Speaker 1: Get technology with tech Stuff from stuff dot Com. Hey there,
Speaker 1: and welcome to Tech Stuff. I'm your host, Jonathan Strickland,
Speaker 1: together once again reunited with Scott Benjamin who was joining
Speaker 1: me today in the studio. Thanks Scott reunited. Isn't there
Speaker 1: a song? Reunited? It feels so good? Yeah, that's it. Yeah,
Speaker 1: that's the one. Thanks for having me. I appreciate it.
Speaker 1: And we're going to tackle a couple of different stories
Speaker 1: that have been in the news over the past several
Speaker 1: weeks now as at the time we're recording this, obviously
Speaker 1: the episode will publish a little bit later, but we
Speaker 1: wanted to talk about some stuff that has to do
Speaker 1: with artificial intelligence, with autonomy, with vehicles, and also just
Speaker 1: a robots in general. So we're gonna start with probably
Speaker 1: the more sobering of the two stories, the story about
Speaker 1: Tesla Auto Pilot um and specifically the fatal accident that
Speaker 1: have and on May seventh, two thousand sixteen, involving Joshua Brown,
Speaker 1: And and what does that mean? What do we know
Speaker 1: about the accident as of the recording of this show,
Speaker 1: What does it mean for for autonomous vehicles? Why, why
Speaker 1: does Tesla maintain that Tesla autopilot isn't autonomous. We're gonna
Speaker 1: get into all those details, but first I just want
Speaker 1: to give a quick kind of layout of the order
Speaker 1: of events. So the accident happened on May seven, six
Speaker 1: in Florida. UM Joshua Brown was in a vehicle Tesla
Speaker 1: Model S that what had autopilot engaged, and I was
Speaker 1: traveling eastward down the highway when a semi truck was
Speaker 1: turning left. The semi truck was traveling westward down that
Speaker 1: same highway, turning left to cross onto another street, which
Speaker 1: meant that the semi truck's trailer was crossing the traffic
Speaker 1: that Joshua's car or the direction that Joshua's car was
Speaker 1: going in. UH. Neither the car nor Joshua appeared to
Speaker 1: detect the trailer. They didn't see it, didn't react to it,
Speaker 1: and so there was a collision. We'll get more into
Speaker 1: more details about the collision a little bit, and UM
Speaker 1: Mr Brown passed away due to that. He died from
Speaker 1: his injuries. The Tesla actually released information to the National
Speaker 1: Highway Traffic Safety Administration about a week and a half
Speaker 1: after it happened, giving them the details of the accident.
Speaker 1: UH just a couple of days later, they held a
Speaker 1: big shareholder meeting that's gonna come into play a little bit.
Speaker 1: And then it wasn't until June that Tesla posted a
Speaker 1: blog that acknowledged and disclosed this accident. And so this
Speaker 1: is kind of it's kind of a multi tiered thing
Speaker 1: that we're gonna chat about, not just the technology, uh,
Speaker 1: not just what kind of of effect is this going
Speaker 1: to have on the on on driver assist systems and
Speaker 1: and autonomous vehicles moving forward, but also the implications some
Speaker 1: people have raised saying that perhaps Tesla was trying to
Speaker 1: hide the fact that there was this accident in light
Speaker 1: of the fact that we're going to have a shareholder
Speaker 1: meeting and and offer more stocks. They raised like one
Speaker 1: point four billion dollars in stocks. So we're gonna attack
Speaker 1: all of that. So the start, Scott, how would you
Speaker 1: describe Tesla autopilot? Tesla autopilot? Okay, so I guess you
Speaker 1: can't call it autonomous, right, That's the first thing we
Speaker 1: need to get out of the way. It's it's a
Speaker 1: legality issue. And we've talked about this, I think on
Speaker 1: other podcasts that I've been here for sure tech stuff
Speaker 1: certainly on car stuff and the it's it's again it's
Speaker 1: a legal issue because you can't say autonomous because that
Speaker 1: indicates that there doesn't necessarily have to be a driver
Speaker 1: in place behind the wheel. And again it's just a
Speaker 1: it's a word thing. It's a word play thing right now,
Speaker 1: because most major manufacturers have autonomous like systems in the works,
Speaker 1: autopilot like systems in the works um or they already
Speaker 1: have them implemented, but they have a strict rule that
Speaker 1: a driver has to be you know, in the driver
Speaker 1: position at all times, ready to take control at any time.
Speaker 1: And some of them even say that you have to
Speaker 1: have hands on the wheel, as did the test La situation.
Speaker 1: Here the Tesla, when you agree to enter autopilot mode,
Speaker 1: you you have to I don't know, if you click
Speaker 1: on something on that giant screen that they have essentially
Speaker 1: like in terms of service saying like you are acknowledging
Speaker 1: that in order to have autopilot on, you are supposed
Speaker 1: to keep your hands on the wheel as well as
Speaker 1: maintain alertness to your surroundings, not just you know, not
Speaker 1: just shut down and allow the card to take over. Okay,
Speaker 1: we have more to say about that as we go
Speaker 1: here too, because you'll find that there's a lot of
Speaker 1: shenanigans that go along with with people in autopilot mode
Speaker 1: that shouldn't be happening because of this terms. You know, this,
Speaker 1: this term of agreement that you sign, and so Mr
Speaker 1: Brown had agreed to that, and then we will later
Speaker 1: find out that he was in a negligence of that.
Speaker 1: And listen, I want to also get this out of
Speaker 1: the way too, is that we were not here to
Speaker 1: point fingers at the dead guy or any by any means.
Speaker 1: But um, as we go through this and see if
Speaker 1: you agree with this as we talk here, but um,
Speaker 1: I really feel that Tesla is not necessarily in the
Speaker 1: wrong here, right, and I don't I feel it's more
Speaker 1: the fault of the driver himself than it is Tesla
Speaker 1: by by all means. Right, Let's let me see if
Speaker 1: you if you think this is fair. I would I
Speaker 1: would say that over the last decade, really a couple
Speaker 1: of decades, we've seen more automated systems or driver assist
Speaker 1: systems come into play. Some are are pretty you know,
Speaker 1: still rely entirely upon human input. Like I would argue
Speaker 1: power steering falls into that kind of category. It's the
Speaker 1: car itself is not taking over any steering in power steering.
Speaker 1: But that's a driver assist feature. It's helping someone operate
Speaker 1: a vehicle without having to do ridiculous amounts of turning
Speaker 1: a wheel in order to actually do what you need
Speaker 1: to do. Sure, we've seen so many of these in
Speaker 1: the past, I mean in the recent past, I guess
Speaker 1: with with lane keep systems. You know that that's part
Speaker 1: of the autonomous system that we're talking or almost said,
Speaker 1: the driver assist system talking about from Tesla, the autopilot um.
Speaker 1: You know it. It maintains the lane, It maintains a
Speaker 1: distance between the vehicle in front of it and uh
Speaker 1: and and tries to keep that at a reasonable I
Speaker 1: would believe that you would be able to set the
Speaker 1: distance that you want, or maybe it doesn't based on
Speaker 1: a calculation of your speed versus the distance it needs
Speaker 1: to break right, like like that basic rule of thumb
Speaker 1: that you should be able to count to three when
Speaker 1: you see the vehicle ahead of you passes something like
Speaker 1: a lamp. Yeah, and then you street lamp, you count
Speaker 1: you know, one, one thousand, two and thousand or three,
Speaker 1: you know, and there's a there's a just kind of
Speaker 1: a general rule of thumb. As you said, you know
Speaker 1: that that uh, you know, at this speed, you have
Speaker 1: this amount of time time in order to react, and
Speaker 1: that's just something that humans need. I suppose it's a
Speaker 1: little faster. Of course for an autopilot system that can
Speaker 1: it can do things a lot quicker, although it has
Speaker 1: to do so in a way that's safe and isn't
Speaker 1: going to injure a person. So in other words, like
Speaker 1: technically you could have a a a computer system follow
Speaker 1: a little closer to a car and be able to
Speaker 1: react faster, but momentum is still a thing. And what
Speaker 1: about the driver behind you? Exactly? Yeah, behind got the
Speaker 1: human driver behind you, so they may not be able
Speaker 1: to react that quickly. And you also have the issue
Speaker 1: of when you come to a stop, you've got so
Speaker 1: much mass, you've got so much momentum built up that
Speaker 1: even if your car is capable coming to a stop
Speaker 1: at that at that reduced distance between you and the
Speaker 1: person in front of you, they're still going to be
Speaker 1: a very measurable uh effect on the person sitting in
Speaker 1: that car. It's gonna you're gonna be jerked around a lot. Yeah,
Speaker 1: and this wasn't necessarily the case with this crash. You
Speaker 1: know it wasn't this is a truck. You have to
Speaker 1: imagine what it would be like if a semi truck
Speaker 1: was crossing your path in front of you, I mean
Speaker 1: perpendicular to the road right, almost like you're coming up
Speaker 1: to a crossroads and there's a semi truck going going
Speaker 1: perpendicular ninety degrees from where you're going. Yeah, the cab
Speaker 1: has passed in front of you. You're now at that
Speaker 1: part of the trailer where there's nothing below it but
Speaker 1: the cab or the trailers above you, and the rear
Speaker 1: wheels have yet to cross the road. So that's the
Speaker 1: position where this was. This was when Mr Brown went
Speaker 1: underneath the trailer, and so you you know the you
Speaker 1: you're thinking, well, how come he neither he nor the
Speaker 1: car detected this. Well, there are a couple of different
Speaker 1: things that people have said so far. One was that
Speaker 1: the sky was brightly lit that day, that the trailer
Speaker 1: itself was white, and therefore it was more difficult to
Speaker 1: differentiate between the trailer and the sky. Uh So, from
Speaker 1: just an optical standpoint like then the dual spectrum, it
Speaker 1: was hard to see well for the computer to understand
Speaker 1: that I mean, you would see a truck in front
Speaker 1: of you if you had your eyes on the road.
Speaker 1: That's That's the other part of this is that the
Speaker 1: human element, I believe, and as we get as we
Speaker 1: go through here, I think you're going to see more
Speaker 1: and more that my my, my thoughts on this whole
Speaker 1: thing are that he wasn't watching at all. I mean,
Speaker 1: there was no there were no eyes up on the
Speaker 1: road at all. This was completely an autopilot mode and
Speaker 1: he was hands off for the whole thing. Because if
Speaker 1: he were hands on, it is hard to imagine how
Speaker 1: he could not have seen the truck simply because you're
Speaker 1: talking about him traveling eastward. It was in the afternoon,
Speaker 1: so the sun should be behind him, not in front
Speaker 1: of him, so he shouldn't shouldn't have sun in his eyes.
Speaker 1: But it's gonna be bright on the trailer, if it's
Speaker 1: a white trailer, it's gonna be bright against that bright sky.
Speaker 1: And I can see how that would be difficult to
Speaker 1: differentiate between you know that in the sky for the computer,
Speaker 1: I guess, you know, if there's no chrome trim or
Speaker 1: anything that you know that makes a um some type
Speaker 1: of delineation that says this is the beginning of another
Speaker 1: chick and they can and then can detect it. It's
Speaker 1: also moving all Another thing that this is all hinges
Speaker 1: on is that there's an eyewitness report that came out
Speaker 1: in early July on a site called Teslaaratti and it's
Speaker 1: a it's kind of just a compliment compilation of Tesla news,
Speaker 1: you know, of all all news, you know, SpaceX, Tesla Motors,
Speaker 1: Investor News, etcetera. And one of the witnesses to this accident,
Speaker 1: in addition to the truck driver, which we'll hear from
Speaker 1: in just a minute, said that prior to this accident,
Speaker 1: this is crazy, the Model S was on the same
Speaker 1: road as this person, this this woman driver. She was
Speaker 1: on us A in Florida, and the Model S on
Speaker 1: on autopilot at that time, passed her while she was
Speaker 1: driving at eighty five miles per hour. So he's going
Speaker 1: in excessive eighty five miles per hour, where let's just
Speaker 1: say it's it's a ballpark one hundred miles an hour.
Speaker 1: Have you ever seen what happens to car when it
Speaker 1: crashes a hundred miles per hour? It's it's devastating. I mean,
Speaker 1: you've got to keep in mind that most crash tests
Speaker 1: that are done are done at a much much lower speed,
Speaker 1: and yet they're dramatic in the outcome. Yeah, you would
Speaker 1: be shocked to see what kind of damage that happens.
Speaker 1: And let's says, you know, a side impact collision, you know,
Speaker 1: those those really dramatic ones where the whole the car
Speaker 1: seems to bend in half in the car enters the
Speaker 1: other vehicle. Practically that that's happening somewhere around thirty five
Speaker 1: thirty thirty five miles per hour. This is this is
Speaker 1: a car traveling at one hundred miles per hour, let's
Speaker 1: say more than five to be fair, more than any
Speaker 1: for sure. And uh and of course at that point
Speaker 1: of the trailer which we're talking about it, what happened
Speaker 1: was it sheared the roof off of the vehicle. And
Speaker 1: I think we can all understand what that probably means
Speaker 1: to the driver of that vehicle. It's horrific. So beyond that,
Speaker 1: the car continued on, and it didn't continue on a long,
Speaker 1: long distance. And I'm looking at a diagram that was
Speaker 1: drawn up here of the crash investigation scene, and it's
Speaker 1: not the scale or anything, but the car doesn't go
Speaker 1: a whole lot farther in its in its own lane.
Speaker 1: It did veer off the road, went through one fence
Speaker 1: or went through a ditch, went through a fence, went
Speaker 1: across the field, through another fence and into a pole,
Speaker 1: so to ditch. Two fences and a pole, and that's
Speaker 1: where it came to rest. Is After that it kind
Speaker 1: of rotated to arrest. Um the truck. The driver of
Speaker 1: the truck said that it all happened so fast that
Speaker 1: by the time he didn't even I don't even know
Speaker 1: if he felt the impact, of course, but by the
Speaker 1: time he even checked his mirrors, the vehicle was already
Speaker 1: beyond you know, the impact site. He couldn't he could
Speaker 1: even pick it up. He couldn't spot it, um other
Speaker 1: than looking, you know, I guess at this point he
Speaker 1: had to look to his left to see it out
Speaker 1: in the field somewhere. Um, it's moving, it's traveling that fast.
Speaker 1: So there's this disconnect between what what happened in that
Speaker 1: vehicle just seconds before the the the crash, the impact,
Speaker 1: and what happened. And you know, I don't know if
Speaker 1: I should say it that way. Maybe there's a I
Speaker 1: guess just not enough information out there, like what was
Speaker 1: happening in the car beforehand. It's not disconnected. It's just
Speaker 1: we just need to know more information and we don't
Speaker 1: quite yet. Yeah, the fact that you know, you had
Speaker 1: you had different eyewitnesses saying that, like one saying that
Speaker 1: there was a portable DVD player with a screen showing
Speaker 1: a Harry Potter movie. That someone else said there was
Speaker 1: a portable DVD player inside the car, but it wasn't
Speaker 1: actually running at the time. Can I tell you something,
Speaker 1: What's that The driver of the truck who went to
Speaker 1: check on this driver out in the field as he approached,
Speaker 1: he said that he did hear a Harry Potter movie playing,
Speaker 1: but did not see it. But that's the way he
Speaker 1: that's the only way that he was able to discern
Speaker 1: that it was a Harry Potter movie. He could hear
Speaker 1: the audio from that, because I guess it's and if
Speaker 1: you saw the wreck, it's a mangled mess. It's it's
Speaker 1: a it's a horrific car crash scene. Um. But he
Speaker 1: was one of the first people on the scene, of course,
Speaker 1: and he did, in fact here a Harry Potter movie playing.
Speaker 1: So it appears, at least from the limited information that
Speaker 1: we have it appears that that this was a case
Speaker 1: where the person behind the wheel was not following the
Speaker 1: directions stated specifically under engaging the autopilot that you you know,
Speaker 1: need to have your full attention on the road and
Speaker 1: have been ready to take over. Um, that's what it
Speaker 1: looks like. Also, we should say that, yes, the optical
Speaker 1: camera system failed in that it did not recognize the
Speaker 1: fact that there was a truck crossing its path, which
Speaker 1: is that's pretty dramatic. But some people have said, well
Speaker 1: aren't there backups, like beyond optical, wasn't their radar? Well, yeah,
Speaker 1: and as radar. Here's the thing, though, the trailer is
Speaker 1: off the ground right, it's it's above the ground because
Speaker 1: you've got that space between you know, where the chassis
Speaker 1: is and the trailer a part. And the problem is
Speaker 1: that the radar system can misinterpret that to be an
Speaker 1: overhead sign because it's it's detecting a surface, a flat
Speaker 1: surface that's above the ground. And Tesla autopilot essentially ignores
Speaker 1: those because if it did, and every time we went
Speaker 1: down the highway, your car would start to break every
Speaker 1: time you start to approach an overhead sign. If it
Speaker 1: has identified that as a potential collision could be a
Speaker 1: real problem. Yeah, it could mean that you're actually causing
Speaker 1: accidents because you're you're hitting the brake on a highway
Speaker 1: when everything is perfectly fine. Uh So, I mean you
Speaker 1: could argue that maybe this this was at least partly
Speaker 1: a failure of technology in the sense that the optical
Speaker 1: cameras did not pick up the truck. Or it could
Speaker 1: be that the car was just traveling so fast that
Speaker 1: even even at that advanced speed that computers can react to,
Speaker 1: it would not have been able to react fast enough
Speaker 1: at detecting the truck and being able to do anything
Speaker 1: about it. Now you're hitting out. Something that I wanted
Speaker 1: to to make clear here too, is that when we
Speaker 1: first talked about this, when we first heard about this ourselves,
Speaker 1: I have thought that I had imagined that this vehicle
Speaker 1: continued on down the road and you know, the autopilot
Speaker 1: remain engaged, and um, you know, it was it was
Speaker 1: like it was almost like a ghost car, ghost ship
Speaker 1: traveling down the road with no one, no one at
Speaker 1: the wheel of course, And um, I thought I thought
Speaker 1: it was a much greater distance that had traveled after
Speaker 1: the accident. But now that I'm hearing that. You know,
Speaker 1: he's traveling at such a high rate of speed. And
Speaker 1: I look at this diagram now, I know it's not
Speaker 1: to scale, but it's really if if it's anywhere close
Speaker 1: to the way it's drawn here. Um, you know, it's
Speaker 1: not like it's five miles down the road. It's right
Speaker 1: there where this car came to rest. If he's traveling
Speaker 1: that quickly and something like the top is being sheered
Speaker 1: off the car in the grand scheme of things that
Speaker 1: it's not like a full on impact into a wall
Speaker 1: or anything that's that's it's relatively easy to take the
Speaker 1: top off of the vehicle. It's mostly glass and a
Speaker 1: few beams. That's it quickly handled by you know that
Speaker 1: type of speed. So for it to just travel that
Speaker 1: far on its own momentum, it's own you know, the
Speaker 1: chared over velocity. I guess, um, I could see a
Speaker 1: car taking a quarter mile to come to arrest from
Speaker 1: something that that uh, that fast and not quite as
Speaker 1: abrupt as a as a as a dead on him
Speaker 1: packed sure, and you know it's I think we do
Speaker 1: have to stress again. Tesla has always maintained that autopilot
Speaker 1: is really a collection of integrated driver assist systems that
Speaker 1: together make it safer to operate a vehicle, and they
Speaker 1: have data to back that up. The big, the big
Speaker 1: point that they like to mention is the number of
Speaker 1: miles driven by vehicles in autopilot mode without a fatality.
Speaker 1: This was the first fatality of anyone driving a Tesla
Speaker 1: vehicle in autopilot mode, and they say that the cars
Speaker 1: had accumulated something like a hundred thirty million miles of
Speaker 1: travel without having a fatality, which is above average. Right, Yeah,
Speaker 1: because in the United States, again, according to Tesla, they
Speaker 1: cited a number saying that it's nine million miles for
Speaker 1: every particular model of car. That's the that's the average,
Speaker 1: is that every nine million miles driven by a vehicle,
Speaker 1: there's a fatality. Yeah. That's in the US, the US.
Speaker 1: Globally it's different, Yes, sixty it's it's it's sixty million
Speaker 1: miles globally, which is the global numbers. I've got global
Speaker 1: numbers if you want to hear. Yeah, they're huge. Alright.
Speaker 1: So globally auto related deaths per year, one point three
Speaker 1: million people died per year in auto related deaths. And
Speaker 1: that's an It says an average of about it's just
Speaker 1: just under thirty three hundred deaths every single day from
Speaker 1: auto related deaths. Now in the United States, it's significantly less,
Speaker 1: but it's still a high number. Um. It is it's
Speaker 1: estimated in we still have estimate numbers. I think the
Speaker 1: latest year for concrete numbers is probably twenty fourteen or
Speaker 1: thirteen even um it's estimated that thirty eight thousand, three
Speaker 1: hundred people are killed every year in the United States
Speaker 1: alone on the roads, and that's about an average of
Speaker 1: a hundred and five per day. So this is one
Speaker 1: accident that's happened with autopilot, and it gets so much attention,
Speaker 1: it's so much, So much focus has put on this
Speaker 1: one accident because of the autopilot element. That's that's been
Speaker 1: um you know, put out there into the media, and
Speaker 1: a lot of people are of course focused on that
Speaker 1: one thing. And I would guess that Elon Musk is uh,
Speaker 1: you know, kind of scratched his head saying like, well,
Speaker 1: this statistically it's about to happen. I mean, of course,
Speaker 1: we don't want a car that is going to have
Speaker 1: this occur. We don't want it to happen again ever,
Speaker 1: but statistically it's going to happen, and and accidents are inevitable, inevitable,
Speaker 1: and so our fatalities. There's just there's no way to
Speaker 1: create a one death proof vehicle. You can't do it.
Speaker 1: There's always gonna be some wild card that you just
Speaker 1: can't account for. You can't there's no way to anticipate
Speaker 1: every potential scenario. And in fact, that is an important
Speaker 1: thing to point out, is that this this situation, that uh,
Speaker 1: this tragic situation was kind of the perfect storm of
Speaker 1: elements for this accident to have happened. It should in
Speaker 1: most case, it should not have happened. And in fact,
Speaker 1: you know, people have criticized tesla Um. Some of the
Speaker 1: journalists have criticized tesla for uh not just for the
Speaker 1: the fact that autopilot appears to have played a part
Speaker 1: in a fatal accident, never mind the fact that there
Speaker 1: so many other fatal accidents happening with so many other
Speaker 1: vehicles that uh, you know that well, they don't garner
Speaker 1: the attention because this one, because it's not as novel
Speaker 1: an idea as autopilots as the first. But not only
Speaker 1: did they they criticize them for that, but also and
Speaker 1: I can understand this as well, the fact that Tesla
Speaker 1: did not disclose the accident until after it had had
Speaker 1: this shareholder meeting where it had offered more stock and
Speaker 1: made more money. Uh. The company's response was that the
Speaker 1: accidents not material to Tesla's business and in fact, you
Speaker 1: would never expect other automakers to have to do the
Speaker 1: same thing. It's bad optics, you know, it doesn't look good.
Speaker 1: But there's also you know, again there's no precedent for
Speaker 1: this by any this is the first time this has happened,
Speaker 1: which automatically means that there's definitely going to be more
Speaker 1: interest anyway. So I given the fact that it is autopilot,
Speaker 1: I lean a little more toward it might have been
Speaker 1: better for Tesla to get ahead of this rather than
Speaker 1: to talk about it a month more than a month afterward,
Speaker 1: but with a very logical explanation of why it happened
Speaker 1: and that likely will happen again. It's just this is
Speaker 1: simply the first time it's happened. And then also he
Speaker 1: could he could have stressed you know that, yeah, we've
Speaker 1: we've achieved a hundred and thirty million miles to travel
Speaker 1: without a fatality at this point. That's that's again way
Speaker 1: above average. Yeah. In fact, you know, he says like, well,
Speaker 1: if you extrapolate, which, by the way, I'm just gonna
Speaker 1: say what Musk said essentially. But this extrapolation, I completely understand,
Speaker 1: is not uh not an apples to apples kind of thing.
Speaker 1: Must as well, Let's assume that in two thousand fifteen,
Speaker 1: the Tesla autopilot feature were universally available on all vehicles globally. Globally,
Speaker 1: that would mean that there would be five hundred thousand
Speaker 1: fewer deaths in two thousand fifteen due to car accidents.
Speaker 1: I don't quite understand that at all. I mean, okay,
Speaker 1: the global figure that I just gave you is one
Speaker 1: point three million, so I can understand the half of
Speaker 1: that point. But you can't say for sure that an
Speaker 1: autopilot system would have corrected or made adjustments so that,
Speaker 1: you know, half of those people would still be alive.
Speaker 1: But yeah, it's interesting because here I understand how he's
Speaker 1: doing his math. He's saying, globally speaking, there's one fatality
Speaker 1: for every sixty miles driven million sixty million miles driver.
Speaker 1: That's why I'm I'm sorry, that is a very important distinction.
Speaker 1: That's okay, huge, huge factor there sixty million miles driven,
Speaker 1: so one fatality every sixty million miles driven. With Tesla
Speaker 1: autopilot records, there's one fatality for one thirty million miles driven.
Speaker 1: Therefore that the Usla autopilot is twice as safe. Fuzzy math,
Speaker 1: very fuzzy math. But but we get this point saying
Speaker 1: that the driver assist systems, when used properly, are they
Speaker 1: really do improve the safety of a vehicle. So it's true.
Speaker 1: That leads to the the discussion about why are people
Speaker 1: not using this properly, Why are people and whether this
Speaker 1: was the case with Joshua Brown's particular instant or not,
Speaker 1: Like we suspect things, but we don't know for sure.
Speaker 1: But we do know for sure that people have been
Speaker 1: jackasses in Tesla vehicles running on autopilot because their YouTube
Speaker 1: videos of it. Absolutely and unfortunately for for this this case,
Speaker 1: for this guy, uh, there are videos of him engaging
Speaker 1: in some of these activities. I mean, I've seen videos
Speaker 1: of people, not necessarily uh, Mr Brown, but I've also
Speaker 1: seen people you know, that are in traffic and autopilot
Speaker 1: mode taking a nap, or playing cards, or playing guitar,
Speaker 1: not air guitar, but playing guitar, uh, doing all kinds
Speaker 1: of things. I mean just you know, facing sideways instead
Speaker 1: of forward. Um, it's just it's I guess it's fun
Speaker 1: to get online and kind of show what you can
Speaker 1: do other than driving in rush hour traffic. That's that.
Speaker 1: That's the point is is a lot of these videos
Speaker 1: that a lot of these videos are making is that
Speaker 1: look what I'm doing, I'm making use of my time
Speaker 1: aside from just driving home my laptop out, I'm still
Speaker 1: working or whatever the case might be, shopping. Unfortunately, Joshua
Speaker 1: Brown also has some of these videos out there that
Speaker 1: shows him him engaged in some of these activities. And
Speaker 1: you know the thing is these cars, especially the Tesla,
Speaker 1: they have of course engine control modules, lots of modules
Speaker 1: in this one in the Tesla models. That's going to
Speaker 1: tell the tale. That's going to say, it's kind of
Speaker 1: like an event recorder at a black box, if you will,
Speaker 1: for for autmobile, and it's going to, uh, let us
Speaker 1: know what Speedy was traveling, exactly what happened before and
Speaker 1: and after this accident immediately after. It's going to also
Speaker 1: let us know when the last time there was any
Speaker 1: kind of driver input into the system and all this
Speaker 1: can be read via code, and if somebody was careful
Speaker 1: enough to remove those modules properly, which I hope they were,
Speaker 1: will be able to kind of piece this all together,
Speaker 1: you know, in reverse order, and figure out what happened.
Speaker 1: And it may be a while and or possibly even
Speaker 1: never before we hear the details of that investigation, and
Speaker 1: they may may keep that tight. Yeah. So, but it's
Speaker 1: it's again, it's one of those things where we see people, uh,
Speaker 1: disregarding Tesla's very clear message about what autopilot is intended
Speaker 1: to be. I have said a few times this past
Speaker 1: week when talking about the story that part of the
Speaker 1: issue to me is calling the feature autopilot in the
Speaker 1: first place. Not again not assigning blame to Tesla, but
Speaker 1: just saying that I think some people are taking this
Speaker 1: word autopilot and they're thinking it means more than what
Speaker 1: it's supposed to do. We got to think that autopilot
Speaker 1: is really a collection of systems. They're integrated, so it's
Speaker 1: that's pretty cool, but they're they're systems that have been
Speaker 1: found on on high end vehicles for the past few years, uh,
Speaker 1: that are integrated in such a way that almost feels
Speaker 1: like the cars really taking over. But it's not not
Speaker 1: quite there yet, and Tesla has maintained like, no, it's
Speaker 1: not an autonomous type of thing. It could do a
Speaker 1: lot of stuff. And and if your hands are on
Speaker 1: the wheel and you're paying attention, it may feel like
Speaker 1: I don't even need to be here for this to work.
Speaker 1: But but but the reality is that if you see
Speaker 1: a semi trailer trailer in tractor crossing the road in
Speaker 1: front of you, you're going to react by touching the
Speaker 1: brake or swerving to avoid that that vehicle. You're going
Speaker 1: to see it ahead of time. I I just have
Speaker 1: a gut feeling that there were no eyes up in
Speaker 1: this situation. There were no hands on the wheel at all.
Speaker 1: There was probably no driver input for quite some time
Speaker 1: in this case. And I just again just a gut feeling.
Speaker 1: But I mean, just that the way the accident happened,
Speaker 1: I can't see it the other way. And that's of
Speaker 1: course this is all borrowing any kind of medical situation.
Speaker 1: But I think, but I think we would have heard
Speaker 1: that by now if that had been the case, if
Speaker 1: there was like a heart attack or a stroke, or
Speaker 1: a medical situation was so dire that he was unable
Speaker 1: to interact with the vehicle in any way. I think
Speaker 1: that we would have heard about that by now, but
Speaker 1: you never know. I mean, we'll have to let all
Speaker 1: that kind of come out in the wash, and it will.
Speaker 1: But I mean, you gotta understand that this is going
Speaker 1: to happen in other makes and models of cars as
Speaker 1: well that have systems that are autonomous like or you know,
Speaker 1: autopilot like, and that you know, um, the Mercedes that
Speaker 1: will do the same thing, or the bmw s that
Speaker 1: will do the same thing, or the Chryslers or any
Speaker 1: of these cars that can drive themselves in traffic. People
Speaker 1: are going to kind of take that to the extreme
Speaker 1: and and not pay attention. It's like, um, you're just
Speaker 1: taking advantage of the situation, right and the you know,
Speaker 1: there's a very real fear in the technology sphere that
Speaker 1: this will end up creating hurdles for auton amous vehicles
Speaker 1: down down down the road. I didn't want to do
Speaker 1: a pun there, but I wouldn't have did one anyway.
Speaker 1: So but that, yeah, in the future, you're going to
Speaker 1: see some hurdles in the way of autonomous vehicles because
Speaker 1: of this. It's to me, it's it's apples and oranges,
Speaker 1: because an autonomous vehicle, especially if you're taking the route
Speaker 1: that Google is taking, there's no way to interact with
Speaker 1: that vehicle apart from telling it where you want to
Speaker 1: go it there's there are no controls, there's no break,
Speaker 1: there's no accelerator, there's no steering wheel, there's nothing, and
Speaker 1: that in that case, you have to really convincingly demonstrate
Speaker 1: that the technology is robust and capable of responding to
Speaker 1: a myriad of situations, well beyond just the typical traffic
Speaker 1: situations you would run into on a day to day basis,
Speaker 1: but some of the more extraordinary experiences that you could encounter,
Speaker 1: because you know, one day may not be exactly the
Speaker 1: same as the next. You may have one day where
Speaker 1: you're driving to work and everything is pretty much normal,
Speaker 1: and then maybe the next day you try to work
Speaker 1: and who knows, a poultry truck has just spilled a
Speaker 1: big load of chickens all across the road. That happens
Speaker 1: here in Georgia. Let me tell you that happens two
Speaker 1: or three times a year here in Georgia. Yeah, it's
Speaker 1: not that uncommon. Yeah, it's uh. I grew up in Gainesville, Georgia,
Speaker 1: poultry capital of the world. We've got a chicken statue
Speaker 1: in the middle of town. That's not a lie. Um
Speaker 1: and yeah, it happens. It's one of those things where
Speaker 1: but but it's one of those things where you if
Speaker 1: you're programming an autonomous vehicle out in Mountain View, California,
Speaker 1: you're not necessarily thinking, Hey, what happens if chickens are everywhere?
Speaker 1: Do we have a chicken plan? Yeah, that says, but
Speaker 1: that's the source of stuff you have to take into account.
Speaker 1: My my worry is that we're going to see a
Speaker 1: disproportionate response from various UH agencies in in the wake
Speaker 1: of this accident, which again tragic accident. We hate to
Speaker 1: see this happen at all UH and and place a
Speaker 1: level of responsibility that is not merited. Yeah, you know,
Speaker 1: I think in the short term, my gut feeling is
Speaker 1: that you're right. But I think that it won't be
Speaker 1: too long before we get back on this full board
Speaker 1: where a lot of people I mean sad to say
Speaker 1: that they'll do this will become part of Tesla's history,
Speaker 1: you know, and they'll say, well, yeah, that happened, but
Speaker 1: we then ran two million tests in order you know,
Speaker 1: electronic tests in order to prevent that from ever happening again.
Speaker 1: And now that situation won't occur ever again in a Tesla. Now,
Speaker 1: what's the next unusual set of circumstances that will lead
Speaker 1: to a driver death? That's gonna that's gonna be the
Speaker 1: next question. Because you can only do so much. You
Speaker 1: can't foresee every single circumstances. Well, and I and that
Speaker 1: also reminds me, in fact, I should have said this earlier.
Speaker 1: But that's a good point in that the Tesla Autopilot
Speaker 1: is a beta service. It's it's in beta, which means
Speaker 1: that it's in testing mode, it's not the final product.
Speaker 1: And in fact, Tesla takes the data gathered from people
Speaker 1: driving an autopilot mode in order to tweak autopilot and
Speaker 1: make it more effective. So, in other words, this is
Speaker 1: a trial of a program that they're still not legally
Speaker 1: ready to call even autonomous. Yet people are treating it
Speaker 1: as it's autonomous. So it's like it's like two levels
Speaker 1: below that. At least, yes, it's it's it's a level
Speaker 1: where if you are treating it like it's an autonomous car,
Speaker 1: you are you are behaving in a way that I
Speaker 1: would argue as irresponsible. Um. And you know, I'm hopeful
Speaker 1: that this will stories like this will become fewer and
Speaker 1: fewer in number, simply because the improvements in technology have
Speaker 1: us avoid some of these accidents where we never have
Speaker 1: a story, right, Like, you're not gonna tell, hey, seventeen
Speaker 1: more accidents didn't happen today. That's not a story, right
Speaker 1: unless you had some sort of we're definitive proof of it,
Speaker 1: you know who. I want to have autonomous systems or
Speaker 1: autopilot systems every driver around me because recently, I don't
Speaker 1: know if this is a thing everywhere. I would guess
Speaker 1: that it is because it distracted driving with smartphones, et cetera.
Speaker 1: Everything else. Uh, there have been several times in his
Speaker 1: last five seven days, maybe I've had several occasions where
Speaker 1: I've had to make an invasive mover at maneuver as
Speaker 1: the vehicle in front of somebody who is coming up
Speaker 1: and behind me with a device in their hand. And
Speaker 1: it's it's just it's hard to try to maintain focus
Speaker 1: on what I'm doing when I'm having to watch what
Speaker 1: people in the lane next to me you are doing,
Speaker 1: because they're they're constantly you know, two wheels over the
Speaker 1: line or um, you know, someone behind me is just
Speaker 1: every time late, breaking and nearly touching my bumper. It
Speaker 1: drives me crazy. If they had an auto or an
Speaker 1: autopilot system, or even an adaptive cruise control that was
Speaker 1: capable of stopping the vehicle like Mercedes or you know
Speaker 1: BMW have, I would love it myself. I would run,
Speaker 1: remain in control. But for everybody else, I have a
Speaker 1: feeling that what you've just described as something that is
Speaker 1: universally wished for that everybody but me. I think that's
Speaker 1: the way. I know how selfish. That's I'm of the
Speaker 1: everybody period, But you know I don't try. Yeah, well,
Speaker 1: there's something to be said for for that as well.
Speaker 1: You know that. You know, if everybody had the system,
Speaker 1: it would work out that way, right, And there's so
Speaker 1: many that are like that. If if it was one implemented,
Speaker 1: a lot of things would be a lot safer. Yeah,
Speaker 1: a lot more boring boring, you say, but you could
Speaker 1: get to where you're going with less traffic. Is it
Speaker 1: more for yeah, well, you would be able to fill
Speaker 1: your time with entertaining things. Is it more involve being
Speaker 1: in a car more boring or boring. Er, it's more boring,
Speaker 1: more boring. I can tell you what's more boring is
Speaker 1: us debating the word. So yeah, we're gonna wrap that
Speaker 1: part up the discussion. So ultimately, uh, I'm hopeful that
Speaker 1: that Tesla autopilot can continue to evolve over time become better.
Speaker 1: I'm hopeful that more people really take it to heart
Speaker 1: that their level of responsibility has not changed when they
Speaker 1: engage autopilot, that that system is there to improve their safety,
Speaker 1: but not replace them as an actual operator of the vehicle,
Speaker 1: not entirely at any rate. Remain vigilant behind the wheel. Yeah,
Speaker 1: don't don't create more terrible stories like I feel for
Speaker 1: Mr Brown's family and I am. I really wish that
Speaker 1: this story had turned out a different way. And of
Speaker 1: course there's a second story that we could talk about
Speaker 1: that um, but we don't have all the details. There
Speaker 1: was one another accident that happens to life first with
Speaker 1: the Tesla Model X. Yeah, that's right, that's their newest
Speaker 1: first that's the SUV looking vehicle, and that was on
Speaker 1: the Pennsylvania Turnpike. Have you ever been on the turnpike? Yeah,
Speaker 1: you know what it's like. Yeah, my wife's from Pennsylvania.
Speaker 1: So I we've also been on it, and the story
Speaker 1: in that case was that supposedly they had turned on autopilot,
Speaker 1: the vehicle struck a guardrail on the right hand side.
Speaker 1: The vehicle then veered across to the left hand side,
Speaker 1: hit the concrete median in the middle of the road,
Speaker 1: and then flipped over. Yeah, this is crazy because this
Speaker 1: is not like, um, you just simply didn't detect something
Speaker 1: above the road surface. This left the lane. Yeah, so
Speaker 1: that's something totally different. We're going to find out a
Speaker 1: lot more about this one, so we and we don't
Speaker 1: have the details yet. We do know that Tesla initially
Speaker 1: said it doesn't look like autopilot was necessarily involved in
Speaker 1: this particular accident, and then they kind of revised that
Speaker 1: to say that the data so far has not supported it,
Speaker 1: but that they are investigating it. Um And to be honest,
Speaker 1: we don't have the full information. Right, We've got the uh,
Speaker 1: the first hand account of the driver. Both the driver
Speaker 1: and his passenger escaped from They didn't I'm sure they
Speaker 1: were injured, but they were They did not die. Maybe
Speaker 1: cut some bruises or something like that. But yeah, it
Speaker 1: wasn't as quite as a um traumatic I guess as
Speaker 1: the other one was. Of course, so we we don't
Speaker 1: have enough information on that at the time of this
Speaker 1: recording to really dive into was this actually a failure
Speaker 1: of autopilot? Because if this were a failure under totally
Speaker 1: different circumstances, then you have to start asking some pretty
Speaker 1: tough questions about Tesla's technology. Can I just make a guess,
Speaker 1: I'll make a guess. An irresponsible guess is that somehow
Speaker 1: the driver disengaged the system. Because the lane departure system
Speaker 1: is something that's been around for so long and they've
Speaker 1: got it so nailed down, really that something like that
Speaker 1: that part of the of the autopilot system with everything
Speaker 1: else that it has to to think about. If it
Speaker 1: just simply left the lane because it couldn't detect the lane,
Speaker 1: that's that's uh, I don't it seems like something is
Speaker 1: up there? It would you would think it would give
Speaker 1: an alert to the driver to say, like bing or
Speaker 1: something like, hey, you know, make sure you're taking control,
Speaker 1: because you know, I've heard of I've heard of these
Speaker 1: systems having a little bit of trouble at it at
Speaker 1: sunrise and sunset detecting detecting white lines on the road
Speaker 1: because of the glare, and maybe that's a you know
Speaker 1: factor in this. I would imagine such a thing like
Speaker 1: here in Atlanta, if it's if it's been raining, uh,
Speaker 1: and then you get sunshine. It is really hard to
Speaker 1: see some of the lines on some of the roads
Speaker 1: here in Atlanta. I do if I feel. Yeah, so
Speaker 1: when you start feeling that bump of the reflector, Okay,
Speaker 1: that's fair, I got you, all right, But again that's
Speaker 1: all irresponsible speculation. Yeah, exactly. We we don't know. So
Speaker 1: so while we're making some wild guesses here, by the
Speaker 1: time this episode comes out, maybe there'll be more information
Speaker 1: that will be available, and perhaps if if it actually
Speaker 1: is ultimately an autopilot issue, we'll revisit this and talk
Speaker 1: more about it. But for now we're going to transition
Speaker 1: over to a different story. And this was one that
Speaker 1: you brought to my attention, Scott. This um. This this
Speaker 1: p posal that was part of the European parliament um
Speaker 1: where they want to talk about robots and and part
Speaker 1: of the proposal that's got the most attention is the
Speaker 1: concept of electronic personhood for robots. Yeah, and that's what
Speaker 1: I came to you with because I wasn't sure if
Speaker 1: this is going to be in a podcast episode or not.
Speaker 1: I just thought it was kind of an interesting little
Speaker 1: news blurer. But I suppose and and I'll be I'll
Speaker 1: be right up front with you when I say that
Speaker 1: I have more questions about this than answers. Really well, Scott, thankfully,
Speaker 1: I have printed out the entire report and I have
Speaker 1: read it, so I am happy to answer some question.
Speaker 1: Have you? Will you read it to us? Now? Slowly?
Speaker 1: Twenty two pages? Let's begin. Actually, I do want to read.
Speaker 1: I do want to read the first paragraph very briefly,
Speaker 1: because I love it so much. So this is the
Speaker 1: this is introduction section A. Whereas from Mary Shelley's Frankenstein's
Speaker 1: Monster to the classical myth of Pygmalion, through the story
Speaker 1: of Prague's Gulam to the robot of Carol Keepec, who
Speaker 1: coined the word, people have fantasized about the possibility of
Speaker 1: building intelligent machines, more often than not androids with human features.
Speaker 1: I would never have expected that to make it into
Speaker 1: this draft. Not only that's not the only fiction reference
Speaker 1: made in this So a famous, famous fictional piece about
Speaker 1: robotics is mentioned, which is, of course Asimov's Laws of robots.
Speaker 1: Have you heard of Asimov's Laws of robotics? So basically,
Speaker 1: in case you're not familiar, first law is, a robot
Speaker 1: may not harm a human or through inaction, allow a
Speaker 1: human to come to harm. Second law is a robot
Speaker 1: must follow the commands of a human unless it were
Speaker 1: to violate the first law. Third law is a robot
Speaker 1: must protect itself from harm unless it would bring it
Speaker 1: into conflict with one of the first two laws. And
Speaker 1: these are critical in this argument because they're going to
Speaker 1: treat them as if they're human with uh, not only
Speaker 1: not only rights, but also responsibilities. They're going to hold
Speaker 1: them accountable for their actions, which is their program by
Speaker 1: humans at this point. So what what is this? Where
Speaker 1: is this all sort out to here? Because the idea
Speaker 1: that a robot that's in a factory creating a part
Speaker 1: or you know, an automotive part, the idea that that
Speaker 1: is soon to be considered an electronic person. Uh, it's
Speaker 1: it's crazy too. It seems insane to me. But the
Speaker 1: goal here, as we'll talk about in I guess a
Speaker 1: little bit more in depth, is that they'll be taxed,
Speaker 1: they will pay into a social security system that will
Speaker 1: then be drawn from by humans, but not robots. Robots
Speaker 1: don't get social security. Well, yeah, you get compensation, all right,
Speaker 1: So these are these are it's true. I'll tell you
Speaker 1: about they get compensation proposal. I'll tell you we're talking maintenance. No,
Speaker 1: is that a compensation? Really? Know what it is? Their
Speaker 1: Their compensation is money money they get paid. Well, okay,
Speaker 1: so that goes to the owner of the robot. But
Speaker 1: the owner of the robot is the one that's paying
Speaker 1: into the social security right, the owner of the robot pays.
Speaker 1: The owner of the robot pays the robot. Well, this
Speaker 1: sounds like a real screw drive. You want to know why? Alright,
Speaker 1: here's here's here's the reason why this gets so it
Speaker 1: gets clear once you start to understand the logic, because
Speaker 1: at first, on the face of it, you're like, this
Speaker 1: is ridiculous. Why would an owner have to pay in
Speaker 1: for social security for a robot which is never going
Speaker 1: to draw on social Security? Yes, why would you ever
Speaker 1: pay a salary to a robot? Well, the compensation fund.
Speaker 1: First of all, I was being a little unfair. That
Speaker 1: was one possible solution to a very real problem. That
Speaker 1: very real problem being when you get to a situation
Speaker 1: in which a robot causes damage or harm, who is
Speaker 1: liable for that damage or harm? And how do you
Speaker 1: compensate the harmed party? And so one of the arguments
Speaker 1: was the more autonomous a robot is, the more it
Speaker 1: is able to interact with its environment in new ways,
Speaker 1: like use machine learning to adapt to its environment and
Speaker 1: work within that environment, the less liable you can hold
Speaker 1: the manufacturer of that robot if it's not something that
Speaker 1: is directly tied to a very basic function of the robot.
Speaker 1: You could argue, while the robot learned something, it learned
Speaker 1: a poor way of doing that thing, someone or something
Speaker 1: was harmed as a result of that. The robots actually
Speaker 1: at fault, not the producer. This is a self aware issue,
Speaker 1: not even self aware, but so much as like like so,
Speaker 1: let's say there there's a famous thing in Stanford where
Speaker 1: uh computer scientists set up a computer with artificial intelligence,
Speaker 1: and they had to observe a pendulum as it swung
Speaker 1: back and forth. Through observing the pendulum, the computer was
Speaker 1: able to figure out the basic laws of motion just
Speaker 1: by observing the behavior of the pendulum swinging without being
Speaker 1: given any information about the laws emotion. Now extend that
Speaker 1: to an idea for a an artificially intelligent device. It
Speaker 1: doesn't have to be self aware. It just has to
Speaker 1: be able to observe things within its environment and adapt
Speaker 1: to them. Another great example would be let's say you've
Speaker 1: made a robot, and you put a robot on a
Speaker 1: on an assembly line, and the robot needs to put
Speaker 1: together a certain thing. And then as the robot attempts
Speaker 1: to put the thing together, at first, the robots pretty crappy.
Speaker 1: It's not doing it very well. But each time it attempts,
Speaker 1: it tries something a little bit different and starts to
Speaker 1: learn what works better than what worked before. You're not
Speaker 1: actually programming the robot to do this. The robot is
Speaker 1: learning how to do this through trial and error, essentially,
Speaker 1: just as a would on the same line exactly. And
Speaker 1: most of the time the robots we talk about an industry,
Speaker 1: they don't fall into that category. They've been designed to
Speaker 1: do a very specific series of actions repeated repetitively, like
Speaker 1: that's it, that's and that's all they do. They don't.
Speaker 1: They don't start putting together a car and then turn
Speaker 1: around and flip burgers that's not the purpose, the idea
Speaker 1: being with these new robots, they'd be more adaptive and
Speaker 1: could therefore change the way they do things in order
Speaker 1: to try and experiment do something a little more effectively
Speaker 1: if in fact, we get to a further stage where
Speaker 1: robots are able to adapt even beyond that level. Because
Speaker 1: really this proposal is more about we're heading down a
Speaker 1: road eventually we're going to need to have legislation to
Speaker 1: to handle these issues. It would be better for us
Speaker 1: to think about it now than when it becomes necessary,
Speaker 1: like like when a problem happens, we have to figure
Speaker 1: out what to do about it. It's more about anticipating
Speaker 1: those problems, all right, I see now. But then the
Speaker 1: knee jerk reaction to this from a lot of people
Speaker 1: is that, uh, you know, the robots are taking my
Speaker 1: job and also they're they're not paying Social Security and
Speaker 1: so so what's gonna happen in the in the end here,
Speaker 1: we're gonna have a uh, we're gonna have an economy
Speaker 1: collapse because it's gonna be all robotic workers in the
Speaker 1: in the factory or going to have massive amounts of
Speaker 1: unemployment across the board. Um, and no one's paying into
Speaker 1: the system that already can't sustain the number of people
Speaker 1: that have retired or are drawing from that right now,
Speaker 1: what's gonna happen when I'm in that position, because it's
Speaker 1: gonna be an entirely robotic work For this is like
Speaker 1: the the the the just the idea that they have,
Speaker 1: you know, it's not it's not the reality. Really. The
Speaker 1: reality is that as the as the robots are slowly
Speaker 1: being implemented in the workforce, humans are also increasing in
Speaker 1: the workforce, but in different jobs. So the robots maybe
Speaker 1: taking this position away slowly. And I've got a few
Speaker 1: numbers here I can mention in a moment um slowly.
Speaker 1: It's it's happening very slowly for for this um, you know,
Speaker 1: like the end of the world scenario that they're thinking of.
Speaker 1: You know that um not into the world, but you
Speaker 1: know what I mean, Well, yeah, the idea, the idea
Speaker 1: of capitalism folding in on itself. Yeah, And and they're
Speaker 1: they're thinking of it happening almost immediately overnight. And if
Speaker 1: it's something like that did happen overnight, that would be
Speaker 1: horrific for the the economy would collapse almost immediately. It
Speaker 1: would be really really difficult for for the system to
Speaker 1: keep up. So it's a much more it's a it's
Speaker 1: a much slower implementation than what people are thinking it is,
Speaker 1: and and that humans are in fact finding jobs in
Speaker 1: other positions and places that you know then keep them
Speaker 1: gainfully employed. And it's just it's a balance. It's all
Speaker 1: a balance right now. But if things were to happen
Speaker 1: quickly as I said it would, it would throw things
Speaker 1: into turmoil. But it's not happening that way. Yeah, it's
Speaker 1: not happening that way right now. The question is will
Speaker 1: it always be more of a gradual thing or will
Speaker 1: will there be a tipping point? Right like will there
Speaker 1: be a development in robotics and artificial intelligence where we
Speaker 1: get to a tipping point where it's a rapid implement
Speaker 1: intation and deployment of automated systems across multiple jobs. Like
Speaker 1: we are seeing certain jobs get more automation involved in them,
Speaker 1: not all of them stay that way. Sometimes a company
Speaker 1: will go in with an automation strategy and then ultimately decide, hey,
Speaker 1: this is not actually working out the way we thought
Speaker 1: it would, and they back off of it. In other cases,
Speaker 1: we see more and more automation go into that space.
Speaker 1: And so what what this proposal is trying to do
Speaker 1: is say, in the case where perhaps we see more
Speaker 1: jobs going away from automation than our generative through automation,
Speaker 1: we would need to have a method to respond to that.
Speaker 1: Here are some potential ways we could do that. But
Speaker 1: they also actually acknowledge this is not necessarily the case.
Speaker 1: In fact, one of the proposals in the draft is,
Speaker 1: by the way, the draft report, I should read out
Speaker 1: the title Draft Report with recommendations to the Commission on
Speaker 1: Civil Law Rules on Robotics in case you were wondering
Speaker 1: if there were such a thing, uh they in the
Speaker 1: draft if they actually state that one of the things
Speaker 1: that should happen is the European Union should create an
Speaker 1: agency or or a department that actually monitors the number
Speaker 1: of jobs in the EU that are quote unquote taken
Speaker 1: by robots and the number of jobs that are created.
Speaker 1: Because they said, we we lack this right now, we
Speaker 1: don't actually have a dedicated group of people that are
Speaker 1: monitoring these job trends. And and in fact, if we
Speaker 1: continue to see more jobs created than are being taken,
Speaker 1: that becomes a non issue, right like, but we don't
Speaker 1: know is the problem I found those numbers. If you
Speaker 1: want to hear what I want to hear, So well,
Speaker 1: just I guess a precursor to this is that, Um,
Speaker 1: in that same draft you're talking about, the European Parliament draft,
Speaker 1: the Committee on Legal Affairs said that organizations should have
Speaker 1: to declare savings they've made in also savings they made
Speaker 1: in social security contributions by using robotics instead of people
Speaker 1: for tax purposes. So that amount then is going to
Speaker 1: be applied to tax. They're will be taxed on that amount.
Speaker 1: So um, well, okay, anyway, let's move on to this.
Speaker 1: There's no proven correlation between increasing robot density and unemployment.
Speaker 1: That's what I was getting at before, is that By
Speaker 1: pointed out that there's a number of employees in the
Speaker 1: German automotive industry. Um that, in fact, well, the whole
Speaker 1: German automoive industry by rose by thirteen percent between two
Speaker 1: thousand and ten, and rather well, industrial robots stock in
Speaker 1: the industry rose seventeen percent and in the same time period, So, um,
Speaker 1: humans up thirteen percent, robots up seventeen percent. Sure, but
Speaker 1: they're they're right now coexisting. Yeah, and it's not like
Speaker 1: ones declining, the other ones increasing, you know, exponentially. It's
Speaker 1: just they're they're kind of growing at the same rate.
Speaker 1: It's just getting bigger, that's all. And I think I
Speaker 1: think part of the issue here is that some people
Speaker 1: who are commenting on the on the report have probably
Speaker 1: not read it, at least not all the way through,
Speaker 1: because I when I read it, the feeling I got
Speaker 1: was not so much that they were saying, Uh, here's
Speaker 1: the problem that we need to solve right now. It
Speaker 1: was more like people have talked about the possibility of
Speaker 1: this thing happening. If this thing in fact happens, we're
Speaker 1: going to be in trouble unless we plan for that eventuality.
Speaker 1: And they say, here are some ways that we could
Speaker 1: at least have have systems in place to to make
Speaker 1: that transition less painful. And the framework of time that
Speaker 1: they're talking about here is a decade or even decades
Speaker 1: in in reality, because they said it's not going to
Speaker 1: happen overnight like we've been saying. And the other they're
Speaker 1: The quick thing that I want to mention is that,
Speaker 1: as you said, most people haven't really read the draft
Speaker 1: or what it read it really entails, but a lot
Speaker 1: of people right away. Will say, oh, well, my toaster
Speaker 1: can make make toast on its own, and my refrigerator
Speaker 1: knows when I need to stock it because it's a
Speaker 1: smart refrigerator. You're gonna charge my smartphone like that's a
Speaker 1: person as well? Are you gonna you know, tax me
Speaker 1: for uh you know all the devices, my my thermostat
Speaker 1: that knows when I'm coming home and makes it warmer. Uh,
Speaker 1: you know, where does this end? What's the what's the ends?
Speaker 1: Like who's going to be tax and why? Yeah, it's
Speaker 1: it's interesting. They actually in the report mentioned that there
Speaker 1: needs to be a new classification either either the whole
Speaker 1: electronic personhood thing. They said that, uh, once we see
Speaker 1: robots received reach a certain level of sophistication, they have
Speaker 1: gone beyond what we would typically refer to as an
Speaker 1: object like a toaster. They say, yeah, a toaster is
Speaker 1: an object. You're not gonna treat a toaster like it's
Speaker 1: a sentient creature or even even a robot with advanced
Speaker 1: uh you know, artificial intelligence doesn't necessarily mean it's sentient.
Speaker 1: And they aren't even saying we should treat them as sentient.
Speaker 1: They just say we might need to come up with
Speaker 1: a new classification, something that's not human or animal, but
Speaker 1: something with a legal classification to deal with robotics in
Speaker 1: a manner that is consistent with just legal proceedings, because
Speaker 1: there's not anything yet well, and one of those parameters
Speaker 1: would have to be something that directly takes the place
Speaker 1: of a human on an assembly line or in a
Speaker 1: fast food restaurant or you know, wherever it would be.
Speaker 1: It's not it's not something that it's not like a
Speaker 1: device that you use would not be considered like you're
Speaker 1: taking a job away from somebody. You don't have somebody
Speaker 1: your house that makes toast for you, and and now
Speaker 1: the toaster is automatic and it's taking away the toaster's job.
Speaker 1: It's not that way. It's it's it's a device that
Speaker 1: you normally would have to operate manually, but now it's
Speaker 1: just a smart device and it does that for you.
Speaker 1: It's just a it's a handy thing. But it's not
Speaker 1: it's not taking away employment from somebody. Yeah, it's uh,
Speaker 1: I mean, I think that particular idea is one that uh,
Speaker 1: some technologists have really been bandying about as a possibility
Speaker 1: like a decade or two decades out. You know, something
Speaker 1: where we actually see more and more automation and artificial
Speaker 1: intelligence taking the place of jobs and fewer and fewer
Speaker 1: opportunities for humans. It's not like it's something that is
Speaker 1: um imperative right now. But again, I think that the
Speaker 1: people who drafted the report are doing it in a
Speaker 1: way that is fairly responsible in the idea that there
Speaker 1: they are looking ahead, like they actually talk about how
Speaker 1: there they need to look ahead ten to fifteen years
Speaker 1: and and anticipate what skills are going to be needed
Speaker 1: in the job, which is really hard to do. Oh
Speaker 1: my gosh, I was just gonna say this is impossible.
Speaker 1: But because look back fifteen years ago and see where
Speaker 1: we were, it was entirely I mean not not maybe
Speaker 1: fifteen years ago. It looked back thirty years ago, it's
Speaker 1: entirely humans doing all that stuff. And it wasn't and
Speaker 1: there were there may be a few simple, simple robots
Speaker 1: doing things. But look at an automation or you know,
Speaker 1: an automated assembly line now in an auto plant. It's
Speaker 1: unbelievable what they're capable of and the number of robots
Speaker 1: versus the number of humans doing that. But I one
Speaker 1: thing I gotta get out of here is this is
Speaker 1: this This opens up so many boxes of worms in
Speaker 1: that we're not talking about many other things here. This
Speaker 1: is strictly this issue. But uh, there's gonna be the
Speaker 1: whole you know, what are we paying these people to
Speaker 1: do the jobs versus what we pay the robots to
Speaker 1: do the job, which is not really paying them. It's
Speaker 1: it's more like paying for the robot to do the
Speaker 1: job and programming and then maintaining it. And then what
Speaker 1: does it due to the price of the product? And
Speaker 1: why is that in there in the first place, Because
Speaker 1: they want to lower the price of the product by
Speaker 1: not having that human that they're gonna have to pay
Speaker 1: Social Security to for thirty years after retirement. The robots
Speaker 1: don't do that. So there's there's so many layers of
Speaker 1: this that we can argue back and forth, and it
Speaker 1: gets very political, it really does. Yeah, I I imagine
Speaker 1: at least that some of the arguments they've made for
Speaker 1: things like the compensation fund for the robot, that's really
Speaker 1: more of a break glass in case robot goes berserk fund.
Speaker 1: I mean that's really what it's meant for. The compensation
Speaker 1: fund is really meant for a Hey, if your robot
Speaker 1: happens to go biserk one day and rampage down the
Speaker 1: street and slap kids around. You're gonna be paying some money. Well,
Speaker 1: this is this is the safety fund for that. What if?
Speaker 1: So here's here's maybe imagine this scenario. Let's say robot
Speaker 1: that's supposed to in stall the front window, you know,
Speaker 1: the glass in the vehicle. What if it just starts
Speaker 1: flinging glass all over the over the factory and and
Speaker 1: does injure human or it does, you know, slice through
Speaker 1: several lines of hydraulic lines for the other robots. How
Speaker 1: do you come for that damage? That's well, let's see
Speaker 1: and and it's one bad apple. One of the things
Speaker 1: they mentioned was that so the conversation fun, like they said,
Speaker 1: was a possible approach. The other thing they talked about
Speaker 1: was obligatory insurance, similar to what you would have with
Speaker 1: car insurance, only in this case it would be the
Speaker 1: company's producing the robots that would be responsible for paying
Speaker 1: that insurance, not the people who purchase or own the robot.
Speaker 1: All right, I know that was a ridiculous example, but
Speaker 1: it's perfectly it's it's perfectly a reasonable example. It goes berserk. Yeah,
Speaker 1: you know what happens. They're saying, like, you know, as
Speaker 1: we get to a point where robots are in are
Speaker 1: able to act more autonomously within an environment, they're going
Speaker 1: to encounter variables that you could not This goes back
Speaker 1: to Tesla Autopilot. They're going to encounter variables that you
Speaker 1: would not have expected when you were first programming office politics. Yeah,
Speaker 1: you know, maybe maybe something uh simple, maybe it's something
Speaker 1: that is that hardly ever happens, but happens at this
Speaker 1: one point, And how does the robot behave in that situation?
Speaker 1: And and there's their argument is that they're going to
Speaker 1: be cases where it is truly unpredictable that you cannot,
Speaker 1: just from its basic programming, necessarily anticipate what the robot's
Speaker 1: going to do. Like say, like it's after work and
Speaker 1: one robot hits on the other robot's girlfriend at the bar,
Speaker 1: and then Monday, there's a lot of tension between the
Speaker 1: two of them. Yet at work it's going to be
Speaker 1: a difficult situation where they are standing around the w
Speaker 1: D forty cooler. That's something you just can't account for
Speaker 1: right now. Well, I mean, like like specifically, the the
Speaker 1: passage that I keep kind of referring to here, it
Speaker 1: says considers that in principle, once the ultimately responsible parties
Speaker 1: have been identified, their liability would be proportionate to the
Speaker 1: actual level of structions given to the robot and of
Speaker 1: its autonomy, so that the greater robots learning capability or
Speaker 1: autonomy is, the lower other parties responsibility should be, and
Speaker 1: the longer robots education has lasted, the greater the responsibility
Speaker 1: of its teacher should be. All right, so this should
Speaker 1: have a lot of robot programmers shaking in their boots
Speaker 1: right now, because that really ups their responsibility for this
Speaker 1: this machine, which is already great, but that will extend
Speaker 1: into if it learns how to adapt to the job.
Speaker 1: And then but then then it's the robot's fault as
Speaker 1: long as there as long as you can make the
Speaker 1: robot autonomous enough, then you're like, I'm free. This is
Speaker 1: like having a kid. I'm responsible for my kid up
Speaker 1: to a certain age, and then after that it's the
Speaker 1: kid's fault. I guess. So I mean it's like, well,
Speaker 1: when when the robot turns eighteen, maybe that's that's when.
Speaker 1: But that's the idea, that's the basic idea of the
Speaker 1: idea is that if if you program a robot so
Speaker 1: that it has very little autonomy, then you would argue,
Speaker 1: logically speaking, the person liable for any damage to the
Speaker 1: robot makes is the person who programmed it or built
Speaker 1: it or whatever, because the robot can only follow the
Speaker 1: instructions that were given to it. If you have a
Speaker 1: robot that has more autonomy and more ability to extrapolate
Speaker 1: from its environment, then it goes beyond the basics that
Speaker 1: you gave the that you equipped the robot with, and
Speaker 1: so it becomes harder to say, oh, it's your fault
Speaker 1: because your robot did this thing. So it's kind of
Speaker 1: like having a kid and a kid growing up and
Speaker 1: you're saying, you know, why can't you control your kid, Like, well,
Speaker 1: my kid is becoming a person, and I mean I can.
Speaker 1: I'm doing the best I can and educating and and
Speaker 1: giving discipline and giving guidance to my kid. But my
Speaker 1: kid is a person. So occasionally my kid chooses to
Speaker 1: do something that you know, we have to have a
Speaker 1: discussion and say, listen, this was a bad choice you made.
Speaker 1: Here's why it was. That kind of all part of
Speaker 1: free will, it is. Yeah, So it's an interesting argument
Speaker 1: though that it's like it's like a child that you
Speaker 1: have to maintain control over for a certain amount of time.
Speaker 1: And then there's a point where you say this is
Speaker 1: operating on its own at this point, responsible for its
Speaker 1: own actions. And and again the report is very clear
Speaker 1: to say that this is stuff that we're talking about
Speaker 1: that decades out. It's not like it's not like this
Speaker 1: is It's not like we're gonna wake up tomorrow and
Speaker 1: our our little remote controlled robot is suddenly gonna be
Speaker 1: no back talking us, no no on the lions right now.
Speaker 1: It's like you pick up part A and put it
Speaker 1: in slot B and then do it again and again
Speaker 1: and again for eighteen hours a day. And and the
Speaker 1: report is essentially saying like we just want to make
Speaker 1: sure that we're not unprepared when when technologology advances beyond
Speaker 1: the stage where at now I mean, Scott, we've seen
Speaker 1: in the past, like with other types of technology, how
Speaker 1: technological development far outpaces the law, and then we have
Speaker 1: to figure out, okay, wait, what does this actually mean
Speaker 1: legally speaking? What what this draft is trying to do
Speaker 1: is get ahead of that and just to say like,
Speaker 1: let's set up the legal frame now, so that we
Speaker 1: aren't caught in that situation when it ultimately happens. Well,
Speaker 1: but it does. It does lead to some jokes. Yeah,
Speaker 1: and what gets everybody's dander up is that you know,
Speaker 1: they're gonna they're they're calling them electronic persons, and that
Speaker 1: right away is is kind of a I don't know,
Speaker 1: it's a is it not. It's not like bully move,
Speaker 1: but it's more like, um, this is definitely something that's
Speaker 1: replacing you as as a person in the or at
Speaker 1: least joining you. Yeah, at the minimum, let's say, is
Speaker 1: joining you. And then the other thing is that I
Speaker 1: think a lot of people feel this way too, is
Speaker 1: that wait a minute, you're gonna tax them as if
Speaker 1: it's a human. Isn't that The reason why they may
Speaker 1: be replaced that human with a machine is that they
Speaker 1: didn't have to be responsible for it after that point,
Speaker 1: like once it retires, because these robots don't retire, they
Speaker 1: don't die, they have you know, they have mechanical issues
Speaker 1: in there, and they are I guess retired in a way,
Speaker 1: and that they're replaced by another one. But you don't
Speaker 1: go on, you don't continue paying for it with a
Speaker 1: pension for the rest of the robots, you know, air
Speaker 1: quote life, you know, um, it's it's it's strange that
Speaker 1: people people want to extrapolate this too, like like it's
Speaker 1: a human and that you'll have to care for it
Speaker 1: for the rest of its its mechanical life as if
Speaker 1: it's a human. But that's not the way it is.
Speaker 1: Really No, I think it's different. I think really what
Speaker 1: they're what they were trying to get at, is that
Speaker 1: there are certain systems we have in place as human
Speaker 1: beings that depend entirely or at least in large part
Speaker 1: on employment taxes, and that if we, in fact do
Speaker 1: reach a future which is still not not necessarily the
Speaker 1: the thing that's going to happen, but if we reach
Speaker 1: a future where automation really has taken over to a
Speaker 1: great extent, Uh, what do we do to protect those
Speaker 1: systems for the people who are still dependent upon them
Speaker 1: until we reach a point where those systems are moot
Speaker 1: because we've moved on to something else. In fact, one
Speaker 1: of the other things they actually mentioned is that the
Speaker 1: Member States could all start to consider the possibility of
Speaker 1: a general basic income, which you know, we've got a
Speaker 1: couple of countries out there in Europe that are are
Speaker 1: experimenting with this to some degree. Uh. I did an
Speaker 1: episode of Forward Thinking's audio podcast where I talked about this,
Speaker 1: and I said, I would use that as a way
Speaker 1: of just seeing what happens. And then, you know, do
Speaker 1: you say, all right, it works, let's try it, or
Speaker 1: do you say, oh boy, that didn't work at all,
Speaker 1: let's not do that. I think we didn't implement it everywhere,
Speaker 1: and I think I think automo manufacturers are gonna hate this.
Speaker 1: I think it's gonna be bad for their business. I
Speaker 1: really do. They're they're not gonna like this at all,
Speaker 1: because that was the benefit to them of having something
Speaker 1: that robot. It doesn't it doesn't have the complaints, it
Speaker 1: doesn't have the you know, the same concerns. Right, you
Speaker 1: have the you have the upfront cost, and you have
Speaker 1: the maintenance cost of the robots, but you don't have
Speaker 1: these ongoing you don't have a salary, you don't have benefits,
Speaker 1: you don't have these other taxes and other elements that
Speaker 1: you would have to have if it were a human workforce.
Speaker 1: And if you start adding all these things that they
Speaker 1: have to pay on the on the end of the
Speaker 1: owner of the robot, you know, the founder of the
Speaker 1: company or the the owner of the company, whoever that
Speaker 1: may be. It maybe a group of people. If they
Speaker 1: have to pay more for that, you better believe that
Speaker 1: that price is going to be passed on to the
Speaker 1: consumer and the price of the price of your automobile
Speaker 1: is going to go skyrocketing. And it just leads to
Speaker 1: a lot of trouble. I mean, there's gonna be um,
Speaker 1: there's gonna be some issues. I think if they if
Speaker 1: they really do go forward with this, and it's just
Speaker 1: a draft now it's an I said, it's kind of
Speaker 1: getting it in people's heads that it may happen. But
Speaker 1: if they really do go forward with this, it's gonna
Speaker 1: cause a lot of trouble. I think. The I think
Speaker 1: the important thing to remember is it's not just that
Speaker 1: it's a draft report, but also that this is a
Speaker 1: report that's giving recommendations, and most of those recommendations really
Speaker 1: boiled down to let's form an actual official European agency
Speaker 1: that is going to oversee this stuff and staff it
Speaker 1: with people who are experts in their field, not just
Speaker 1: technical experts, but regulatory experts, ethical experts, to do to
Speaker 1: to do a lot of the legwork, to make sure
Speaker 1: that if any legislative aims are are created, that they
Speaker 1: are done so with the most information from the most
Speaker 1: the most diverse perspective possible, rather than you know, this
Speaker 1: seems like we should try this, let's do this, let's
Speaker 1: go this way. You be ready, but take your time
Speaker 1: getting there. And I think that that ultimately is the
Speaker 1: message of the report. It is a little whimsical in places,
Speaker 1: the fact that it references fiction. UH you think I
Speaker 1: love it. I think it's great. It was one of
Speaker 1: the things that you can word to me and said,
Speaker 1: can you believe this? You will see to me this
Speaker 1: is you're excited. But I do a show called forward
Speaker 1: Thinking you know where, and so I know how hard
Speaker 1: it is to try and predict the future. I have
Speaker 1: to do it every week fw Cohen thinking it's a
Speaker 1: sponsored by Toyota, this show is not, but forward Thinking
Speaker 1: is anyway the UH doing. Doing the show air, we
Speaker 1: talked about how it's funny because in those episodes when
Speaker 1: we talk about these big, big ideas, things like what
Speaker 1: happens if a UH an artificial intelligence becomes sophisticated enough
Speaker 1: that it is difficult too to differentiate it from an
Speaker 1: intelligent creature to the point maybe it has some form
Speaker 1: of self awareness. Maybe it doesn't, but maybe it seems
Speaker 1: like it does. Like, that's a difficult question. What happens
Speaker 1: if automation were to take over more jobs than it
Speaker 1: could create? What if we were you know, the all
Speaker 1: these different what if questions We always conclude with, you know,
Speaker 1: we don't really know, but it really is important that
Speaker 1: we talk about it and discuss it and start thinking,
Speaker 1: you know what, how would this actually impact us now,
Speaker 1: so that we're not caught by surprise what happens later on.
Speaker 1: And I feel like this draft report is exactly what
Speaker 1: I keep saying and so wild. Part of it is
Speaker 1: funny and and you can joke about like your toaster
Speaker 1: becoming a person, uh, and I would make the same joke.
Speaker 1: I'm also I also admire that someone has taken the
Speaker 1: time to do what I keep asking people to do
Speaker 1: it every episode. I'm like, well, I can't make too
Speaker 1: much fun of them. I've been this is exactly what
Speaker 1: I've been calling for for four years. It's become a reality. Yeah.
Speaker 1: Now I'm just like amused that it happened. Also, I'll
Speaker 1: go ahead and tell you guys, like this report is
Speaker 1: very easy to read. Uh is twenty two pages long,
Speaker 1: and that's after you get past the first couple of
Speaker 1: pages of it's less than twenty pages because the first
Speaker 1: couple of pages are like a cover and a table
Speaker 1: contents and stuff. It's a piec cake. It's it's it's
Speaker 1: actually you know, I mean, it's written in a little
Speaker 1: bit of legal language, but not terrible. Like it's nowhere
Speaker 1: near as dense as some of the stuff I used
Speaker 1: to have to read when I worked in a law firm.
Speaker 1: Those were dark times, my friend. Um, but it's it's
Speaker 1: a pretty easy read. It's a little scattered because you
Speaker 1: feel like some of the sections are repeated, but it's
Speaker 1: worth checking out. And it's all available online and PDF form,
Speaker 1: so you can go and pull down this read it
Speaker 1: see if you you know, think like, is this is
Speaker 1: this prudent? Is it? Is it really proactive? Is it reactionary?
Speaker 1: Is it unnecessary? Should we not worry about this for
Speaker 1: another ten years? I mean it certainly could spark at
Speaker 1: least a conversation. We should also keep in mind, nothing
Speaker 1: in the report is like would become legally binding. It's
Speaker 1: really just a bunch of suggestions. It's just just kind
Speaker 1: of a prep work work framework, I guess for them
Speaker 1: to adhere to later. It's right, it's not even not
Speaker 1: even so much as like a legal proposal as it is. Hey, guys,
Speaker 1: I think it'd be a really good idea if we've
Speaker 1: got some smart people to think about this stuff for
Speaker 1: a while. That's when it comes down to start with
Speaker 1: this and see what you come up with. Yeah, yeah,
Speaker 1: pretty much. And they you know the fact that they say,
Speaker 1: like this is one possible solution. Uh, there they are
Speaker 1: implying at least that they don't know all the answers
Speaker 1: and therefore they're just kind of throwing something out there,
Speaker 1: and maybe there's a much better way of approaching it
Speaker 1: than the way that they have suggested. You know. So
Speaker 1: European Parliament is a lot like us. They have more
Speaker 1: questions than answers on this one. Yeah, but at least
Speaker 1: they're asking to get you know, the top thinkers together
Speaker 1: to try and answer some of these questions. That's true,
Speaker 1: just like how stuff works did with us here to
Speaker 1: That's right. That's that's why we make the big bucks
Speaker 1: Scott get the top thinkers together in the podcast studio. Okay,
Speaker 1: that's a little that's too much. We were really only
Speaker 1: the only two people here, so it was just there's
Speaker 1: no other option. Really, that's right, there's an empty room,
Speaker 1: and I just happened to raise my hand. Yeah. Yeah,
Speaker 1: it's either going to be you know you are Matt
Speaker 1: Frederick and man, I can't stand that guy. So I
Speaker 1: said that just as he was literally passing the window
Speaker 1: I was looking at that. I love Matt. He'll never
Speaker 1: he'll never listen to this. I don't have to worry
Speaker 1: about I'm listening to this, but just in case, I
Speaker 1: love you, Matt. All right. So guys, first of all,
Speaker 1: I gotta thank Scott again for joining me on this
Speaker 1: show and bringing bringing the European Parliament proposal to my
Speaker 1: attention because it has given me a wealth of material.
Speaker 1: Thank you for asking me into the studio again. With you,
Speaker 1: I always have a good time and it's always a
Speaker 1: fun conversation. It's a good back and forth between us. Yeah, yeah,
Speaker 1: we we have a blast. There's certain people that I
Speaker 1: just feel a fun rapport with and I'm happy to say,
Speaker 1: at no time during this particular conversation did I set
Speaker 1: out to break your heart. Yeah you didn't. You didn't
Speaker 1: even he didn't physically strike me either way. Sometimes do it? Sometimes?
Speaker 1: I mean, you know, it's it's a Friday and I'm tired. Honestly,
Speaker 1: I don't think I have the energy. Yeah, you know what,
Speaker 1: usually you do? You too, tried to you try to try,
Speaker 1: try to sing me with you. Usually I usually withhold
Speaker 1: one important piece of information and then see see how
Speaker 1: you react. It normally has something to do with people
Speaker 1: not driving anymore, but I'm not doing that today. So
Speaker 1: of course you can go check out car Stuff. Scott
Speaker 1: is a co host on car Stuff along with Ben
Speaker 1: Bolan and Uh. He does amazing work here at how
Speaker 1: stuff Works, so check that out. And guys, if you
Speaker 1: have any questions or suggestions for future episodes, write me
Speaker 1: my email addresses tech stuff at how stuff works dot
Speaker 1: com or drop me a line on Twitter or Facebook.
Speaker 1: The handle at both of those is text stuff H
Speaker 1: s W and I will talk to you again. Really
Speaker 1: see for more on this and thousands of other topics,
Speaker 1: is a how stuff Works dot com