Speaker 1: Get in touch with technology with tech Stuff from how
Speaker 1: stuff works dot com. Hey there, and welcome to tech Stuff.
Speaker 1: I'm your host, Jonathan Strickland. I'm an executive producer at
Speaker 1: how stuff Works and I love all things tech. Although
Speaker 1: this particular topic maybe a little less than usual because
Speaker 1: it gets pretty harry. Seeing May two thousand eighteen, News
Speaker 1: broke that more than a dozen Google employees had handed
Speaker 1: in their resignations over the company's involvement in a program
Speaker 1: called Project Maven. So what the heck is Project Maven
Speaker 1: and why did those employees leave? And why have an
Speaker 1: estimated four thousand Google employees put their names on petitions
Speaker 1: to end the company's involvement with the project. It's time
Speaker 1: to dive into a really serious current topic. Project Maven
Speaker 1: is a large technology project overseen by the United States
Speaker 1: Defense Department with a specific focus on bringing artificial intelligence
Speaker 1: or AI applications into military functions and campaigns. The argument
Speaker 1: for Project may even was that AI as a field
Speaker 1: has been advancing for years, with particularly impressive advancements made
Speaker 1: in the last couple of years alone, and yet the
Speaker 1: military has lagged behind. As Air Force Lieutenant General Jack
Speaker 1: sent Shanahan wrote in the Bulletin of the Atomic Scientists
Speaker 1: back in November. Quote. The US military still performs many
Speaker 1: activities in a style that would be familiar to the
Speaker 1: military of World War Two end quote. The argument was
Speaker 1: that something needed to change to bring these processes into
Speaker 1: the twenty first century. To that effect, on April two
Speaker 1: thousand seventeen, Robert Work, who then was the Deputy Secretary
Speaker 1: of the Defense Department, released a memo calling for the
Speaker 1: establishment of a new team called Project Maven. Well that's
Speaker 1: the nickname. The other name for the team was the
Speaker 1: Algorithmic Warfare Cross Functional Team. The memos opening paragraph says this,
Speaker 1: and I quote, as numerous studies have made clear, the
Speaker 1: Department of Defense must integrate artificial intelligence and machine learning
Speaker 1: more effectively across operations to maintain advantages over increasingly capable
Speaker 1: adversaries and competitors. Although we have taken tentative steps to
Speaker 1: explore the potential of artificial intelligence, big data, and deep learning,
Speaker 1: I remain convinced that we need to do much more
Speaker 1: and move much faster across d O D that's Department
Speaker 1: of Defense to take advantage of recent and future advances
Speaker 1: in these critical areas end quote. On its face, this
Speaker 1: sounds pretty reasonable, or at least understandable. After all, AI
Speaker 1: has the potential to do enormous good or harm depending
Speaker 1: upon its design and implementation. To not pursue AI in
Speaker 1: the realm of military applications seems like it would be
Speaker 1: a bad idea. Other nations and militaries are certainly exploring
Speaker 1: such options, and the landscape of warfare continues to change
Speaker 1: and become more complex. Artificial or augmented intelligence would be
Speaker 1: really handy in such a world. Being able to work
Speaker 1: with sophisticated programs to identify targets, gather intelligence, and form
Speaker 1: strategies could potentially win a conflict, save lives, or it
Speaker 1: might even allow for a non violent method to resolve
Speaker 1: a situation, which in my mind, tends to be the
Speaker 1: best of all options. The memos third paragraph details what
Speaker 1: this group's focus will be, and I quote yet again,
Speaker 1: the a w c f t S first task is
Speaker 1: to field technology to augment or automate processing, exploitation and
Speaker 1: dissemination p e D for tactical Unmanned aerial system u
Speaker 1: a S and mid altitude full motion video fm V
Speaker 1: in support of the Defeat ISIS campaign. This will help
Speaker 1: to reduce the human factors burden of FMV analysis, increase
Speaker 1: actionable intelligence, and enhance military decision making. A w c
Speaker 1: FT will number one organize a data labeling effort and develop, acquire,
Speaker 1: and or modify algorithms to accomplish key tasks. Number two
Speaker 1: identify required computational resources and identify a path to fielding
Speaker 1: that infrastructure. And number three integrate algorithmic based technology with
Speaker 1: programs of record in nine D day sprints. Now, remember
Speaker 1: a sprint when we talked about agile frameworks is a
Speaker 1: essentially a period of time in which a project takes
Speaker 1: place and you're expected to do numerous updates throughout that
Speaker 1: period and have something that is implementable by the end
Speaker 1: of the sprint. Now, in other words, the earliest task
Speaker 1: for this new project was to work on programs that
Speaker 1: would allow unmanned aerial systems which we commonly refer to
Speaker 1: as drones, to analyze full motion video with object detection
Speaker 1: and classification in an effort to identify members of ISIS,
Speaker 1: areas of interest, equipment and weapons that bad actors might
Speaker 1: have at their disposal. The memo continues on to talk
Speaker 1: about the use of machine learning and automation and efforts
Speaker 1: of improving intelligence, surveillance and reconnaissance missions. The memo established
Speaker 1: May one, twenty seventeen, as the date of the first
Speaker 1: meeting of the a w c F T OR Project
Speaker 1: MAVEN to give reports directly to the Administrator of the program,
Speaker 1: who would be Robert Work himself. Lieutenant General Shanahan was
Speaker 1: named director of the project, which originally had only six
Speaker 1: members on it, and this marked an aggressive strategy to
Speaker 1: implement these technologies in the realm of the combat theater,
Speaker 1: and to do so very quickly. Now that's not to
Speaker 1: say that the Department of Defense was a stranger to
Speaker 1: cutting edge technology. Far from it. In nineteen fifty eight,
Speaker 1: President Dwight D. Eisenhower formed the Advanced Research Projects Agency
Speaker 1: or ARPA, which would change names to the Defense Advanced
Speaker 1: Research Projects Agency or DARPA in nineteen seventy two. While
Speaker 1: the agency has swapped names back and forth since then
Speaker 1: a couple of times, its mission has remained the same.
Speaker 1: The office provides funding for various projects aimed to expand
Speaker 1: science and technology, generally with some thought given towards the
Speaker 1: possible military benefits. Those projects have led to amazing things,
Speaker 1: including the Internet and the development of autonomous cars. But
Speaker 1: while those projects have had and will continue to have
Speaker 1: a major impact both in military and non military uses,
Speaker 1: the focus wasn't narrow enough for the purposes of Project Mayven.
Speaker 1: This project marked a change, one in which the military
Speaker 1: would be reaching out to experts in the various disciplines
Speaker 1: that comprise artificial intelligence, with the goal of improving military
Speaker 1: capabilities that could be implemented as soon as possible in
Speaker 1: a real world combat theater setting. Obviously, this raised many
Speaker 1: questions about the process and implementation of technologies. The political
Speaker 1: climate was, to put it mildly delicate. Many companies weren't
Speaker 1: eager to get involved in projects in the wake of
Speaker 1: Donald Trump's election to president, and various information leaks about
Speaker 1: governments and corporations had left many more companies a little
Speaker 1: cautious about getting involved in defense contracts. Part of the
Speaker 1: strategy to deal with this reluctance was a tight focus
Speaker 1: on a specific implementation of AI, that being full motion
Speaker 1: video analysis. The AI and Project MAVEN isn't meant to
Speaker 1: take any sort of military or offensive action. Instead, it's
Speaker 1: meant to sift through data. More on that in just
Speaker 1: a second, but first let's take a quick break to
Speaker 1: thank our sponsor. Not only was the committee looking for
Speaker 1: rapid development, the project also had the goal of streamlining
Speaker 1: all the bureaucratic red tape most parties had to endure
Speaker 1: when applying for funding from the government. The contracting procedures
Speaker 1: with the government had a well earned reputation for being
Speaker 1: laborious and slow. This alone discouraged many from applying to
Speaker 1: be part of government projects. Why would you go through
Speaker 1: the long approval process when you could work in the
Speaker 1: private sector and make money the entire time. Also, project
Speaker 1: may even focused on reducing the pains of contracting with
Speaker 1: government agencies. I thought that was kind of a clever
Speaker 1: part of the project, not just the idea of finding
Speaker 1: a way to get these technologies rapidly developed and deployed,
Speaker 1: but how to streamline the process on the front end
Speaker 1: to encourage more participants in the project. And then there's
Speaker 1: the desire for rapid deployment. Getting technology out in the
Speaker 1: field can be a long process on top of everything else.
Speaker 1: In short, all the stages of funding, developing, and implementing
Speaker 1: technology are traditionally so slow when it comes to government
Speaker 1: contracts that by the time you get the tech out
Speaker 1: into the real world, it's already obsolete. Project may even
Speaker 1: aimed to change all that. The goal was to develop
Speaker 1: tools and iterations and allow the user community that's their quote,
Speaker 1: to test them as they became available. Now, in this case,
Speaker 1: the user community happens to be the military to create
Speaker 1: an AI that can analyze full motion video and look
Speaker 1: look for specific things within that video. That was the
Speaker 1: whole purpose of the project, and it called for an
Speaker 1: artificial neural network. I've talked about these before, but let
Speaker 1: me give a quick rundown of what this is right now.
Speaker 1: Roughly speaking, and artificial neural network is a system of
Speaker 1: one or more computers in which units of calculation called neurons,
Speaker 1: connect to one another through weighted values called synapses in
Speaker 1: an effort process information in a way that's similar to
Speaker 1: how our brains work. As these neurons perform operations on data,
Speaker 1: they send the data through the synapses, which affects the
Speaker 1: data itself. This data eventually emerges as output, though the
Speaker 1: design of the neural network determines how many neurons it
Speaker 1: must pass through before this happens. The goal is to
Speaker 1: create a system that can actually learn, once trained to
Speaker 1: do something, so Let's say you've got an artificial neural
Speaker 1: network and you want to train it to recognize a
Speaker 1: specific image, and we'll say, for the purposes of this example,
Speaker 1: that the image is a cat. You start to feed
Speaker 1: the artificial neural network a series of images, some of
Speaker 1: them cats and some of them of other things, and
Speaker 1: you design the network so it identifies an object as
Speaker 1: a cat by process of elimination. And if it does
Speaker 1: identify something as a cat and it's not a cat,
Speaker 1: it generates an error. That error then back propagates through
Speaker 1: the whole network, and the system quote unquote learns that
Speaker 1: that particular image did not represent a cat, and if
Speaker 1: it encounters that image again, it won't mistakenly identify the
Speaker 1: image as a cat. The same is true if it
Speaker 1: fails to identify a cat that is present in an image.
Speaker 1: Doing this millions of times will refine the system as
Speaker 1: it learns what is and is not a cat. Google
Speaker 1: actually did something similar to this several years ago. Google's
Speaker 1: research and development lab created an artificial neural network consisting
Speaker 1: of sixteen thousand computer processors with a billion connections within
Speaker 1: the system. They fed the system ten million YouTube video
Speaker 1: thumbnails selected at random, then they gave the system a
Speaker 1: list of twenty thousand items. The system began to recognize
Speaker 1: pictures of cats using a deep learning algorithm. And remember,
Speaker 1: an algorithm is just a set of instructions directions that
Speaker 1: you follow in order to get to a specific result.
Speaker 1: The big breakthrough year was that this system was able
Speaker 1: to recognize the image of a cat without first being
Speaker 1: taught what a cat actually was. It learned through training
Speaker 1: itself by looking at this large set of data. In
Speaker 1: a similar fashion, Project May even wished to develop an
Speaker 1: artificial neural network that could identify potential ISIS activity. Lieutenant
Speaker 1: General Shanahan wrote about how the military has countless hours
Speaker 1: of footage gathered by unmanned aerial systems or drones. A
Speaker 1: quick word about these. The ones he named specifically included
Speaker 1: the Scan Eagle, the m Q one C Gray Eagle,
Speaker 1: and the m Q nine Reaper. The Boeing in situ
Speaker 1: Scan Eagle is a low altitude drone that is more
Speaker 1: than five ft long or about one and a half meters,
Speaker 1: with a wingspan a little more than ten ft or
Speaker 1: three point one one ms wide. It can travel at
Speaker 1: ninety two miles per hour. Also at kilometers per hour
Speaker 1: at top speed, and it can stay in flight for
Speaker 1: more than twenty four hours at a time. Has high
Speaker 1: resolution imaging sensors on it, including thermal imagery sensors. The
Speaker 1: m Q one C Gray Eagle is built by General Atomics.
Speaker 1: It's a medium altitude drone and is an upgrade to
Speaker 1: the famous Predator drone. It's much larger than the Scan Eagle,
Speaker 1: at twenty eight feet or eight point five three ms
Speaker 1: long and a wingspan of fifty six feet or seventeen
Speaker 1: meters wide. It can travel at a hundred two miles
Speaker 1: per hour or three nine kilometers per hour at top speed,
Speaker 1: and it, unlike the Scan Eagle, can be armed with
Speaker 1: stuff like bombs and missiles. The m Q nine Reaper,
Speaker 1: sometimes called the Predator B is even larger. It's more
Speaker 1: than thirty six ft long or about eleven meters, it's
Speaker 1: got a wingspan of sixty ft seven inches or twenty meters,
Speaker 1: and it can travel at three hundred miles per hour
Speaker 1: or two kilometers per hour at top speed, and it
Speaker 1: can also carry a various armory of weapons all on itself.
Speaker 1: So those are drones that could be used for offensive measures.
Speaker 1: While the Lieutenant General was talking only about using an
Speaker 1: artificial neural network to analyze video captured by devices like this.
Speaker 1: Naming a couple of drones that are weaponized likely raised
Speaker 1: many eyebrows, but let me stick with what he was
Speaker 1: pitching back in November. Just for his argument, Shanahan specifically
Speaker 1: talked about how these drones were gathering thousands of hours
Speaker 1: of video intelligence, but sifting through that intelligence required even
Speaker 1: more time and many human analysts. Even then, you could
Speaker 1: only tackle a fraction of what was being gathered. This
Speaker 1: meant that most of the time you were reacting to
Speaker 1: something that had happened in the field. For example, if
Speaker 1: an improvised explosive detonated, you might scour through video footage
Speaker 1: of the area leading up to the detonation in an
Speaker 1: attempt to identify the persons responsible for it and then
Speaker 1: track their movements. It still takes an incredible amount of
Speaker 1: time and work to follow these things, but one of
Speaker 1: you could automate the system, bringing up analysts to look
Speaker 1: at what Shanahan was referring to as higher value analysis
Speaker 1: work and AI system that could comb through hours of
Speaker 1: data and automatically classify and label things, categorizing them either
Speaker 1: as mundane and unimportant or something to pay attention to
Speaker 1: flagging it for human analysis. It could conceivably make a
Speaker 1: huge difference and speed things up. Not at the start.
Speaker 1: Humans labeled more than one hundred fifty thousand images to
Speaker 1: train Maven on data sets, with the goal of increasing
Speaker 1: that up to one million images by the end of January.
Speaker 1: This would give Maven a start at being able to
Speaker 1: identify various objects at different distances, resolutions, angles, and more.
Speaker 1: Because remember, computer vision is a tricky thing. Teaching a
Speaker 1: computer to recognize an image of something is tricky enough,
Speaker 1: even if you're just sticking to one kind of lighting,
Speaker 1: one orientation. I always use the example of a coffee mug.
Speaker 1: Let's say you've got a red, bright red coffee mug
Speaker 1: and the handles pointed toward the left with respect to
Speaker 1: your view through an image, and you teach a computer
Speaker 1: this is a coffee mug. Well, what happens if you
Speaker 1: have it under a different lighting so it doesn't look
Speaker 1: like it's bright red, and maybe you've turned it so
Speaker 1: that the handles facing the other way, and maybe the
Speaker 1: angle is a little bit different, so you're looking kind
Speaker 1: of down into the cup. Will the computers still be
Speaker 1: able to recognize that as a coffee mug. You have
Speaker 1: to train it. And then let's say that you change
Speaker 1: the color of the coffee mug. Is the exact same shape,
Speaker 1: but now it's blue instead of red. Will the computer
Speaker 1: recognize it. Let's say that you change the shape of
Speaker 1: the coffee mug. Now it's a different style of coffee
Speaker 1: mug from the previous one. We humans can pick up
Speaker 1: on this very quickly. You teach a human a couple
Speaker 1: of things about coffee mugs, and then they kind of
Speaker 1: get the innate grasp of it. You can show them
Speaker 1: all sorts of different sizes, shapes, colors, lighting conditions. They're
Speaker 1: going to recognize that as a coffee mug. The same
Speaker 1: is not necessarily true with computers, so training it is
Speaker 1: a laborious process. Now, once it is trained, it can
Speaker 1: go through data far faster than a human could, but
Speaker 1: you still have to teach it. Shanahan viewed this project
Speaker 1: as proof that a small, nimble team approach in getting
Speaker 1: the right parties involved worked, and that this in turn
Speaker 1: would spawn a new era of high tech projects aimed
Speaker 1: at incorporating AI into other military operations. He also even
Speaker 1: expressed a little caution about this era. So what exactly
Speaker 1: about all of this prompted so many at Google to
Speaker 1: protest the company's involvement. Well, I'll explain that in just
Speaker 1: a second, but first let's take another quick break to
Speaker 1: thank our sponsor. By the end of twenty seen technology
Speaker 1: developed for a project Maven was in use in various
Speaker 1: sights in the Middle East, and that's an incredible turnaround.
Speaker 1: It was less than a year that had gone by
Speaker 1: since the April memo had launched the project, and already
Speaker 1: AI algorithms were being trained to look for specific types
Speaker 1: of data within full motion video footage. Not only was
Speaker 1: it being used in the Middle East, the military was
Speaker 1: already starting to use it in other parts of the
Speaker 1: world like Africa. The military stress that this tech was
Speaker 1: meant to augment personnel's abilities in gathering and sifting through information.
Speaker 1: It was meant to flag data so that a human
Speaker 1: analyst could look it over. Nothing was automatically happening through
Speaker 1: this system. There was no intent to do anything beyond
Speaker 1: analyzing information the military was already gathering. But that's still
Speaker 1: a pretty alarming revelation for many people and over at Google.
Speaker 1: Google being a company that was handling a lot of
Speaker 1: this information, a lot of these algorithms, and working with
Speaker 1: the military to develop them. Worries we're growing that it
Speaker 1: would not stop at data analysis, and this brings us
Speaker 1: to the petition that thousands of Google employees signed. The
Speaker 1: Google petition opens with a pretty clear message. Quote, we
Speaker 1: believe that Google should not be in the business of war. Therefore,
Speaker 1: we asked that project may even be canceled, and that
Speaker 1: Google draft publicize and enforce a clear policy saying that
Speaker 1: neither Google nor its contractors will ever build warfare technology.
Speaker 1: End quote. The petition also expressed skepticism about Project Maven's
Speaker 1: stated purpose. In the third paragraph, it reads, quote, recently
Speaker 1: Googler's voice concerns about Maven internally, Diane Green responded, assuring
Speaker 1: them that the technology will not operate or fly drones
Speaker 1: and will not be used to launch weapons. While this
Speaker 1: eliminates a narrow set of direct applications, the technology is
Speaker 1: being built for the military, and once it's delivered, it
Speaker 1: could easily be used to assist in these tasks end quote.
Speaker 1: The petition states that beyond the ethical and moral implications
Speaker 1: of the project, that it will do damage to the company,
Speaker 1: including hurting its ability to attract talent to work for Google, saying,
Speaker 1: if we have a reputation for giving the military technology
Speaker 1: that helps them kill people, it's gonna be really hard
Speaker 1: to convince new developers to come work for our company.
Speaker 1: A Google spokesperson responded to the petition with a letter
Speaker 1: It says, quote MAVEN is a well publicized Department of
Speaker 1: Defense project, and Google is working on one part of it,
Speaker 1: specifically scope to be for non offensive purposes and using
Speaker 1: open source object recognition software available to any Google Cloud customer.
Speaker 1: The models are based on unclassified data only. The technology
Speaker 1: is used to flag images for human review and is
Speaker 1: intended to save lives and save people from having to
Speaker 1: do highly td is work. End quote. So the response
Speaker 1: here saying this technology, these algorithms are already available and
Speaker 1: they're open source. Anyone could take that source code and
Speaker 1: develop applications based upon it. So really, Google could take
Speaker 1: the contract and make some money off of it, or
Speaker 1: not take the contract, but their work still ends up
Speaker 1: being used for that purpose because it's open source and
Speaker 1: anyone can use it. According to this spokesperson, the AI
Speaker 1: and project may even is only assisting humans by pulling
Speaker 1: up that data that may be of interest while ignoring
Speaker 1: everything else, so it's not making any decisions on its own.
Speaker 1: But even Shanahan states in his blog post that there
Speaker 1: are ethical questions when it comes to incorporating AI that
Speaker 1: must be addressed. He urges for the development of quote,
Speaker 1: technological and organizational safeguards to ensure that Washington's military use
Speaker 1: of AI is consistent with national values end quote. He
Speaker 1: also points out that AI could be vulnerable to different
Speaker 1: failure modes that could be disastrous, and that these two
Speaker 1: must be taken into consideration. So he's saying that we
Speaker 1: have to implement it responsibly, and we have to be
Speaker 1: aware of its failure points so that we can make
Speaker 1: sure that it's not vulnerable to them, because otherwise we're
Speaker 1: going to rely far too heavily on a dangerous technology
Speaker 1: that could end up causing irreparable harm if misused. To
Speaker 1: further complicate matters, other groups have also urged Google to
Speaker 1: step away from military projects. In April two thousand eighteen,
Speaker 1: one year after May Even launched as a project, the
Speaker 1: Tech Workers Coalition, which is a group representing employees of
Speaker 1: major tech companies like Google, IBM, Microsoft, Amazon, and others,
Speaker 1: launched their own petition stating that tech should not be
Speaker 1: in the business of war. This petition says that military
Speaker 1: contracts break user trust, in this case the user being
Speaker 1: either the general public or in the case of big
Speaker 1: companies like ib UM, other companies, and the International Committee
Speaker 1: for Robot Arms Control meaning autonomous weapons not you know
Speaker 1: the arms of a robot issued an open letter to
Speaker 1: Google urging the company to stop pursuing military contracts. More
Speaker 1: than ninety academics signed this paper. The letter paints a
Speaker 1: very grim picture of a possible use for Maven, that
Speaker 1: of identifying targets based upon probabilities arrived at by analyzing
Speaker 1: long range surveillance footage, ultimately resulting in signature strikes and
Speaker 1: pattern of life strikes, meaning that Google would at least
Speaker 1: be somewhat complicit in targeted killings. The letter goes on
Speaker 1: to state that while the express purpose of Maven is
Speaker 1: purely for analysis, such tools could be turned toward automated
Speaker 1: target recognition in the future. Those of you who are
Speaker 1: Terminator fans might think of this as another step toward
Speaker 1: the mythical sky net system, which would ultimately turn against
Speaker 1: humans and attempt to wipe us out. Sending Arnold Schwarzenegger
Speaker 1: back in time. The letter ends with three requests, First
Speaker 1: that Google terminate its project may even contract with the
Speaker 1: Department of Defense. Second, that the company commit not to
Speaker 1: develop military technologies nor to allow the personal data is
Speaker 1: collected to be used for military operations. And finally that
Speaker 1: it pledged to neither participate in nor support the development, manufacture, trade,
Speaker 1: or use of autonomous weapons, and to support efforts to
Speaker 1: ban autonomous weapons. So far, Google hasn't shown any signs
Speaker 1: of following those suggestions. In fact, it's been reported that
Speaker 1: the company is actively bidding on another Department of Defense
Speaker 1: project called the Joint Enterprise Defense Infrastructure or JEDI. This
Speaker 1: project's goal is to create a suite of cloud services
Speaker 1: for the Department of Defense. It's largely intended to reduce
Speaker 1: complexity in military data storage systems, which at the moment
Speaker 1: are fragmented across multiple branches and departments. The at EYE
Speaker 1: contract will go to a single vendor, which means one
Speaker 1: company stands to make a lot of money from the project.
Speaker 1: That's hard to walk away from. I suppose that if
Speaker 1: thousands of your employees are protesting the move, it might
Speaker 1: warrant some soul searching. Now, current wisdom states that Amazon
Speaker 1: is probably in the lead for that Jedi contract. Anyway,
Speaker 1: it might behoove Google to consider listening to its employees
Speaker 1: in an effort not to alienate its workforce and to
Speaker 1: potentially damage the company's reputation to the point where no
Speaker 1: one will come and work for it, or very few
Speaker 1: and not necessarily the best and brightest. I'm very conflicted
Speaker 1: about this. On the one hand, using artificial intelligence to
Speaker 1: augment people's abilities to do what they've already started doing.
Speaker 1: Is it makes sense to me using it to help
Speaker 1: people cut down on endless hours of work? I get that.
Speaker 1: On the other hand, if you do think about this
Speaker 1: as being a stepping stone towards using AI to actually
Speaker 1: target and potentially kill people, that is terrifying. It is
Speaker 1: terrifying to think of the amount of power that gives
Speaker 1: people the uh the removal of barriers to commit such actions,
Speaker 1: because if you think about military actions, you have to
Speaker 1: think if you are in command of the possibility of
Speaker 1: the loss of human life on your side, right, you
Speaker 1: have to consider that you have to say how many
Speaker 1: how many people are we going to lose if we
Speaker 1: commit to this action and is our commitment to that
Speaker 1: action justifiable based on how many people we think we're
Speaker 1: gonna lose. Well, if you start using automated systems, then
Speaker 1: that number creeps down closer to zero for your side. Right,
Speaker 1: If you're using automated systems to carry out your attacks,
Speaker 1: then you have fewer casualties on your side, and that
Speaker 1: might mean that you're more willing to enter into those
Speaker 1: situations and thus more people do die. It's just there
Speaker 1: are people on the other side. So you might, as
Speaker 1: a military personnel, considered that a good thing, but for
Speaker 1: others like myself, you might consider it pretty horrifying. So
Speaker 1: I totally understand why there are Google employees walking out
Speaker 1: of the company resigning they are unable to resolve their
Speaker 1: philosophical beliefs with the moves that the company has made
Speaker 1: in the last year. Uh. I also understand the need
Speaker 1: to incorporate AI into military operations. So this is a
Speaker 1: very complicated topic. It's not something that's so easy to
Speaker 1: say this is wrong and we shouldn't do it. Because
Speaker 1: I also agree with Shanahan who says other organizations out there, countries,
Speaker 1: militaries and others are already working on this, and so
Speaker 1: we need to do it too, just so that we
Speaker 1: don't end up falling behind. There cannot be an AI gap,
Speaker 1: so it becomes another arms race, which a lot of
Speaker 1: people have likened a I two in the past. Anyway,
Speaker 1: I wraps up this discussion about Project Maven. If you
Speaker 1: guys have any suggestions for future topics I can tackle
Speaker 1: here on tech Stuff, please send them to me. My
Speaker 1: email address is tech stuff at our stuff works dot com,
Speaker 1: or you can draw me a line on Twitter or Facebook.
Speaker 1: To handle with both of those is text stuff h
Speaker 1: s W. Remember we have an Instagram account. You can
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Speaker 1: on twitch dot tv slash tech Stuff. Come on over
Speaker 1: there on a Wednesday or Friday. You're gonna see me
Speaker 1: record these shows live, and you'll see as I slowly
Speaker 1: lose my sanity as more and more people walk in
Speaker 1: and out of the door that's directly adjacent to this
Speaker 1: recording studio, necessitating that I re record the thing I
Speaker 1: just said a second earlier. If you want to see
Speaker 1: Jonathan go insane, go to twitch dot tv slash tech
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Speaker 1: be part of the fun. I hope to see there,
Speaker 1: and I'll talk to you again really soon. For more
Speaker 1: on this and thousands of other topics, is a How
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