脳コンピューターインプラントに社会は備えられているか？

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I'm Bob Safian, former editor-in-chief of Fast Company, and I'll be your host as each episode breaks down what you need to know right now. You can find Rapid Response wherever you get your podcasts. you know you might trust people you might trust matt angle or you might trust elon musk but like who knows a year or two from now like who's going to be at the helm but one thing that's more durable is trusting a business model we want to empower people to make choices and that's both a right to use technology, access their own ring when they want to, and a right to not have it used against them. So ultimately, it's about empowering people to make choices for themselves. Hi, everyone. We are fresh off Masters of Scale Summit. It's an annual two-day event in San Francisco

where we hear from some of the world's most visionary voices, including co-host Reed Hoffman, Google's Eric Schmidt, and Signal's Meredith Whitaker. I had a fantastic time taking it all in, and I hosted several conversations of my own, and we'll be bringing those to the show starting with today's episode. Live on the summit stage, I spoke with two top experts in the area of brain-computer interfaces. Matt Angle is the CEO of Paradramix, building time-chip implants for the brain. These devices turn neural signals into words without the need to speak or type. And AI makes these devices so much more powerful, processing and interpreting brain data at unprecedented speeds. And our second guest is Nida Farhani. She teaches law and philosophy at Duke University and is the author of the book, The Battle for Your Brain, Defending the Right to Think Freely in the Age of Neurotechnology. She's pioneered this idea of thought privacy, the right to own your own thoughts in an era where computers can actually read minds.

I'm so excited for you to hear this one, so let's get into it. I'm Rana Elkhalyubi, and this is Pioneers of AI, a podcast taking you behind the scenes of the AI revolution. So we are going to be talking about computer implants in your brain. But before we do that, we wanted to show a short video of your work, Matt, at Paradromics. So tell us, who are we about to see and what are they doing? Okay, so we're going to have a conversation, and pretty quickly I think it's going to jump to mind reading. And a lot of people wonder, like, how soon is that? What would that look like? Well, what you're going to look at in this next clip is a woman in our first clinical trial. She's a participant with motor neuron disease. She has severe dysarthria, which means that she lost her ability to speak clearly. and she enrolled in the trial to help understand how brain-computer interfaces can help people who

have lost the ability to speak to communicate again and so what you'll be seeing is she will be thinking words in her inner monologue and as she thinks those words they will appear on the screen directly from her brain and to clarify this is quite different than eye to kind of the eye tracking where you point at a track pad and with your eye movement it types and just like connect it to your people might be interested like you know many of us have seen like steven hawking give speeches but those were pre-recorded speeches where he was uh thinking he was communicating through uh motor movements kind of typing things out uh at something like one or two words per minute and so you'll see this comes a lot faster because it's reading directly from the mind you guys have been married almost 45 years so maybe what advice do you have for us for marriage

don't sweat the small stuff What would be your message to your co-workers as you're retiring? It has been an absolute privilege to be a part of the team. Very powerful work. can you kind of clarify what part of the brain is this device capturing so this device is implanted in an area called 55b and it's kind of the grand central station for language in the brain so it represents a lot of different things it represents when we're trying to speak the language that we're trying to say with our muscles is there it also represents when we think in the quietness of our own mind a series of words it appears there even right now when you're 55d my words are in your

brain if we had the debbie downer voice in my head yeah i mean if you're ruminating and you're thinking about things it would be there and so it's very interesting because it's received and expressed and internalized language you know why does it matter where this device is implanted Yeah look so first incredible right It so amazing to see that somebody who is unable to speak is able to speak again And I'm deeply excited about that. Matt and I have been in conversation for a while since my book came out in 2023, The Battle for Your Brain, Defending the Right to Think Freely in the Age of Neurotechnology, When, you know, what I said was we're pretty quickly moving backward from this kind of intentionally communicated speech, which is what you were doing at that point. That is like people painstakingly in their motor cortex, forming the words to try to speak and communicate it into the world and getting to the place where the things that you're passively thinking in your mind, like your actual inner monologue, the mental space where like you are you and all of those things that you're not saying out loud.

and you might never say out loud can suddenly be accessed. And that's amazing for people who need it. It's terrifying that that space, right, space of mental privacy, that thing that you don't say, like, no, I really love your couch. No, honey, that dress looks amazing on you, right? Those things suddenly could be accessed. And so my book really looked at, like, how might that happen, not for the person like this who we absolutely want to make it possible for, But for the rest of us who might opt into a similar kind of technology, a wearable technology, where this technology might overcome the last frontier of privacy, we have our kind of last bastion of privacy. So is this just around the corner? We've been talking about brain-computer interfaces for years. So how close is this technology? I mean, it's already around the corner. You just saw it. I mean, so, I mean, that's, you know, we've been having conversations about this and a lot of the early BCI, just like Nina was describing, it was people would try to say something and the physical act of trying to say something, even if you're paralyzed, produces motor signatures that allow you to move an arm or to create the sounds of speech.

but already we're going up one level in the cognitive stack and detecting the words that you are thinking i can tell you that bci companies will continue to go up that stack because the number of people who can get a communications prosthesis increases as you move up the stack there are people who have stroke and the area of the brain that we're recording from right now might be damaged so we might have to go a level up and i mean that's a really good thing right someone who has aphasia who can't express themselves anymore to be able to go directly into the area of the brain where they're thinking they have the intention they have like the semantic concept of what they want to say and record that that's really exciting and also right so i mean and also incredible again let me just say for for even just for this patient you want to go back as early as possible. Me having this conversation right now with you, I'm not painstakingly choosing every single word. It just comes naturally, right? My thoughts flow from me

naturally. How I'm feeling flows naturally. And to give people that capability makes a lot of sense. In fact, that's why a lot of consumer-based companies are starting to look at how do you develop wearable neurotechnology that allows you to interact with your devices. So instead of, you know, your smart glasses requiring that you actually move around, you have a neural band from meta that allows you to have motor neuron activity that's picked up at your wrist from your brain down your arm to your wrist picks up your intention to type or swipe or move and increasingly more companies are trying to get to that point they're not going to be as good obviously at getting an inner monologue as what yours does but we want to go backwards it makes it more seamless it makes it more seamless for her and the further back you go there's at least two problems like that right The first one is there is no safe space, right? There's like your implicit automatic reaction. Think about the bias that you have. You've worked on it for a lifetime. You know that you have particular like biases that are internal. You automatically react to somebody or something, but you filter it on many later steps of consciousness.

That's picked up. And who are you? Are you the person who automatically reacted to something? Are you the person who expressed it into the world? And like how does the device decide which one you are? As an engineering problem, you can already see the difference between attempted speech and imagined speech. So, you know, we can choose to build a product that separates those streams and lets users decide how it's used. But I think the point is the company that records the data will have access to it. And you have to trust whoever you're allowing. Put something in your brain. Right. Trust is actually, yeah. Well, I trust you, Matt. But some of the other players, well, let's talk about that. It's very focused on this idea of a prosthetic and restoring speech and communication to people who really need it. There is a consumer version of this, which is kind of the human 2.0, where we're all getting these implants in our brains. It's giving us entirely new abilities. Elon Musk's Neuralink is the best example of that. Is that the endgame for paradigms? Well, something that I would say is, you know, you might trust people.

You might trust Matt Engel or you might trust Elon Musk. But, like, we may be there, who knows a year or two from now, like, who's going to be at the helm. But one thing that's more durable is trusting a business model. And so one of the places where we've seen tech go in the wrong direction is when the users stop being the customers. So a lot of us have experienced kind of social media apps, a number of different platforms where we're getting a service, but someone else is paying. And so the services end up being steered toward them and not us. That's one place where I think we have good alignment right now for implantable brain computer interfaces. We're building medical devices. These are devices that are prescribed by a doctor for a person. They're paid for by a hospital, reimbursed by a payer. And the business model is channeled toward us delivering things for that patient in a regulatory environment. You're not going to be selling my thoughts. Well, yes, right? I mean, so Matt won't.

We can trust Matt. But Matt is right for two reasons that this is a problem. One is already there are fights that are happening where people are trying to acquire the neural data. They're trying to acquire the neural data from the companies. They're trying to acquire the neural data from the research institutions. There are patients who want access to their neural data who are being told it's not your data, it's our data because we collected it. And there are offers on the table to buy the neural data. And if those offers come true, then suddenly it becomes the commodification of neural data. The trust collapses and it's your brain, right? It literally like what you thinking and what you feeling And I mean not hyperbole anymore It literally what you thinking and what you feeling The second that we haven talked about yet is the convergence with AI right And this part really important which is, so in order for all of this to be interpreted, it's interpreted using AI models. More and more of the AI companies have major investments in neurotech companies, Elon, right? Open AI.

And they're increasingly on device. They're integrated, right? You have AI with Neurotech. Let him unpack. He's so good at it. Okay, Matt. What part of it? Because I can understand, like, you need machine learning and predictive AI to kind of translate the signals. Here's a great practical intersection. Okay. So we're building these tools for people who are paralyzed. Why wouldn't we want to give them excellent clawed integration? Like, why wouldn't we want them to be able to prompt AI agents, even maybe humanoid robots, directly with their thoughts? We have visual language action models now that could control a robot by just thinking about what you want it to do. Can I ask you, just as you're building this, unpack it up on the screen, your patients had pleasure that then switched to privilege. And is that like an AI model predicting what her brain signals actually mean? Then she's overriding what the predicted next word is and correcting it. That was what's called an engram model. We hear about large language models.

That's a small language model. And that's where if you know the phonemes, like the first five phonemes, then you can predict the sixth phoneme. And so what you saw is one of them, a great example was the sentence was the excitement of the race. And then it switched to the excitement of the work. That was an example of really early on the language model thought it knew better. And then when it got to the end of the sentence, it went back and looked and said, no, actually, based on the brain data, it was this sentence. You could see it flipping back and forth in real time. Right. So when you have the model that lives on the devices and it and we're moving backwards further and further and further into your thought processes and the model is predicting what you think and you feel. And then there's output. How do we make sure that there's still a human who is thinking those things rather than experiencing what a model has predicted based on early signals that then have feedback into the person and changes how they're thinking? Like, no, no, no, this is not the word I thought. and it corrects it. But you might not even experience it that way, right?

You would experience it as if this is my thought because... Well, not necessarily. I mean, we all went through this with voice-to-text. Voice-to-text sucked for a while, and it still sometimes in a noisy environment is not that good. But that's later. You're speaking it. You're talking about picking up thought processes before you've ever articulated them. Not what we're doing right now, but yeah, that's a thing that will exist. And so then how do you have a sort of shared control architecture where some of that signal is coming from you, some of it's coming from the AI. I'm actually glad you mentioned it. That's one of the reasons why we're really long on high data rate. Because let's take, for instance, speech. If each of you were sitting there writing down what I was saying right now, which I hope you all are, it takes about 40 bits per second to transcribe human speech. So if you want to build a speech prosthesis that's based on a wearable device with two bits per second. That means that the AI is filling in 38 bits per second of the language that you're communicating. The only way, if you're trying to control a robot,

let's say, we right now, we could probably have a humanoid robot that would play golf for us, where we'd say like, hey, go out there and play golf for me. And it would come back and be like, yeah, 18 holes in one, congratulations. But if you wanted embodied control of that robot, you wanted to feel what it was like, you're paralyzed and you want to play golf, you would need a lot more data to communicate back and forth. So this kind of trade-off with agency, the more data you have, the more you get to embody that interaction. We will be right back after a short break. Can we talk about, like, use cases?

Because we're talking about language for now, and also is it language agnostic? Like, if I'm thinking in Arabic, would it capture that or not? Right now the models are trained on a specific language, but if you think about it, like, automated translation can happen in 12 seconds. Okay. And is language the only use case or are there other use cases? Well, that's what I was about to say. I mean, you said quad integration, and I think we kind of breezed past that for a moment. Like multimodal, right? Yeah. No, because what you were really hinting at is something different, which is not just quad integration the way we're thinking about it, which is like let's go type in our output, but the super-powered human who is now like merged with quad and then maybe a bionic body and then maybe flying swarms of drones. I'm like, I mean, so. Okay, so merged is a little bit much. That's a loaded word, but I'll tell you what I think will happen in the next five years. There is a company called Merge, right? So that's different. Someone who is in a clinical trial who has a brain-computer interface in a higher cognitive area,

they're going to be able to communicate intentions directly with an AI system. So right now, the way that we work, let's say, with Claude or ChatGPT is you type a prompt, you realize it wasn't exactly what you wanted, you sort of do a new prompt, and there's an iterative process. Or if you are a prompt engineer, you write a huge prompt at the beginning. But actually, a lot of the time, that context, that intention exists in your mind from the onset. and so um it will be possible for for people who have certain kinds of vcis to put more context into that initial prompt and even what we know instead of like vibe coding your vibe living right i mean you have to think about it just right now we're looking at cognitive outsourcing i mean part of when you go to write something the act of going and trying to sequence it and put it into words you realize your initial intention wasn't uh fully baked out and so some of that work that you do is um is important and so if we start right if we start working in a different flow

we'll have to adapt okay so you talk about thought privacy to your house what does that mean and what is it going to look like yeah we need it clearly so my next book which comes out this march is called cognitive extinction which is saving human thought while we still can i get a little darker from the battle like there was a battle and then we lost and it just like as we moving to no there still a hope They saving human thought while we still can. But, but here's why, which is I care deeply about a space of mental privacy, right? There's this space that you are you, the space where you can cultivate your own thoughts, the space where you can try on things for size without anybody else judging you and having that space that's your own. I'm deeply excited for the patients that you're helping and think that it's incredibly important. But I worry where you were just talking about offloading already, what a lot of the early work shows is that when you use AI systems to bypass metacognition, like the part of you that's actually present and working through it, the you, the agency that we're talking about in this

conference kind of fades into oblivion and the machine takes over, right? You sit in the back seat. You're like an automaton. We've all done that. We're in our car. We're driving somewhere. we don't even realize that we're doing it and we get there and i don't mean like our tesla i mean literally like we we mean to be driving ourselves so there's there's a world in which the way you describe it it's the person through metacognition prompting and changing and then there's the world in which you just sort of sit back and you're like well the ai agent the ai agent can sort of sense what i want but driving is it is a great example because there's some processes where we want to be more present and more engaged and then there's like driving to work when we want to think about something else or doing our taxes where we actually want minimal engagement will we even know the difference right the world of which ai is literally inside our brain especially because we're already saying ai is very good at doing things like manipulating or you describe the prompt you think that's not quite what i want usually it works the opposite which is you put some incoherent prompt into the system it comes back and it says you're so smart that is like

like i agree with you here is exactly what you just said it's not at all but you're like yeah that is what i said and you ratify it suddenly it becomes the thing you put out into the world how is that when you have merger between i know you don't like the word merge joining these things together how you safeguard against like some of the ways this can go wrong like what are some of the protections we can put in place well i mean it is a product design exercise so one example is that if in this neural state space you can separate things that people want to say from things that people want to think privately just allowing for those things to be treated differently according to the way the user wants now one question would be are there constraints that you even want to put in place against the user's uh intentions so like there's a world you You say, well, you know, someone should be free to decide how present they want to be when filling out their tax returns.

Or there's a world where we might as a society say, I don't know, actually, I think you should still have to, you know, pay attention to this. Or you should still have to go through the thought process of writing out exactly what you want your robot to be. Now you start making me nervous on the other side because who gets to decide, right? Those kinds of choices. Is it you? Probably. Yeah, it's probably me. Wait, this is a heated debate. I love it. But final question to both of you. And you're taking human in the loop to like a whole new level. The theme of the summit is agency, right? So in this world of convergence of AI and your attack, what does it mean to be human? And what does it mean to be in control? And I'm going to give you the last word. So Matt, you go first. From my perspective, we want to give people the most optionality. And you have the most optionality if you have a high data rate between the system you're controlling and yourself. I think if you have to defer to the AI to do a bunch of things for you and you don't have enough input into steering that process, then you do start outsourcing things significantly.

If you have enough data to, let's say, embody the robot or to make sure that the speech that's coming out is coming from you and not from a language model, then that gives you the most options. And you still have to make a lot of hard decisions, but I think from the engineering perspective, data gives options. Amazing. Nita? How do I say no to that? So I have been advocating for a basic right, which is the right to self-determination over your brain and mental experiences. I call it cognitive liberty. And we are making great headway in laws and policies, but also in design and working with companies like Matt's and others to develop standards as to what that means from a standard perspective, where the technology is designed in ways that enhance user agency, autonomy, and self-determination, but also safer against the misuse. the commodification of neural data that puts the products in misalignment ultimately with where

people are, giving people user-level controls. But it's the reason why I also resist a little bit this idea of putting limits on what people can do with their own devices. What we want to do is empower people. We want to empower people to make choices. And that's both a right to use technology, access their own brain when they want to, and a right to not have it used against them, to not use it in ways that oppress them. So ultimately, it's about empowering people to make choices for themselves. Yeah. Well, thank you both so much. Thank you for joining us. Thank you. Thanks, everybody. This technology is so powerful and can do so much to restore human communication. But what really stuck with me is this idea of thought privacy. Our brains generate all kinds of thoughts, but then we filter some of them out for better or worse. So what would the world look like if your thoughts become verbalized or captured way upstream without any filters,

or possibly even without your consent? And so who brings this technology into the world really matters. Thank you so much for joining me. I'll be back next week with a new episode. Pioneers of AI is a Wait What original. Our executive producer is Eve Trow. Video editing by Eric Purcell. Our senior talent executive is Stephanie Stern. Mixing and mastering by Brian Pugh. Original music by Ryan Holiday. You can join the conversation on LinkedIn, Instagram, TikTok, YouTube, and X. Just search for at Pioneers of AI. Thank you.