Speaker 1: Welcome to tech Stuff, a production of I Heart Radios,
Speaker 1: How Stuff Works. Hey there, and welcome to tech Stuff.
Speaker 1: I'm your host, Jonathan Strickland. I'm an executive producer with
Speaker 1: I Heart Radio and How Stuff Works and a love
Speaker 1: of all things tech and A couple of recent stories
Speaker 1: in the summer of twenty nineteen have been about the
Speaker 1: subject of brain computer interfaces or b C eyes. That's
Speaker 1: a topic I've touched on with previous episodes of Tech Stuff,
Speaker 1: and if you listened to the show Forward Thinking, we
Speaker 1: covered it on that show as well. But since we've
Speaker 1: now got people like Elon Musk and Mark Zuckerberg behind
Speaker 1: the efforts of creating BC eyes, I figured to be
Speaker 1: a good time to revisit the topic, talk about what
Speaker 1: it is, how far along or not far along we
Speaker 1: are with the technology and the ethical can iterations we
Speaker 1: need to keep in mind when we're developing tech like this.
Speaker 1: So a brain computer interface is exactly what it sounds like.
Speaker 1: It's a methodology to allow a user to control or
Speaker 1: interact with a computer directly through brain activity through thought.
Speaker 1: It marries the complicated subjects of neuroscience and computer science
Speaker 1: and a lot of media outlets sort of gloss over
Speaker 1: how truly complicated this is. We have a tendency to
Speaker 1: either think of our brains as being kind of like computers,
Speaker 1: or of computers as being kind of like brains, but
Speaker 1: really they're quite different, and creating an interface that can
Speaker 1: translate the operations of one so that it makes sense
Speaker 1: to the other is harder than it sounds. The goal
Speaker 1: of a brain computer interface is to strip away as
Speaker 1: much of the barrier between our intent and the computer's
Speaker 1: actions as possible, is to get beyond the limitations of
Speaker 1: other types of interfaces. So let's talk about those other
Speaker 1: interfaces for a second to kind of have a comparison here. So,
Speaker 1: in the very early days of computers, like the earliest
Speaker 1: electro mechanical computers, the interface was incredibly complicated. It consisted
Speaker 1: of switches and plugs, so you'd have to physically make
Speaker 1: changes to the machine to run a different calculation. You
Speaker 1: programmed it by physically changing the connections. Operating a computer
Speaker 1: required learning a pretty intricate system, so it was a
Speaker 1: very high barrier to using computers. But on the other hand,
Speaker 1: there were hardly any computers to use, so it wasn't
Speaker 1: like people were stumped all the time. It wasn't like
Speaker 1: you were in the I. T Department looking at a
Speaker 1: manual that was five thousand pages long. There are only
Speaker 1: a few computers in the world at all. Now, gradually
Speaker 1: this gave way to other interface systems, and it first
Speaker 1: they were still incredibly complicated, at least by today's standards.
Speaker 1: The punch cards of yesterday are a really good example.
Speaker 1: You could feed a series of punch cards which represented
Speaker 1: a program, to a computer. The computer would read the
Speaker 1: punch cards, make whatever calculations were indicated by those punch cards,
Speaker 1: and then it might in turn spit out a different
Speaker 1: set of punch cards, or it might light up some
Speaker 1: indicator lights. Maybe if you were lucky, you had a
Speaker 1: printer and it would print out a result. But boy,
Speaker 1: it was still a pretty tough barrier of entry as
Speaker 1: far as computer use was concerned. It wasn't something the
Speaker 1: average person could tackle on his or her own. Now.
Speaker 1: A huge breakthrough was the incorporation of computer displays and keyboards,
Speaker 1: and there were other advances in computers at the time
Speaker 1: that also made a huge difference, like the development of
Speaker 1: operating systems and high level programming languages. And we obviously
Speaker 1: still use keyboards and displace today. So these were really
Speaker 1: sticky types of interfaces so to speak. Actually that could
Speaker 1: be literal if you tend to drink sugary sodas while
Speaker 1: you're computing, but I'm mostly talking about the metaphorical here. Anyway.
Speaker 1: The computer mouse would then expand how we would interact
Speaker 1: with computers, as would the graphic user interface or gooey.
Speaker 1: This would allow us to have new ways to interact
Speaker 1: with our machines, and then we would see further advancements
Speaker 1: like voice recognition systems and touch screen interfaces. It was
Speaker 1: pretty typical that each advance in technology, if it was
Speaker 1: implemented well, would make interactions with computers easier and more natural.
Speaker 1: So when you see a kid look at a screen
Speaker 1: and the kid has never really played with keyboard, mouse
Speaker 1: or even touch screens, yet you might see them reach
Speaker 1: out and try to touch things on the screen, Well,
Speaker 1: that tells you, oh, a touch screen might work better
Speaker 1: for certain things. Maybe not everything, but certain things. And
Speaker 1: then you start to implement that kind of interface in
Speaker 1: low and behold, you see I've created a new way
Speaker 1: to interact with this machine. Well, brain computer interfaces would
Speaker 1: remove even those small gaps between our intent and executing
Speaker 1: a command on a computer. Ideally, you would have a
Speaker 1: non invasive technology, meaning you wouldn't have to have any
Speaker 1: kind of surgery or anything in order to actually use
Speaker 1: this stuff, and that technology would be able to interpret
Speaker 1: your thoughts as commands, and then the computer would carry
Speaker 1: those out, and the computer could potentially send information back
Speaker 1: to you through those same channels that you could interpret
Speaker 1: in some meaningful way. And there are a lot of
Speaker 1: potential uses for this kind of technology, and many of
Speaker 1: those uses are truly noble in their mission. For example,
Speaker 1: and I'll talk a lot about this in this episode,
Speaker 1: it could allow people who have severe mobility issues and
Speaker 1: outlet for interacting with the world around on them that
Speaker 1: they might not otherwise have. With the proper interface, someone
Speaker 1: who is paralyzed and may not be able to move
Speaker 1: or even speak could use the interface to activate commands
Speaker 1: on a computer in order to communicate with others or
Speaker 1: carry out tasks with the help of robotics and automated systems.
Speaker 1: We've actually seen applications of brain computer interfaces do this
Speaker 1: kind of thing already to a limited degree, and frankly,
Speaker 1: it's amazing and inspiring. I I highly recommend you seek
Speaker 1: out stories and videos about these types of projects because
Speaker 1: they are phenomenal. But there are use cases beyond helping
Speaker 1: people gain more autonomy, and some of them are a
Speaker 1: bit well, let's say they're a bit questionable. So let's
Speaker 1: walk down the history of brain computer interfaces and then
Speaker 1: we will revisit these specific examples, as well as what
Speaker 1: is currently going on with Elon Musk and Facebook getting
Speaker 1: into the game. Well before such a thing could even
Speaker 1: be theorized as a brain computer interface, we first had
Speaker 1: to understand more about how the brain itself works. And
Speaker 1: this is a non trivial thing. The brain was largely
Speaker 1: an organ of mystery for a very long time. In
Speaker 1: the late nineteenth century, physicians and scientists were first starting
Speaker 1: to learn that there is electrical activity in the brains
Speaker 1: of mammals. We started to get an understanding that our
Speaker 1: nervous system is an electrochemical system, that electricity and chemicals
Speaker 1: play a very important part in sending messages through this
Speaker 1: system in a very sophisticated way. Now, this was the
Speaker 1: same time that physicists were getting a better understanding about energy,
Speaker 1: and so there was a curiosity about energy in the brain.
Speaker 1: The brain does stuff, It must get energy, it must
Speaker 1: use energy. What is that mechanism? What the physicists of
Speaker 1: the time didn't yet understand was that the brain was
Speaker 1: this electro chemical machine. They didn't have a complete picture yet.
Speaker 1: So for a few decades, research mostly with animals like dogs, rabbits,
Speaker 1: and monkeys, showed that brains generated electrical activity in some fashion,
Speaker 1: and by the early twentieth century we had a rudimentary
Speaker 1: understanding of brain waves. Then Hans Burger, a German psychiatrist
Speaker 1: and physicist, recorded the first human E E G. In
Speaker 1: the mid nineteen twenties. Now, Burger was interested in investigating
Speaker 1: psychical energy in the brain. He was convinced that there
Speaker 1: is some energy beyond what is needed to do quote
Speaker 1: unquote work that would be thinking and operating the human body.
Speaker 1: He never did uncover any sort of psychical energy and
Speaker 1: his research, but his invention of the electro and cephalogram
Speaker 1: would set the stage for neuroscience in the twentieth century.
Speaker 1: And I'll have to do a full episode about Burger
Speaker 1: in the future because he was a really interesting person.
Speaker 1: His life story is full of drama. Now, over the
Speaker 1: next several decades after Burger's invention of the e G,
Speaker 1: or at least the the refining of the e G,
Speaker 1: since there were sort of precursors to the E e
Speaker 1: G before Burger got involved anyway. Over the following years,
Speaker 1: scientists and doctors refined their understanding of electrical activity in
Speaker 1: the brain, and they observed phenomena like R E M sleep.
Speaker 1: They identified different types of brain waves. Neuroscientists also got
Speaker 1: a deeper understanding about what the different parts of the
Speaker 1: brain do and are responsible for, and that gets really
Speaker 1: super complicated. Their sections of the brain that are dedicated
Speaker 1: to very specific tasks and major parts of the brain
Speaker 1: include stuff like the frontal lobe, the parietal lobe, the
Speaker 1: temporal lobe, the occipital lobe, cerebellum, and more. And I
Speaker 1: am no neuroscientist, and to go into deep detail on
Speaker 1: all of these parts would necessitate at least a couple
Speaker 1: of episodes plus an expert on the subject matter. So
Speaker 1: I'm just gonna leave the general discussion of the brain
Speaker 1: with an acknowledgement that they are really complicated. Now, there's
Speaker 1: still a ton that we don't know about the brain,
Speaker 1: and probably there's stuff we don't know that we don't
Speaker 1: know but we've made a lot of progress, which has
Speaker 1: led to some enterprising researchers, scientists, and technologists to look
Speaker 1: into ways to create an interface between the machine in
Speaker 1: our heads and the computers around us. In the nineteen sixties,
Speaker 1: a neurophysicist named William gray Walter demonstrated that the electrical
Speaker 1: signals and brains could do useful work outside of our noggins.
Speaker 1: And it was a fairly primitive demonstration, but an effective one.
Speaker 1: He had subjects who had electrode implants for e g s.
Speaker 1: By the way, e g s can either involve having
Speaker 1: surgical implants of electrodes or electrodes that are part of
Speaker 1: you know, the sticky pads that stick against the scalp.
Speaker 1: They have to be positioned in very precise places. But
Speaker 1: you can have invasive or non invasive e g s.
Speaker 1: What William gray Walter was working with were the invasive types.
Speaker 1: So he had these people who are wired up e
Speaker 1: g s and they were navigating through a slide show
Speaker 1: with an old slide show projector, and they were using
Speaker 1: a remote control to advance to the next slide. So
Speaker 1: when they were done looking at a slide, or if
Speaker 1: they were told to go to the next slide. They
Speaker 1: would push a button and it would go to the
Speaker 1: next slide. But what Walter didn't tell these people who
Speaker 1: had their e g s hooked up to the system
Speaker 1: was that the remote control was a nert it. It
Speaker 1: didn't work at all. It was just a dummy remote. Rather,
Speaker 1: when the subject's brain sent the command I'm going to
Speaker 1: use the remote now, the electrodes would pick up that
Speaker 1: brain activity and it would send those signals onto an amplifier,
Speaker 1: which would boost the signal enough to send a command
Speaker 1: to go to the next slide to the projector. It's
Speaker 1: a very simple one, just the same sort of electrical
Speaker 1: impulse that the projector would get if you push the
Speaker 1: button now. The subjects reportedly were startled by this experience
Speaker 1: because frequently they would make the decision that they were
Speaker 1: going to go to the next slide, and they would
Speaker 1: be in the process of pushing the button when the
Speaker 1: slide would change in advance before they had pushed the button.
Speaker 1: They said it started to feel like the slide projector
Speaker 1: had anticipated their action. It had guessed that they were
Speaker 1: ready to move on even though they had not yet
Speaker 1: pushed the button. And in a way, that's exactly what
Speaker 1: it had done, or rather it was able to act
Speaker 1: faster than the subject was, and it raised some really
Speaker 1: interesting questions about consciousness because the implication was that we
Speaker 1: can arrive at a decision to do something before we
Speaker 1: are actually aware of the decision we have made. And
Speaker 1: so in theory, if you have a brain computer interface,
Speaker 1: you might get the sensation that you're working with a
Speaker 1: machine that's actually anticipating what you want to do before
Speaker 1: you are aware that you wanted to do it, which
Speaker 1: is both kind of creepy and amazing. Now, in reality,
Speaker 1: it's because you wanted to do that thing, but your
Speaker 1: awareness of your desire hasn't caught up yet. It's brains
Speaker 1: are funny things. It's also possible that because of those
Speaker 1: implanted electrodes, which can detect activity and relatively small regions
Speaker 1: of the brain, allowed for more precision when looking for
Speaker 1: signals that would indicate I'm going to push the button,
Speaker 1: rather than signals that would indicate something like blink now
Speaker 1: or eat soon or whatever. So, in other words, it's
Speaker 1: very important to target the neurons that are going to
Speaker 1: be responsible for whatever activity you're looking for. You can't
Speaker 1: just have, you know, a general brain reading device that's
Speaker 1: looking for any electrical activity in the brain. There's always
Speaker 1: electrical activity in the brain, so you have to be
Speaker 1: looking for precise activity, or else you would have a
Speaker 1: system that's constantly activating under no particular impulse. Jacques J.
Speaker 1: Vidal coined the phrase brain computer interface in nineteen The
Speaker 1: DOLL presented a plan towards establishing the technology for such
Speaker 1: an interface at the University of California at Los Angeles.
Speaker 1: And it should come as no surprise that one of
Speaker 1: the big organizations that has funded a lot of research
Speaker 1: into brain computer interfaces is DARPA, or the Defense Advanced
Speaker 1: Research Projects Agency in the United States. This is the
Speaker 1: part of the Department of Defense that oversees money that
Speaker 1: can be granted to projects that relate back to national
Speaker 1: security and defense strategies for the United States. Sometimes these
Speaker 1: projects have an obvious connection to national defense, such as
Speaker 1: research into new types of weaponry. Other times the connection
Speaker 1: might not be quite as clear, such as the DARPA
Speaker 1: Grand challenges that help bootstrap the development of driverless car technologies.
Speaker 1: But I think you could agree that brain computer interfaces,
Speaker 1: you could think of a lot of different potential uses
Speaker 1: to augment national defense with that kind of technology. So
Speaker 1: DARPA has funded a ton of research into BC eyes
Speaker 1: and much of that work has had incredible results. Now
Speaker 1: I'm not just talking about device that would let you control,
Speaker 1: say a computer cursor with your mind, but technologies that
Speaker 1: would help people regain lost senses like hearing or vision.
Speaker 1: And it's all through stimulating neurons in specific ways, so
Speaker 1: it becomes a bidirectional communications channel. It's incredible stuff. And
Speaker 1: again the subject matter is vast and it would require
Speaker 1: lots of episodes. But the bit I wanted to focus
Speaker 1: on in the early history was a project in nineteen
Speaker 1: seventy four. It was called the Close Coupled Man Machine
Speaker 1: Systems Project, and later on it would undergo a name change.
Speaker 1: It would become known as bio cybernetics. To quote the article,
Speaker 1: DARPA funded efforts in the development of novel brain computer
Speaker 1: interface technologies in the April two thousand, fifteen Journal of
Speaker 1: Neuroscience Methods. Quote. This program investigated the application of human
Speaker 1: physiological signals, including brain signals as measured non invasively using
Speaker 1: either E E G or magneto and cephalography m EG,
Speaker 1: to enable direct communication between humans and machines, and to
Speaker 1: monitor neural states associated with vigilance, fatigue, emotions, decision making, perception,
Speaker 1: and general cognitive ability. The program yielded notable advancements such
Speaker 1: as detailed understanding of single trial sensory evoked responses in
Speaker 1: the e g. Of human participants. These efforts demonstrated that
Speaker 1: neural activity in response to visual checkerboard stimuli alternating at
Speaker 1: different frequencies at each of four fixation points could be
Speaker 1: decoded in real time and used to navigate a cursor
Speaker 1: through a simple maze. End quote. Fascinating stuff. Now we're
Speaker 1: gonna take a quick break, but when we come back,
Speaker 1: I'll give a little bit more about the history and
Speaker 1: talk about the different approaches to brain computer interfaces. Now
Speaker 1: to detail every bc I project since the early nineteen
Speaker 1: seventies would take us hours. There have been countless. Some
Speaker 1: of them have led to amazing sets and breakthroughs, some
Speaker 1: revealed frustrating barriers and challenges that we've yet to overcome.
Speaker 1: I'll talk about a few more examples in a moment,
Speaker 1: and I should stress that I'm just kind of arbitrarily
Speaker 1: picking these examples because there's been so much amazing work
Speaker 1: in this field. But before I get into that, I
Speaker 1: want to talk about one of the biggest challenges in
Speaker 1: the way of a robust brain computer interface, and that's
Speaker 1: reading the signals of the brain reliably. So there are
Speaker 1: two broad categories you can consider when it comes to
Speaker 1: monitoring brain activity, and those would be invasive methods and
Speaker 1: non invasive methods, or surgical and non surgical. Typically, though
Speaker 1: there are some methods that are considered non invasive that
Speaker 1: still involve implanting stuff into the brain, it's just it
Speaker 1: tends to be through less invasive procedures like an injection
Speaker 1: as opposed to brain surgery. And uh yeah, But generally
Speaker 1: we're talking about technology that has to be surgically implanted
Speaker 1: on the brain, or to anology that can monitor brain
Speaker 1: activity without first having to you know, crack open a skull.
Speaker 1: And as you can imagine, this is a pretty big
Speaker 1: difference right between these categories. So let's break down the
Speaker 1: pros and cons of each of them. So the cons
Speaker 1: with invasive approaches are pretty darn easy to anticipate, right,
Speaker 1: I mean, we use brain surgery as a stand in
Speaker 1: for any activity that requires an incredible amount of knowledge, understanding,
Speaker 1: and skill to perform. It's right out there with rocket science.
Speaker 1: We do that because we know brain surgery is freaking hard,
Speaker 1: it's risky, and I think it's safe to say that
Speaker 1: the vast majority of people out there aren't too keen
Speaker 1: to undergo a surgical procedure unless the potential benefits are
Speaker 1: truly impressive, maybe life saving or life changing. Invasive methods
Speaker 1: typically involve either implanting electrodes directly into brain matter or
Speaker 1: using small sensor pads that essentially stick to the exterior
Speaker 1: of the brain. Implanting electrodes comes with its own set
Speaker 1: of challenge is and one is that it can cause
Speaker 1: scarring in the brain, and if scar tissue forms near
Speaker 1: the electrode, it can interfere with the electrodes ability to
Speaker 1: pick up that electrical activity from neurons, so the scarring
Speaker 1: process can prevent the electrodes from being able to do
Speaker 1: their jobs. Another challenge is that sometimes an electrode could
Speaker 1: shift slightly in the brain, and even a small shift
Speaker 1: could mean the electrode would no longer be able to
Speaker 1: pick up signals from the targeted neurons. There have been
Speaker 1: some impressive advancements in getting around these challenges. Philip our
Speaker 1: Kennedy of Emory University, which is just down the road
Speaker 1: from our office in Atlanta, developed a neural electrode with
Speaker 1: a tip encased in a tiny glass cone. Neurons would
Speaker 1: actually grow into the cone and reach the electrode. The
Speaker 1: cone helped protect the electrode from scarring, and the neurons
Speaker 1: growing into the cone helped it resist any shifting. Kennedy
Speaker 1: worked with a few patients to test the design and
Speaker 1: work out actual useful brain computer interactions. One of those
Speaker 1: patients was a man named Johnny Ray, a man who
Speaker 1: was nearly immobile and incapable of communication after a severe stroke.
Speaker 1: Surgeons implanted electrodes in Ray's brain in March, and Ray
Speaker 1: learned how to move a cursor on a screen. He
Speaker 1: was imagining that he was moving the cursor with his
Speaker 1: hand like he was making hand movements, or imagining that
Speaker 1: because he didn't have that capability anymore. He later learned
Speaker 1: to move a cursor on a screen to highlight letters,
Speaker 1: and then he would click on them like with a mouse,
Speaker 1: except he did it by twitching his shoulders, one of
Speaker 1: the few muscle movements he could still do. When he
Speaker 1: was asked by the media what he felt when he
Speaker 1: moved the cursor, he spelled out the word nothing, which
Speaker 1: doctors actually interpreted to mean that Ray no longer had
Speaker 1: to even imagine moving his hand anymore. His brain had
Speaker 1: become trained to move the cursor through thought alone without
Speaker 1: having to have the hand as sort of an intermediate step.
Speaker 1: And this highlights one of the biggest ed vantages that
Speaker 1: the invasive methodology has over the non invasive version. Implants
Speaker 1: have a more direct path to the neurons that they
Speaker 1: are monitoring. They are more precise, they're more finely attuned.
Speaker 1: They can pick up signals much more easily. Brown University
Speaker 1: professor John P. Donohue is another pioneer using electrode implants
Speaker 1: as part of research into brain computer interfaces. His team
Speaker 1: created a system called brain Gate, which initially had ninety
Speaker 1: six electrodes arrayed on a small implant, and by small
Speaker 1: immunit measures about four millimeters per side. It's about the
Speaker 1: size of a baby aspirin. As Science Daily put it,
Speaker 1: the stories about brain Gate are pretty inspiring. People who
Speaker 1: have become paralyzed have undergone the surgical procedure to have
Speaker 1: the electrode array implanted in their brains, then they have
Speaker 1: gone through an extensive training period to learn how to
Speaker 1: use this technology. In that training period, they learn how
Speaker 1: to control some exterior technology with their thoughts. It might
Speaker 1: be a cursor on a screen, giving them the ability
Speaker 1: to communicate and run applications kind of like a computer mouse.
Speaker 1: It could be a robotic limb. And on top of that,
Speaker 1: there's been work to create systems that can replicate a
Speaker 1: sense of touch in the user. So not only can
Speaker 1: the person with the implants in commands to an external
Speaker 1: piece of technology, they can also experience tactile feedback as
Speaker 1: if that external tech was one of their natural limbs.
Speaker 1: So a person outfitted with a robotic arm connected to
Speaker 1: this type of interface could not just pick stuff up,
Speaker 1: which is already phenomenal with a robotic limb, they could
Speaker 1: actually feel how tightly they were holding the thing they
Speaker 1: picked up, and that becomes really important for things like
Speaker 1: fine motor skills. And this is incredible stuff. But I
Speaker 1: would still argue that it's fairly primitive in the sense
Speaker 1: that I think we're just at the very dawn of
Speaker 1: being able to harness this type of technology that we
Speaker 1: We've made some incredible strides, but there's a long way
Speaker 1: to go. Now, let's get back to the non invasive approach.
Speaker 1: So a clear advantage here is that you don't have
Speaker 1: to have any sort of surgical procedure to make use
Speaker 1: of noninvasive technology. And an e G can be an
Speaker 1: example of a noninvasive approach. Right, you just have those
Speaker 1: electrodes that you slap onto your scalp, but you don't
Speaker 1: have to have a transcranial system. Uh So you can't
Speaker 1: have e G s that are transcranial, meaning that they
Speaker 1: it requires brain surgery and you have wires that stick
Speaker 1: out through your cranium, through your skull. But you can
Speaker 1: have noninvasive ones too. But even with the electrodes on
Speaker 1: the scalp, we run into other problems, and a big
Speaker 1: one is that the signals in our brains aren't really
Speaker 1: that strong electrically speaking, and their skulls are fairly decent
Speaker 1: at muffling those signals. Plus, if we're moving around a
Speaker 1: lot having the rig we're using it, it needs to
Speaker 1: remain steady because otherwise we might end up misaligning things
Speaker 1: and again we end up reading the wrong neurons, and
Speaker 1: then an irrelevant brain signal could initiate a command that
Speaker 1: we weren't intending to send. That's obviously a big challenge.
Speaker 1: Now we can get a really good look at what's
Speaker 1: going on inside the brain using noninvasive technology like an
Speaker 1: m r I, But in an m r I requires
Speaker 1: a person to lay very still inside a very large
Speaker 1: and very noisy machine for quite a long time, so
Speaker 1: it's not a practical solution. If you want to build
Speaker 1: a brain computer interface for day to day use. There's
Speaker 1: a lot of work going into finding a methodology to
Speaker 1: read brain signals, either directly or indirectly through noninvasive means.
Speaker 1: Getting a method to a point where the precision and
Speaker 1: accuracy rivals the implanted electrodes is a non trivial challenge.
Speaker 1: DARPA is funding a lot of research into that area. However,
Speaker 1: it stands to reason that if the agency wants to
Speaker 1: use bc I technology for divinse purposes, it would be
Speaker 1: ideal to have a version that doesn't require the user
Speaker 1: to first undergo a surgical for seizure. In May two
Speaker 1: thousand nineteen, the agency announced it was working with six
Speaker 1: different teams to explore non invasive bc I strategies and
Speaker 1: what was called the next generation non Surgical neuro Technology
Speaker 1: or in three program. Included in those teams are people
Speaker 1: from Carnegie Mellon University, the Palo Alto Research Center or Park,
Speaker 1: and Telendyne Scientific among others, and the proposals are really interesting.
Speaker 1: One from Battel Memorial Institute proposes electro magnetic neuro transducers
Speaker 1: that are quote non surgically delivered to neurons of interest
Speaker 1: into quote. They will then take electrical signals from the
Speaker 1: neurons and convert them into magnetic signals, which could then
Speaker 1: be picked up by an external transceiver, and the neuro
Speaker 1: transducers could also perform the same process in reverse, taking
Speaker 1: incoming magnetic fields or magnetic fluctuations and transmitting them as
Speaker 1: electric signals to neurons and the brain, so it could
Speaker 1: be bi directional. Other methods including acousto optical approach, which
Speaker 1: means the team responsible plans to use ultrasonic signals to
Speaker 1: guide light into the brain to detect a neural activity.
Speaker 1: There's a similar one, but it would use magnetic fields
Speaker 1: rather than light, while still using ultrasonic signals to generate
Speaker 1: localized electric currents in the brain. It's all really fascinating stuff,
Speaker 1: and it also quickly gets beyond my understanding of neuroscience
Speaker 1: and physics, so I won't spend a whole lot more
Speaker 1: time talking about them, but they are pretty darn nifty.
Speaker 1: In the meantime, researchers have been relying on the established
Speaker 1: E e G. Technology to do a lot of the
Speaker 1: groundwork for a noninvasive approach, but as I mentioned, that
Speaker 1: has some big limitations to it, so it's just a
Speaker 1: stepping stone, and there are other groups looking at different
Speaker 1: ways to measure brain activity for the purposes of an interface.
Speaker 1: Finding a method is replicable and accurate is still a
Speaker 1: really hard thing to do, whether it's looking specific fickly
Speaker 1: at neuron activity or maybe something like keeping tabs on
Speaker 1: changes in blood flow in the brain, so you're looking
Speaker 1: at sort of an indirect indicator in those cases. At
Speaker 1: the same time, researchers are starting to rely upon machine
Speaker 1: learning strategies to help train the technology to determine whether
Speaker 1: or not any particular signal is a real hit or
Speaker 1: a false flag. So this is actually a multidisciplinary endeavor.
Speaker 1: It's going to rely on many different technologies as well
Speaker 1: as our understanding of neuroscience, which continues to grow. Okay,
Speaker 1: so we know about the tech and we know a
Speaker 1: bit about history. We know that still in fairly early
Speaker 1: stages of development. When we come back, I'll talk about
Speaker 1: Elon Musk, Facebook, and brain computer interfaces. But first let's
Speaker 1: take another quick break. So in July two thousand nineteen,
Speaker 1: one of the many tech stories to come out about
Speaker 1: Elon Musk, because there's never a shortage of them, had
Speaker 1: to do with the startup company Neuralalink. Now, for some people,
Speaker 1: this was the first they had ever heard of Musk's
Speaker 1: interest in creating a brain computer interface, but in fact
Speaker 1: he had been talking about this kind of thing since
Speaker 1: at least two thousand and sixteen. At the CODE Conference
Speaker 1: of two thousand and sixteen, he talked about a ton
Speaker 1: of stuff, including a technology called neural lace. Neural lace
Speaker 1: is a term for a mesh of electrodes that could
Speaker 1: graft into the brain through a simple injection in the
Speaker 1: ideal implementation, so no full brain surgery was would be needed,
Speaker 1: and ideally it would be wireless and offer the chance
Speaker 1: to interact with computer systems through thought alone, which is
Speaker 1: pretty nifty, but it's also essentially science fiction, at least
Speaker 1: in that incarnation. Not that the idea has no merit,
Speaker 1: but rather, we hadn't any real clue on how to
Speaker 1: go about doing it. Yet it's only a little bit
Speaker 1: better than saying, you know, it's sure would be nice
Speaker 1: if we had teleporters. Well, yeah, it would be nice,
Speaker 1: But that doesn't mean we can suddenly build teleporters just
Speaker 1: because it would be nice to have them now. In
Speaker 1: two thousand sixteen, Musk said he was interested in developing
Speaker 1: this neural lace technology and if nobody else was going
Speaker 1: to pursue it, he would do it himself, meaning he
Speaker 1: would fund it himself. The next year, two thousand seventeen,
Speaker 1: for those keeping score, he announced he was backing a
Speaker 1: startup called Neuralalink, which would attempt to bring this dream
Speaker 1: to life. Musk said at the time that one of
Speaker 1: the biggest challenges was around bandwidth, or how much data
Speaker 1: can pass through an interface in a given amount of time.
Speaker 1: I would argue that challenge it is a big one,
Speaker 1: but it's further down the road than some of the
Speaker 1: more immediate challenges. So why did Musk say that, I'll
Speaker 1: get to that. The two thousand nineteen announcement was all
Speaker 1: about giving a few more details about the general plan
Speaker 1: to achieve this science fiction vision. And Neuralink is working
Speaker 1: to create flexible threads of electrodes, and each thread would
Speaker 1: have essentially an electrode array with a potential density of
Speaker 1: three thousand, seventy two electrodes distributed across ninety six threads.
Speaker 1: Now by comparison, brain Gates array had a hundred twenty
Speaker 1: eight electrode channels in it, so this would be much
Speaker 1: more dense. The threads themselves would only measure a few
Speaker 1: microns in width and would be very very flexible, which
Speaker 1: would hopefully cut down on the possibility of them shifting.
Speaker 1: They would be able to to move with the brain
Speaker 1: instead of remaining still with comparison to the brain and
Speaker 1: Neuralink has worked on a robotic device that would automatically
Speaker 1: embed the threads into the brain of a recipient. This
Speaker 1: would require surgery. According to the Verge, this robotic device
Speaker 1: looks like a cross between a microscope and a sewing
Speaker 1: machine and it can implant up to six threads per minute. Now.
Speaker 1: Musque stated the reason he was talking about neuralinks were
Speaker 1: at the time was largely as a recruiting strategy to
Speaker 1: get more talent to apply to work on the Neuralink team,
Speaker 1: and his end goal is not to help those who
Speaker 1: have severe mobility and communication limitations gained some autonomy, although
Speaker 1: they will be some of the people that would first
Speaker 1: be exposed to this technology. Instead, it's to create a
Speaker 1: bridge between humanity and AI. And this might be why
Speaker 1: Musk was talking about that barrier, that bandwidth barrier, because
Speaker 1: for there to be a meaningful exchange of data, you
Speaker 1: need to be able to move a lot of information
Speaker 1: very quickly back and forth. Presumably, and Musk has made
Speaker 1: it pretty clear that he is concerned about the possibility
Speaker 1: that AI could bring about an existential crisis for humanity.
Speaker 1: So to me, this sounds like if you can't beat them,
Speaker 1: join them type of strategy. Musk seems to say the
Speaker 1: interface would serve as a step toward merging human and
Speaker 1: artificial intelligence, perhaps pushing humanity into a trans human state.
Speaker 1: We'd no longer be human beings as we would classically
Speaker 1: define the term. Now, I have to stress again that
Speaker 1: such a future, if it is even possible, is still
Speaker 1: a long way away. The neuralink approach has a long
Speaker 1: way to go just for a basic functionality, and building
Speaker 1: a meaningful interface that can bring together human and artificial
Speaker 1: intelligence is another matter entirely. In fact, I'm not even
Speaker 1: sure what such a thing would mean. That would it
Speaker 1: mean enhancing human intelligence with AI? And and if so,
Speaker 1: how would that work? How could a computer system and
Speaker 1: a brain work together like that, not just communicating back
Speaker 1: and forth, but working as a cohesive unit. I'm not
Speaker 1: really sure. I'm not sure if anybody is sure. Now
Speaker 1: that's not to say it's not possible. It very well
Speaker 1: maybe possible, but it's way beyond my humble understanding. Musk's
Speaker 1: vision is an interesting one, but it also raised is
Speaker 1: a lot of ethical questions. Now, presumably this technology will
Speaker 1: not come cheaply, so who exactly would be able to
Speaker 1: afford such a bio enhancement. So let's assume, for the
Speaker 1: sake of argument, that Must's vision becomes reality, and that
Speaker 1: this technology works the way he intended it to, which
Speaker 1: I'm still not convinced is actually possible. But let's say
Speaker 1: it is possible and it happens. Would that mean we
Speaker 1: would actually see a new class system, one that essentially
Speaker 1: mirrors the massive divide between the most wealthy and the
Speaker 1: poorest people of today. But more so, would we have
Speaker 1: a very small population of elite rich and enhanced people
Speaker 1: overseeing a massive you know, the rest of us, because
Speaker 1: I know I don't make enough money to fall into
Speaker 1: the cyber human tax bracket. Again, we're so far away
Speaker 1: from this being oppressing matter, but it's the sort of
Speaker 1: question we have to ask when we talk about an
Speaker 1: amazing future. Whose future or are we talking about? Because
Speaker 1: if it's not everyone's future, I think it kind of stinks.
Speaker 1: Speaking of stinking, let's segue over to Facebook, and that
Speaker 1: might betray my opinion on this next item in our
Speaker 1: bc I discussion. So at the two thousand, nineteen f
Speaker 1: eight or FATE Conference, which is Facebook's conference for developers,
Speaker 1: one of the many presentations was on Facebook's efforts to
Speaker 1: fund the development of what has been called a mind
Speaker 1: reading device, So what gives well? Researchers at the University
Speaker 1: of California at San Francisco are helming this project and
Speaker 1: the ultimate goal, at least the ultimate short term goal,
Speaker 1: is to create a non invasive device or method that
Speaker 1: will allow a user to transmit words or commands to
Speaker 1: a computer device through thought alone. And the short term
Speaker 1: goal is to develop such a system that can handle
Speaker 1: up to one words per minute with a one thousand
Speaker 1: word vocabular larry, and an error rate below sevent Now
Speaker 1: those parameters should already tell you that this goal is
Speaker 1: a tough one. We have no way to take raw
Speaker 1: brain data from the speech center of the brain and
Speaker 1: figure out what a person is trying to say all
Speaker 1: by itself, right, I couldn't just slap a headset onto
Speaker 1: a person have them think words and no immediately what
Speaker 1: they're saying. To get to that point, we actually have
Speaker 1: to train a computer system to recognize certain brain patterns
Speaker 1: that represent specific words and the speech center of the brain.
Speaker 1: That's what the researchers have been working on. So, like
Speaker 1: the other examples I've given, these researchers have been working
Speaker 1: with volunteers who elected to have surgeons implant electrodes into
Speaker 1: their brains. And these were volunteers who were already undergoing
Speaker 1: surgical procedures to treat stuff like epilepsy, So it wasn't
Speaker 1: like they just walked in off the street. They were
Speaker 1: electing to do this in addition to other treatments they
Speaker 1: were seeking. The subjects were then given a series of
Speaker 1: multiple choice questions. Now these were questions that didn't have
Speaker 1: a right or wrong answer, so you could get a
Speaker 1: question like how are you feeling today, and then the
Speaker 1: answers could include stuff like tired, happy, sad, lonely, that
Speaker 1: kind of thing. That's just an example from my own head.
Speaker 1: By the way, I don't know for a fact that
Speaker 1: that was an example question from their procedure. The subjects
Speaker 1: would then answer out loud. They would say what their
Speaker 1: choice was verbally, and during the whole test, the researchers
Speaker 1: would record the brain activity in the subject's speech center
Speaker 1: as it was going on. Doing this over and over
Speaker 1: would establish a sort of picture neurologically speaking of how
Speaker 1: specific responses quote unquote looked in the brain. So when
Speaker 1: you were ready to say happy, then the neurons in
Speaker 1: your brain fire in a specific kind of pattern, and
Speaker 1: the the the the e G picks that up and
Speaker 1: it it's kind of like making a picture. So if
Speaker 1: the computer sees a picture that looks like that one,
Speaker 1: it might interpret that you have said the word happy.
Speaker 1: After training machine learning algorithm on the data, the researchers
Speaker 1: tried to test the system and they would feed brain
Speaker 1: data into the system without telling the system what the
Speaker 1: data referred to. It would say, all right, which question
Speaker 1: was asked and which answer was given, so the system
Speaker 1: tried to figure that out based upon the amount of
Speaker 1: data it had gathered in its training process. It did
Speaker 1: fairly well figuring out which question was asked, getting it
Speaker 1: right s the time, so three times out of four.
Speaker 1: It was slightly less successful at guessing what the answer
Speaker 1: was by the subject. It was not as good about
Speaker 1: that it was about success rate, but that's still pretty impressive.
Speaker 1: It's a long way away from the stated goal of
Speaker 1: the project to get that error rate down below sev
Speaker 1: Especially with a vocabulary of a thousand words, it's got
Speaker 1: to get more complicated as the number of words increases,
Speaker 1: because the more words the system has to identify, the
Speaker 1: harder it has to be. It has to be able
Speaker 1: to recognize differences between each of those words to determine
Speaker 1: which one was intended. Okay, so what does Facebook want
Speaker 1: to do with this technology, assuming that they're able to
Speaker 1: mature the technology and have it perform up to the
Speaker 1: level that they want well, the company has said that
Speaker 1: the goal is to create a system in which a
Speaker 1: user can just think a command or message and send
Speaker 1: it to a computer. So rather than look down at
Speaker 1: your phone to dash off a quick text to your BFF.
Speaker 1: You could concentrate and send that message by thought alone
Speaker 1: to your phone, and then commanded to send the message
Speaker 1: onward without every taking the phone out of your pocket
Speaker 1: or out of a purse or whatever. You're just concentrating
Speaker 1: and making it happen. Now, the skeptics among you might say, hey, Jonathan,
Speaker 1: wouldn't you say that Facebook has a somewhat spotty reputation
Speaker 1: when it comes to stuff like privacy and security? And
Speaker 1: my response would be, you bet you. I'm sure the
Speaker 1: company has anticipated this. Folks at Facebook have already said
Speaker 1: that this system would only pick up words that were
Speaker 1: in the speech center of the brain, and only words
Speaker 1: that the system had been trained on for that matter,
Speaker 1: and that it wouldn't pick up just random surface thoughts.
Speaker 1: So you'd have to be thinking about saying the word
Speaker 1: for it to be detected by the technology. Presumably this
Speaker 1: makes everything okay, I'm not quite ready to sign on
Speaker 1: to that just now, but anyway, that being said, I
Speaker 1: would imagine for the system to work, each user would
Speaker 1: first have to train their individual instance of that system.
Speaker 1: It's sort of like the old voice recognition programs out there.
Speaker 1: You first had to go through a fairly extensive calibration
Speaker 1: process with voice recognition systems that had to learn your
Speaker 1: voice in order for it to be able to respond properly.
Speaker 1: I imagine you'd have to do something similar with a
Speaker 1: mind reading system like this, where you'd have to actively
Speaker 1: think about specific words in sort of a two to
Speaker 1: oriole in order to train the system on how your
Speaker 1: brain lights up when you are thinking those words. To
Speaker 1: put it another way, the neurons in my head might
Speaker 1: light up a slightly different way when I say the
Speaker 1: word cat than they would in your head when you
Speaker 1: say the word cat, and each person would need to
Speaker 1: make sure their version of this technology understood how they thought.
Speaker 1: But that also means putting in a lot more prep
Speaker 1: time before you can actually use the technology to dash
Speaker 1: off an email or something. Another potential use is for
Speaker 1: a hands free interface for technology like augmented reality glasses,
Speaker 1: which frankly makes me even more worried. You can see
Speaker 1: the use of such technology right away. You could wear
Speaker 1: one of these glasses which can overlay digital this information
Speaker 1: on top of your view of the world around you,
Speaker 1: so you could stare at a building, for example, and
Speaker 1: think what address is that, and just by thinking that
Speaker 1: the a r handset could consult the Internet and come
Speaker 1: back with some information and say that is this address
Speaker 1: on this street, which is pretty useful. But let's paint
Speaker 1: a more terrifying scenario. Facebook has an enormous amount of
Speaker 1: information on millions, in fact billions of people. So let's
Speaker 1: say you've got a pair of Facebook branded augmented reality
Speaker 1: goggles and it's got a brain computer interface as part
Speaker 1: of the system, so you can just think commands and
Speaker 1: the goggles will pick up on what you are asking
Speaker 1: them to do. And because so many people use Facebook
Speaker 1: and many people have public accounts, you could walk down
Speaker 1: the street and get quick bits of information about all
Speaker 1: the people you were looking at. You know, you get
Speaker 1: facial recognition software, it recognizes who the person is starts
Speaker 1: pulling up your information on them that's publicly available. Maybe
Speaker 1: you even figure out how to exploit the system and
Speaker 1: get access to information beyond what was allowed for the
Speaker 1: general public. This could be a massive privacy problem. Now, again,
Speaker 1: we are a long way away from that particular type
Speaker 1: of technology becoming reality, but the possibility is there. There's
Speaker 1: no denying Facebook has access to a stupendous amount of
Speaker 1: information about all of us and we don't even need
Speaker 1: the brain computer interface for that to be a problem.
Speaker 1: You could just have the A R glasses themselves with
Speaker 1: a deep connection to Facebook's databases and a way of
Speaker 1: interacting with it, even if it's with voice commands or
Speaker 1: mobile app or whatever, and you can still have these problems.
Speaker 1: It's just it seems even more insidious if you don't
Speaker 1: have to do anything other than just stare at someone
Speaker 1: and think it. It seems pretty spooky and creepy. And
Speaker 1: it's these sort of scenarios that remind us we have
Speaker 1: to be careful as we develop technologies to make sure
Speaker 1: that they are applied ethically without posing harm to others.
Speaker 1: We've got to ask ourselves what are the consequences of
Speaker 1: this technology, both the intended and unintended consequences, and who
Speaker 1: benefits most from it and who could be who stands
Speaker 1: to to be victimized by it anyway, I think brain
Speaker 1: computer interfaces really have great potential to do an enormous
Speaker 1: amount of good, especially for people who otherwise have a
Speaker 1: really difficult struggle just being able to interact with the
Speaker 1: world around them and to have any sort of autonomy
Speaker 1: at all, and to even just be able to communicate
Speaker 1: with others. I think that that alone makes it a
Speaker 1: worthy endeavor to pursue, but we do need to make
Speaker 1: sure that we're doing it for the right reasons and
Speaker 1: we're not just doing it because somebody is scared that
Speaker 1: robots are going to take over the world, or a
Speaker 1: company really wants to know what you're thinking, because the
Speaker 1: more data the company has about you, the better it
Speaker 1: can sell things to you or sell you to other things.
Speaker 1: Keeping that in mind is very important. That's it for
Speaker 1: this episode. If you have any suggestions for future episodes
Speaker 1: of tech Stuff, maybe something that's happy and fun and
Speaker 1: not nearly as terrifying and orwellian, send me a message.
Speaker 1: The email is tech Stuff at how stuff works dot com,
Speaker 1: or you can pop over to our website that's tech
Speaker 1: stuff podcast dot com. You'll find an archive of all
Speaker 1: of our previous episodes on there, as well as links
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Speaker 1: to our online store, where every purchase you make goes
Speaker 1: to help the show and we greatly appreciate it, and
Speaker 1: I will talk to you again really soon. Tech Stuff
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