Speaker 1: Welcome to this week's classic episode. Let's play conspiracy Jeopardy.
Speaker 1: The category is Google the Pentagon and AI.
Speaker 2: I don't even know what to say about this one. Guys, like,
Speaker 2: this is again, this is twenty eighteen. We didn't even understand,
Speaker 2: We didn't even understand episode.
Speaker 3: No, it's probably a really teachable moment for all of us.
Speaker 3: We should go back and listen to the whole thing too,
Speaker 3: and learn from our past selves. That's one of the
Speaker 3: things that's weird about doing podcasts, you guess ever think
Speaker 3: about that there's this weird version this history of us
Speaker 3: being kind of varyingly behind and ahead of the eight
Speaker 3: ball over the years, and sometimes it terrifies me to
Speaker 3: go back and revisit it. So y'all out there in
Speaker 3: conspiracy realists think can do it for us.
Speaker 1: From UFOs to psychic powers and government conspiracies, history is
Speaker 1: riddled with unexplained events. You can turn back now or
Speaker 1: learn this stuff they don't want you to know.
Speaker 2: Welcome back to the show.
Speaker 4: My name is My name is Noah.
Speaker 1: They call me Ben. We are joined with our super
Speaker 1: producer Paul Big Apple decand most importantly, you are you.
Speaker 1: You are here, and that makes this stuff they don't
Speaker 1: want you to know. Today, we're going to talk about
Speaker 1: a company called Google, commonly known as Google. That's its
Speaker 1: street name. That's such a popular name, that's become a
Speaker 1: verb in American English. They have a parent company who
Speaker 1: could call it, the real company, which is known as Alphabet.
Speaker 1: And we've talked about this a little bit in the past,
Speaker 1: but we want to whatever we mentioned Google establish that
Speaker 1: from the jump at the top, because it's strange how
Speaker 1: relatively obscure that fact remains. And now, while Google O'tabet
Speaker 1: whatever you want to call it may not be the
Speaker 1: largest company in the world in terms of capital or
Speaker 1: territory or material possessions, it is undoubtedly one of the
Speaker 1: most influential organizations on the planet, at least in terms
Speaker 1: of its connection to human beings or the ways in
Speaker 1: which it influences networks or organizations or webs of human beings.
Speaker 1: Most people on this planet, literally most people think about
Speaker 1: that have heard of Google, even if they have somehow
Speaker 1: not directly interacted with it, And arguably, on a slightly
Speaker 1: more controversial note, most people have in some way to
Speaker 1: some degree been affected by the actions of the US military,
Speaker 1: whether that's something that happened generations ago in their own
Speaker 1: country or an adjacent country, or to an ancestor, or
Speaker 1: whether something is happening to them now as we record
Speaker 1: this episode, and so today begins the question spoiler alert.
Speaker 1: It also ends with a question, and our beginning question
Speaker 1: is this what happens when these groups Google Alphabet, whatever
Speaker 1: you want to call it, and the US military or
Speaker 1: Uncle Sam, what happens when they join forces? Because they
Speaker 1: have so, they have vultrons up, and they have vultroned
Speaker 1: up in a again controversial way, it involves unmanned aerial systems,
Speaker 1: also known as drones.
Speaker 4: You are the ones that like deliver your Amazon packages, right.
Speaker 1: Yeah, and some variation of them. Yeah, they're commonly called drones,
Speaker 1: of course, but unmanned aerial vehicles or UAVs have been
Speaker 1: a long running trope in science fiction, and surprisingly for
Speaker 1: many people, some version of this technology existed long before
Speaker 1: the modern day. There wasn't a history rattling moment when
Speaker 1: the first drone ever went airborne. And that's in large
Speaker 1: part because it's very difficult for us to isolate exactly
Speaker 1: when the early version of an invention ends and the
Speaker 1: first modern versions begin. Matt when you and I worked
Speaker 1: on the invention show Stuff of Genius. We ran into
Speaker 1: this pretty often. Somebody comes up with a rough approximation
Speaker 1: of an idea and then over a course of years, decades,
Speaker 1: or even centuries in some cases, people continually make small
Speaker 1: improvements until it becomes the thing we know. Most inventions
Speaker 1: are not a Eureka moment in reality. I mean, they
Speaker 1: may be a Eureka moment in terms of the idea
Speaker 1: or the epiphany, but most inventions in reality, and when
Speaker 1: we get to the hardware phases are going to be
Speaker 1: created by people standing on the shoulders of giants.
Speaker 2: Yeah, it ends up being the person who makes it
Speaker 2: marketable rather than just creates it.
Speaker 1: Oh good call, and a very sad and capitalist call. Right,
Speaker 1: it's the person who popularizes it. So if we look
Speaker 1: at the first modern version of a drone, an unmanned vehicle,
Speaker 1: would it be one of those bombs in the eighteen
Speaker 1: hundreds that was strapped to a balloon and then just
Speaker 1: sort of put off like something bad will happen, We
Speaker 1: can't steer it. There wasn't a person on that and
Speaker 1: it was being used as a weapon. Or was it
Speaker 1: the initial V one rockets that Germany deployed during World
Speaker 1: War Two. In the early nineteen hundreds, military groups did
Speaker 1: use drones. They had radio controlled versions that were just
Speaker 1: for target practice. Engineers developed unmanned aircraft that again had
Speaker 1: munitions of some sort. These weren't drones the way we
Speaker 1: think of them in the current age. But there's you know,
Speaker 1: there are other examples, like cruise missiles. These things were
Speaker 1: the first cruise missiles, often called flying torpedoes. They were
Speaker 1: not meant to return to base, and drones are meant
Speaker 1: to function like very very smart, sometimes very very deadly boomerangs.
Speaker 1: They come out, they ain't come back, and somebody.
Speaker 2: Claps yeah, generally not the people being targeted.
Speaker 1: Generally, yes, yes, generally not. You are correct, my friend.
Speaker 1: During the Cold War and the Vietnam War or the
Speaker 1: series of conflicts collectively known as the Vietnam War here
Speaker 1: in the US, Uncle Sam ramped up research on drones.
Speaker 1: It was no longer just an interesting idea posed by
Speaker 1: a few eccentric scientists and engineers. In fact, by the
Speaker 1: time of the Vietnam War, unmanned drones flew thousands of
Speaker 1: high risk reconnaissance missions, and they got shot down all
Speaker 1: the time. But In that process, they saved the lives
Speaker 1: of human pilots who otherwise would have been a board.
Speaker 1: And I thought about I thought about you, Matt when
Speaker 1: I was looking into this because another precedent for drones,
Speaker 1: which we won't go into in this episode, another president
Speaker 1: for drones where weaponized bats. Did you ever hear about this?
Speaker 4: The oneted to drop the little bombs?
Speaker 1: Yeah, well, yes, that's a version of it. Yeah, they
Speaker 1: said bats can fly, we have access to them.
Speaker 2: Well yeah, I mean you could go back to carrier
Speaker 2: pigeons as being a type of drone as well.
Speaker 1: Yeah, I mean there's not a person aboard.
Speaker 5: There's a really cool episode of the podcast of the
Speaker 5: Memory Palace about the bats that's called idy Bitty Bombs.
Speaker 4: It's quite good.
Speaker 1: Yeah, yeah, so check that one out for more information.
Speaker 1: Around the same time Vietnam War, it goes this far back.
Speaker 1: Around the same time of Vietnam War, engineers started adding
Speaker 1: real time surveillance ability to drones, so cameras. Right today
Speaker 1: we look at I guess the closest thing we have
Speaker 1: to a military version of the first drone would be
Speaker 1: the MQ one Predator, was first unveiled in nineteen ninety five,
Speaker 1: which is weird when you think about it because that
Speaker 1: was such a long time ago. And in two thousand
Speaker 1: and two, the CIA used the MQ one Predator to
Speaker 1: make its first successful kill of a quote unquote enemy
Speaker 1: combatant in Afghanistan. Since then, since just two thousand and two,
Speaker 1: this technology has grown by cartoonishly extreme leaps and bounds,
Speaker 1: and it's currently on the bleeding edge of scientific advancement. Yeah.
Speaker 2: And if that MQ one Predator drone, that's the drone
Speaker 2: that you have seen before, that's the one that is
Speaker 2: in pictures all over the place, that is the I mean,
Speaker 2: I guess being one of the first, it just became
Speaker 2: iconic in that way. Just gonna want to throw that
Speaker 2: in there.
Speaker 1: Yeah, it looks like a windowless commercial plane with an
Speaker 1: upside down tail fin, right, two upside down tail fins.
Speaker 2: Yeah, it's kind of The shape is slightly slightly odd,
Speaker 2: but yeah, it's it's pretty cool.
Speaker 1: And as these drones become more and more common in
Speaker 1: theaters of war or in commercial industries like Amazon using them,
Speaker 1: or recreational use like you buy a when one is
Speaker 1: a gift, they're also doing the inorganic version of Specie
Speaker 1: eighting you know, speci eating is when a relatively common
Speaker 1: ancestor through generations and generations, produces different species of the
Speaker 1: same template. Right, So these drones are becoming increasingly specialized.
Speaker 1: They have varying ranges of abilities and odds. Are you've
Speaker 1: seen one, right, We've all seen toy drones.
Speaker 4: The little quad copter guys.
Speaker 5: Yeah, and you gotta wonder too, like how does that
Speaker 5: work patent wise? Like did someone come up with that
Speaker 5: design and it was just generic enough to be copied?
Speaker 5: Like I always wonder about things like that, like the
Speaker 5: fidget spinner, Like did that guy just do a bad
Speaker 5: job of patenting the original fidget spinner? Or is it
Speaker 5: so generic that that doesn't even apply. I'm wondering that
Speaker 5: that's the same thing about the design of those quad
Speaker 5: toy drones.
Speaker 1: Entirely speculative, but it's probably at the very least a
Speaker 1: series of patents. Yeah, they have to multiple things in play,
Speaker 1: I would imagine.
Speaker 5: Pro tip speaking of a play, if you're gonna get
Speaker 5: one of those for your kids, get a good one
Speaker 5: because the cheap ones you might think you got a deal,
Speaker 5: they just don't fly, They suck.
Speaker 1: And they're battery vampires too.
Speaker 5: Oh, my god, that was the thing, Like we got one, like, oh,
Speaker 5: it flies for about four minutes, four minutes, Like that's
Speaker 5: not fun tops tops. Yeah, but what kind of batteries
Speaker 5: do the big boys use? Are they fueled or are
Speaker 5: they do you know that's classified?
Speaker 2: Yeah, sorry, we can't talk about it.
Speaker 4: You can't tell me.
Speaker 2: No, I thought we were pals. Google it all right.
Speaker 1: Oh yeah, so some of the on a serious note,
Speaker 1: some of those power systems would vary, and by the
Speaker 1: time we dive into one and this episode comes out,
Speaker 1: it may have changed. Interesting, that's how quickly they're moving
Speaker 1: on these. So we've seen these, right, and we've probably
Speaker 1: seen photographs or videos of the larger of these tiny drones,
Speaker 1: things like the Predator, like Matt just described. You can
Speaker 1: find a photograph of it pretty easily. The differences are
Speaker 1: stark and astonishing, and missiles are not the biggest difference.
Speaker 1: The fact that they're weaponized. While that is incredibly dangerous
Speaker 1: and possibly fatal, that is not the biggest difference. Some
Speaker 1: of the bigger differences are going to be on the
Speaker 1: inside of the drone. We're talking things like GPS, real
Speaker 1: time satellite feeds, super complex microprocessors, and more, they're putting
Speaker 1: brains on board of these things. And perhaps most disturbingly,
Speaker 1: some drones are edging closer and closer and closer to
Speaker 1: what's commonly known as artificial intelligence or technically known as
Speaker 1: machine consciousness. And we're close to an old science fiction
Speaker 1: question becoming a real question. Well, the first true artificial intelligence,
Speaker 1: the first true machine consciousness be a weapon of war.
Speaker 2: Yes, highly likely, definitely.
Speaker 1: Yeah, why is that met?
Speaker 2: That's because innovation through the military is one of the
Speaker 2: ways that innovations occur. The biggest innovations and inventions occur
Speaker 2: because there's funding from a military somewhere, and it's not
Speaker 2: like it's the military itself doing these things. It is
Speaker 2: usually a private company or someone who's being given a grant,
Speaker 2: a government grant to do it.
Speaker 5: We see this time and time again with many of
Speaker 5: the stories that we've talked about, where the military is
Speaker 5: also always like decades ahead of what consumers will ever
Speaker 5: get their hands on, and it might be ten twenty
Speaker 5: years before it trickles down into the public where maybe
Speaker 5: we can have a you know, terabyte thumb drive, just
Speaker 5: as a silly example, where they've had that technology probably
Speaker 5: for a decade at this point.
Speaker 2: I would say the only way for it, not for
Speaker 2: the first machine consciousness, true machine consciousness, to not be
Speaker 2: a weapon, is for every private company on the planet
Speaker 2: to say I'm not going to do.
Speaker 1: That, right, Yeah, for us all kumbayah and do some
Speaker 1: hands across America on the tech sphere, right, or hands
Speaker 1: across the world. So with this in mind, we're also
Speaker 1: hitting on a larger phenomenon, this kind of kind of unfortunate.
Speaker 1: We're a family show, but we also endeavor at our
Speaker 1: best to be an honest when the great leaps and
Speaker 1: technology are not almost always, but the majority of the time,
Speaker 1: the great leaps and technology are driven by human vices.
Speaker 1: A desire to win a war, a desire to have
Speaker 1: more you know, social attention or more financial access than
Speaker 1: a rival.
Speaker 2: Or how do we compress all of this?
Speaker 1: Porn Right, that's the other one. That's the third one,
Speaker 1: a desire for us because in a very very real
Speaker 1: and concrete and provable way, pornography is the reason that
Speaker 1: you or your parents had a VHS instead of a
Speaker 1: Beta MAX. It's the reason, Like we talked about this
Speaker 1: I think previously. Yes, yeah, so often we all too
Speaker 1: often we as a species are driven by non noble motivations,
Speaker 1: but that doesn't mean that we're not smart. We are
Speaker 1: a jar of very very smart, very belligerent cookies, and
Speaker 1: we've been putting some of the smartest cookies of our
Speaker 1: species into the search for artificial intelligence and machine learning,
Speaker 1: a search that continues as we record this episode.
Speaker 2: So just a little while ago, in July of twenty seventeen,
Speaker 2: there were these two researchers named Greg Allen and Taniel
Speaker 2: Chan and they published a study which was called Artificial
Speaker 2: Intelligence and National Security, and in this they put forward
Speaker 2: goals for developing law policies specifically that would that would
Speaker 2: put ideas forth in how do you with AI when
Speaker 2: it comes to national security military spending? Like what should
Speaker 2: we as a species do when it comes to these
Speaker 2: two things colliding? And here are some of their findings.
Speaker 2: They again said the most transformative innovations in the field
Speaker 2: of AI are coming from the private sector and academic world,
Speaker 2: not from the government in military. So currently, right now
Speaker 2: AI is something that's happening outside of the realm of
Speaker 2: the military, which in July twenty seventeen, yay, that's a
Speaker 2: good thing, maybe because you know, there could be some
Speaker 2: nefarious private sector humans as well, But that's point A.
Speaker 2: The second one is that the current capabilities of AI
Speaker 2: have quote significant potential for national security, especially in the
Speaker 2: areas of cyber defense and satellite imagery analysis. And then
Speaker 2: the last thing, I'm just going to read this whole
Speaker 2: thing as a quote. Future progress in AI has the
Speaker 2: potential to be a transformative national security technology on par
Speaker 2: with nuclear weapons, aircraft, computers, and biotech, so some of
Speaker 2: the most influential technologies on weaponry on war. They're saying
Speaker 2: AI is going to be the next big thing.
Speaker 1: And they're not just talking the talk, right.
Speaker 2: No, they are not just talking to the talk at all.
Speaker 2: According to the Wall Street Journal, the Defense Department spent
Speaker 2: seven point four billion dollars on artificial intelligence related areas
Speaker 2: in twenty seventeen. Seven point four billion dollars on AI.
Speaker 1: And you know, not to not to harp too much
Speaker 1: on Eisenhower, but I believe he's the one who had
Speaker 1: a quote that said every rocket the US builds represents
Speaker 1: this many schools that we could have built but didn't.
Speaker 1: And there are a couple of things, if we're being
Speaker 1: entirely fair about that number, that we have to acknowledge.
Speaker 1: First is that this is only the money we know of,
Speaker 1: so seven point four billion, let's call that an at least, right,
Speaker 1: And then on the other end artificial intelligence related areas.
Speaker 1: That doesn't mean they're just building a silicon brain, right,
Speaker 1: that there are many other things that we might not
Speaker 1: associate directly with machine intelligence, that maybe function is support
Speaker 1: or infrastructure. So this is all, This is the whole meal.
Speaker 1: This isn't just the hamburger.
Speaker 2: Yeah, well, and we agreed. We should especially point out
Speaker 2: that the Department of Defense budget for fiscal year twenty
Speaker 2: seventeen was five hundred and forty billion dollars around that number.
Speaker 1: Still the biggest in the world. Yeah, and that's publicly acknowledged. Again,
Speaker 1: I can't keep saying that enough. Publicly acknowledged.
Speaker 2: That's what they ask Congress for.
Speaker 1: Yes, it's true. Before I derail us, what do you
Speaker 1: think should pause for a word from our sponsor?
Speaker 4: That seems wise.
Speaker 1: Here's where it gets crazy. We've painted a little bit
Speaker 1: of the picture, right. We know this story now, fellow
Speaker 1: conspiracy realist. It is a story of drones. It is
Speaker 1: a story of private industry. It is a story of
Speaker 1: government interaction, a story of war and a story of secrets.
Speaker 1: But in this age of instantaneous information, we know more
Speaker 1: than we would have known, say even two decades ago.
Speaker 1: We know more about what's happening now. Similar to the
Speaker 1: drones acquiring real time surveillance technology, we are able to
Speaker 1: be more aware of surroundings in a distant land. And
Speaker 1: that's how we know about something called what's it called METT.
Speaker 2: It's the Algorithmic Warfare Cross Functional Team, also known as
Speaker 2: Project Maven.
Speaker 5: And this was announced on April twenty six of twenty
Speaker 5: seventeen in a and internal memo from the Deputy Secretary
Speaker 5: of Defense Robert Bob o work.
Speaker 2: Yeahobo, he goes by bob work. But I just thought, yeah,
Speaker 2: Boba work. So I guess we can just read parts
Speaker 2: of this memo if you want to. It's kind of
Speaker 2: hard to digest, that's the only thing. So maybe if we.
Speaker 1: Anyway walk through parts, get down, humanize it.
Speaker 2: Yes, let's let's do that. Let's do that. Here we go.
Speaker 2: I'll be I'll be the dry and the dry part. Here,
Speaker 2: Here we go. The aw CFT's first task is to
Speaker 2: field technology to augment or automate processing, exploitation, and dissemination
Speaker 2: for tactical unmanned aerial systems. Okay, okay, so good god,
Speaker 2: Well let's keep going a little bit. So, so it's
Speaker 2: gonna augment or automate stuff for UAVs or drones and
Speaker 2: mid altitude full motion video in support of the Defeat
Speaker 2: ISIS campaign, and this will help to reduce the human
Speaker 2: factor's burden of full motion video analysis, increase actionable intelligence,
Speaker 2: and enhance military decision making.
Speaker 1: So what that all means is the PED processing, exploitation,
Speaker 1: and dissemination means that they're hoping again to get a
Speaker 1: brain on board your local neighborhood predator or whatever drone
Speaker 1: they end up using by the time you are listening
Speaker 1: to this episode. And the processing part is going to
Speaker 1: be the analysis, which often would be the human part
Speaker 1: of the equation. The exploitation would be the ability to
Speaker 1: take action on that analysis, right to use that knowledge,
Speaker 1: and dissemination would be sharing the information, determining what information
Speaker 1: is relevant, what is irrelevant, and to send where that's
Speaker 1: PED And that's the full motion video is similar to
Speaker 1: the same thing because it's it's a little bit easier
Speaker 1: to take a bunch of numbers that are sensed a
Speaker 1: bunch of temperature variables, for instance, and tell a computer
Speaker 1: or an automated system that whatever is within this range,
Speaker 1: do action X. Whatever is outside of this range, do action.
Speaker 2: Why, you know, even if the action is just alert
Speaker 2: the human user, the person that's going to actually analyze
Speaker 2: the thing.
Speaker 1: Yeah, absolutely absolutely, And that's tougher with video, right because
Speaker 1: there are many many more factors of play. Would you
Speaker 1: say that sounds correct?
Speaker 2: Absolutely? It just depends on what kind of sensors they're
Speaker 2: using on the drones. If it's you know, is it
Speaker 2: a heat based imaging system, is it just a you know,
Speaker 2: I mean, what are you looking at? Essentially? What is
Speaker 2: the data that you're looking at? And that's really hard
Speaker 2: to tell because it's going to change the depending on
Speaker 2: the model of drone and what they're you know, deploying.
Speaker 2: The really interesting one of the really interesting things here
Speaker 2: in my mind is that, you know, we're talking about
Speaker 2: a single drone and having an onboard system, but they're
Speaker 2: also talking about having a system that can analyze the
Speaker 2: footage from all the drones that they have deployed in
Speaker 2: a single space and then have the machine be able
Speaker 2: to take all that data in and tell you what's
Speaker 2: going on, and then send that whatever the algorithm decides
Speaker 2: needs to happen, disseminate all of that information out to
Speaker 2: the entire team that's also there, so you really have that.
Speaker 2: One of the things we talked about recently in another episode,
Speaker 2: a full scope picture of the battlefield essentially, so everyone
Speaker 2: at all times sees exactly what's happening on the battlefield.
Speaker 1: As close to an omniscient observer as possible. Yeah, as well,
Speaker 1: we used to say humanly possible, but that's no longer
Speaker 1: the case, right.
Speaker 2: Yeah, exactly, So let's keep going on here a little
Speaker 2: bit with what the memo said. This program will initially
Speaker 2: provide computer vision algorithms for object detection, classification and alerts
Speaker 2: for full motion video ped Further sprints will incorporate more
Speaker 2: advanced computer vision technology. After successful sprints in support of
Speaker 2: intelligence surveillance reconnaissance, this program will prioritize the integration of
Speaker 2: similar technologies into other defense intelligence mission areas, so it's
Speaker 2: not just for this single drone operation that they're gonna
Speaker 2: deploy it to. It's going to be for bigger things.
Speaker 2: It goes on to say, this program will also consolidate
Speaker 2: existing algorithm based technology initiatives related to mission areas of
Speaker 2: the Defense Intelligence Enterprise or DIE, including all initiatives that
Speaker 2: develop employ or field artificial intelligence, automation, machine learning, deep learning,
Speaker 2: and computer vision algorithms. So really they're talking about everything
Speaker 2: in the future for military applications.
Speaker 1: So beyond far beyond drones. Oh yes, these could also
Speaker 1: be submarines for instance. These could be satellites, these could
Speaker 1: be space shuttles.
Speaker 2: It could be surveillance, just video camera surveillance that's just
Speaker 2: on the ground either, right, you know, is this.
Speaker 5: The kind of stuff where eventually you could program a
Speaker 5: drone or some kind of killing machine with parameters that
Speaker 5: are like legally sanctioned and you can say, okay, search
Speaker 5: and destroy X target or this type of target.
Speaker 1: That's the fear. The potential is there, The potential is there. Absolutely,
Speaker 1: So essentially, what they're saying here is that DARPA and
Speaker 1: the Pentagon have already poured tons of money into this
Speaker 1: automated collection of data. And they're not alone. Other members
Speaker 1: of the Alphabet Soup Gang, which is a very endearing
Speaker 1: name for them, like the Apple Dumpling Gang, right, the
Speaker 1: Alphabet Soup Gang as other members of course n SA
Speaker 1: and so on. They have also put forth tons of
Speaker 1: money and time into automating the collection of data, and
Speaker 1: the next step is discover is discovering a means of
Speaker 1: automating the analysis of data. And the step after that,
Speaker 1: the especially spooky one, is enabling these unmanned machines to
Speaker 1: immediately act in real time on the results of their
Speaker 1: onboard analysis. So to the questioning Posonal, the answer would
Speaker 1: be yes, they want to have at least the capability
Speaker 1: to make a judge, jury, and executioner on an unmanned vehicle.
Speaker 1: This doesn't mean they'll do it. A lot of tech
Speaker 1: companies do have problems with it, or at least with
Speaker 1: actualizing that potential.
Speaker 5: Yeah, you even see problems with the self driving cars.
Speaker 5: I mean, as much as much R and d as
Speaker 5: have gone into those, they're certainly not infallible.
Speaker 4: And they get into fender benders and make mistakes.
Speaker 2: Absolutely of Let's just have one more little quote here,
Speaker 2: and this is from the chief in charge of this
Speaker 2: Algorithmic Warfare Cross Function Team or Project MAVEN, and he's
Speaker 2: speaking specifically to what they hope to achieve in the
Speaker 2: near term with this project. And he says, quote people
Speaker 2: in computers will work symbiotically to increase the ability of
Speaker 2: weapons systems to detect objects. Eventually, we hope that one
Speaker 2: analyst will be able to do twice as much work,
Speaker 2: potentially three times as much as they're doing now. That's
Speaker 2: our goal. So in the short term, somebody sat down
Speaker 2: with him, had a meeting, and we want to increase
Speaker 2: just basically what our analysts can get done, and we're
Speaker 2: gonna save money on that end, We're gonna save time
Speaker 2: and we're gonna be more efficient. That's what this whole
Speaker 2: project is about, at least in his eyes or his
Speaker 2: pr thing that he got to say. So what we're
Speaker 2: talking about with this project so far is just what
Speaker 2: it means to achieve what it wants to achieve. We
Speaker 2: haven't discussed how it was going to achieve all of this,
Speaker 2: and that is where we have our friend Google.
Speaker 5: Yes, Google, Google is nobody's friend. If Google was an
Speaker 5: ice cream flavor, they'd be pre Lanes and Google.
Speaker 2: Yes.
Speaker 4: And I can't say that word on the podcast. Every
Speaker 4: time you say project Mayven, I think it's a project Mayhem.
Speaker 2: Yeah, slightly different. So we know here that both the
Speaker 2: Defense Department and Alphabet and Google are saying that this collaboration,
Speaker 2: them working together in any way on this at all,
Speaker 2: is all about AI assisted analysis of drum footage. That is,
Speaker 2: that is what they're saying. That is the party line
Speaker 2: on both sides. The p rtists put forth is everything's cool.
Speaker 2: We're just working on looking at video guys.
Speaker 1: It's cool, right, right, specifically through something called tensor flow AI.
Speaker 2: Yeah, Noel, you looked into this, right. What is TensorFlow?
Speaker 5: This is from the website of TensorFlow trademark. I'm gonna
Speaker 5: do it like I'm doing an ad read. TensorFlow is
Speaker 5: an open source software library for high performance numerical computation.
Speaker 5: It's flexible architecture allows easy deployment of computation across a
Speaker 5: variety of platforms CPUs, GPUs, TPUs, and from desktops to
Speaker 5: clusters of servers to mobile and edge devices. Originally developed
Speaker 5: by researchers and engineers from the Google Brain team within
Speaker 5: Google's AI organization, it comes with strong support from machine
Speaker 5: learning and deep learning, and the flexible numerical computation core
Speaker 5: is used across many other scientific domains.
Speaker 4: Yep, that one.
Speaker 2: Yeah, that's the what.
Speaker 5: No, seriously, TensorFlow can actually feel kind of like totally
Speaker 5: future science fiction kind of stuff for people who are
Speaker 5: not already familiar with how machine learning works. But there's
Speaker 5: some pretty awesome introductions primers out there if you would
Speaker 5: like to learn more, particularly a YouTube video.
Speaker 2: Yeah, it's about a forty five minute essentially on how
Speaker 2: it functions. But it's good, it's interesting, it's over my head.
Speaker 1: And the cool thing when I found that one the
Speaker 1: cool thing about that guy is he's If you watch
Speaker 1: the video, he says, if you have any questions, you
Speaker 1: can email him directly.
Speaker 2: Oh my gosh, I don't really.
Speaker 1: Yeah, I don't know if he knew that his email
Speaker 1: address was going out on YouTube, but he seemed pretty approachable.
Speaker 2: And that video is on the Coding Tech YouTube page
Speaker 2: and it's called TensorFlow one oh one. Really awesome intro
Speaker 2: into TensorFlow.
Speaker 4: Super awesome.
Speaker 5: But yeah, but forty five minutes is probably about the
Speaker 5: shallowest deep dive you're going to get into the subject.
Speaker 5: And I mean that is a glowing endorsement of the
Speaker 5: quality of this this walkthrough.
Speaker 1: Yeah, so what exactly has TensorFlow done so far?
Speaker 2: So in the research for this show, we came across
Speaker 2: an open letter that was written from the International Committee
Speaker 2: for Robot Arms Control, and they go into just some
Speaker 2: of the details of exactly what is happening here the
Speaker 2: collaboration between Google and the Department. So let's kind of
Speaker 2: look at this. They were looking at an article from
Speaker 2: Defense one in which they note that the Joint Special
Speaker 2: Operations Forces they've conducted trials already using video footage from
Speaker 2: this other smaller UAV called scan Eagle. It's a specific
Speaker 2: surveillance drone, and the project is also slated to expand
Speaker 2: to even quote larger medium altitude predator and reaper drones
Speaker 2: by next summer. So these are the ones we spoke
Speaker 2: about in the beginning. These are the ones that are
Speaker 2: actively functioning in Syria and Afghanistan and other in Iraq
Speaker 2: and other places like that, and eventually to this thing
Speaker 2: called gorgon Stare, which sounds amazing, right.
Speaker 4: Sounds scary, yeah, and it.
Speaker 2: Turns it might. So this is these are specific sensors
Speaker 2: and it's a technology package that's been it's been used
Speaker 2: on these MQ nine reapers, which is just the newest relation.
Speaker 2: Yeah yeah, and man, it sounds really scary. But you
Speaker 2: can learn more about this right now. If you search
Speaker 2: for gorgan go r gon Stare and maybe drone or predator,
Speaker 2: that's probably the best way to look into it. And
Speaker 2: there's all kinds of information that's been officially released on
Speaker 2: this program already. So okay, so we know that this
Speaker 2: thing's been used in these smaller projects. Now it's going
Speaker 2: to be moved on to these Predator and Reaper drones,
Speaker 2: and they're thinking that it's going to get expanded even further.
Speaker 2: And I don't even we don't even know what that
Speaker 2: expansion could be at this point, because the drone technology
Speaker 2: is growing. It's just a lot of it is classified.
Speaker 1: Right, Yeah, a lot of it is classified, and as
Speaker 1: we've established earlier in the episode ode, that's really common.
Speaker 1: In fact, a lot of it will probably be classified
Speaker 1: for a number of years.
Speaker 2: Well yeah, if you think about it this way. So
Speaker 2: the gorgon Stare, it can allegedly and I just say
Speaker 2: this because I haven't actually seen it, but it uses
Speaker 2: a high tech series of cameras that can quote view
Speaker 2: entire towns.
Speaker 5: Like what like Google Earth style like yeah, that kind
Speaker 5: of zoom, yeah, okay.
Speaker 2: Active running looking at an entire town. And then if
Speaker 2: you apply this machine learning to it and you can
Speaker 2: see every human being walking around, and then the technology
Speaker 2: gets more and more powerful, then you could really just
Speaker 2: have a complete surveillance state from above.
Speaker 5: Yeah, that's that's pretty scary, Like you can see them
Speaker 5: in their homes. Is it have some kind of like
Speaker 5: heat vision that works from afar?
Speaker 2: That's a great question. Then I don't know the answer too.
Speaker 2: I certainly hope not. Maybe it would be good for
Speaker 2: a military application, but that's terrifying.
Speaker 5: That's the problem, right, Like you can't put this stuff
Speaker 5: back in the box. Like, even if it starts off
Speaker 5: as a military application, it's going to eventually get in
Speaker 5: the hands of Not to say that the military has
Speaker 5: our best interests at all times, but it could make
Speaker 5: its way into a more nefarious use.
Speaker 1: If we were to put a list of all the
Speaker 1: technologies that expanded past their intended use on one side,
Speaker 1: and a list of all the technologies that people agreed
Speaker 1: not to pursue on the other side, one list would
Speaker 1: be very very long. I mean, we for a species
Speaker 1: that loses cities and even entire civilizations, we're pretty good
Speaker 1: at finding and replicating technology, and we don't like to
Speaker 1: lose it. We did an earlier episode on things like
Speaker 1: so called Damascus steel or Greek fire. But looking in
Speaker 1: that it was very difficult for us to find examples
Speaker 1: of technology that was truly lost in the modern day.
Speaker 1: Once Pandora's jar is unscrewed, then the it's kadie bar
Speaker 1: the door. Yeaistic statement, I Ardi.
Speaker 4: Those badgers get out of that bag.
Speaker 1: They will eat you alive, and you can't get them
Speaker 1: back in.
Speaker 2: No, man, Well, here's the thing. The badgers with this
Speaker 2: project badgers in the bag. They don't even know where
Speaker 2: the other one is right now. They're so far gone
Speaker 2: from each other. Because this is where you get into
Speaker 2: the whole targeted killing thing that was really big in
Speaker 2: what two thousand and seven, two thousand and eight as
Speaker 2: we got on through the Obama administration, where drones were
Speaker 2: being used more and more to target mostly males, and
Speaker 2: males were considered if you're of a certain age, you
Speaker 2: could kind of prove that this male was of a
Speaker 2: certain age even from a drone, that person would be
Speaker 2: considered an enemy combatant in certain aspects or in certain ways.
Speaker 2: And if you're using these algorithms to just figure out
Speaker 2: you know, if you can just figure out it's a
Speaker 2: male in in you know, above a certain age. Then
Speaker 2: that's what Google is helping them do is figure out
Speaker 2: how to kill people from Afar that are males of
Speaker 2: a certain age. Right.
Speaker 1: And this goes into a quotation that you found, Matt,
Speaker 1: that gave me some chills.
Speaker 2: Oh yeah. A quote from Eric Schmidt, who was who
Speaker 2: up until last year or the end of last year,
Speaker 2: he was the executive chairman at Google in alphabet, and
Speaker 2: he says, there's a general concern in the tech community
Speaker 2: of somehow the military industrial complex using their stuff to
Speaker 2: kill people incorrectly.
Speaker 4: Hold on there, how do you kill people incorrectly?
Speaker 1: That's that's the way of doing Yeah, that's what gave
Speaker 1: me chills, Matt, when you were originally talking about this,
Speaker 1: the idea of killing people incorrectly. The implication there is
Speaker 1: frightening because Schmidt is jumping straight across and completely sidelining
Speaker 1: the recognition that maybe the tech community doesn't want to
Speaker 1: kill people in general.
Speaker 4: Is that just linguistic jiu jitsu kind of it's a bit.
Speaker 1: Yeah, absolutely, yeah, it's a bit.
Speaker 2: And that just so you know, that was a quote
Speaker 2: from a keynote address he was giving at the New
Speaker 2: American Security, Artificial Intelligence and Global Security.
Speaker 1: Summit, right before the panel on how to correctly kill people.
Speaker 2: Yeah, it was in November of twenty seventeen. Yeah, it
Speaker 2: was right before that panel.
Speaker 4: You shoot him in the face, that's how you do it,
Speaker 4: and make eye contacts.
Speaker 1: Huh yeah.
Speaker 4: Yeah.
Speaker 1: So the situation then seems on the cusp of something
Speaker 1: a rapid evolution, perhaps an evolution that's already occurring. And
Speaker 1: we've talked about the motivations of the military, we've talked
Speaker 1: about the technical aspects, we've talked about what the suits
Speaker 1: and the generals want. But what about the employees, What
Speaker 1: about the people who are actually doing the work. As
Speaker 1: we know, often those are the people who are the most.
Speaker 2: Ignored, a lot of them bucked right, yes, and we'll
Speaker 2: learn about that right after a quick break. Oo.
Speaker 1: So to bring the focus on the employees, the ones
Speaker 1: who are actually out there writing the code that you know,
Speaker 1: many times they probably won't get credit for, we need
Speaker 1: to look at their own internal activism. See Google and
Speaker 1: Alphabet employees were well aware of these moves far before
Speaker 1: the official announcement, way before twenty seventeen. Of course, they
Speaker 1: know this stuff is happening because they're working on things
Speaker 1: like this. Behind the scenes.
Speaker 2: Might be compartmentalized, but they're working on things. Sure they
Speaker 2: can you know, employees talk.
Speaker 1: Sure. For instance, do you remember that terrible sci fi
Speaker 1: series The Cube guys we.
Speaker 2: Do the movie?
Speaker 1: I think there are three?
Speaker 4: There was one of them was Hypercube. I remember that.
Speaker 5: I like the first one though, I quite enjoyed it.
Speaker 5: But yeah, it's it's it's shlock, but it's fun.
Speaker 1: But the thing about it is it's a bit of
Speaker 1: a cautionary tale because the premise of The Cube spoiler
Speaker 1: alert is that a bunch of different experts were paid
Speaker 1: to research and construct specific components of what would later
Speaker 1: become this death trap, and they didn't know that what
Speaker 1: they were building would be used in this certain way.
Speaker 1: They thought they were just making heat sensors, right, they
Speaker 1: thought they were just making hatches. They thought they were
Speaker 1: just making lasers, Yeah, laser grids.
Speaker 5: The first scene the guy actually gets cubed by a
Speaker 5: laser grid in a cube in a cube. That's pretty mad.
Speaker 5: And the thing too about that is like, is it
Speaker 5: just for funzies? Like you don't really know, Like why
Speaker 5: why are they in there? Is this just some like
Speaker 5: rich a hole. It's just trying to like, you know,
Speaker 5: you don't find out.
Speaker 2: That, yeah, you will, really, you gotta keep going.
Speaker 4: We got a cue. How far? How far? How deep
Speaker 4: does this rabbit hole, this rabbit cube go?
Speaker 2: My friend, Well, somebody's going to make another one, and
Speaker 2: we're gonna find out.
Speaker 4: You think some of the definitive one.
Speaker 1: Sure, it'll probably be a prequel or something that's cool.
Speaker 1: You can also, you know, I'm sure read spoilers on
Speaker 1: the wiki or on the online in a form somewhere.
Speaker 1: But luckily, at least for their own ethical well being
Speaker 1: or their ability to sleep at night, the many of
Speaker 1: the Google and Alphabet employees were able to communicate with
Speaker 1: each other. They were aware of the implications of what
Speaker 1: would happen if all this stuff was assembled together like
Speaker 1: the Avengers or Captain Planet and the Planeteers, so they
Speaker 1: took action. First, they gathered to write an internal petition
Speaker 1: requesting the organization pull away from this agreement with Uncle Sam. Petitions,
Speaker 1: it should be said, are not inherently unusual at Google,
Speaker 1: but this one was particularly important and particularly crucial to
Speaker 1: the future of the company because first, it was created
Speaker 1: with the knowledge that this program, this cooperation with Project
Speaker 1: Maven is only a very small baby step in what
Speaker 1: management hopes will be a long, elaborate staircase, a much
Speaker 1: larger series of cooperations. You see, Maven is not a
Speaker 1: one off thing. It's not its own it's not its
Speaker 1: own centerpiece. It is a pilot program. It is taking
Speaker 1: a concept and running it around the block to see
Speaker 1: how it drives. Secondly, Google employees believe that this project
Speaker 1: is symptomatic of what they see as a larger and
Speaker 1: growing problem in Google. They say the company is becoming
Speaker 1: less and less transparent across all all facets, public facing,
Speaker 1: government facing, employee facing, user facing, and they've even shed
Speaker 1: their old famous motto don't be evil.
Speaker 2: Yeah, but now if you go to let's see the
Speaker 2: Google dot com slash about our company slash our dash company,
Speaker 2: it says this is what their mission statement is now
Speaker 2: quote organize the world's information and make it universally accessible
Speaker 2: and useful, and maybe be a little evil if needed.
Speaker 2: I don't see that written anywhere where.
Speaker 5: I think it's implied. I think getting rid of that
Speaker 5: original mission statement and getting into these kind of deals
Speaker 5: implies such things.
Speaker 1: They do have a on their Code of Conduct they
Speaker 1: made some changes that have a wonky timeline about them too,
Speaker 1: Because there's an article on Gizmoto by Kate Conger wherein
Speaker 1: the author finds the section of the old Code of
Speaker 1: Conduct that was archived by the way back Machine on
Speaker 1: and listening to the State carefully April twenty first, twenty
Speaker 1: eighteen that still has all that don't be evil mentioned. Yeah, right,
Speaker 1: And then the updated version that was first archived on
Speaker 1: May fourth, twenty eighteen took out all but one of
Speaker 1: those mentions of don't be evil, and the Code of
Speaker 1: Conduct itself says it has not been updated since April
Speaker 1: fifth of twenty eighteen, So the timeline doesn't match up.
Speaker 1: User error. Possibly hmm, possibly.
Speaker 2: Wayback machine, what you're doing over there?
Speaker 1: Yeah? Did they get to you, wayback machine? Regardless of
Speaker 1: you know, whether you feel that this is just a
Speaker 1: series of unconnected dots being forced into a larger perceived pattern,
Speaker 1: whether you think people are practicing confirmation bias, or whether
Speaker 1: there really is something rotten there in Silicon Valley, the
Speaker 1: fact of the matter is you can read the full
Speaker 1: text of the petition online and find out what the
Speaker 1: Google employees themselves thought. We have a few highlights here.
Speaker 1: We cannot, they say in the petition outsource the moral
Speaker 1: responsibility of our technologies to third parties. Google stated values
Speaker 1: make this clear. Every one of our users is trusting us,
Speaker 1: never jeopardize that. Ever, this contract referring to MAVEN puts
Speaker 1: Google's reputation at risk and stands in direct opposition to
Speaker 1: our core values. Building this technology to assist the US
Speaker 1: government in military surveillance and potentially lethal outcomes is not acceptable.
Speaker 1: Recognizing Google's moral and ethical responsibility and the threat to
Speaker 1: Google's reputation, we request that you cancel this project immediately, draft, publicize,
Speaker 1: and enforce a clear policy stating that neither Google nor
Speaker 1: its contractors will ever build warfare technology.
Speaker 5: And a writer for en Gadget actually reached out to
Speaker 5: Google and they were provided with the following statement.
Speaker 4: Quote.
Speaker 5: An important part of our culture is having employees who
Speaker 5: are actively engaged in the work that we do. We
Speaker 5: know that there are many open questions involved in the
Speaker 5: use of new technologies, so these conversations with employees and
Speaker 5: outside experts are hugely important and beneficial. MAVEN is a
Speaker 5: well publicized DoD project, and Google is working on one
Speaker 5: part of it, specifically scope to be for non offensive
Speaker 5: purposes and using open source object recognition software available to
Speaker 5: any Google Cloud customer. The models are based on unclassified
Speaker 5: data only. The technology is used to flag images for
Speaker 5: human review and is intended to save lives and save
Speaker 5: people from having to do highly tedious work.
Speaker 4: I'm just gonna finish. I think it's worth it. Any
Speaker 4: military use of machine learning naturally raises valid concerns. We're
Speaker 4: actively engaged across the company in a comprehensive discussion of
Speaker 4: this important topic and also with outside experts as we
Speaker 4: continue to develop our policies around the development and use
Speaker 4: of our machine learning technologies.
Speaker 2: So basically, we're gonna keep making this project. Sorry, guys.
Speaker 4: Yeah, it's cool, but it's okay.
Speaker 1: Because we're going to have a quote unquote healthy conversation
Speaker 1: about it. Here's what happens next. As you said, mat,
Speaker 1: Google refuses to backwave from this project. They're still going
Speaker 1: to go through Noel. As as we can clean from
Speaker 1: the statement you read, they say it is going to
Speaker 1: be nonviolent and there's no spooky stuff going on. It's
Speaker 1: all unclassified. Over three thousand engineers signed this petition and
Speaker 1: a dozen resigned. More may resign in the future. This
Speaker 1: resignation wave is happening as we record this, and it's
Speaker 1: due to a coldly fascinating moral quandary. It's this, how
Speaker 1: responsible are these engineers for the applications of their inventions?
Speaker 1: Is for example, the creator of the Winchester repeating rifle
Speaker 1: guilty for the deaths caused by that weapon. His wife
Speaker 1: thought so, and that's why she built a crazy mansion
Speaker 1: out west, which we still, believe it or not, have
Speaker 1: never visited.
Speaker 4: Oh man, I really want to go.
Speaker 1: Yeah, I think we should absolutely go. Paul, would you
Speaker 1: go with us if we If we go to the
Speaker 1: Winchester mansion, we got we got an ardent thumbs up
Speaker 1: from him, they both.
Speaker 4: Paul's got some some beefy thumbs Yeah.
Speaker 2: You go into all the rooms first, Paul.
Speaker 4: Yeah, it's just a test for traps.
Speaker 2: Yeah. No.
Speaker 5: But it also like Oppenheimer, right, he was famously had
Speaker 5: serious qualms about the way his technology was used in
Speaker 5: terms of being weapons of mass destruction.
Speaker 1: And Einstein also tortured by the He didn't build a
Speaker 1: physical thing, but he was tortured by the idea that
Speaker 1: his own realizations had led to this. So with this
Speaker 1: in mind, if an engineer builds software for the purpose of, say,
Speaker 1: more efficiently delivering payloads to locations in near Earth orbit,
Speaker 1: and that same software is later used to deliver payloads
Speaker 1: of bombs to people that the drones owners don't care for.
Speaker 1: Is that engineer then responsible for the ensuing damage and
Speaker 1: or death. It's a quandary that a lot of people
Speaker 1: are having a hard time answering to go back and
Speaker 1: noll to something you mentioned earlier about the dilemmas of
Speaker 1: autonomous vehicles. One of the current nie unanswerable questions, or
Speaker 1: at least when that hasn't been answered yet, is what
Speaker 1: happens if there is an imminent accident that's going to
Speaker 1: occur and you're in an autonomous vehicle. Does the vehicle
Speaker 1: swerve and hit a pedestrian? Does it prioritize the person
Speaker 1: in the vehicle their life over the life of a
Speaker 1: person who deserves to live just as much but happens
Speaker 1: not to be in the vehicle, And if so, who
Speaker 1: is responsible? Is it the person who is in the
Speaker 1: vehicle for not taking control if they could. Is it
Speaker 1: the company that manufactured the vehicle? Is it the engineer
Speaker 1: who made the software that made the vehicle make that choice.
Speaker 1: The trolley problem of the old thought exercise becomes increasingly concrete,
Speaker 1: increasingly dangerous, and increasingly complicated, and frankly, we're not equipped
Speaker 1: to answer it at this point.
Speaker 5: No, it's it's it's it's an utter conundrum because what
Speaker 5: you know to be that programmer who gets to make
Speaker 5: that decision, you're essentially playing god, aren't you.
Speaker 4: It's like what life is more valuable? You know? Is
Speaker 4: it our customer or is it the pedestrian.
Speaker 5: There's really no way of properly answering that without making
Speaker 5: a serious judgment, call a hard and fast choice.
Speaker 1: Right, Yeah, you could bake in something where it's just
Speaker 1: an absolute calculation of the number of lives. So, for instance,
Speaker 1: in that case, if there is a crowd of five
Speaker 1: people who are gathered for their Paul Decant fan club meeting,
Speaker 1: which inexplicably takes place on the sidewalk by a busy road.
Speaker 1: If those five people are gathered for that meeting and
Speaker 1: there's only one person in the car, does the car say, Okay,
Speaker 1: we'll just pop the airbags and hope this one person survives,
Speaker 1: but we're not going to kill five people for one
Speaker 1: And then what if there are two people in that
Speaker 1: car and one of them is pregnant. And what if
Speaker 1: the five people on the sidewalk celebrating with the Paul
Speaker 1: Decant fan club, what if they're all in their seventies
Speaker 1: right and pass report of age generally speaking? You know
Speaker 1: what I mean? This this is the kind of stuff
Speaker 1: that we have not yet, as far as we know,
Speaker 1: learned to program for.
Speaker 5: Then before you know it, you've got you know, power
Speaker 5: hungry cars mowing down old ladies because they've you know,
Speaker 5: they've they've lived their life.
Speaker 4: They're expendable.
Speaker 1: But like, what what about a school bus? Does a
Speaker 1: school bus, based on the number of kids it has,
Speaker 1: does that have just immunity to always prioritize the children
Speaker 1: on the bus. It's very politically difficult to argue against.
Speaker 2: That, oh man man.
Speaker 1: Matt leaned back for that.
Speaker 2: Oof, Yeah, because of what happens when a public bus
Speaker 2: and then a school bus are both operating and there's
Speaker 2: a crash a minute.
Speaker 1: I don't know, because I'm marta. Most of the buses
Speaker 1: are empty, Oh shade, It's true, It's true.
Speaker 5: What about the street cars? The street car even emptier empties.
Speaker 1: There's there's not even a driver.
Speaker 2: Yeah. At this point, the Marta buses are just hopping
Speaker 2: on the trolleys.
Speaker 4: This is some serious Atlanta inside baseball.
Speaker 1: It is true. Learn about our public infrastructure debacles. We're
Speaker 1: working on it. We're doing our best things.
Speaker 4: It's gonna be called it's gonna be rebranded to the atl.
Speaker 2: WHOA, that's cool.
Speaker 1: Yeah, nothing weird about that, nothing forced about that. Right.
Speaker 1: So Google is unfazed. They're not only going to continue
Speaker 1: this project, which we should also say is not super
Speaker 1: super big. It's publicly described as being worth a minimum
Speaker 1: of nine million dollars. That's a lot of money to
Speaker 1: normal people. That's not a lot of money to Google.
Speaker 1: But they are vying for additional projects within this military space,
Speaker 1: and this is not unprecedented. IBM has a long standing
Speaker 1: relationship with the US military on a number of fronts
Speaker 1: and also cough cough, Nazi Germany cough cough.
Speaker 4: Yes, did you guys know the Hugo boss designed the
Speaker 4: Nazi uniform?
Speaker 1: Yes?
Speaker 4: I did not know that until yesterday. Shock.
Speaker 5: What a great pr team they must have to still
Speaker 5: be around after that.
Speaker 1: Seriously, well, I mean there were a lot of German
Speaker 1: companies that.
Speaker 4: Were for sure Volkswagen, even I think was interesting.
Speaker 1: On an additional note, IBM itself may be drawing an
Speaker 1: ethical line. They have signaled that they will not create
Speaker 1: intelligent drones for warfare, and a blog post they had
Speaker 1: recently IBM said they're committed to the ethical and responsible
Speaker 1: advancement of AI technology and the AI or machine consciousness
Speaker 1: should be used to augment human decision making rather than
Speaker 1: replace it. So that's similar to the argument that automated
Speaker 1: vehicle systems for consumers should be doing a lot of
Speaker 1: assisted driving, but there should always be a human behind
Speaker 1: the wheel.
Speaker 2: That's probably a good call International Business Machines.
Speaker 1: That's true. Oh, that's true. And of course shout out
Speaker 1: to everybody who listened to our other episodes on the
Speaker 1: evil of machine consciousness, And personally I prefer that term
Speaker 1: to AI because what why is it artificial?
Speaker 2: Right?
Speaker 1: Why are we so special?
Speaker 2: Yeah, And at this point I'm just going to urge
Speaker 2: everybody to go through and read that open letter that
Speaker 2: was written by the International Committee for Robot Arms Control.
Speaker 2: There are some pretty terrifying things that they go into there,
Speaker 2: specifically about the slippery slope that Project Maven represents. So
Speaker 2: I would go and read that. You can find it
Speaker 2: Robot Arms Control Open Letter.
Speaker 1: I when you first showed this to me, Matt, I
Speaker 1: was cartoonishly tickled because I originally read the title as
Speaker 1: the International Committee for Robot Arms.
Speaker 2: Yeah.
Speaker 1: Yeah, and I didn't read the control part. At the end, Man,
Speaker 1: it was a long day. So what do they say, though,
Speaker 1: what's one thing that really stood out to you in
Speaker 1: this letter?
Speaker 2: Well, here's the quote. We are just a short up
Speaker 2: away from authorizing autonomous drones to kill automatically without human
Speaker 2: supervision or meaningful human control. Tight that alone. Just you know,
Speaker 2: if you arm these weapons, these flying autonomous weapons, with
Speaker 2: the ability to make those decisions, yeah, that's a target
Speaker 2: that's not a target, that is definitely a target kill.
Speaker 1: What happens if they get hacked as well.
Speaker 2: Or if they just are just operating someone loses control
Speaker 2: somehow just however.
Speaker 1: Or if they're operating independently somewhere and they have some
Speaker 1: sort of cognitive leap, and they say, you know, the
Speaker 1: best way to achieve the objective is to get rid
Speaker 1: of everyone. That would almost never happen. We're talking the
Speaker 1: odds of winning the lottery eight times in a row.
Speaker 4: We're talking about like a terminator scenario, right.
Speaker 1: Some Skynet stuff for now that is still relegated to
Speaker 1: the realm of dystopian science fiction.
Speaker 2: But they do make another really great point. I just
Speaker 2: want to say here. They are deeply concerned about the
Speaker 2: possible integration of Google's data, the data that they have
Speaker 2: on everyone on you, probably massive data set, integrating that
Speaker 2: with this military surveillance data and combining that and applying
Speaker 2: it to this targeted killing.
Speaker 4: Notion so you can cross reference.
Speaker 2: Yeah, and this is a you know, these aren't just
Speaker 2: some Joe Schmoe's getting together and saying, hey, we need
Speaker 2: to write this letter, you guys. These are some serious
Speaker 2: engineers and academics and people who are working in these
Speaker 2: fields saying like raising a flag and saying no, no, no, no, no,
Speaker 2: we got to watch this.
Speaker 1: We know where this could go. Yeah, and now we
Speaker 1: draw this episode to a close, and we don't have
Speaker 1: a solid answer or prediction. We're right here with you, folks,
Speaker 1: unless you are working directly for Project Mavin, right, we
Speaker 1: don't know. No one knows where exactly we are going
Speaker 1: to paraphrase Jim Wilder and Willie walk up.
Speaker 5: Unless we forget to mention that Google is also obviously
Speaker 5: doing some super innovative, fascinating things that are quite good
Speaker 5: for humanity. Potentially, they're using machine learning to develop testing
Speaker 5: software that can actually find different complications related to diabetes
Speaker 5: and also early signs of breast cancer, and the FDA,
Speaker 5: according to this article from Wired, is already in early
Speaker 5: stages of approving AI software that can help doctors make
Speaker 5: very important life or death medical decisions. And this is
Speaker 5: from an article called Google's new AI head is so
Speaker 5: smart he doesn't need AI. About this guy, Jeff Dean,
Speaker 5: who is a big part of a lot of Google's
Speaker 5: AI innovations.
Speaker 1: That's a great point because we can't we cannot forget
Speaker 1: how large and varied Google and Alphabetter's organizations are. There's
Speaker 1: Google dot org as well, where you can learn about
Speaker 1: how they're using data to uncover racial injustice or building
Speaker 1: open source platforms to translate books for disadvantaged kids. It's
Speaker 1: absolutely right. I really appreciate bringing it up because they're
Speaker 1: not just this solely evil thing, right, And sometimes those
Speaker 1: aims of these these large departments within Google may even
Speaker 1: contradict one another.
Speaker 5: And you got to think, too, like an argument, maybe
Speaker 5: that a big high mucky mucket Google might make about
Speaker 5: getting involved in something like this is like, well, if
Speaker 5: it's not us, you know, and we're obviously going to
Speaker 5: handle it with thoughtfulness and care. If it's not us,
Speaker 5: it's going to be somebody else who might do a
Speaker 5: less good job, you know, and not think about the ramifications.
Speaker 5: So you know, even that statement that we read earlier,
Speaker 5: it was pretty measured.
Speaker 4: I thought it was actually not bad.
Speaker 1: Yeah, just kill people correctly, right.
Speaker 5: Well, okay, you got me there, Ben, I guess what
Speaker 5: I mean is though it did sound like pure pr
Speaker 5: it was like, we get it.
Speaker 4: It's a thing.
Speaker 5: We understand that there is there are always consequences associated
Speaker 5: with this kind of stuff, but we're aware of them
Speaker 5: and we feel that we're equipped to help mitigate some
Speaker 5: of that. But it's against the badger're out of the
Speaker 5: bag scenario, right, It's not up to you anymore at
Speaker 5: that point.
Speaker 1: And if you would like to learn more about Project
Speaker 1: Maven specifically, please check out tech Stuff. They have a
Speaker 1: podcast that just came out on this program. It's hosted
Speaker 1: by our longtime friends sometimes Nemesis and Complaint Department Jonathan Strickland.
Speaker 1: Available twenty four to seven for any issues or criticisms
Speaker 1: you have of stuff they don't want you to know,
Speaker 1: you can reach of me is Jonathan dot Strickland to
Speaker 1: HowStuffWorks dot com.
Speaker 5: He just launched a live chat kind of situation too,
Speaker 5: so we can suss out your issues in real time.
Speaker 2: Yeah, yeah, yeah, like a drone, exactly like a drone.
Speaker 2: It'll especially help you out on Twitch if he's ever
Speaker 2: on there.
Speaker 1: No, let's say Google does somehow create a policy banning
Speaker 1: any and all military partnerships. He let's go a little
Speaker 1: bit further and say that all US tech companies follow
Speaker 1: their lead and do the same thing, because there are
Speaker 1: industry wide calls for everyone not to play this particular obo.
Speaker 1: I mean, let's even go further and say that all
Speaker 1: tech companies in the world refuse to help the US
Speaker 1: build self aware weapons of war. You know who will
Speaker 1: continue this research? All caps, every single country that can
Speaker 1: afford it, every single private company that does not have
Speaker 1: the same moral quandaries about hypothetical scenarios, every single individual
Speaker 1: that does not have those kind of quandaries. It is
Speaker 1: again going to happen, and it.
Speaker 4: Gets worse the AI race.
Speaker 1: Yeah, it is. That's a good way to put it
Speaker 1: and to paraphrase Billy Mays, but wait, it gets worse.
Speaker 1: We'd like to end today's episode on an ethical quandary
Speaker 1: question that you could feel free to suss out yourself.
Speaker 1: Have a couple of couple of beers over, if you drink, meditate,
Speaker 1: if you do that, whatever you do to get yourself
Speaker 1: in a thoughtful headspace, and let us know what are
Speaker 1: the implications here. What sort of machine consciousness are we creating?
Speaker 1: Are we making something that will be inherently belligerent? And
Speaker 1: if so, If the world's first machine consciousness is built
Speaker 1: to kill, how will this influence is later increasingly self
Speaker 1: directed actions, its thoughts, it's recognizations, it's emotions, or whatever
Speaker 1: those equivalents are. Imagine whether they're imagine if you would
Speaker 1: that there were two different versions of machine consciousness. One
Speaker 1: maybe is built to optimize agricultural projects in a transforming ecosystem,
Speaker 1: and the other is built to finds people and annihilate
Speaker 1: them or buildings. What happens next? Where do they go?
Speaker 1: Do these things like the early drones? Do they increasingly
Speaker 1: speciate and become more attenuated. There's the argument that we
Speaker 1: have with biological entities, with human minds, and that is that, yes,
Speaker 1: people change, but they don't change in the way you think.
Speaker 1: Over time, we tend to become more concentrated versions of
Speaker 1: who we were in the beginning. Now one could say
Speaker 1: that this is not something to be too disturbed by,
Speaker 1: because a human engineer could drop in and maybe incept
Speaker 1: this machine mind with a different, different line of code
Speaker 1: that would alter its behavior. And maybe now it says
Speaker 1: I'm tired of killing right, or I have new programming.
Speaker 1: But we have to consider that if we are as
Speaker 1: a species creating minds that may one day have their
Speaker 1: own agency as much as as a human being, maybe
Speaker 1: more eventually, maybe in our lifetimes, they will have more
Speaker 1: agency and potential because they won't have the same biological,
Speaker 1: hardwired limits that human beings have. What kind of minds
Speaker 1: are we building? And why?
Speaker 2: You can find us on Twitter and Facebook where we're
Speaker 2: conspiracy stuff, conspiracy stuff show on on uh Instagram that's
Speaker 2: the where that one is. You can find our podcast
Speaker 2: and everything else that's stuff they don't want you to
Speaker 2: know dot com. UH tell us what you think of,
Speaker 2: like what kind of minds are we creating? Like Ben
Speaker 2: speaking to what's happened Heady stuff heady mind. Yes, this
Speaker 2: is uh terrifying and I need to use the restroom
Speaker 2: now because I am the p has been done scared
Speaker 2: right out of me.
Speaker 4: We better, we better take care of that right now.
Speaker 5: Oh we need As we are not AI, we still
Speaker 5: have to, you know, take care of our bodily needs.
Speaker 4: But in the meantime, if you.
Speaker 2: Would like it, and that's the end of this classic episode.
Speaker 2: If you have any thoughts or questions about this episode,
Speaker 2: you can get into contact with us in a number
Speaker 2: of different ways. One of the best is to give
Speaker 2: us a call. Our number is one eight three three
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