Speaker 1: Welcome to tech Stuff, a production from iHeartRadio. Be there
Speaker 1: and welcome to tech Stuff. I'm your host, Jonathan Strickland.
Speaker 1: I'm an executive producer with iHeartRadio. And how the tech
Speaker 1: are you today? I thought I would talk about a
Speaker 1: few fundamental principles that underlie technology, at least as identified
Speaker 1: by a blog called Simplicable. The name of the author
Speaker 1: on all the articles I was looking at was John Spacey,
Speaker 1: so it appears to be John Spacey at the helm
Speaker 1: of this blog, which I think is based out of Singapore.
Speaker 1: So these are concepts that apply to or drive technology
Speaker 1: and technological change and innovation. And it goes beyond things
Speaker 1: like circuits or electricity or mechanical systems or anything like that.
Speaker 1: These are more like ideas and observations that underlie technology,
Speaker 1: again as identified by Simplicable. So I don't wish to
Speaker 1: suggest that these are universal fundamental principles, just rather that
Speaker 1: I came across this list Unsimplicable and I thought it
Speaker 1: was interesting, so I thought I would talk about some
Speaker 1: of them today. So first up, we've got a concept
Speaker 1: that ties in with Moore's law to an extent. You
Speaker 1: could argue that Moore's law is another fundamental principle. In fact,
Speaker 1: it's one of the ones that's listed by simplicable. I
Speaker 1: think that's going a little far to call it a
Speaker 1: fundamental principle. It's certainly an observation that people have attempted
Speaker 1: to push beyond some pretty hard boundaries. But as a refresher,
Speaker 1: just so that you understand what I'm talking about here,
Speaker 1: Moore's law stems from an observation that Gordon Moore paid
Speaker 1: back in the middle of the last century, actually, when
Speaker 1: he saw that economic and technological factors were contribute meeting
Speaker 1: to a system where there was an economic demand for
Speaker 1: progressively more powerful microprocessors and later on computer chips, and
Speaker 1: that this demand in turn created an incentive for fabrication
Speaker 1: companies to come up with ways to meet that demand. Like,
Speaker 1: it wasn't just magical that the fabrication companies were able
Speaker 1: to make more powerful processors. They saw the demand there
Speaker 1: and then they said, okay, well, how can we make
Speaker 1: something that meets that demand. It's not just magically happening
Speaker 1: on its own. So every so often we would see
Speaker 1: companies find new ways to fit more discrete components onto
Speaker 1: a square inch of silicon wafer. As they were able
Speaker 1: to a couple of years previously. So generally speaking, the
Speaker 1: law of Moore's law boiled down to every eighteen to
Speaker 1: twenty four months, fabrication companies would find a way to
Speaker 1: double the number of transistors that they could it onto
Speaker 1: a silicon wafer an inch of silicon wafer square inch. Now,
Speaker 1: over time, this concept morphed into a similar but different one.
Speaker 1: We still call it Moore's law, but now we don't
Speaker 1: necessarily say that the processors of today have twice as
Speaker 1: many transistors on it as the processors from two years ago.
Speaker 1: For example, now we say every two years or so
Speaker 1: the chips that fabrication companies are producing are twice as
Speaker 1: powerful as the ones from two years earlier. So, in
Speaker 1: other words, if you bought a high end processor in
Speaker 1: twenty ten, and then you bought another high end processor
Speaker 1: in twenty twelve, the twenty twelve one should be twice
Speaker 1: as powerful as the twenty ten one, And then in
Speaker 1: twenty fourteen, if you bought one, that chip should be
Speaker 1: twice as powerful as the one that you had bought
Speaker 1: back in twenty twelve. Now we also tend to get
Speaker 1: a little loosey goosey with a whole concept of what
Speaker 1: power means in this context. Often this comes down to
Speaker 1: processing speed, how fast can the chip process information, how
Speaker 1: fast can it complete executions of operations, But powerful can
Speaker 1: also include some other concepts like bitwidth, and you can
Speaker 1: think of bitwidth as how large of a chunk of
Speaker 1: data can this processor handle. So if the bitwidth is greater,
Speaker 1: the processor can handle larger chunks of data. To me,
Speaker 1: one interesting thing about Moore's law is how we choose
Speaker 1: to interpret it so that it will remain relevant over
Speaker 1: the years. Because pretty much everyone has acknowledged we're running
Speaker 1: up against some obstacles that are just impossible to get
Speaker 1: around based on the technology we have developed so far.
Speaker 1: Let me explain that a little bit more so. As
Speaker 1: you reduce the size of these components so that you
Speaker 1: can fit more of them onto a silicon wafer, you
Speaker 1: start getting down to a size where you're encountering issues
Speaker 1: with quantum mechanics, and these quantum mechanics issues are not
Speaker 1: in alignment with the way that we want our electronics
Speaker 1: to work. Essentially, we get to a point where the
Speaker 1: pathways we have created for electrons are so small that
Speaker 1: the electrons have the potential to exist in a different
Speaker 1: part of the pathway than where we want them to be. So,
Speaker 1: if you think of transistor gates as actually being physical gates,
Speaker 1: as in, you know, you're when it's closed, you're not
Speaker 1: allowed to go through once you get to a certain size,
Speaker 1: there's a potential for an electron to be on the
Speaker 1: other side of the gate without having to actually physically
Speaker 1: pass through the gate. It just means that there's the
Speaker 1: possibility that the electron could be on the other side.
Speaker 1: And as long as there's a possibility, it means that
Speaker 1: sometimes that's what happens. And if you can't control where
Speaker 1: the electrons are, then the gates mean nothing, and it
Speaker 1: means that you're going to get computational errors. So there
Speaker 1: are fundamental physical limitations to how small we can make
Speaker 1: things if they're working the way that we have designed
Speaker 1: microprocessors for you know, the better part of a century.
Speaker 1: So that means that we have to come up with
Speaker 1: other means, other ways to try and eke out more
Speaker 1: performance in these chips. If we want Moore's law to
Speaker 1: remain relevant, and that's only if we say, all right,
Speaker 1: we want Moore's law to remain relevant, but not the
Speaker 1: original Moore's law. We're talking about our reinterpretation of that
Speaker 1: observation that was made, you know, in the middle of
Speaker 1: the nineteen hundreds. So that is kind of where we
Speaker 1: are with Moore's law. It's still sort of relevant, but
Speaker 1: mostly because we're willing to bend on how we interpret
Speaker 1: it and how we define it. So no one wants
Speaker 1: to reach a point where they have to admit that
Speaker 1: the rate of improvement is slowing down. No one wants
Speaker 1: to get to that point. So we'll just keep on
Speaker 1: moving things around, like doing the balls and cups routine,
Speaker 1: until we can no longer fool ourselves into thinking that
Speaker 1: we're able to keep this rate of change up. And
Speaker 1: this is what brings us up to a different fundamental principle,
Speaker 1: as defined by Sipplicable called accelerated change or accelerating change,
Speaker 1: I should say, and that's just what it sounds like,
Speaker 1: because we all realize that over time, stuff changes. Accelerating
Speaker 1: change means that the rate of change itself is changing.
Speaker 1: It's not just that things are changing day to day.
Speaker 1: It's the concept that they're changing more quickly than the
Speaker 1: rate of change was before, and that this is driven
Speaker 1: by technology and how we use that technology. So with
Speaker 1: this kind of concept, we would be able to look
Speaker 1: at any ten year span. So let's say we looked
Speaker 1: at nineteen fourteen to nineteen twenty three, and then let's
Speaker 1: say we compared that with a more recent ten year span,
Speaker 1: so let's say twenty fourteen to twenty twenty three. Then
Speaker 1: we ask the question in which of those ten year spans,
Speaker 1: In which of those decades would we see more change?
Speaker 1: And if we want to get specific, where did we
Speaker 1: see more technologically driven or oriented change. Since the nineteen
Speaker 1: fourteen to nineteen twenty three decade predates the invention of
Speaker 1: the transistor, it's pretty easy for us to say, well,
Speaker 1: the most recent decade has seen way more innovation driven
Speaker 1: by technology. It's not even comparable. And that's true, but
Speaker 1: we should also remember once again, these advancements in technology,
Speaker 1: they're not happening in a vacuum. It's not like technology,
Speaker 1: if left to itself, will evolve and improve over time.
Speaker 1: Stuff in the world shapes our approach to technology, and
Speaker 1: then our technology shapes the stuff in the world and
Speaker 1: our interaction with it. So in nineteen fourteen, you would say, well,
Speaker 1: what kind of factors were influencing technological development. In nineteen fourteen, well,
Speaker 1: there was a big one. It was the Great War,
Speaker 1: which was later called World War One. They didn't call
Speaker 1: it that at the beginning because there were still optimists
Speaker 1: back then. They weren't expecting there to be a second one.
Speaker 1: In fact, they called it the War to End all wars.
Speaker 1: It turns out that was wrong. Anyway, this war spurred
Speaker 1: a ton of innovation as various countries tried to find
Speaker 1: more efficient ways to kill the enemy while sustaining fewer
Speaker 1: losses of their own, or at the very least just
Speaker 1: killing war of them than they managed to kill of us.
Speaker 1: So we got lots of stuff like machine guns, motorized
Speaker 1: military vehicles, airplanes were used in warfare. Chemical warfare became
Speaker 1: a thing. We also got some other stuff that wasn't
Speaker 1: expressly made to kill people, like gas masks which was
Speaker 1: meant to save people, and field radios. Anyway, my point
Speaker 1: is that the concept of accelerating change isn't something that
Speaker 1: we can just isolate from the rest of the world.
Speaker 1: It's also something that can lead people to make predictions
Speaker 1: that I think may at best be a long shot.
Speaker 1: It's what has fueled a ton of discussion around concepts
Speaker 1: like the singularity. This is this idea that we reach
Speaker 1: a point where change is happening so quickly and it's
Speaker 1: so constant that there is no way that you can
Speaker 1: meaningfully talk about the way things are, because by the
Speaker 1: time you're done making a sentence, they ain't that way
Speaker 1: no more. They've changed already. So this idea, which relates
Speaker 1: to other concepts like humans becoming something more than human,
Speaker 1: the so called transhuman approach. Transhuman in this case meaning
Speaker 1: something beyond humanity. It doesn't have anything to do with
Speaker 1: something like the transgender community. That it's a different thing,
Speaker 1: very important thing, but different. This concept of transhumanism is
Speaker 1: about no longer being strictly human the way we would
Speaker 1: define it today, and that could include lots of things.
Speaker 1: It usually includes some form of augmented intelligence. Either we
Speaker 1: figured out a way to boost our own biological intelligence,
Speaker 1: or we've incorporated technology into us in some way that
Speaker 1: that then boosts our intelligence. Sometimes we also have an
Speaker 1: idea of digital immortality thrown in there. Mostly it feels
Speaker 1: a lot like stuff that's in the realm of science
Speaker 1: fiction rather than stuff that's in reality. But I would
Speaker 1: argue that it's based on this perception that change is
Speaker 1: happening faster with every passing year. And if that's your
Speaker 1: basic argument, well, then it stands to reason that at
Speaker 1: some point the rate of change will be such that
Speaker 1: there will be no meaningful way to quantify it. But
Speaker 1: like Moore's law, I would say this belief is based
Speaker 1: off things that may not be universally or permanently true.
Speaker 1: I think one of the mistakes that some futurists make
Speaker 1: is that they equate all change with what we see
Speaker 1: in things like Moore's law, because Moore's law describes exponential
Speaker 1: rates of improvement right with at least with processor complexity,
Speaker 1: which then we redefined as processor power or performance, So
Speaker 1: that same rate of change would then apply to everything
Speaker 1: with the way some futurists frame stuff out. But that's
Speaker 1: just not true. We don't see exponential change in everything
Speaker 1: that's related to technology. Some things actually change at an
Speaker 1: even faster rate, they might start to approach a hyperbolic
Speaker 1: rate of change, But some things experience much slower change.
Speaker 1: They don't advance that quickly, like battery technology does not
Speaker 1: advance nearly as quickly as microprocessor technology. So it appears
Speaker 1: to me that the singularity is going to require a
Speaker 1: lot more than just super fast processors, unless we decide
Speaker 1: to redefine what the singularity is, and then we could
Speaker 1: say we're already in it because we've redefined it, which
Speaker 1: we kind of have done with Moore's law. I guess
Speaker 1: we could do that, but it's not very satisfying. So
Speaker 1: accelerating change is one of those fundamental ideas in tech
Speaker 1: that may or may not apply depending on the tech
Speaker 1: type we're talking about. I would say that for some technologies,
Speaker 1: like autonomous vehicles, for example, we have not seen accelerating change. Instead,
Speaker 1: we saw an initial burst of innovation, incredible innovation, and
Speaker 1: for a few years that continued and it did look
Speaker 1: like it was accelerating change. But now we're seeing engineers
Speaker 1: having to hone in on specific limitations and problems and
Speaker 1: challenges within autonomous vehicle technology, and these require careful solutions,
Speaker 1: and some problems might be accounted for, but lots more
Speaker 1: have been discovered or are not accounted for, and we
Speaker 1: aren't seeing accelerating change in that field anymore. Iterative changes,
Speaker 1: which is still good, like we're still seeing advancements, but
Speaker 1: it's not going at this you know, breakneck speed. That
Speaker 1: accelerating change suggests. Okay, we've got a lot more principles
Speaker 1: to cover. I think it's time for us to take
Speaker 1: a quick break. All right, we're gonna move on to
Speaker 1: a different fundamental principle that Simplicable has identified as being,
Speaker 1: you know, fundamental to technology. And so let's talk about complexity.
Speaker 1: You can think of complexity falling into one of two categories.
Speaker 1: Simplicable calls it essential complexity and then accidental complexity, or
Speaker 1: what I would refer to as non essential complexity. Now,
Speaker 1: if something has essential complexity, that doesn't necessarily mean there's
Speaker 1: no way to simplify the technology. It might be possible
Speaker 1: to simplify it, but it's essential complexity. That means that
Speaker 1: if we were to try and simplify this technology, to
Speaker 1: streamline it or remove features or anything like that, then
Speaker 1: in the process, we would also reduce the usability or
Speaker 1: value of that technology. So, in other words, we could
Speaker 1: make it less complex, but we would also make it
Speaker 1: less good, or less desirable or less useful. This can
Speaker 1: fall into subjective perceptions. It's not just an objective truth.
Speaker 1: So for example, let's say you've got a team and
Speaker 1: they're developing a smartphone, and their initial lineup of features
Speaker 1: are all the typical ones you would find in a smartphone.
Speaker 1: It'll be able to make calls, they'll be able to
Speaker 1: send and receive emails and text messages. It'll be able
Speaker 1: to take photos, all that kind of stuff. The complexity
Speaker 1: necessitates certain design decisions, right, Like, in order to achieve
Speaker 1: the things you have listen did as what the smartphone
Speaker 1: has to do, you've got to make certain design decisions
Speaker 1: to support it. This all is just logical, right, And
Speaker 1: that could range from everything from the size of the
Speaker 1: battery you're gonna need if you want to have a
Speaker 1: useful phone life so it lasts at least a day.
Speaker 1: It may involve things like screen resolution. You want to
Speaker 1: make sure that people can see whatever it is that's
Speaker 1: being displayed. There, process or power to support all these
Speaker 1: different functions, Like, all these things become necessary considerations in
Speaker 1: order to provide a good experience. But let's say there's
Speaker 1: someone on your team who just doesn't see the value
Speaker 1: in having a camera and a smartphone. Maybe this person
Speaker 1: never uses the camera on their smartphone at all. Maybe
Speaker 1: they just don't take pictures. They don't see it as
Speaker 1: being fundamentally important to a smartphone's design. They could argue
Speaker 1: that you could drastically simplify the design of the smartphone
Speaker 1: if you just ditched the camera right. That means you
Speaker 1: get rid of the lenses, you get rid of all
Speaker 1: the sensors, you get rid of all the stuff that
Speaker 1: otherwise would have to be in the smartphone for the
Speaker 1: camera to work. And then you could either make the
Speaker 1: smartphone smaller, you know, create a smaller form factor because
Speaker 1: it no longer has to house those components, or dedicate
Speaker 1: that space for something else. Or even this could precipitate
Speaker 1: into changes for things like the battery life and the
Speaker 1: processor because it no longer would need to support the
Speaker 1: functions of a camera like these are sort of a
Speaker 1: cascading list of decisions that this could affect. However, someone
Speaker 1: else might say, well, this smartphone has no camera. It's
Speaker 1: not a good smartphone. I would argue it's not even
Speaker 1: a smartphone at all because there's no camera in it,
Speaker 1: And to them, the reduction in complexity has resulted in
Speaker 1: a reduction of usability or value. Again, there's no objective
Speaker 1: truth here. It's all dependent upon how you feel about it.
Speaker 1: But there is a general understanding that technologies can only
Speaker 1: be simplified and made more efficient and less clunky up
Speaker 1: to a point, and once you get beyond that point,
Speaker 1: you start to lose whatever it was that makes the
Speaker 1: technology useful in the first place. Now, if we go
Speaker 1: to accidental or non essential complexity, we've got the opposite.
Speaker 1: This describes a technology's tendency to have functions or features
Speaker 1: or elements to it that make it more complex but
Speaker 1: add no extra value to the technology itself, which means
Speaker 1: if you get rid of it, not only do you
Speaker 1: not eliminate something valuable, you might actually increase the value
Speaker 1: of the technology because you've gotten rid of some clutter.
Speaker 1: Now this could be software, it could be hardware. Like
Speaker 1: it doesn't have to be a physical technology. It could
Speaker 1: be something like a bug in software that when you
Speaker 1: eliminate it, not only does it make it less complex,
Speaker 1: but now the software works more effectively. So you've increased
Speaker 1: the value of the software. Even if you were to
Speaker 1: just argue that eliminating the bug reduces the size, like
Speaker 1: the data size of the software itself, you have increased
Speaker 1: its value, right because size is it's not an infinite
Speaker 1: resource that we have like your machines that run software
Speaker 1: have a limitation on how much they can handle. And
Speaker 1: if you start to reduce the demands of software by
Speaker 1: eliminating bugs, that increases that software's value, maybe not monetarily,
Speaker 1: but certainly from a process standpoint. So, with essential complexity,
Speaker 1: reducing complexity reduces the text value. With accidental complexity, reducing
Speaker 1: complexity increases the technology's value. Now there's a related tech
Speaker 1: issue I would like to kind of dip my toe
Speaker 1: in and mention here. That's called feature creep. Now, this
Speaker 1: is when a team is building out a technology and
Speaker 1: then they begin to add in features that were not
Speaker 1: included in the original plan for the tech. You know, oh,
Speaker 1: what if we were to add neon lights, or what
Speaker 1: about we put speakers on the outside of the car.
Speaker 1: Feature creep happens a lot in tech space. It can
Speaker 1: again happen in hardware and in software. It can also
Speaker 1: get to a point where it will doom a project
Speaker 1: or the very least delay it for ages and potentially
Speaker 1: mean that you end up with something that is less
Speaker 1: valuable because of all that feature creep, which ties into
Speaker 1: another fundamental principle that simplicable identifies where they say worse
Speaker 1: is better. By that, they mean not that if a
Speaker 1: technology is worse, it's better than a better technology, But
Speaker 1: sometimes a technology that has fewer functions but works really
Speaker 1: well is going to be viewed as more valuable than
Speaker 1: a device that has way more functions but it's harder
Speaker 1: to use, Which makes sense, right. If you make something
Speaker 1: that is easy to use and it does what it's
Speaker 1: supposed to do, then people are going to gravitate toward
Speaker 1: that more than they will technologies that it might have
Speaker 1: a lot more bells and whistles, but they don't do
Speaker 1: anything particularly well that doesn't typically stand the test of
Speaker 1: time well. Feature creep plays into both of these things here,
Speaker 1: both the complexity issue and the worst is better issue. Now,
Speaker 1: to me, the definitive example of feature creep, the one
Speaker 1: I would use if I were doing my TED talk
Speaker 1: on what feature creep is and why it's bad, would
Speaker 1: be the game Duke Nukem Forever. It was an infamous
Speaker 1: game while it was in development, and once it published
Speaker 1: it no longer became infamous. It just kind of became
Speaker 1: a bit of a punching bag, or sometimes just completely dismissed.
Speaker 1: So if you're not familiar with the Duke nucom franchise.
Speaker 1: It follows this overly macho male hero who's based a
Speaker 1: lot on characters that Arnold Schwarzenegger has played or Bruce Campbell.
Speaker 1: In fact, it lifts a lot of lines straight from
Speaker 1: the Evil Dead movies. Use Campbell Evil Dead movies when
Speaker 1: they were really campy and stuff. And it's a first
Speaker 1: person shooter game that a company called three D Realms
Speaker 1: originally announced in nineteen ninety seven. They'll keep in mind
Speaker 1: when studios announce a game, it typically means that they've
Speaker 1: already been working on it for a while, so they
Speaker 1: announced it in nineteen ninety seven, but the game wouldn't
Speaker 1: actually come out until two thousand and eleven. Now, video
Speaker 1: games can take a long time in development, but fourteen
Speaker 1: years is atypical, although Star Citizen might catch up in
Speaker 1: a couple of years if they don't have a full
Speaker 1: game released before then. And one of the many problems
Speaker 1: that was causing a lot of these delays was feature creep. See.
Speaker 1: While the team at three D Realms was working on
Speaker 1: the game, other companies were releasing updated game engines that
Speaker 1: supported more features, so you could build on the game
Speaker 1: engine you were depending upon already and continue building out
Speaker 1: your game. But the fear was that when Duke Nucom
Speaker 1: would release, it would look dated against games that were
Speaker 1: created on the more recent game engines. So you get
Speaker 1: the head of the project who suddenly demands that the
Speaker 1: team swaps to a different game engine, a more recent one,
Speaker 1: and that necessitates starting from scratch for most aspects of
Speaker 1: the game, like almost all the assets needed to be
Speaker 1: redone in order to work with this new game engine,
Speaker 1: and it sets the entire development process back to the beginning.
Speaker 1: Then you would have times where the leader of the
Speaker 1: project would want capabilities that were starting to show up
Speaker 1: in other games to then be incorporated into Duke nukeomb forever,
Speaker 1: when that had not been a consideration earlier in development.
Speaker 1: So as a result, the game was constantly going through development,
Speaker 1: then revisions, and sometimes complete restarts, and by the end
Speaker 1: of it all, I think it was pretty safe to
Speaker 1: argue that the game was filled with non essential complexity.
Speaker 1: And of course, by the time it finally published under
Speaker 1: a different company. At that point, because it had changed hands,
Speaker 1: it was no longer really a relevant game to the
Speaker 1: sensibilities of most gamers. You know, the even if the
Speaker 1: gameplay had been stellar and free of things like bugs
Speaker 1: and other issues. The tone of the game no longer
Speaker 1: fit what people wanted anymore because more than ten years
Speaker 1: had gone by since the game had been announced, and
Speaker 1: people's tastes in gameplay and game tone had changed in
Speaker 1: that time. So feature creep really was a huge problem
Speaker 1: for that game. Well, here's another concept that Simplicable includes
Speaker 1: as a fundamental principle of technology, the creativity of constraints.
Speaker 1: This one really speaks to me. Basically, this idea says
Speaker 1: it is much easier to be creative and innovative when
Speaker 1: you're working within some form of constraint, because constraints drive decisions,
Speaker 1: and if you are without constraint, you have no limiting
Speaker 1: factors that make it necessary to decide to go one
Speaker 1: way versus another. Any decision you make appears to be
Speaker 1: as valid and viable as any other decision you could make,
Speaker 1: because there's nothing pushing back against you. And that can
Speaker 1: mean you just end up spinning your wheels a lot
Speaker 1: and you don't really make any progress. Constraints can be
Speaker 1: pretty much anything. Budget is probably the big one, right.
Speaker 1: Usually you're working within some sort of budget, and that
Speaker 1: means at least in theory, you can't make decisions that
Speaker 1: would require more money than the budget allows. Obviously, lots
Speaker 1: of projects go over budget, but the budget is meant
Speaker 1: to serve as that constraint. A deadline is another constraint
Speaker 1: you might face. You know, you have to finish your
Speaker 1: task by some appointed time. But there can be lots
Speaker 1: of other types of constraints, even in tech. Some of
Speaker 1: them could be technological constraints, like it's just physically not
Speaker 1: possible for you to go beyond a certain level of
Speaker 1: performance because of the limitations of technology. There can be
Speaker 1: material constraints. Maybe you know you can't go further in
Speaker 1: any particular direction because the materials that you can use
Speaker 1: have their own physical limitations, and if you were to
Speaker 1: try and push beyond that, you would break the device
Speaker 1: or whatever it might be. You can have social constraints,
Speaker 1: maybe there are things that are not socially acceptable that
Speaker 1: you back away from with decisions as you're making. You know,
Speaker 1: this technology. There could be legal constraints. Maybe there are
Speaker 1: regulations or laws that mean that you can't do certain things,
Speaker 1: and that means you have to come up with creative
Speaker 1: solutions to get your technology to work. Properly while still
Speaker 1: being within that legal framework. So with constraints, you end
Speaker 1: up saying, I need to do X, that's my goal.
Speaker 1: But meanwhile, AB and C are all in my way,
Speaker 1: So how can I achieve my goal? And you start
Speaker 1: problem solving, and the problem solving shapes not just how
Speaker 1: you get around those challenges. That problem solving actually shapes
Speaker 1: the end product itself. The thing you make in part
Speaker 1: is a reflection of the constraints that you encountered while
Speaker 1: you were making it. But if you don't have constraints,
Speaker 1: then you don't have those guidelines, right, You don't have
Speaker 1: anything to push against, no hard edges that you're gonna
Speaker 1: bump up against and have to work around, and honestly,
Speaker 1: that can stifle creativity. That particular concept really rings out
Speaker 1: to me because I've encountered it myself when I've played
Speaker 1: certain types of video games, right Like, there are big,
Speaker 1: open world video games that are exploration based and there's
Speaker 1: very little direction, and that can feel too vast. I
Speaker 1: feel like I'm not really doing anything. And then there
Speaker 1: are smaller, more modest games. They might be much more
Speaker 1: directed or have very defined goals that you need to achieve,
Speaker 1: and those really resonate with me because I feel like
Speaker 1: I'm making progress as I play it. Now, this is
Speaker 1: not to say the big open world games with very
Speaker 1: little direction are bad. They're not bad, and the people
Speaker 1: who love them are not bad people. They're not wrong
Speaker 1: for loving them. It's just something that fundamentally doesn't work
Speaker 1: with the way my brain works. And so for me,
Speaker 1: those constraints really are important because they provide structure, and
Speaker 1: with that structure, I can then feel if I'm doing
Speaker 1: well or not well. Without structure, I don't know that,
Speaker 1: and then I start tumbling into an existential crisis. And y'all,
Speaker 1: you've heard enough episodes of this show. You know nobody
Speaker 1: wants that. Okay, we're going to come back in just
Speaker 1: a moment and talk about one other principle that simplicable identifies.
Speaker 1: Keeping in mind they have others than the ones I've
Speaker 1: just mentioned, and we'll finish off this episode from there.
Speaker 1: But first, let's take another quick break to think our sponsors. Now,
Speaker 1: as I mentioned at the top of this episode, I
Speaker 1: was just kind of surfing around the web, which dates
Speaker 1: me right, using terminology like that. That's fine. I'm an
Speaker 1: old man, I get it, and I found this simplicable
Speaker 1: blog which I had never seen before, and I started
Speaker 1: reading this article about the different fundamental principles of technology,
Speaker 1: and this one also really stood out to me because
Speaker 1: I think it's one that we can easily contextualize right
Speaker 1: now based upon things that are playing out at this
Speaker 1: very moment. And that is the principle of cultural lag.
Speaker 1: And again this is these are things that surround technology
Speaker 1: and technological development. Right We're not talking about the actual
Speaker 1: things that make the technology work. So what is cultural lack? Well,
Speaker 1: it's pretty much what it sounds like. It's essentially when
Speaker 1: technology outpaces society in some way. Technology or the things
Speaker 1: that the technology introduces, like the possibilities the technology creates
Speaker 1: are ones that society lacks the facility to handle. So
Speaker 1: I would argue, right now, we're really seeing this with
Speaker 1: generative AI and then artificial intelligence in general, because keep
Speaker 1: in mind, generative AI is one application of artificial intelligence.
Speaker 1: Generative AI is a type of AI, but not all
Speaker 1: AI is generative AI. Right, all cats are mammals, but
Speaker 1: not all mammals are cats. So generative AI has some
Speaker 1: potential applications that society is just not prepared to handle.
Speaker 1: Everything from copyright infringement, to plagiarism, to the capacity to
Speaker 1: generate and disseminate misinformation. All of these are issue with
Speaker 1: generative AI that we just don't have the ability to handle,
Speaker 1: or even being able to differentiate between something that was
Speaker 1: created by generative AI versus something that was created by
Speaker 1: a person. We're not really able to handle that either.
Speaker 1: And again, artificial intelligence in general also falls into the
Speaker 1: category of a technology that we have you know, cultural
Speaker 1: lag associated with it. So often I talk about this
Speaker 1: within the context of legislation as various politicians and leaders
Speaker 1: around the world struggle with the challenges created by technological
Speaker 1: innovation and how can they take advantage of that innovation,
Speaker 1: how can they try not to stifle innovation, but at
Speaker 1: the same time, how can they protect the people and
Speaker 1: institutions of a country from harm based upon what this
Speaker 1: technological innovation can do. And we're even still seeing it
Speaker 1: here in the United States with regard to like base
Speaker 1: principles of what the Internet in general and the Web
Speaker 1: in particular allow, right, I mean, that's why we get
Speaker 1: arguments about stuff like Section two thirty here in the
Speaker 1: United States. There's a cultural lag that is significant because
Speaker 1: keep in mind section two thirty. Section two thirty is
Speaker 1: what protects online platforms from being held liable for the
Speaker 1: content that users post to those platforms. Right, Like, if
Speaker 1: you were solely responsible for the content that goes up
Speaker 1: on a website, all the content that goes up on
Speaker 1: the website comes from you, and you start posting stuff
Speaker 1: that's illegal, well, logic dictates you should be able to
Speaker 1: be held accountable for posting illegal material. You posted it,
Speaker 1: you created it, you posted it, you're the one responsible.
Speaker 1: But if instead you create a website that allows anyone
Speaker 1: to post there, and some other person you've never heard of,
Speaker 1: you don't know them, you've never met them, they come
Speaker 1: to your website and they post something illegal, section two
Speaker 1: thirty would protect you from being held accountable for the
Speaker 1: thing that this other person did. You provided the space,
Speaker 1: but you didn't create the content. And section two thirty
Speaker 1: itself has got some limitations. You're supposed to at least
Speaker 1: put forth reasonable effort to remove illegal material, or else
Speaker 1: you can lose the protection of section two thirty anyway.
Speaker 1: All of this was worked out as part of the
Speaker 1: Communications Decency Act of nineteen ninety six, the year before
Speaker 1: three D Realms announced the development of Duke Nukem forever.
Speaker 1: So it was nineteen ninety six when Section two thirty
Speaker 1: was first written into law, and we're still struggling with
Speaker 1: it today. You still have people on either side of
Speaker 1: the political ideologies who want to either eliminate Section two
Speaker 1: thirty or to amend it significantly for very different ideological reasons.
Speaker 1: But you know, there's this agreement that on both sides
Speaker 1: that it's not what they want, and that shows a
Speaker 1: cultural lag that's really significant. I mean, we tried to
Speaker 1: acknowledge it back in ninety six, and more than a
Speaker 1: decade later, more than a decade and a half later,
Speaker 1: we're still trying to grapple with it. That's a significant
Speaker 1: cultural lag. Now, there are several other topics that Simplicable
Speaker 1: lists as foundational principles of technology. I'm not sure that
Speaker 1: I agree with that classification in every case. I think
Speaker 1: they are things that relate to technology and are to
Speaker 1: varying degrees important. I don't know if I would call
Speaker 1: them fundamental principles. However, I think all of the ideas
Speaker 1: are well worth discussing, and I will likely do another
Speaker 1: episode on this in the future because I find it
Speaker 1: really interesting. To think about these concepts and observations and
Speaker 1: how do they interact with our approach to technology. And
Speaker 1: there are tons more that they list, so we'll we'll
Speaker 1: get to those in another episode if you'd like to
Speaker 1: read up on them, by the way, and just to
Speaker 1: see what Simplicable lists as fundamental principles of technology, as
Speaker 1: well as all the other stuff that's unsipplicable. The url
Speaker 1: is just simplicable dot com. That's s I M P
Speaker 1: L I C A B L E dot com. Now
Speaker 1: full disclosure, I do not have any connection to that site.
Speaker 1: I didn't know it existed before today. I don't know
Speaker 1: anyone who writes for it. I just stumbled across it
Speaker 1: by chance and thought that the pages about, you know,
Speaker 1: these foundational principles of technology were really interesting and there's
Speaker 1: tons more on the site as well, so if you're
Speaker 1: so inclined, you should check it out. I'm very thankful
Speaker 1: that I came across them because it gave me a
Speaker 1: lot to think about. And as I said, I don't
Speaker 1: agree with all the conclusions made by Simplicable, but I
Speaker 1: think it ends up being kind of find details that
Speaker 1: are arguably subjective. So it could just be because my
Speaker 1: point of view is slightly different, but it ultimately may
Speaker 1: mean that we're both arguing the same thing, we're just
Speaker 1: doing it in slightly different terms. So again, no slight, unsimplicable.
Speaker 1: I think the goal is really an ideal one. They
Speaker 1: want to produce informative, straightforward and objective information to help
Speaker 1: educate people, which I think is a great thing to do.
Speaker 1: Certainly I strive to do some of those things, but
Speaker 1: not all of them, at least not all the time.
Speaker 1: All Right, Well, that's it for this episode. Like I said,
Speaker 1: I'll do another one coming up. Also, I've got a
Speaker 1: lot of travel coming up in the near future where
Speaker 1: I'll be recording remotely. Got a really exciting opportunity to
Speaker 1: record an interview in a studio that's in Las Vegas,
Speaker 1: which I will be doing pretty soon, so be on
Speaker 1: the lookout or listen out for those. We've got some
Speaker 1: more episodes of Smart Talks with IBM that are going
Speaker 1: to publish in the near future in this feed, and
Speaker 1: also an episode of The Restless Ones, the show that
Speaker 1: I host where I talk with various chief officers usually
Speaker 1: CIOs or CTOs of companies to kind of get insight
Speaker 1: into their leadership. Process and their approach to technology. We'll
Speaker 1: have one of those episodes published in this feed in
Speaker 1: the not too distant future as well, says you can
Speaker 1: hear my other work besides the stuff that I do
Speaker 1: here for tech Stuff, I'm still the same Dufiss no
Speaker 1: matter what where you put me, So no fear there,
Speaker 1: but I wanted to give you the heads up on that.
Speaker 1: And yeah, this month turned into at least the back
Speaker 1: half of this month has turned into something that's far
Speaker 1: busier than I had originally anticipated when the month started,
Speaker 1: so I wanted to just kind of give a shout
Speaker 1: out and make you all aware of what was going on.
Speaker 1: All right, that's it. I'm getting out of here. I
Speaker 1: hope you are all well, and I'll talk to you
Speaker 1: again really soon. Tech Stuff is an iHeartRadio production. For
Speaker 1: more podcasts from iHeartRadio, visit the iHeartRadio app, Apple Podcasts,
Speaker 1: or wherever you listen to your favorite shows.