Speaker 1: Welcome to tech Stuff, a production of I Heart Radios,
Speaker 1: How Stuff Works. Hey there, and welcome to tech Stuff.
Speaker 1: I'm your host, Jonathan Strickling. I'm an executive producer with
Speaker 1: How Stuff Works and my Heart Radio and I love
Speaker 1: all things tech. I always have to qualify that after
Speaker 1: I say it, because then I end up covering topics
Speaker 1: like this one today where I don't love all things tech.
Speaker 1: I guess it's it's being a little a little disingenuous
Speaker 1: to make that claim. But recently, critical thinking has really
Speaker 1: been on my mind a lot. I always want to
Speaker 1: be a critical thinker, though like most humans, I do
Speaker 1: have lapses. Sometimes I encounter a message that is so
Speaker 1: appealing that my desire for it to be true can
Speaker 1: override my skepticism, and I'll fail to ask myself or
Speaker 1: anyone else for that matter, important questions to make sure
Speaker 1: that what is being promised is in fact realistic and achievable.
Speaker 1: My goal is to minimize the number of times I
Speaker 1: go along with a pitch simply because it was a
Speaker 1: really good pitch. But technology sometimes makes that really hard.
Speaker 1: And I want to talk about this challenge because it's
Speaker 1: one that we all encounter. Technology is undeniably amazing. Just
Speaker 1: think about how much humans have achieved in a very
Speaker 1: short amount of time. For most of human history, our
Speaker 1: technological advancement was really slow. We completed some monumental achievements
Speaker 1: in art and architecture, and sadly, in finding new ways
Speaker 1: to kill each other, but apart from some early experiments
Speaker 1: and steam power, and a few interesting ideas from geniuses
Speaker 1: like Leonardo da Vinci, we really didn't see incredibly rapid advances.
Speaker 1: Then we get to the nineteenth century, when a combination
Speaker 1: of factors led to the Industrial Revolution. That revolution increased
Speaker 1: productivity and lead to conditions that made it possible for
Speaker 1: more innovators to experiment and expand our knowledge, understanding, and
Speaker 1: ability to exploit the world around us. Then we get
Speaker 1: to the twentieth century and the development of computers and
Speaker 1: the transistor, manaturization, mass produced plastic, and some other important
Speaker 1: innovations that would allow for truly rapid technological evolution. Consider this,
Speaker 1: When I was a kid, there was no public internet,
Speaker 1: cell phones were pretty much restricted to R and D labs.
Speaker 1: Personal computers had just entered the market. Many of today's
Speaker 1: fastest growing companies couldn't have existed because the business they
Speaker 1: are based off of didn't have a platform yet. For
Speaker 1: a while, it remained possible for the average person to
Speaker 1: know enough about the technology they encountered to deal with
Speaker 1: it when things went wrong, at least for most of
Speaker 1: the technology. Some like television sets and stuff, we're already
Speaker 1: well beyond the understanding of the average person. But this
Speaker 1: actually got harder to do as technology advanced, and we've
Speaker 1: seen it manifest in many ways. A good example of
Speaker 1: this is in the automotive industry. Classic cars can be complicated,
Speaker 1: but with some training and practice and owner can learn
Speaker 1: how to do maintenance and repairs on a lot of
Speaker 1: different parts of the car by themselves. There's a learning
Speaker 1: curve there, but it's totally possible, and there are a
Speaker 1: lot of people who love to take old cars and
Speaker 1: restore them as sort of a passion project. Today cars
Speaker 1: tend to have components in them that are high tech
Speaker 1: and sealed away in such a way as to make
Speaker 1: it difficult or impossible to access without proprietary tools and
Speaker 1: a deep understanding of how they work. You might not
Speaker 1: be able to tell what's wrong with a car without
Speaker 1: a special diagnosis scanning tool. And after learning what's wrong,
Speaker 1: you might not be able to do anything about it yourself.
Speaker 1: As cars get more advanced with features like various sensors
Speaker 1: and systems for stuff like lane assist, adaptive cruise control,
Speaker 1: parking assist, and more, they become harder to maintained by
Speaker 1: the owner. They're turning into what folks call a black box,
Speaker 1: in which you have a type of technology where the
Speaker 1: inner workings are hidden away from the user. It doesn't
Speaker 1: literally have to be hidden from sight, it can just
Speaker 1: be so complicated that the average person finds it inaccessible.
Speaker 1: And this leads us to a real challenge. As we
Speaker 1: have learned more about the universe, we've specialized in our
Speaker 1: focus we had to. We quickly reached a point in
Speaker 1: which it's pretty much impossible to have a deep understanding
Speaker 1: of all subjects. Then of our understanding has grown, we've
Speaker 1: pushed back the boundaries of ignorance. But now there's just
Speaker 1: too much to know for any one person to know
Speaker 1: it all. And the stuff we've built has capitalized on
Speaker 1: this focused understanding, but it also means that it's created
Speaker 1: a barrier for us. We might know that something works,
Speaker 1: but we don't necessarily understand how it works because it's
Speaker 1: based off a principle that's alien to us, and this
Speaker 1: was bound to happen, but it creates a dangerous situation.
Speaker 1: It's dangerous for a few different reasons. First, we as
Speaker 1: consumers can grow complacent. We expect stuff to work, and
Speaker 1: when that stuff doesn't work, we're frustrated. Worse, because we
Speaker 1: probably don't understand how that stuff works, we don't really
Speaker 1: know how to go about fixing it. On a positive note,
Speaker 1: that usually means there's opportunity for people with expertise to
Speaker 1: make a living as a troubleshooter or repair professional, but
Speaker 1: it means that as consumers we have less ability to
Speaker 1: work with the stuff we actually consume. Second, our technology
Speaker 1: is approaching the point where it could be really dangerous
Speaker 1: if we don't understand exactly how it's working. As machine
Speaker 1: learning models and artificial intelligence become more sophisticated, it becomes
Speaker 1: more important for us to understand how these systems are
Speaker 1: coming to conclusions. It's pretty cool to say, hey, I
Speaker 1: built this machine learning model and I train AI on
Speaker 1: how to recognize a person's face. Maybe you built the
Speaker 1: model to work with a camera manufacturer so that the
Speaker 1: cameras they make automatically detective face and then focus on it.
Speaker 1: But that same technology could potentially be used in tracking
Speaker 1: and identification systems, and if that system was being used
Speaker 1: by say, law enforcement, you want to understand exactly how
Speaker 1: the system is identifying people so that you can audit
Speaker 1: it and make sure that it's being accurate and not
Speaker 1: having a lot of false flags. Otherwise you run the
Speaker 1: risk of having the machine mistakenly identify people during an investigation,
Speaker 1: which at the very least could be disruptive. Or to
Speaker 1: go back to cars for a second, consider driverless cars. Now.
Speaker 1: I am still optimistic about driverless cars, but I've tempered
Speaker 1: my expectations on when we might see them. In my mind,
Speaker 1: I was thinking, well, a car decked out with sensors
Speaker 1: and a really fast computer system would be able to
Speaker 1: detect potential problems and react to them far faster and
Speaker 1: more logically than a human. I even thought a computer
Speaker 1: system could be able to monitor completely around a vehicle,
Speaker 1: whereas a human is typically focused on whatever is directly
Speaker 1: in front of him or her, or perhaps in a mirror,
Speaker 1: but can't pay attention to all directions at the same time.
Speaker 1: And sure machines can react in a fraction of the
Speaker 1: time it takes humans to do it. But machines are
Speaker 1: really good at handling routine situations and then responding appropriately.
Speaker 1: The more unusual an event, the harder it is for
Speaker 1: the machine to cope with it. Machines typically aren't terribly adaptive,
Speaker 1: and so with many millions of cars on the road,
Speaker 1: plus bicyclists, pedestrians, animals, debris, weather events, and other factors,
Speaker 1: it's pretty rare for any drive of a significant length
Speaker 1: to be completely quote unquote normal. So we need to
Speaker 1: design autonomous cars that can adapt to situations. But that
Speaker 1: also means we need to understand what decisions a car
Speaker 1: will make, or the very least, determine why a car
Speaker 1: behaved in one way versus an alternative. And so there's
Speaker 1: a move in AI and artificial neural network circles to
Speaker 1: make these processes as transparent as possible so that we're
Speaker 1: not caught off guard when a machine takes a particular action.
Speaker 1: And third, advanced technology has given us unrealistic expectations of
Speaker 1: exactly what was possible. After all, two hundred years ago,
Speaker 1: we wouldn't really dream of going up into space. A
Speaker 1: century ago, we might dream of it, but we still
Speaker 1: had no real understanding of how we would accomplish it.
Speaker 1: Then within another five decades we were sending people up
Speaker 1: to space, then to the moon, and now we have
Speaker 1: private companies designing launch vehicles that can return to Earth
Speaker 1: to be refurbished and used again in future launches. That's
Speaker 1: pretty incredible. We also have seen technology go from enormous
Speaker 1: to the very tiny. In the nineteen forties, a computer
Speaker 1: took up a lot of space, maybe the entire floor
Speaker 1: of a building, and it's processing power would be a
Speaker 1: fraction of what you'd find in the average smartphone. These days,
Speaker 1: managorization and Moore's Law have conditioned us to think that
Speaker 1: technology is capable of pretty much anything. I mean, it
Speaker 1: has to be. We wouldn't have assumed that it would
Speaker 1: be easy to get your hands on a portable computer,
Speaker 1: capable of acting like a camera, a communications device, and
Speaker 1: a direct link to the world's largest repository of human knowledge,
Speaker 1: even if most of that knowledge seems to be centered
Speaker 1: on cats. But that means when someone comes forward with
Speaker 1: extraordinary claims, it's easier for us to take them at
Speaker 1: face value. Technology has created an environment in which what
Speaker 1: was impossible yesterday becomes a mundane everyday task tomorrow, and
Speaker 1: this means that people can leverage that to our disadvantage.
Speaker 1: In some cases, you might be with an outright snake
Speaker 1: oil salesman type, someone who knows very well that the
Speaker 1: dream they're peddling isn't based in reality. But in other
Speaker 1: cases you might have sincere people who truly believe they've
Speaker 1: either cracked the code on something that was previously thought
Speaker 1: impossible or they feel they're right on the cusp and
Speaker 1: if they can just get enough funding to cover costs,
Speaker 1: they'll get the rest of the way there. Now. In
Speaker 1: a way, this could be a good thing, as it
Speaker 1: means that innovators have more access to resources than ever before,
Speaker 1: and it could lead to great discoveries. But in other
Speaker 1: cases it can lead to frustration, financial hardship, and worse.
Speaker 1: When we come back after this quick break, I'll give
Speaker 1: an example that's in everyone's minds right now. There's probably
Speaker 1: no better company to point to when you're talking about
Speaker 1: the dangers of wishful thinking than Theopness. And I know
Speaker 1: it's been in the news a lot. You've probably heard
Speaker 1: tons about it, maybe you've seen the documentary about it,
Speaker 1: maybe you've seen the the various articles or listen to
Speaker 1: the podcasts about it. But we're going to talk about
Speaker 1: a little bit more in this context and just to
Speaker 1: give you an overview in case you haven't encountered this.
Speaker 1: A woman named Elizabeth Holmes founded the company after she
Speaker 1: dropped out of Stanford. I do not know her. I
Speaker 1: do not know whether or not she sincerely believed or
Speaker 1: believes that the text she was seeking to invent could
Speaker 1: really work. But I do know that as of right now,
Speaker 1: it isn't working, and that's a big problem for those
Speaker 1: of you who are unfamiliar with the story. Let's give
Speaker 1: a quick summary. Elizabeth Holmes wanted to create tech that
Speaker 1: could disrupt the health care industry. It would, in theory,
Speaker 1: give more control an agency to consumers who could learn
Speaker 1: much more about their health on their own without the
Speaker 1: need to make an appointment with a doctor and undergo
Speaker 1: numerous blood draws to have various blood tests performed. The
Speaker 1: basic idea was that Sara no Nos would develop a
Speaker 1: device capable of taking a very small sample of blood,
Speaker 1: small enough to be drawn from the tip of a finger.
Speaker 1: They would then run a battery of tests to look
Speaker 1: for indicators of different conditions and diseases within a relatively
Speaker 1: short time. It would produce the results, giving the user
Speaker 1: more information about their health, which in theory, would help
Speaker 1: that person have meaningful conversations with a physician if there
Speaker 1: were any markers that raised concern. And it's a very powerful,
Speaker 1: very compelling idea. There are technologies like labs on a
Speaker 1: chip and microprocessors designed to detect the presence of certain
Speaker 1: markers that indicate the presence of illness, but this would
Speaker 1: wrap all of that up into a single package. In fact,
Speaker 1: Homes worked on a project related to this. After her
Speaker 1: first year at Stanford. She joined the Genome Institute in
Speaker 1: single Or and was overseeing blood tests. She first envisioned
Speaker 1: a sort of arm band that would use micro needles,
Speaker 1: and those micro needles would both draw small blood samples
Speaker 1: and would also administer medication on an as needed basis.
Speaker 1: She later led a team to work on a machine
Speaker 1: that would accept a small capsule containing a blood sample
Speaker 1: an attempt to run multiple tests on that sample. This
Speaker 1: was in stark contrast with the normal medical procedure in
Speaker 1: which a doctor or nurse would draw numerous vials of
Speaker 1: blood for testing send those samples off to one of
Speaker 1: two major lab testing companies in the United States. If
Speaker 1: Sarinos's technology worked, the company could totally up end that
Speaker 1: system in the US. Patients could go to a clinic
Speaker 1: to have a test run and get the results back
Speaker 1: in hours, rather than having to take a trip to
Speaker 1: the doctor's office, sit for a blood draw, and wait
Speaker 1: several days. They could end up being cheaper than the
Speaker 1: old approach. Sarainos executives like Homes stressed that this would
Speaker 1: put patients in control of their own health information and
Speaker 1: could provide many benefits, such as a heads up for
Speaker 1: possible problems in the future or catching something early enough
Speaker 1: to treat it before it became too severe. But the
Speaker 1: problem is that this depended upon that if Thara Noss
Speaker 1: technology worked. Thing. As it turned out, the tech wasn't working.
Speaker 1: At least, it wasn't working at the level of the
Speaker 1: company was striving for the engineers that thereas were trying
Speaker 1: really hard to create a diagnostic device that could take
Speaker 1: that small blood sample and run it through a lot
Speaker 1: of tests. But as it turns out, that's actually incredibly complicated.
Speaker 1: Using such a small sample was already a huge challenge.
Speaker 1: On top of that, you have issues you have to
Speaker 1: worry about, like contamination. A contaminated sample could give off
Speaker 1: false positives, creating a situation in which a patient believes
Speaker 1: they might have a particular disease or a condition when
Speaker 1: that isn't really the case, or it could mask something
Speaker 1: that the patient would need to know about, but because
Speaker 1: the results would be inconclusive, they wouldn't know about it. Now.
Speaker 1: Perhaps the hope was that the company would be able
Speaker 1: to develop the technology rapidly with the help of large
Speaker 1: investments in the company. And sure enough, there were a
Speaker 1: lot of folks with deep pockets who poured money into thoroughness,
Speaker 1: and you can sort of understand why. If it all worked,
Speaker 1: it would be a revolution in medicine. The company would
Speaker 1: stand to gain billions of dollars, The cause appeared to
Speaker 1: be noble, and the outcome looked like it would be
Speaker 1: incredibly profitable. It was a very tempting opportunity, and many
Speaker 1: didn't resist that temptation. On top of all that, it
Speaker 1: was dependent upon technology, and as I mentioned, we've come
Speaker 1: to a point where we believe technology can do just
Speaker 1: about anything. So it didn't seem outside the realm of
Speaker 1: possibility that a microchip inside a Suffici CICAD machine would
Speaker 1: be able to run a series of tests on the
Speaker 1: small blood sample and come up with meaningful results. But
Speaker 1: flash forward a few years and a bombshell of an
Speaker 1: article revealing that there was really a shell game going
Speaker 1: on at Sarais tells us that now we know the
Speaker 1: technology was a failure, that THEOS was depending upon the
Speaker 1: same sort of machines that the company was purporting to
Speaker 1: replace with its innovative approach, that hundreds or thousands of
Speaker 1: patients in trial locations were potentially at risk due to
Speaker 1: unreliable results, and that the company used some pretty draconian
Speaker 1: tactics to keep employees in line and prevent them speaking
Speaker 1: out about what was going on. It's about as bad
Speaker 1: an outcome as you could imagine. What's more, there are
Speaker 1: those who say that even if everything had worked, the
Speaker 1: whole enterprise was misguided in the first place. A Piece
Speaker 1: and Wired by Gnoam Cohen cites a couple of those people.
Speaker 1: The piece has the title the other Big lesson we
Speaker 1: should learn from thoroughness. Cohen mentions Faye Flam, who wrote
Speaker 1: a piece in Bloomberg that argued thoroness was tapping into
Speaker 1: another deep human desire, the illusion of controlling our own
Speaker 1: destiny through thous We could end up getting our own
Speaker 1: test results and then apply our own interpretations to them.
Speaker 1: Perhaps we would interpret them in a way that is
Speaker 1: most comforting to us, or one that seems to align
Speaker 1: with our preconceived ideas about our health. This isn't exactly
Speaker 1: the best way to handle a medical issue. Surely it
Speaker 1: makes more sense to have a trained medical professional provide
Speaker 1: an unbiased, objective interpretation of test results that gives you
Speaker 1: the best chance to take appropriate actions that will help
Speaker 1: you lead a better, healthier life. So yeah, it was
Speaker 1: a really compelling sales pitch, no wonder so many people
Speaker 1: were on board. If it worked, it would be cheaper,
Speaker 1: less painful, more convenient, and at least on the surface,
Speaker 1: more empowering than the established method. It was the sort
Speaker 1: of thing we'd want to believe in, so people did.
Speaker 1: I think autonomous cars are following a similar trajectory. Now,
Speaker 1: to be clear, I feel that a lot of great
Speaker 1: work has been done in autonomous cars. They are much
Speaker 1: further along than a mythical blood testing device that only
Speaker 1: ever got approval for performing one type of blood test
Speaker 1: when it was supposed to be able to run more
Speaker 1: than one hundred of them, but we still have a
Speaker 1: long way to go. Unfortunately, because of our experiences dealing
Speaker 1: with truly amazing tech and the expectation that, of course,
Speaker 1: technology can take care of the problem, we've had some
Speaker 1: high profile accidents that prove this isn't the most reliable philosophy. Again,
Speaker 1: it would be understandable to put a lot of faith
Speaker 1: in the tech. Google's self driving cars, which have been
Speaker 1: pioneers in the field, famously operated at first in secret
Speaker 1: and then openly for hundreds of driving miles without a
Speaker 1: single accident, or at least that was the official story.
Speaker 1: There have been a few accidents, most of which were
Speaker 1: likely the fault of a human driver, either the safety
Speaker 1: operator in the autonomous vehicle or the driver of another car,
Speaker 1: but later reports suggested that there were some serious accidents,
Speaker 1: at least a few of which were caused by the
Speaker 1: autonomous driving system behaving in an unexpected way. The company
Speaker 1: kept these accidents quiet, and so there was an unearned
Speaker 1: expectation of safety with this tech. Then enter Tesla and
Speaker 1: the autopilot feature in the company's electric vehicles. While the
Speaker 1: company issued a statement that made it clear that this
Speaker 1: feature wasn't supposed to replace a human driver. That didn't
Speaker 1: stop people from trying it out that way. Most of
Speaker 1: those people didn't have any problems, but in at least
Speaker 1: a couple of cases, drivers using autopilot ended up in
Speaker 1: tragic situations. One of those was the case of Joshua
Speaker 1: Brown in two thousand sixteen, his s Tesla crashed into
Speaker 1: a semi truck. Brown had been using the autopilot feature.
Speaker 1: According to the vehicle's datalogues. Out of the thirty seven
Speaker 1: minutes Brown had the autopilot feature turned on, his hands
Speaker 1: were on the wheel for just twenty five seconds total,
Speaker 1: in direct violation of the policy that Tesla had set.
Speaker 1: The company stressed the autopilot isn't meant to replace human
Speaker 1: drivers and that the cars driver should have had their
Speaker 1: hands on the wheel at all times. The second fatal
Speaker 1: incident happened in March two thousand eighteen, when way Walter
Speaker 1: Huang's Model X veered into a highway safety barrier. Recently,
Speaker 1: his family sued Tesla, alleging the company was aware of
Speaker 1: the dangers of the features, that Huang had been operating
Speaker 1: the vehicle within the parameters of autopilot, and that Tesla
Speaker 1: had been using drivers like Wong to beta test changes
Speaker 1: to the feature in the wild. That suit is just
Speaker 1: getting started as I record this episode, and I don't
Speaker 1: mean to pick on Tesla, after all. I started this
Speaker 1: by talking about how Google kept several accidents on the
Speaker 1: q T. One of Uber's self driving cars in its
Speaker 1: beta test program in Arizona, struck and killed a pedestrian
Speaker 1: in March two thousand eighteen. State prosecutors decided that Uber
Speaker 1: isn't liable for the accident, but that the safety operator
Speaker 1: who was in the car might bear some responsibility for
Speaker 1: failing to act before the accident. According to venture Beat,
Speaker 1: the operator was streaming a video of the voice and
Speaker 1: watching that rather than the road. It's quite possible that
Speaker 1: companies pushing autonomous car technology are doing their best to
Speaker 1: keep incidents quiet in an effort to avoid government regulations
Speaker 1: and interference which could threaten the profitability of such a pursuit.
Speaker 1: But at the same time, these high profile incidents have
Speaker 1: dealt a blow to consumer confidence about the technology in general,
Speaker 1: and they really reinforce that driving is more complicated than
Speaker 1: just staying within your lane and breaking if something is
Speaker 1: in the way. Before I wrap up this section, I
Speaker 1: do want to also mention that, at least according to Tesla,
Speaker 1: the autopilot feature has proven to be safer than human
Speaker 1: drivers operating vehicles unassistant. According to Tesla's report, there was
Speaker 1: one accident per two point eight seven million miles driven
Speaker 1: where autopilot was engaged and one accident per one point
Speaker 1: seven six million miles driven when it wasn't, and that
Speaker 1: according to government statistics, the average is an automobile crash
Speaker 1: every four hundred thirty six thousand miles. However, skeptical researchers
Speaker 1: have found that Tesla hasn't always been honest or at
Speaker 1: the very least correct about safety reports. A firm called
Speaker 1: Quality Control Systems sued the United States National Highway Traffic
Speaker 1: Safety Administration, or in ht s A, in order to
Speaker 1: get the data the agency said had proved that Tesla's
Speaker 1: autopilot had cut back on crashes by fort In fact,
Speaker 1: QCs found at in cases in which all the data
Speaker 1: was available, which was just a fraction of the cases
Speaker 1: the nh t s A had used to come up
Speaker 1: with that mark, the auto steer feature on autopilot actually
Speaker 1: increased crash rates by So what does all this mean.
Speaker 1: I'll get back to that in a second, but first
Speaker 1: let's take a quick break. So am I saying you
Speaker 1: shouldn't believe anyone, Well, that's not quite it. I think
Speaker 1: a better thing to say is don't accept anything at
Speaker 1: face value. Sometimes people can just be wrong about stuff.
Speaker 1: It happens to me more often than I care to admit.
Speaker 1: But the responsible thing to do in those cases is
Speaker 1: to own up to the mistake and correct it where
Speaker 1: you can. I am certain that at least some people
Speaker 1: who thought they were onto some sort of free energy device,
Speaker 1: for example, really did. They were onto something. Others might
Speaker 1: have suspected that what they were pursuing was impossible, but
Speaker 1: they had already invested too much to back out at
Speaker 1: any rate. Whether it's a perpetual motion machine or an
Speaker 1: over unity engine, the simple fact is that these devices
Speaker 1: have never been proven to actually work as described supporters say.
Speaker 1: This is because there are powerful entities like petroleum companies
Speaker 1: that will use every means to keep such devices from
Speaker 1: being deployed. But at the level of classical physics, such
Speaker 1: a device would have to defy laws of physics that
Speaker 1: have stood the test of time. Now does that mean
Speaker 1: that such a device is impossible. No, it's not impossible,
Speaker 1: but it does mean you need truly extraordinary, irrefutable proof
Speaker 1: that it worked. In other cases, people are being outright
Speaker 1: dishonest in an effort to advance their own agendas. They
Speaker 1: might take efforts to hide any deficiencies in the technology,
Speaker 1: or to overly elevate stuff that's working to make it
Speaker 1: seem more important than it is. They might just be
Speaker 1: stalling for time in the hopes that a breakthrough is
Speaker 1: right around the corner and they can reap the benefits
Speaker 1: once it all pans out. Now, we're going to see
Speaker 1: technology continue to advance and evolve. In most cases, we'll
Speaker 1: see it do so gradually, perhaps so gradually that we
Speaker 1: don't really appreciate how incredible that technology can be. I
Speaker 1: have owned smartphones for about ten years or so, and
Speaker 1: now I take it for granted that I have access
Speaker 1: to them. But as a kid, it would have totally
Speaker 1: floored me to know that such a thing would be
Speaker 1: possible in my lifetime, let alone that I would actually
Speaker 1: own one. When confronted with claims about technology, it's good
Speaker 1: to ask questions questions like how is this possible? How
Speaker 1: does it work. What is it doing differently from earlier
Speaker 1: versions of this tech. If it's a technology that relates
Speaker 1: to a specialized field, it might be necessary to consult
Speaker 1: experts in that field to get good answers. There's no
Speaker 1: shame in that back. If someone presented a technology to
Speaker 1: me with claims that the whole thing worked on quantum principles,
Speaker 1: I need to consult with an expert. I have the
Speaker 1: most basic understanding of high level quantum physics, and once
Speaker 1: you get past that, it's all beyond me. I might
Speaker 1: suspect something fishy, but I'd have no way of knowing
Speaker 1: on my own anyway. If my suspicions were warranted, I
Speaker 1: would need to consult with someone far more educated and
Speaker 1: experience than I in the world of quantum physics to
Speaker 1: get a better handle on it. Now, the more vague
Speaker 1: the claims, the more skepticism you should apply. If the
Speaker 1: claim includes disconnected scientific terminology, particularly if it is getting
Speaker 1: into fields like quantum physics, that's a red flag. You
Speaker 1: need to pay closer attention to those claims, or might
Speaker 1: even include non scientific or meaningless language, which is another
Speaker 1: big warning sign. Maybe you'll see a device that claims
Speaker 1: that if you wear it. The device will boost your
Speaker 1: quote unquote energy in some way, but what does that
Speaker 1: actually mean? Terms must first be defined, and then you
Speaker 1: can move on to the next question, which is, well,
Speaker 1: how the heck does it do this thing you claim
Speaker 1: it's doing. For gadgets or technologies that cite experts, it's
Speaker 1: good to find out who those experts are. If there's
Speaker 1: language like studies show that blah blah blah blah blah,
Speaker 1: it's good to find out who did the actual study.
Speaker 1: Was it a reputable third party that could provide an objective,
Speaker 1: unbiased point of view, or was it an in house
Speaker 1: team or biased party. There's lending credence to claims without
Speaker 1: actually finding out if those claims have merit. Moreover, we
Speaker 1: have to remember that tech isn't magic, though science fiction
Speaker 1: author Arthur C. Clark did once observe that any sufficiently
Speaker 1: advanced technology would seem to be magic to us. Technology
Speaker 1: has limits. There are fundamental physical limits that tech can't breakthrough.
Speaker 1: And just because we see tech doing some stuff really
Speaker 1: well doesn't mean it can do everything equally well. I
Speaker 1: know I go on about critical thinking a lot in
Speaker 1: this show, but the reason I do that is I
Speaker 1: want people to apply that skill set in their lives
Speaker 1: to make better informed decisions. I want you, guys to
Speaker 1: avoid pitfalls, whether they are purposefully placed in your path
Speaker 1: or not. I want you to be able to spot
Speaker 1: a mistake or a scam. I want you to follow
Speaker 1: your suspicions when you feel something isn't on the up
Speaker 1: and up. And along with that, I do urge the
Speaker 1: use of compassion. Please keep in mind that not everyone
Speaker 1: hawking tech that promises too much is doing so out
Speaker 1: of malice or agreed. Some could be genuinely misled by
Speaker 1: what the tech can do, and so it's a good
Speaker 1: idea to have critical thinking and compassion go hand in hand.
Speaker 1: Try to understand not just how realistic the claim is,
Speaker 1: but the person making the claim. If they're intentionally trying
Speaker 1: to mislead people and take advantage of them, well they're
Speaker 1: kind of scummy and I feel they should be called
Speaker 1: out on that behavior. But maybe they're just believing in
Speaker 1: something they want to believe in because of the promise
Speaker 1: it makes. That doesn't necessarily make them bad. They might
Speaker 1: mean they are gullible, or that they are in a
Speaker 1: situation that they desperately want out of, and the promise
Speaker 1: seems to suggest an escape route. So long story short,
Speaker 1: don't believe all the hype. Ask questions, ask for clarification
Speaker 1: when you get answers, to make sure that those answers
Speaker 1: are actually substantive and they mean something. Be prepared to
Speaker 1: dismiss a claim if the support for that claim is lacking.
Speaker 1: Also be prepared to accept a claim if the support
Speaker 1: merits it. One of the biggest complaints about skeptics is
Speaker 1: that they are seen as people who dismiss claims out
Speaker 1: of hand, and for some people that is true, although
Speaker 1: we typically call them deniers rather than skeptics. But most
Speaker 1: of us try to keep in mind that if extraordinary
Speaker 1: proof for a claim exists, we should be willing to
Speaker 1: adjust our world view to incorporate this new idea, even
Speaker 1: if it previously seemed impossible. The proof just has to
Speaker 1: be there, And don't just assume everyone is out to
Speaker 1: pull one over on you. Just be aware there are
Speaker 1: those people out there too. In short, be good human beings,
Speaker 1: and keep in mind again technology as it advances, we're
Speaker 1: going to keep running into this problem. Because we see
Speaker 1: it do amazing things in one arena, we might expect
Speaker 1: it can do equally amazing things in another and that's
Speaker 1: not always the case. Well, that's it for this soapbox
Speaker 1: edition of tech Stuff and my regular or call for
Speaker 1: critical thinking. I think it's particularly important to consider it
Speaker 1: now in the wake of things like Thorinus and Facebook
Speaker 1: and all of its controversies and related technological issues. And
Speaker 1: of course you can and should use critical thinking well
Speaker 1: outside the world of technology. You should apply it pretty
Speaker 1: much everywhere in your life so that you can be
Speaker 1: reasonably sure you're getting the real deal and not being misled.
Speaker 1: If you guys have suggestions for a future episode of
Speaker 1: tech Stuff, you can contact me. The email adjust for
Speaker 1: the show is tech Stuff at how stuff Works dot com,
Speaker 1: or you can drop me on line on Facebook or Twitter.
Speaker 1: The handle for both of those is tech Stuff hs W.
Speaker 1: You can head on over to our website that's tech
Speaker 1: stuff podcast dot com as an archive of all of
Speaker 1: our previous episodes plus links to our background on the show,
Speaker 1: as well as to our our online store, where every
Speaker 1: purchase you make goes to help the show. We greatly
Speaker 1: a pre ate it, and I will talk to you
Speaker 1: again really soon. Yeah. Tech Stuff is a production of
Speaker 1: I Heart Radio's How Stuff Works For more podcasts from
Speaker 1: my heart Radio, visit the i heart Radio app, Apple podcasts,
Speaker 1: or wherever you listen to your favorite shows.