POTUS is in the position of trying to “fix” them.

Since both these treaties are multilateral deals, to make even minor adjustments POTUS would have to enter multilateral negotiations with partners (such as Germany’s quantum-physicist-turned-politician, Angela Merkel) who would be unlikely to cow-tow to his bullying style. Robbed of his signature strategy, he’d rather scrap the whole thing and start all over, taking on partners one at a time in bilateral negotiations. So, that’s what he’s trying to do.

A more effective strategy would be to forget everything his ghostwriter put into his self-congratulatory “How-To” book The Art of the Deal, enumerate a list of what’s actually wrong with these documents, and tap into the cadre of veteran treaty negotiators that used to be available in the U.S. State Department to assemble a team of career diplomats capable of fixing what’s wrong without throwing the babies out with the bathwater.

But, that would violate his narcissistic world view. He’d have to admit that it wasn’t all about him, and acknowledge one of the first principles of project management (another discipline that he should have vast knowledge of, but apparently doesn’t):

Begin by making sure the needs of all stakeholders are built into any project plan.”

Reaping the Whirlwind

Tornado
Powerful Tornado destroying property, with lightning in the background. Solarseven/Shutterstock.com

24 October 2018 – “They sow the wind, and they shall reap the whirlwind” is a saying from The Holy Bible‘s Old Testament Book of Hosea. I’m certainly not a Bible scholar, but, having been paying attention for seven decades, I can attest to saying’s validity.

The equivalent Buddhist concept is karma, which is the motive force driving the Wheel of Birth and Death. It is also wrapped up with samsara, which is epitomized by the saying: “What goes around comes around.”

Actions have consequences.

If you smoke a pack of Camels a day, you’re gonna get sick!

By now, you should have gotten the idea that “reaping the whirlwind” is a common theme among the world’s religions and philosophies. You’ve got to be pretty stone headed to have missed it.

Apparently the current President of the United States (POTUS), Donald J. Trump, has been stone headed enough to miss it.

POTUS is well known for trying to duck consequences of his actions. For example, during his 2016 Presidential Election campaign, he went out of his way to capitalize on Wikileaks‘ publication of emails stolen from Hillary Clinton‘s private email server. That indiscretion and his attempt to cover it up by firing then-FBI-Director James Comey grew into a Special Counsel Investigation, which now threatens to unmask all the nefarious activities he’s engaged in throughout his entire life.

Of course, Hillary’s unsanctioned use of that private email server while serving as Secretary of State is what opened her up to the email hacking in the first place! That error came back to bite her in the backside by giving the Russians something to hack. They then forwarded that junk to Wikileaks, who eventually made it public, arguably costing her the 2016 Presidential election.

Or, maybe it was her standing up for her philandering husband, or maybe lingering suspicions surrounding the pair’s involvement in the Whitewater scandal. Whatever the reason(s), Hillary, too, reaped the whirlwind.

In his turn, Russian President Vladimir Putin sowed the wind by tasking operatives to do the hacking of Hillary’s email server. Now he’s reaping the whirlwind in the form of a laundry list sanctions by western governments and Special Counsel Investigation indictments against the operatives he sent to do the hacking.

Again, POTUS showed his stone-headedness about the Bible verse by cuddling up to nearly every autocrat in the world: Vlad Putin, Kim Jong Un, Xi Jinping, … . The list goes on. Sensing waves of love emanating from Washington, those idiots have become ever more extravagant in their misbehavior.

The latest example of an authoritarian regime rubbing POTUS’ nose in filth is the apparent murder and dismemberment of Saudi Arabian journalist Jamal Khashoggi when he briefly entered the Saudi embassy in Turkey on personal business.

The most popular theory of the crime lays blame at the feet of Mohammad Bin Salman Al Saud (MBS), Crown Prince of Saudi Arabia and the country’s de facto ruler. Unwilling to point his finger at another would-be autocrat, POTUS is promoting a Saudi cover-up attempt suggesting the murder was done by some unnamed “rogue agents.”

Actually, that theory deserves some consideration. The idea that MBS was emboldened (spelled S-T-U-P-I-D) enough to have ordered Kashoggi’s assassination in such a ham-fisted way strains credulity. We should consider the possibility that ultra-conservative Wahabist factions within the Saudi government, who see MBS’ reforms as a threat to their historical patronage from the oil-rich Saudi monarchy, might have created the incident to embarrass MBS.

No matter what the true story is, the blow back is a whirlwind!

MBS has gone out of his way to promote himself as a business-friendly reformer. This reputation has persisted despite repeated instances of continued repression in the country he controls.

The whirlwind, however, is threatening MBS’ and the Saudi monarchy’s standing in the international community. Especially, international bankers, led by JP Morgan Chase’s Jamie Dimon, and a host of Silicon Valley tech companies are running for the exits from Saudi Arabia’s three-day Financial Investment Initiative conference that was scheduled to start Tuesday (23 October 2018).

That is a major embarrassment and will likely derail MBS’ efforts to modernize Saudi Arabia’s economy away from dependence on oil revenue.

It appears that these high-powered executives are rethinking the wisdom of dealing with the authoritarian Saudi regime. They’ve decided not to sow the wind by dealing with the Saudis because they don’t want to reap the whirlwind likely to result!

Update

Since this manuscript was drafted it’s become clear that we’ll never get the full story about the Kashoggi incident. Both regimes involved (Turkey and Saudi Arabia) are authoritarians with no incentive to be honest about this story. While Saudi Arabia seems to make a pretense of press freedom, this incident shows their true colors (i.e, color them repressive). Turkey hasn’t given even a passing nod to press freedom for years. It’s like two rival foxes telling the dog about a hen house break in.

On the “dog” side, we’re stuck with a POTUS who attacks press freedom on a daily basis. So, who’s going to ferret out the truth? Maybe the Brits or the French, but not the U.S. Executive Branch!

Doing Business with Bad Guys

Threatened with a gun
Authoritarians make dangerous business partners. rubikphoto/Shutterstock

3 October 2018 – Parents generally try to drum into their childrens’ heads a simple maxim: “People judge you by the company you keep.

Children (and we’re all children, no matter how mature and sophisticated we pretend to be) just as generally find it hard to follow that maxim. We all screw it up once in a while by succumbing to the temptation of some perceived advantage to be had by dealing with some unsavory character.

Large corporations and national governments are at least as likely to succumb to the prospect of making a fast buck or signing some treaty with peers who don’t entertain the same values we have (or at least pretend to have). Governments, especially, have a tough time in dealing with what I’ll call “Bad Guys.”

Let’s face it, better than half the nations of the world are run by people we wouldn’t want in our living rooms!

I’m specifically thinking about totalitarian regimes like the People’s Republic of China (PRC).

‘Way back in the last century, Mao Tse-tung (or Mao Zedong, depending on how you choose to mis-spell the anglicization of his name) clearly placed China on the “Anti-American” team, espousing a virulent form of Marxism and descending into the totalitarian authoritarianism Marxist regimes are so prone to. This situation continued from the PRC’s founding in 1949 through 1972, when notoriously authoritarian-friendly U.S. President Richard Nixon toured China in an effort to start a trade relationship between the two countries.

Greedy U.S. corporations quickly started falling all over themselves in an effort to gain access to China’s enormous potential market. Mesmerized by the statistics of more than a billion people spread out over China’s enormous land mass, they ignored the fact that those people were struggling in a subsistence-agriculture economy that had collapsed under decades of mis-managment by Mao’s authoritarian regime.

What they hoped those generally dirt-poor peasants were going to buy from them I never could figure out.

Unfortunately, years later I found myself embedded in the management of one of those starry-eyed multinational corporations that was hoping to take advantage of the developing Chinese electronics industry. Fresh off our success launching Test & Measurement Europe, they wanted to launch a new publication called Test & Measurement China. Recalling the then-recent calamity ending the Tiananmen Square protests of 1989, I pulled a Nancy Reagan and just said “No.”

I pointed out that the PRC was still run by a totalitarian, authoritarian regime, and that you just couldn’t trust those guys. You never knew when they were going to decide to sacrifice you on the altar of internal politics.

Today, American corporations are seeing the mistakes they made in pursuit of Chinese business, which like Robert Southey’s chickens, are coming home to roost. In 2015, Chinese Premier Li Keqiang announced the “Made in China 2025” plan to make China the World’s technology leader. It quickly became apparent that Mao’s current successor, Xi Jinping intends to achieve his goals by building on technology pilfered from western companies who’d naively partnered with Chinese firms.

Now, their only protector is another authoritarian-friendly president, Donald Trump. Remember it was Trump who, following his ill-advised summit with North Korean strongman Kim Jong Un, got caught on video enviously saying: “He speaks, and his people sit up at attention. I want my people to do the same.

So, now these corporations have to look to an American would-be dictator for protection from an entrenched Chinese dictator. No wonder they find themselves screwed, blued, and tattooed!

Governments are not immune to the PRC’s siren song, either. Pundits are pointing out that the PRC’s vaunted “One Belt, One Road” initiative is likely an example of “debt-trap diplomacy.”

Debt-trap diplomacy is a strategy similar to organized crime’s loan-shark operations. An unscrupulous cash-rich organization, the loan shark, offers funds to a cash-strapped individual, such as an ambitious entrepreneur, in a deal that seems too good to be true. It’s NOT true because the deal comes in the form of a loan at terms that nearly guarantee that the debtor will default. The shark then offers to write off the debt in exchange for the debtor’s participation in some unsavory scheme, such as money laundering.

In the debt-trap diplomacy version, the PRC stands in the place of the loan shark while some emerging-economy nation, such as, say, Malaysia, accepts the unsupportable debt. In the PRC/ Malaysia case, the unsavory scheme is helping support China’s imperial ambitions in the western Pacific.

Earlier this month, Malaysia wisely backed out of the deal.

It’s not just the post-Maoist PRC that makes a dangerous place for western corporations to do business, authoritarians all over the world treat people like Heart’s Barracuda. They suck you in with mesmerizing bright and shiny promises, then leave you twisting in the wind.

Yes, I’ve piled up a whole mess of mixed metaphors here, but I’m trying to drive home a point!

Another example of the traps business people can get into by trying to deal with authoritarians is afforded by Danske Bank’s Estonia branch and their dealings with Vladimir Putin‘s Russian kleptocracy. Danske Bank is a Danish financial institution with a pan-European footprint and global ambitions. Recent release of a Danske Bank internal report produced by the Danish law firm Bruun & Hjejle says that the Estonia branch engaged in “dodgy dealings” with numerous corrupt Russian officials. Basically, the bank set up a scheme to launder money stolen from Russian tax receipts by organized criminals.

The scandal broke in Russia in June of 2007 when dozens of police officers raided the Moscow offices of Hermitage Global, an activist fund focused on global emerging markets. A coverup by Kremlin authorities resulted in the death (while in a Russian prison) of Sergei Leonidovich Magnitsky, a Russian tax accountant who specialized in anti-corruption activities.

Magnitsky’s case became an international cause célèbre. The U.S. Congress and President Barack Obama enacted the Magnitsky Act at the end of 2012, barring, among others, those Russian officials believed to be involved in Magnitsky’s death from entering the United States or using its banking system.

Apparently, the purpose of the infamous Trump Tower meeting of June 9, 2016 was, on the Russian side, an effort to secure repeal of the Magnitsky Act should then-candidate Trump win the election. The Russians dangled release of stolen emails incriminating Trump-rival Hillary Clinton as bait. This activity started the whole Mueller Investigation, which has so far resulted in dozens of indictments for federal crimes, and at least eight guilty pleas or convictions.

The latest business strung up in this mega-scandal was the whole corrupt banking system of Cyprus, whose laundering of Russian oligarchs’ money amounted to over $20B.

The moral of this story is: Don’t do business with bad guys, no matter how good they make the deal look.

News vs. Opinion

News reporting
Journalists report reopening of Lindt cafe in Sydney after ISIS siege, 20 March 2015. M. W. Hunt / Shutterstock.com

26 September 2018 – This is NOT a news story!

Last week I spent a lot of space yammering on about how to tell fake news from the real stuff. I made a big point about how real news organizations don’t allow editorializing in news stories. I included an example of a New York Times op-ed (opinion editorial) that was decidedly not a news story.

On the other hand, last night I growled at my TV screen when I heard a CNN commentator say that she’d been taught that journalists must have opinions and should voice them. I growled because her statement could be construed to mean something anathema to journalistic ethics. I’m afraid way too many TV journalists may be confused about this issue. Certainly too many news consumers are confused!

It’s easy to get confused. For example, I got myself in trouble some years ago in a discussion over dinner and drinks with Andy Wilson, Founding Editor at Vision Systems Design, over a related issue that is less important to political-news reporting, but is crucial for business-to-business (B2B) journalism: the role of advertising in editorial considerations.

Andy insisted upon strictly ignoring advertiser needs when making editorial decisions. I advocated a more nuanced approach. I said that ignoring advertiser needs and desires would lead to cutting oneself off from our most important source of technology-trends information.

I’m not going to delve too deeply into that subject because it has only peripheral significance for this blog posting. The overlap with news reporting is that both activities involve dealing with biased sources.

My disagreement with Andy arose from my veteran-project-manager’s sensitivity to all stakeholders in any activity. In the B2B case, editors have several ways of enforcing journalistic discipline without biting the hand that feeds us. I was especially sensitive to the issue because I specialized in case studies, which necessarily discuss technology embodied in commercial products. Basically, I insisted on limiting (to one) actual product mentions in each story, and suppressing any claims that the mentioned product was the only possible way to access the embodied technology. In essence, I policed the stories I wrote or edited to avoid the “buy our stuff” messages that advertisers love and that send chills down Andy’s (and my) spine.

In the news-media realm, journalists need to police their writing for “buy our ideas” messages in news stories. “Just the facts, ma’am” needs to be the goal for news. Expressing editorial opinions in news stories is dangerous. That’s when the lines between fake news and real news get blurry.

Those lines need to be sharp to help news consumers judge the … information … they’re being fed.

Perhaps “information” isn’t exactly the right word.

It might be best to start with the distinction between “information” and “data.”

The distinction is not always clear in a general setting. It is, however, stark in the world of science, which is where I originally came from.

What comes into our brains from the outside world is “data.” It’s facts and figures. Contrary to what many people imagine, “data” is devoid of meaning. Scientists often refer to it as “raw data” to emphasize this characteristic.

There is nothing actionable in raw data. The observation that “the sky is blue” can’t even tell you if the sky was blue yesterday, or how likely it is to be blue tomorrow. It just says: “the sky is blue.” End of story.

Turning “data” into “information” involves combining it with other, related data, and making inferences about or deductions from patterns perceivable in the resulting superset. The process is called “interpretation,” and it’s the second step in turning data into knowledge. It’s what our brains are good for.

So, does this mean that news reporters are to be empty-headed recorders of raw facts?

Not by a long shot!

The CNN commentator’s point was that reporters are far from empty headed. While learning their trade, they develop ways to, for example, tell when some data source is lying to them.

In the hard sciences it’s called “instrumental error,” and experimental scientists (as I was) spend careers detecting and eliminating it.

Similarly, what a reporter does when faced with a lying source is the hard part of news reporting. Do you say, “This source is unreliable” and suppress what they told you? Do you report what they said along with a comment that they’re a lying so-and-so who shouldn’t be believed? Certainly, you try to find another source who tells you something you can rely on. But, what if the second source is lying, too?

???

That’s why we news consumers have to rely on professionals who actually care about the truth for our news.

On the other hand, nobody goes to news outlets for just raw data. We want something we can use. We want something actionable.

Most of us have neither the time nor the tools to interpret all the drivel we’re faced with. Even if we happen to be able to work it out for ourselves, we could always use some help, even if just to corroborate our own conclusions.

Who better to help us interpret the data (news) and glean actionable opinions from it than those journalists who’ve been spending their careers listening to the crap newsmakers want to feed us?

That’s where commentators come in. The difference between an editor and a reporter is that the editor has enough background and experience to interpret the raw data and turn it into actionable information.

That is: opinion you can use to make a decision. Like, maybe, who to vote for.

People with the chops to interpret news and make comments about it are called “commentators.”

When I was looking to hire what we used to call a “Technical Editor” for Test & Measurement World, I specifically looked for someone with a technical degree and experience developing the technology I wanted that person to cover. So, for example, when I was looking for someone to cover advances in testing of electronics for the telecommunications industry, I went looking for a telecommunications engineer. I figured that if I found one who could also tell a story, I could train them to be a journalist.

That brings us back to the CNN commentator who thought she should have opinions.

The relevant word here is “commentator.”

She’s not just a reporter. To be a commentator, she supposedly has access to the best available “data” and enough background to skillfully interpret it. So, what she was saying is true for a commentator rather than just a reporter.

Howsomever, ya can’t just give a conclusion without showing how the facts lead to it.

Let’s look at how I assemble a post for this blog as an example of what you should look for in a reliable op-ed piece.

Obviously, I look for a subject about which I feel I have something worthwhile to say. Specifically, I look for what I call the “take-home lesson” on which I base every piece of blather I write.

The “take-home lesson” is the basic point I want my reader to remember. Come Thursday next you won’t remember every word or even every point I make in this column. You’re (hopefully) going to remember some concept from it that you should be able to summarize in one or two sentences. It may be the “call to action” my eighth-grade English teacher, Miss Langley, told me to look for in every well-written editorial. Or, it could be just some idea, such as “Racism sucks,” that I want my reader to believe.

Whatever it is, it’s what I want the reader to “take home” from my writing. All the rest is just stuff I use to convince the reader to buy into the “take-home lesson.”

Usually, I start off by providing the reader with some context in which to fit what I have to say. It’s there so that the reader and I start off on the same page. This is important to help the reader fit what I have to say into the knowledge pattern of their own mind. (I hope that makes sense!)

After setting the context, I provide the facts that I have available from which to draw my conclusion. The conclusion will be, of course, the “take-home lesson.”

I can’t be sure that my readers will have the facts already, so I provide links to what I consider reliable outside sources. Sometimes I provide primary sources, but more often they’re secondary sources.

Primary sources for, say, a biographical sketch of Thomas Edison would be diary pages or financial records, which few readers would have immediate access to.

A secondary source might be a well-researched entry on, say, the Biography.com website, which the reader can easily get access to and which can, in turn, provide links to useful primary sources.

In any case, I try to provide sources for each piece of data on which I base my conclusion.

Then, I’ll outline the logical path that leads from the data pattern to my conclusion. While the reader should have no need to dispute the “data,” he or she should look very carefully to see whether my logic makes sense. Does it lead inevitably from the data to my conclusion?

Finally, I’ll clearly state the conclusion.

In general, every consumer of ideas should look for this same pattern in every information source they use.

Noble Whitefoot or Lying Blackfoot?

Fake News feed
How do you know when the news you’re reading is fake? Rawpixel/Shutterstock

19 September 2018 – Back in the mid-1970s, we RPI astrophysics graduate students had this great office at the very top of the Science Building at Rensselaer Polytechnic Institute.The construction was an exact duplicate of the top floor of an airport control tower, with the huge outward-sloping windows and the wrap-around balcony.

Every morning we’d gather ’round the desk of our compatriot Ron Held, builder of stellar-interior computer models extraordinaire, to hear him read “what fits” from the days issue of The New York Times. Ron had noticed that when taken out of context much of what is written in newspapers sounds hilarious. He had a deadpan way of reading this stuff out loud that only emphasized the effect. He’d modified the Times‘ slogan, “All the news that’s fit to print” into “All the news that fits.”

Whenever I hear unmitigated garbage coming out of supposed news outlets, I think of Ron’s “All the news that fits.”

These days, I’m on a kick about fake news and how to spot it. It isn’t easy because it’s become so pervasive that it becomes almost believable. This goes along with my lifelong philosophical study that I call: “How do we know what we think we know?”

Early on I developed what I call my “BS detector.” It’s a mental alarm bell that goes off whenever someone tries to convince me of something that’s unbelievable.

It’s not perfect. It’s been wrong on a whole lot of occasions.

For example, back in the early 1970s somebody told me about something called “superconductivity,” where certain materials, when cooled to near absolute zero, lost all electrical resistance. My first reaction, based on the proposition that if something sounds too good to be true, it’s not, was: “Yeah, and if you believe that I’ve got this bridge between Manhattan and Brooklyn to sell you.”

After seeing a few experiments and practical demonstrations, my BS detector stopped going off and I was able to listen to explanations about Cooper Pairs, and electron-phonon interactions and became convinced. I eventually learned that nearly everything involving quantum theory sounds like BS until you get to understand it.

Another time I bought into the notion that Interferon would develop into a useful AIDS treatment. Being a monogamous heterosexual, I didn’t personally worry about AIDS, but I had many friends who did, so I cared. I cared enough to pay attention, and watch as the treatment just didn’t develop.

Most of the time, however, my BS detector works quite well, thank you, and I’ve spent a lot of time trying to divine what sets it off, and what a person can do to separate the grains of truth from the BS pile.

Consider Your Source(s)

There’s and old saying: “Figures don’t lie, but liars can figure.”

First off, never believe anybody whom you’ve caught lying to you in the past. For example, Donald Trump has been caught lying numerous times in the past. I know. I’ve seen video of him mouthing words that I’ve known at the time were incorrect. It’s happened so often that my BS detector goes off so loudly whenever he opens his mouth that the noise drowns out what he’s trying to say.

I had the same problem with Bill Clinton when he was President (he seems to have gotten better, now, but I’m still wary).

Nixon was pretty bad, too.

There’s a lot of noise these days about “reliable sources.” But, who’s a reliable source? You can’t take their word for it. It’s like the old riddle of the lying blackfoot indian and the truthful whitefoot.

Unfortunately, in the real world nobody always lies or always tells the truth, even Donald Trump. So, they can’t be unmasked by calling on the riddle’s answer. If you’re unfamiliar with the riddle, look it up.

The best thing to do is try to figure out what the source’s game is. Everyone in the communications business is selling something. It’s up to you to figure out what they’re selling and whether you want to buy it.

News is information collected on a global scale, and it’s done by news organizations. The New York Times is one such organization. Another is The Wall Street Journal, which is a subsidiary of Dow Jones & Company, a division of News Corp.

So, basically, what a legitimate news organization is selling is information. If you get a whiff that they’re selling anything else, like racism, or anarchy, or Donald Trump, they aren’t a real news organization.

The structure of a news organization is:

Publisher: An individual or group of individuals generally responsible for running the business. The publisher manages the Circulation, Advertising, Production, and Editorial departments. The Publisher’s job is to try to sell what the news organization has to sell (that is, information) at a profit.

Circulation: A group of individuals responsible for recruiting subscribers and promoting sales of individal copies of the news organization’s output.

Advertising: A group of individuals under the direct supervision of the Publisher who are responsible for selling advertising space to individuals and businesses who want to present their own messages to people who consume the news organization’s output.

Production: A group of individuals responsible for packaging the information gathered by the Editorial department into physical form and distributing it to consumers.

Editorial: A group of trained journalists under a Chief Editor responsible for gathering and qualifying information the news organization will distribute to consumers.

Notice the italics on “and qualifying” in the entry on the Editorial Department. Every publication has their self-selected editorial focus. For a publication like The Wall Street journal, whose editorial focus is business news, every story has to fit that editorial focus. A story that, say, affects how readers select stocks to buy or sell is in their editorial focus. A story that doesn’t isn’t.

A story about why Donald Trump lies doesn’t belong in The Wall Street Journal. It belongs in Psychology Today.

That’s why editors and reporters have to be “trained journalists.” You can’t hire just anybody off the street, slap a fedora on their head and call them a “reporter.” That never even worked in the movies. Journalism is a profession and journalists require training. They’re also expected behave in a manner consistent with journalistic ethics.

One of those ethical principles is that you don’t “editorialize” in news stories. That means you gather facts and report those facts. You don’t distort facts to fit your personal opinions. You for sure don’t make up facts out of thin air just ’cause you’d like it to be so.

Taking the example of The Wall Street Journal again, a reporter handed some fact doesn’t know what the reader will do with that fact. Some will do some things and others will do something else. If a reporter makes something up, and readers make business decisions based on that fiction, bad results will happen. Business people don’t like that. They’d stop buying copies of the newspaper. Circulation would collapse. Advertisers would abandon it.

Soon, no more The Wall Street Journal.

It’s the Chief Editor’s job to make sure reporters seek out information useful to their readers, don’t editorialize, and check their facts to make sure nobody’s been lying to them. Thus, the Chief Editor is the main gatekeeper that consumers rely on to keep out fake news.

That, by the way, is the fatal flaw in social media as a news source: there’s no Chief Editor.

One final note: A lot of people today buy into the cynical belief that this vision of journalism is naive. As a veteran journalist I can tell you that it’s NOT. If you think real journalism doesn’t work this way, you’re living in a Trumpian alternate reality.

Bang your head on the nearest wall hoping to knock some sense into it!

So, for you, the news consumer, to guard against fake news, your first job is to figure out if your source’s Chief Editor is trustworthy.

Unfortunately, it’s very seldom that most people get to know a news source’s Chief Editor well enough to know whether to trust him or her.

Comparison Shopping for Ideas

That’s why you don’t take the word of just one source. You comparison shop for ideas the same way you do for groceries, or anything else. You go to different stores. You check their prices. You look at sell-by dates. You sniff the air for stale aromas. You do the same thing in the marketplace for ideas.

If you check three-to-five news outlets, and they present the same facts, you gotta figure they’re all reporting the facts that were given to them. If somebody’s out of whack compared to the others, it’s a bad sign.

Of course, you have to consider the sources they use as well. Remember that everyone providing information to a news organization has something to sell. You need to make sure they’re not providing BS to the news organization to hype sales of their particular product. That’s why a credible news organization will always tell you who their sources are for every fact.

For example, a recent story in the news (from several outlets) was that The New York Times published an opinion-editorial piece (NOT a news story, by the way) saying very unflattering things about how President Trump was managing the Executive Branch. A very big red flag went up because the op-ed was signed “Anonymous.”

That red flag was minimized by the paper’s Chief Editor, Dean Baquet, assuring us all that he, at least, knew who the author was, and that it was a very high official who knew what they were talking about. If we believe him, we figure we’re likely dealing with a credible source.

Our confidence in the op-ed’s credibility was also bolstered by the fact that the piece included a lot of information that was available from other sources that corroborated it. The only new piece of information, that there was a faction within the White House that was acting to thwart the President’s worst impulses, fitted seamlessly with the verifiable information. So, we tend to believe it.

As another example, during the 1990s I was watching the scientific literature for reports of climate-change research results. I’d already seen signs that there was a problem with this particular branch of science. It had become too political, and the politicians were selling policies based on questionable results. I noticed that studies generally were reporting inconclusive results, but each article ended with a concluding paragraph warning of the dangers of human-induced climate change that did not fit seamlessly with the research results reported in the article. So, I tended to disbelieve the final conclusions.

Does It Make Sense to You?

This is where we all stumble when ferreting out fake news. If you’re pre-programmed to accept some idea, it won’t set off your BS detector. It won’t disagree with the other sources you’ve chosen to trust. It will seem reasonable to you. It will make sense, whether it’s right or wrong.

That’s a situation we all have to face, and the only antidote is to do an experiment.

Experiments are great! They’re our way of asking Mommy Nature to set us on the right path. And, if we ask often enough, and carefully enough, she will.

That’s how I learned the reality of superconductivity against my inbred bias. That’s how I learned how naive my faith in interferon had been.

With those cautions, let’s look at how we know what we think we know.

It starts with our parents. We start out truly impressed by our parents’ physical and intellectual capabilities. After all, they can walk! They can talk! They can (in some cases) do arithmetic!

Parents have a natural drive to stuff everything they know into our little heads, and we have a natural drive to suck it all in. It’s only later that we notice that not everyone agrees with our parents, and they aren’t necessarily the smartest beings on the planet. That’s when comparison shopping for ideas begins. Eventually, we develop our own ideas that fit our personalities.

Along the way, Mommy Nature has provided a guiding hand to either confirm or discredit our developing ideas. If we’re not pathological, we end up with a more or less reliable feel for what makes sense.

For example, almost everybody has a deep-seated conviction that torturing pets is wrong. We’ve all done bad things to pets, usually unintentionally, and found it made us feel sad. We don’t want to do it again.

So, if somebody advocates perpetrating cruelty to animals, most of us recoil. We’d have to be given a darn good reason to do it. Like, being told “If you don’t shoot that squirrel, there’ll be no dinner tonight.”

That would do it.

Our brains are full up with all kinds of ideas like that. When somebody presents us with a novel idea, or a report of something they suggest is a fact, our first line of defense is whether it makes sense to us.

If it’s unbelievable, it’s probably not true.

It could still be true, since a lot of unbelievable stuff actually happens, but it’s probably not. We can note it pending confirmation by other sources or some kind of experimental result (like looking to see the actual bloody mess).

But, we don’t buy it out of hand.

Nobody Gets It Completely Right

As Dr. Who (Tom Baker) once said: “To err is computer. To forgive is fine.”

The real naive attitude about news, which I used to hear a lot fifty or sixty years ago is, “If it’s in print, it’s gotta be true.”

Reporters, editors and publishers are human. They make mistakes. And, catching those mistakes follows the 95:5 rule.That is, you’ll expend 95% of your effort to catch the last 5% of the errors. It’s also called “The Law of Diminishing Returns,” and it’s how we know to quit obsessing.

The way this works for the news business is that news output involves a lot of information. I’m not going to waste space here estimating the amount of information (in bits) in an average newspaper, but let’s just say it’s 1.3 s**tloads!

It’s a lot. Getting it all right, then getting it all corroborated, then getting it all fact checked (a different, and tougher, job than just corroboration), then putting it into words that convey that information to readers, is an enormous task, especially when a deadline is involved. It’s why the classic image of a journalist is some frazzled guy wearing a fedora pushed back on his head, suitcoat off, sleeves rolled up and tie loosened, maniacally tapping at a typewriter keyboard.

So, don’t expect everything you read to be right (or even spelled right).

The easiest things to get right are basic facts, the Who, What, Where, and When.

How many deaths due to Hurricane Maria on Puerto Rico? Estimates have run from 16 to nearly 3,000 depending on who’s doing the estimating, what axes they have to grind, and how they made the estimate. Nobody was ever able to collect the bodies in one place to count them. It’s unlikely that they ever found all the bodies to collect for the count!

Those are the first four Ws of news reporting. The fifth one, Why, is by far the hardest ’cause you gotta get inside someone’s head.

So, the last part of judging whether news is fake is recognizing that nobody gets it entirely right. Just because you see it in print doesn’t make it fact. And, just because somebody got it wrong, doesn’t make them a liar.

They could get one thing wrong, and most everything else right. In fact, they could get 5 things wrong, and 95 things right!

What you look for is folks who make the effort to try to get things right. If somebody is really trying, they’ll make some mistakes, but they’ll own up to them. They’ll say something like: “Yesterday we told you that there were 16 deaths, but today we have better information and the death toll is up to 2,975.”

Anybody who won’t admit they’re ever wrong is a liar, and whatever they say is most likely fake news.

Social Media and The Front Page

Walter Burns
Promotional photograph of Osgood Perkins as Walter Burns in the 1928 Broadway production of The Front Page

12 September 2018 – The Front Page was an hilarious one-set stage play supposedly taking place over a single night in the dingy press room of Chicago’s Criminal Courts Building overlooking the gallows behind the Cook County Jail. I’m not going to synopsize the plot because the Wikipedia entry cited above does such an excellent job it’s better for you to follow the link and read it yourself.

First performed in 1928, the play has been revived several times and suffered countless adaptations to other media. It’s notable for the fact that the main character, Hildy Johnson, originally written as a male part, is even more interesting as a female. That says something important, but I don’t know what.

By the way, I insist that the very best adaptation is Howard Hawks’ 1940 tour de force film entitled His Girl Friday starring Rosalind Russell as Hildy Johnson, and Cary Grant as the other main character Walter Burns. Burns is Johnson’s boss and ex-husband who uses various subterfuges to prevent Hildy from quitting her job and marrying an insurance salesman.

That’s not what I want to talk about today, though. What’s important for this blog posting is part of the play’s backstory. It’s important because it can help provide context for the entire social media industry, which is becoming so important for American society right now.

In that backstory, a critical supporting character is one Earl Williams, who’s a mousey little man convicted of murdering a policeman and sentenced to be executed the following morning right outside the press-room window. During the course of the play, it comes to light that Williams, confused by listening to a soapbox demagogue speaking in a public park, accidentally shot the policeman and was subsequently railroaded in court by a corrupt sheriff who wanted to use his execution to help get out the black(!?) vote for his re-election campaign.

What publicly executing a confused communist sympathizer has to do with motivating black voters I still fail to understand, but it makes as much sense as anything else the sheriff says or does.

This plot has so many twists and turns paralleling issues still resonating today that it’s rediculous. That’s a large part of the play’s fun!

Anyway, what I want you to focus on right now is the subtle point that Williams was confused by listening to a soapbox demagogue.

Soapbox demagogues were a fixture in pre-Internet political discourse. The U.S. Constitution’s First Amendment explicitly gives private citizens the right to peaceably assemble in public places. For example, during the late 1960s a typical summer Sunday afternoon anywhere in any public park in North America or Europe would see a gathering of anywhere from 10 to 10,000 hippies for an impromptu “Love In,” or “Be In,” or “Happening.” With no structure or set agenda folks would gather to do whatever seemed like a good idea at the time. My surrealist novelette Lilith describes a gathering of angels, said to be “the hippies of the supernatural world,” that was patterned after a typical Hippie Love In.

Similarly, a soapbox demagogue had the right to commandeer a picnic table, bandstand, or discarded soapbox to place himself (at the time they were overwhelmingly male) above the crowd of passersby that he hoped would listen to his discourse on whatever he wanted to talk about.

In the case of Earl Williams’ demagogue, the speech was about “production for use.” The feeble-minded Williams applied that idea to the policeman’s service weapon, with predictable results.

Fast forward to the twenty-first century.

I haven’t been hanging around local parks on Sunday afternoons for a long time, so I don’t know if soapbox demagogues are still out there. I doubt that they are because it’s easier and cheaper to log onto a social-media platform, such as Facebook, to shoot your mouth off before a much larger international audience.

I have browsed social media, however, and see the same sort of drivel that used to spew out of the mouths of soapbox demagogues back in the day.

The point I’m trying to make is that there’s really nothing novel about social media. Being a platform for anyone to say anything to anyone is the same as last-century soapboxes being available for anyone who thinks they have something to say. It’s a prominent right guaranteed in the Bill of Rights. In fact, it’s important enough to be guaranteed in the very first of th Bill’s amendments to the U.S. Constitution.

What is not included, however, is a proscription against anyone ignoring the HECK out of soapbox demagogues! They have the right to talk, but we have the right to not listen.

Back in the day, almost everybody passed by soapbox demagogues without a second glance. We all knew they climbed their soapboxes because it was the only venue they had to voice their opinions.

Preachers had pulpits in front of congregations, so you knew they had something to say that people wanted to hear. News reporters had newspapers people bought because they contained news stories that people wanted to read. Scholars had academic journals that other scholars subscribed to because they printed results of important research. Fiction writers had published novels folks read because they found them entertaining.

The list goes on.

Soapbox demagogues, however, had to stand on an impromptu platform because they didn’t have anything to say worth hearing. The only ones who stopped to listen were those, like the unemployed Earl Williams, who had nothing better to do.

The idea of pretending that social media is any more of a legitimate venue for ideas is just goofy.

Social media are not legitimate media for the exchange of ideas simply because anybody is able to say anything on them, just like a soapbox in a park. Like a soapbox in a park, most of what is said on social media isn’t worth hearing. It’s there because the barrier to entry is essentially nil. That’s why so many purveyors of extremist and divisive rhetoric gravitate to social media platforms. Legitimate media won’t carry them.

Legitimate media organizations have barriers to the entry of lousy ideas. For example, I subscribe to The Economist because of their former Editor in Chief, John Micklethwait, who impressed me as an excellent arbiter of ideas (despite having a weird last name). I was very pleased when he transferred over to Bloomberg News, which I consider the only televised outlet for globally significant news. The Wall Street Journals business focus forces Editor-in-Chief Matt Murray into a “just the facts, ma’am” stance because every newsworthy event creates both winners and losers in the business community, so content bias is a non-starter.

The common thread among these legitimate-media sources is existance of an organizational structure focused on maintaining content quality. There are knowlegeable gatekeepers (called “editors“) charged with keeping out bad ideas.

So, when Donald Trump, for example, shows a preference for social media (in his case, Twitter) and an abhorrence of traditional news outlets, he’s telling us his ideas aren’t worth listening to. Legitimate media outlets disparage his views, so he’s forced to use the twenty-first century equivalent of a public-park soapbox: social media.

On social media, he can say anything to anybody because there’s nobody to tell him, “That’s a stupid thing to say. Don’t say it!”

Thinking Through Facial Recognition

Makeup
There are lots of reasons a person might wear makeup that could baffle facial recognition technology. Steven J Hensley / Shutterstock.com

5 September 2018 – A lot of us grew up reading stories by Robert A. Heinlein, who was one of the most Libertarian-leaning of twentieth-century science-fiction writers. When contemplating then-future surveillance technology (which he imagined would be even more intrusive than it actually is today) he wrote (in his 1982 novel Friday): “… there is a moral obligation on each free person to fight back wherever possible … ”

The surveillance technology Heinlein expected to become the most ubiquitous, pervasive, intrusive and literally in-your-face was facial recognition. Back in 1982, he didn’t seem to quite get the picture (pun intended) of how automation, artificial intelligence, and facial recognition could combine to become Big Brother’s all-seeing eyes. Now that we’re at the cusp of that technology being deployed, it’s time for just-us-folks to think about how we should react to it.

An alarm should be set off by an article filed by NBC News journalists Tom Costello and Ethan Sacks on 23 August reporting: “New facial recognition tech catches first impostor at D.C. airport.” Apparently, a Congolese national tried to enter the United States on a flight from Sao Paulo, Brazil through Washington Dulles International Airport on a French passport, and was instantly unmasked by a new facial-recognition system that quickly figured out that his face did not match that of the real holder of the French passport. Authorities figured out he was a Congolese national by finding his real identification papers hidden in his shoe. Why he wanted into the United States; why he tried to use a French passport; and why he was coming in from Brazil are all questions unanswered in the article. The article was about this whiz-bang technology that worked so well on the third day it was deployed.

What makes the story significant is that this time it all worked in real time. Previous applications of facial recognition have worked only after the fact.

The reason this article should set off alarm bells is not that the technology unmasked some jamoke trying to sneak into the country for some unknown, but probably nefarious, purpose. On balance, that was almost certainly (from our viewpoint) a good thing. The alarms should sound, however, to wake us up to think about how we really want to react to this kind of ubiquitous surveillance being deployed.

Do we really want Big Brother watching us?

Joan Quigley, former Assemblywoman from Jersey City, NJ, where she was Majority Conference Leader, chair of Homeland Security, and served on Budget, Health and Economic Development Committees, wrote an op-ed piece appearing in The Jersey Journal on 20 August entitled: “Facial recognition the latest alarm bell for privacy advocates.” In it she points out that “it’s not only crime some don’t want others to see.”

There’s a whole lot of what each of us does that we want to keep private. While we consider it perfectly innocent, it’s just nobody else’s business.

It’s why the stalls in public bathrooms have doors.

People generally object to living in a fishbowl.

So, ubiquitous deployment of facial recognition technology brings with it some good things, and some that are not so good. That argues for a national public debate aimed at developing a consensus regarding where, when and how facial recognition technology should be used.

Framing the Debate

To start with, recognize that facial recognition is already ubiquitous and natural. It’s why Mommy Nature goes through all kinds of machinations to make our faces more-or-less unique. One of the first things babies learn is how to recognize Mom’s face. How could the cave guys have coordinated their hunting parties if nobody could tell Fred from Manny?

Facial recognition technology just extends our natural talent for recognizing our friends by sight to its use by automated systems.

A white paper entitled Top 4 Modern Use Cases of Biometric Technology crossed my desk recently. It was published by security-software firm iTrue. Their stated purpose is to “take biometric technology to the next level by securing all biometric data onto their blockchain platform.”

Because the white paper is clearly a marketing piece, and it is unsigned by the actual author, I can’t really vouch for the accuracy of its conclusions. For example, the four use cases listed in the paper are likely just the four main applications they envision for their technology. They are, however, a reasonable starting point for our public discussion.

The four use cases cited are:

  1. Border control and airport security
  2. Company payroll and attendance management
  3. Financial data and identity protection
  4. Physical or logical access solutions

This is probably not an exhaustive list, but offhand I can’t think of any important items left off. So, I’ll pretend like it’s a really good, complete list. It may be. It may not be. That should be part of the discussion.

The first item on the list is exactly what the D.C. airport news story was all about, so enough said. That horse has been beaten to death.

About the second item, the white paper says: “Organizations are beginning to invest in biometric technologies to manage employee ID and attendance, since individuals are always carrying their fingerprints, eyes, and faces with them, and these items cannot be lost, stolen, or forgotten.”

In my Mother’s unforgettable New England accent, we say, “Eye-yuh!”

There is, however, one major flaw in the reasoning behind relying on facial recognition. It’s illustrated by the image above. Since time immemorial, folks have worn makeup that could potentially give facial recognition systems ginky fits. They do it for all kinds of innocent reasons. If you’re going to make being able to pass facial recognition tests a prerequisite for doing your job, expect all sorts of pushback.

For example, over the years I’ve known many, many women who wouldn’t want to be seen in public without makeup. What are you going to do? Make your workplace a makeup-free zone? That’ll go over big!

On to number three. How’s your average cosplay enthusiast going to react to not being able to use their credit or debit card to buy gas on their way to an event because the bank’s facial recognition system can’t see through their alien-creature makeup?

Transgender person
Portrait of young transgender person wearing pink wig. Ranta Images/Shutterstock

Even more seriously, look at the image on the right. This is a transgender person wearing a wig. Really cute isn’t he/she? Do you think your facial recognition software could tell the difference between him and his sister? Does your ACH vendor want to risk trampling his/her rights?

Ooops!

When we come to the fourth item on the list, suppose a Saudi Arabian woman wants to get into her house? Are you going to require her to remove her burka to get through her front door? What about her right to religious freedom? Or, will this become another situation where she can’t function as a human being without being accompanied by a male guardian? We’re already on thin ice when she wants to enter the country through an airport!

I’ve already half formed my own ideas about these issues. I look forward to participating in the national debate.

Heinlein would, of course, delight in every example where facial recognition could be foiled. In Friday, he gleefully pointed out ” … what takes three hours to put on will come off in fifteen minutes of soap and hot water.”