Don’t Forget About Covid-19 June 17, 2021
Posted by Peter Varhol in travel, Uncategorized.Tags: European Union, ovid-19, travel
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I haven’t written about Covid-19 for a while, at least in part because the news, at least in the US, has been trending positive. Of course that’s a good thing, but it shouldn’t hide the fact that both America and the world still have a long way to go.
In fact, it is a sobering fact that worldwide, more people have died of Covid-19 already in 2021 than in the watershed year of 2020, where there seemed to be so much suffering and death.
I am hoping to be able to begin the technical conference circuit in Europe once again this fall. And while I see excited headlines of how the European Union is opening up even to unvaccinated travelers this summer, the devil is in the details, and the details are sparse and contradictory.
In particular, it appears that individual countries and even municipalities within those countries can impose their own rules, and the implications can change almost on a day-by-day basis. If you go to another country, the rules may change yet again before you come home. If that happens, you may find yourself quarantining, or worse.
I still mask, and take extra precautions when traveling. But I like to know the rules in my destination before getting on the plane. And to not have those rules change while I’m on the plane.
But let’s not forget that the pandemic is not over, not by a long run. Navigating the world today is going to be much trickier than a year ago.
On Inattentional Blindness and Popular Culture June 6, 2021
Posted by Peter Varhol in Education, Technology and Culture.Tags: Inattentional blindness, the invisible gorilla
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I recently saw a cartoon that updated a Mary Tyler Moore meme into 2021 (thanks, @sjvn), in which she threw a mask into the air, rather than her hat. This caused me to go back and review several of the MTM intro songs, including the lengthier one that was never part of the TV show. As I listened (and especially watched) these, I came to the realization that MTM could well have been my older sister, forty-some years ago. I especially felt Mary’s pensive look as she’s driving down the highway in her Mustang (the models change, but the Mustang is forever). How will you make it on your own? must have defined a generation of women coming of age in the 1970s. The details with my sister differ, but the theme, I think, is correct.
I broached this topic to my sister this evening, and she readily agreed. “I really enjoyed watching the show in the early 1970s.”
My sister would have been somewhat younger than the real life MTM (to be fair, perhaps 15 years), but still in the age range where women first started graduating college in numbers, and trying to find their place in life. It was especially challenging in our own culture, where women largely married at 18 and took care of the household for the steelworker. She was the first of our extended family to go to college.
But she had more to say. “I really disliked it when Mary kept getting screwed over (figuratively) by all the men in the newsroom and her life.”
I, several years younger and male, never picked up on that dynamic that was so readily apparent to her that she recalled it decades later. In addition to trailblazing among the first generations of professional women (she was trained as a teacher, ultimately for the last 15 years of her career an accomplished data analyst), her eyes were wide open to the inequities that many of us never saw.
And this brings me to inattentional blindness. The best example of this is The Invisible Gorilla, a book published in 2010, co-authored by Christopher Chabris and Daniel Simons. They designed an experiment where subjects had to keep track of passing around a basketball, only to have a person dressed in a gorilla costume walk across the court. A full 50 percent of the subjects did not see the gorilla.
So there is plenty that we don’t see in life. And often the only way we see it is to talk to other people, candidly, about their own experiences. Give it a try.
Driverless Cars Are Decades Away, If At All May 31, 2021
Posted by Peter Varhol in aviation, Machine Learning, Technology and Culture.Tags: autonomous vehicles, driverless cars, Tesla
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I am not a fan of Elon Musk. While at one level I appreciate his audaciousness, which seems to enable him to accomplish impossible goals through sheer force of will, the arrogance through which that force is delivered tends to cheapen it for me. It is perhaps fortunate that he cares not one whit about what I think.
Nevertheless, one area that we disagree on starkly is the self-driving car. Musk recently released a new version of Autopilot for Tesla, which he is referring to as Vision. He believes that Vision will enable Tesla to achieve full driverless experiences within two years.
Um, no. While Autopilot and Vision might seem a bit like magic, they have serious limitations. And the complexity inherent in fully self-driving cars is far more enormous than we have tackled to date. We tend to liken it to aircraft autopilots, which are charged with mostly maintaining straight and level flight on a given course. Modern autopilots can also successfully land a plane, but that is a well-understood and relatively simple maneuver.
Equating self-driving cars to an autopilot is a bad analogy. Cars travel in three dimensions, with unexpected obstacles and often poor weather. Aircraft have multiple pilots that can take over immediately in case of unexpected events. These pilots are also paying attention to the flight information, rather than sleeping or playing a game.
Effectively, the only way to have one fully self-driving car is to make every car on the highway self-driving. You are not going to stop manual drivers from pulling out in front of you, or cutting you off, or driving more slowly than your self-driving car wants to go. So every single car has to be under positive control. And there may well need to be the equivalent of a staffed control tower to make sure traffic flows smoothly.
So Musk and Tesla will continue releasing incremental upgrades, always claiming that the ultimate breakthrough is only a couple of years away. In reality, it won’t happen during my lifetime.
Education Should Make Us Uncomfortable May 3, 2021
Posted by Peter Varhol in Education, travel.Tags: 1619 Project, critical race theory
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I value education more than almost anything else in life. It is the mechanism by which we grow as individuals, and become better people and citizens. There are few higher purposes in life.
In the seventh grade, I was required to memorize Lincoln’s Gettysburg Address. I did so, but I didn’t know what it meant. It was only subsequent education that I understood just what every single word in the speech said. Today, 50 years later, I can still recite it verbatim, and tell you a powerful story of the meaning behind it.
I am reading stuff today referring to critical race theory, and the 1619 Project, and about how various states are passing laws against teaching such controversial topics.
I don’t quite get what critical race theory and the 1619 Project are all about, but I can tell you one thing. If they make you uncomfortable, you should learn about them.
I was made comfortable in my education, of history, civics, social studies, and current events in my public school years. In retrospect, some of the approaches to learning these topics then are laughable to me today. I became uncomfortable when I learned that we sent Japanese immigrants to concentration camps, and that we more or less massacred most native Americans through the early 1900s, and much more. And worse, that we vilified and murdered workers who were seeking a decent pay and work hours in the 1900s.
So my understanding of my country became more nuanced. I still think the United States has the best system and greatest democracy ever, while recognizing that there is substantial room for improvement. That’s what ongoing education buys you – an appreciation of what you have, coupled by a desire to make it better.
Most people don’t go that route. Instead, they like narratives that make Americans the unabashed good guys. Well, guess what? We weren’t, and we aren’t.
That doesn’t make us evil; it makes us human. Like people everywhere, we do the best we can. I have had the opportunity to meet and talk to people in many different countries, on their home turf. In many cases (Spain with Franco, Ukraine over the past decade, Serbs in the late 1990s, Swedes in World War II), their national histories contain ugly periods. Yet the people I talk to strive to make the future better. Mykola, in Ukraine, was a Chernobyl baby, born within the restricted zone, and told me that he snuck out to participate in the massive government protests of 2012. “I supported my extended family and couldn’t get into trouble,” he told me. “But I needed to be there.”
That’s what good, ordinary people do when confronted with their national history – they work to make things better. If we know and appreciate our history, we can too.
Our COVID Messaging Continues to Be Awful May 1, 2021
Posted by Peter Varhol in Uncategorized.Tags: CDC, COVID
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This morning, I received a call from a distraught friend. She was on her morning constitutional in a Boston suburb when she was accosted and harassed by two separate women. For wearing a mask.
Yes, that’s right. Both yelled at her that masks were not longer required outdoors, and that she shouldn’t be wearing one.
Well, first, that’s not true. What is true is that the Centers for Disease Control has issued a recommendation to the effect that fully vaccinated individuals can choose not to wear a mask outdoors (my friend is vaccinated, but still chooses to wear a mask, as do I). However dubious that recommendation, neither Massachusetts nor my home state of New Hampshire have lifted their outdoor mask mandates. Those are the mandates that have the force of law, not a recommendation by the CDC.
This brings me to my fundamental point. Our national and state governments continue to do a criminally poor job of communicating facts about COVID, testing, and vaccination. For the last year, mixed messages have emerged from different sources on just about every aspect of the pandemic, leaving honest people lost and confused about just what to believe. It certainly happened under the Trump administration, and it continues under Biden. Folks, if you want society to survive this, get your messages clear, simple, and consistent now.
I have a secondary point too. When messages are mixed and contradictory, people will choose the ones most convenient for their purposes. That means that someone can say that you don’t have to wear masks outdoors, and be misleading rather than lying. And, once again, our government is letting this happen.
Yelling at people on the street is something that I have never seen happen in New England, where civility is bred of coolness toward our neighbors. This kind of emotion is rare in this part of the country.
I told my friend that the next time she is accosted and harassed, she should tell them to chill out and direct them to the legal pot shop down the street.
On Deepfakes and Geography April 27, 2021
Posted by Peter Varhol in Machine Learning, Technology and Culture.Tags: deepfakes, geography
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When I was in the sixth grade, my science teacher sat me down with a book of overlapping aerial images of terrain, and handed me a pair of stereoscopic glasses. “I want you to draw topographical maps of these terrains,” he said. I took to the task assiduously, and in a few weeks had over a dozen hand-drawn topographical maps of well-known terrains. Of course, they were likely pretty inaccurate, as I was working with only my eyesight to add quantitative information to my estimates of depth and slope.
But they weren’t fake, by any means. They were the product of careful observation of the photos, and drawing of the representations. Now we have this thing called deepfakes, where we are able to display highly realistic geographical information and images that have been faked.
It turns out that people aren’t the only raw material for deepfakes. Maps and satellite images can also be faked. Your first thought may be “why?” I know mine was. But the more interesting question may well be who would bother to produce them? Consider these scenarios:
Well, let’s say there is a secret military installation, somewhere in the mountains. We can use deepfakes to hide it entirely in perfectly realistic images shown to the public or to adversaries. Likewise, we can put a fake base somewhere and use its images for similar purposes. Who is to know, unless they try to physically visit.
Let’s say we have a natural disaster, a destructive hurricane or earthquake. For PR or political purposes, we may want to show far less damage than actually occurred. Geographical deepfakes give us the ability to do so.
In both cases, governments can control access to the physical spaces and overhead airspace, so the images can reasonably be presented as ground truth. Except that they’re not. Instead, they are carefully crafted messages, communicating only what their creators want known.
These seem like relatively small transgressions in the grand scheme of things. I’m not at all a conspiracy theorist, so I doubt that such activities can be carried out on a grand scale. We can’t keep people out of, for example, Los Angeles if there is a major earthquake.
But geographical deepfakes take us one step closer into what people are calling the “post-truth” era. There is the saying that “you are entitled to your opinion, but not your facts.” Well, with deepfakes, perhaps you are, if you prepare and present them well enough. To me, that is a frightening proposition.
A Path to AI Explainability April 23, 2021
Posted by Peter Varhol in Machine Learning, Technology and Culture.Tags: AI, explainable artificial intelligence, Pepper
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I mentioned a while ago that I once met Pepper, the Softbank robot that responds to tactile stimulation. This article notes that Pepper can now introspect, that is, work through his “thought” processes aloud as he performs his given activities. I find that fascinating, in that what Pepper is really doing explainable AI, which I have been writing about recently.
The result is that Pepper can not only carry out verbal instructions, but also describe what he is doing in the process. I don’t really understand how to code this, but I do appreciate the result.
Explainable AI is the ability of an AI system to “describe” how it arrived at a particular result, given the input data. It actually consists of three separate parts – transparency, interpretability, and explainability. Transparancy means that we need to be able to look into the algorithms to clearly discern how they are processing input data. Explainability means that we might want to support queries into our results, or to get detailed explanations into more specific phases of the processing.
Further, it appears that Pepper, through talking out his instructions (I really dislike using human pronouns here, but it’s convenient) is able to identify contradictions or inconsistencies that prevent him from completing the activity. That frees Pepper to ask for additional instructions.
That’s an innovative and cool example of explainability, and extends to the ability of the AI to ask questions if the data are ambiguous or incomplete. We need more applications like this.
On Delegating Responsibilities for Work April 22, 2021
Posted by Peter Varhol in Uncategorized.Tags: Work
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I worked for a large commercial software company earlier in my career. As was true of many organizations at the time, we were matrixed between functional departments (Dev, QA, marketing, etc.) and cross-functional projects. At one point, my team was assigned a new member from a functional department. While I was senior to her, I didn’t supervise her.
I had some struggles with her at first, we communicated well and she turned out to be an outstanding contributor. The interesting thing here was that she didn’t want to be told how to do something; she would figure out that part, often in innovative ways. I learned to not give her detailed instructions, but rather just keep her informed as to project direction and needs, and trust that the results would be fast and high-quality.
That was the basis of her conflict with her functional manager. He was aghast at some of the approaches she took, and instead tried to tell her the acceptable way of performing her job. They argued frequently, with him wanting to do her tasks in an accepted (by him) way, and her insistence that she find her own way forward.
She actually outlasted her manager at the company (I was long since gone), at least because she was flexible enough to do what was needed in different ways.
When I ask someone to do something, I’ve usually been comfortable looking at results, not process. Of course there are limits to that. Don’t do anything illegal, don’t bully other people. I also once had a subordinate who would work the hours necessary during the week to get the job done, but refused to work weekends. I was okay with that too.
And some things you have to do for yourself, for speed or symbolic purposes. If there is something unpleasant to be done, then do it yourself.
But in general, people work in different ways, and in ways we may not have seen before. That doesn’t make them wrong. In fact, we may learn something from them.
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