My guest today is a theoretical neuroscientist, technologist and entrepreneur who was named one of Inc. Magazine’s top 10 women to watch in tech in 2013. She co-founded Socos, a cutting-edge startup which applies cognitive modeling to create adaptive, personalized educational technology. She is also a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience pursuing her research in neuroprosthetics.

Previously, she was a junior fellow at Standford’s Mind, Brain & Computation Center and earned her Ph.D. from Carnegie Mellon. Her work and research has received a ton of media attention including the New York Times, NPR, Nature, O Magazine, Forbes, and The Atlantic.

In this interview, we discuss her INCREDIBLE STORY, how technology will be used to predict our learning and performance, how we can change life outcomes, how prosthetic devices will be used to alter and repair or brains and bodies, and the very realistic possibility of a hyper-intelligent superhuman race… and that’s just in the first 30 minutes.

This episode is brought to you by the all new SuperLearner Academy!

In this episode with Dr. Vivienne Ming, we discuss:

• Dr. Ming's journey from a rough childhood and young adulthood to the success she is today
• What is the guiding principle of Dr. Vivienne Ming's life (hint: it deals with optimizing human potential!)
• How does Dr. Vivienne Ming to “maximize human potential,” and where are the low-hanging fruits?
• How is Dr. Ming working to redefine what education looks like?
• The AI models built by Dr. Ming and her wife to predict people's grades, performance, and success
• What actually predicts success and life outcomes in children and in adults based on 122 million profiles?
• How is this ability to predict people's future outcomes actually a curse?
• What is Socos, Dr. Ming's startup, and what are they doing?
• What factors are MOST likely to make a child successful?
• What is “meta learning” and how does it factor in to life outcomes?
• What is fixed and what is changeable in people's lives?
• What are “neuroprosthetics,” and why are they so exciting right now?
• What is the coolest research going on right now in neuroscience?
• What is “neural dust” and why is it a REALLY BIG deal?
• What is the biggest risk with cognitive prosthetics, and why are they scary or not scary?
• What is the likelihood that we will be able to “encode” knowledge into our brains, versus decoding it?
• How can we learn more effectively?
• What are endogenous vs. exogenous motivation, and how do they affect us?
• What is “sleazing” in educational technology?
• An example of how Dr. Ming's thoughts on learning more effectively are 100% in line with those I teach!
• How feedback relates to success in education and learning
• What should you hire based on, if you're hiring employees?
• What $100 has Dr. Vivienne Ming spent recently that most impacted her life
• What book has Dr. Ming given most as a gift and how has it inspired her work?
• What 2 pieces of homework would Dr. Vivienne Ming assign to our audience for this week?

Resources Mentioned in This Episode:

• Socos, Dr. Vivienne Ming's startup
• This podcast episode with Dr. Peter Attia
• Season 2, Episode 1 of Black Mirror
• The Stanford Marshmallow Experiment, an important sociological study
• Article/Video: Mind-controlled exoskeleton kicks off World Cup
• Video: Paralyzed woman controls robotic arm with thoughts
• The Magical Number Seven, Plus or Minus Two a famous article we talk about in my SuperLearning course
• Neural dust and neural nets
• Dr. Rajesh Rao and a Duke University experiment that linked rats' brains over the internet
• The Pomodoro Technique
• Start With Why by Simon Sinek and his legendary TED Talk
• Malcolm Knowles, a researcher on adult andragogy
• The Nexus 9 tablet and the wireless keyboard that goes with it
• The Diamond Age by Neal Stephenson
• Dr. Vivienne Ming's personal website (check it out, you'll be blown away by her CV)

Favorite Quotes from Dr. Vivienne Ming:

Transcript:

Introduction: Welcome to the Becoming SuperHuman Podcast. Where we interview extraordinary people to bring you the skills and strategies to overcome the impossible. And now here's your host. Jonathan Levi.

Jonathan Levi: This episode is brought to you by the all-new and very exciting. SuperLearner Academy. Now SuperLearner Academy is the home of my premium level content and masterclasses from my course on accelerated learning, speed, reading, and memory all the way to my course on productivity. Now in these Masterclasses, I go into the gritty detail that I just can't go into on the podcast or in the books, or in the other online courses.

I offer the worksheets and the homework and the types of individualized attention that can only happen on my own platform where I control the learning experience. So if you want to learn faster, if you want to remember more, if you want to read faster and you want to be able to do this all with a cohesive 10-week program, that's going to take you from wherever you are today, all the way to certifiable, SuperLearner status.

I want you to check out the exclusive discount that we're offering for podcast listeners only at jle.vi/learn. That's jle.vi/learn. 

Greetings, superfriends, and welcome to today’s show.

My guest today is a theoretical neuroscientist, technologist, and entrepreneur who was named one of Inc. Magazine’s top 10 women to watch in tech in 2013. She co-founded Socos, a cutting-edge startup which applies cognitive modeling to create adaptive, personalized educational technology. She is also a visiting scholar at UC Berkeley's Redwood Center for Theoretical Neuroscience pursuing her research in neuroprosthetics.

Previously, she was a junior fellow at Standford’s Mind, Brain & Computation Center and earned her Ph.D. from Carnegie Mellon. Her work and research has received a ton of media attention including the New York Times, NPR, Nature, O Magazine, Forbes, and The Atlantic.

In this interview, we discuss her INCREDIBLE STORY, how technology will be used to predict our learning and performance, how we can change life outcomes, how prosthetic devices will be used to alter and repair or brains and bodies, and the very realistic possibility of a hyper-intelligent superhuman race… and that’s just in the first 30 minutes.

You guys, so I'm very excited to welcome to the show Dr. Vivienne Ming.

Yeah. Welcome to the show. We are so excited to have you today. 

Dr. Vivienne Ming: It's my pleasure to be here. I've been looking forward to this. 

Jonathan Levi: Yeah, myself as well. I'm really, really excited about what you're working on. And honestly, it took all of my speed reading skills to go through your resume and LinkedIn and research because you've just been doing so much different stuff.

Dr. Vivienne Ming: It's been a busy life, although loaded largely on recent years. 

Jonathan Levi: So I tried to summarize it a little bit in the intro, but I'm sure I didn't do it justice. So perhaps you could share with us a little bit of the personal story and the journey that brought you towards theoretical neuroscience and where you are today.

Dr. Vivienne Ming: Absolutely. So I am a native Californian and I grew up a pretty nice life. In fact, I grew up in a Valley that Steinbeck wrote about, he called it the pastures of heaven. So. It was nice and it was comfortable. And I have a lot of advantages and yet really by the age of 25 and pretty thoroughly grounded my life into the dirt, you know, I nearly flunked out of high school and did flunk out of college was pretty miserable and had lost decade as I think of it.

And. You know, my family never gave up. And when I finally figured myself out and what that moment was is. An acceptance that you don't work for happiness, you work to live a life of substance. And, that would be the focus of my life. It may sound a little bleak, but for a good 10 years, that was how I got back into the swing of things.

And I kind of crawled back and. Worked at a convenience store, then manage a convenience store, then managed about things on an abalone farm, and finally found I had a little time and money to go back to school. And I literally flipped a coin, decided I figured out which degrees I could start and finish in a single year crammed all the courses together.

And it was math economics or neuroscience or cognitive neuroscience. And. I had the time I thought math, what would I ever do with math? So I flipped a con in between economics and neuroscience and, you know, obviously it came up heads and I've found myself in this world where people weren't just studying the brain.

They were building AIS and machine learning tools to study it. And suddenly learning was easy. It was, you know, I often say you can pronounce my college, transcript it, uh, everything had a meaning. Everything had a purpose. It didn't matter what the class was. Didn't matter why someone was forcing me to take it.

I found a meaning in that and that meaning I later articulated as this idea of maximizing human potential. Which can sound a little self-help, but in my case, I mean, can I build technology, leverage technology for one individual life, for a team, an organization for society, to be honest, that can really take the story of a life and turn it into what it should have been.

And have us all benefit from it. Oh, I love that. Yeah. That's been my guiding principle for the last 15 years of my life. It took moments in a life that I hope no one else ever has to go through to reach this point. But for me as with so many other stories out there in the world, there were crucial for me to understand, you know, I want to maximize human potential partially because I wanted to do it for myself.

Jonathan Levi: I love that. And it resonates so much with me and with my backstory and you know, why I run a podcast, which is, uh, you know, we claim to give skills and strategies to overcome the impossible. Well, There's a lot of me in that I think. So I certainly resonated with your story. Thanks. Let me ask this. As you mentioned, you're an outspoken advocate of the cause of maximizing human potential.

And that's really, I think why we want to do on this show so much. What does that look like to you from your perspective and in your industry and where do you think the low-hanging fruits are? 

Dr. Vivienne Ming: Sure my industry, you know, it's a funny thing. I find myself often invited to come to speak at big corporate events.

And when you show up before anyone knows who you are, the standard thing is to say, who are you with? Which in some way, you know, it lets them understand you, you know, it's similar to a, I think in England, you know, to ask where you went to school because suddenly they know so much about you. I don't say this with arrogance, but sort of at a loss.

You know, in my industry, my interest is maximizing human potential. I do this as an academic. In a field called cognitive neuroprosthetics where we're interested in. Can we literally jam things in your brain and make you smarter? I do this in education, through developing technologies that can really give kids and adults the opportunity to grow and be the person they could have been.

I do it inside large organizations, modeling talent, and organizational culture. I do it in modeling bias and diversity. You know, I'm the woman that built a Basian model of bias to understand some really interesting research. And I do it in health technology to look at. Treatments I've developed for bipolar disorder and diabetes and autism.

So, you know, this is it. If someone comes to me with an idea that fits into this scheme, I am just stupid about saying yes. If it falls outside that no matter how cool I genuinely think it is, it's a pretty easy, you know, no, as I recently said to a very large and very fun company that recruiting to me to be on their executive team.

This will have to be another and a long line of bad career decisions. So what do I do? You know, I explore the possibilities of cognitive neuroprosthetics. I try to redefine what education means in my case, it means what can we do to give you the best possible life? It's not about grades. It can be about learning skills, but I think there are wonderful tools out there for doing that.

I'm interested instead of working on the tools, I'm interested in the craftsmen, what can I build in a person? Such that they can go do amazing things in the world. So, you know, and it really is very similar. The truth is what you do with the five-year-old and education and what you do with a 35-year-old inside a corporation or inside the army or any other place I've ever looked is shockingly similar.

Jonathan Levi: So I think that's a good segue to talk a little bit about Socos, which is your startup and kind of the type of cognitive modeling and adaptive, personalized educational technology that you guys are working on. How does all that work? I mean, I just heard a really interesting podcast with Dr. Peter Attia, from Singularity talking about, you know, adaptive modeling that would determine if a student has understood something. And if not determine the right way to explain it, explain to us a little bit about what you're working on at Socos and how that all works. 

Dr. Vivienne Ming: Absolutely. Well, I hope he decided my wife and I because about three years ago, we actually published a paper showing that we could take undergrads was in a biology course and MBA students in an economics course and develop these machine learning systems that could learn biology.

Learn economics directly from the students talking to each other. Interesting. And then when that system, which I call it a deep cognitive model when that system is trained up and then used to, not that I think grades are a useful thing to predict, but. Just as a proxy used to predict grades, we've found when new students entered those two classes, even though we didn't involve the faculty, we didn't look at homework or anything we knew at week one, what those new students would get in the class.

Jonathan Levi: Wow. 

Dr. Vivienne Ming: We knew week by week as the course progressed, what they get wrong or right on the final exam. But here's the thing. I've also spent all this time modeling success in the workplace. What predicts the best salespeople, the best skateboarders in fact, in the world? Well, it turns out it's the same thing that decades of education literature says, which is, well, what's not predictive your grades, your standardized test scores.

Interestingly enough, clearly you need to know how to skateboard to be. Tony Hawk or Rodney Mullen, but knowing that you can skateboard doesn't tell me anything about how good you are. So again, it's interesting. The same things that are predictive of life outcomes and little kids are predictive in the workplace.

So what we did is say, well, we have this amazing technology to really understand, uh, learners. Okay. What if we did, instead of predicting grades instead of predicting class rank or, uh, graduation probability and yes, following that up with, and here's how to make them understand the next topic. What have we need something wildly more ambitious?

What if we literally predict life outcomes? Wow, how long someone will live, how happy they'll be, how productive they'll be in their life, how far they'll go in their education. So, first it turns out that it's very predictable. And we do that off of audio recordings from microphones in classrooms, with little kids, we can do that off of reading through the writings of older students.

Again, looking at the conversations people had, Oh my goodness. Give me access to an email or chat stream. And I can tell you everything you ever wanted to know about people, but it's a cursed crystal ball. So if I know your child's going to win the Nobel prize, and I tell you that I actually just made it less likely to happen.

Right. And if they're going to drop out in fifth grade and I tell you that I just made it more likely to happen. Interesting. Yeah. So it's like the old joke about a thermos, you know, it keeps the hot stuff hot and the cold stuff cold. How does it know. So here a lot of forces, cognitive, emotional bias forces pushed towards these negative results, even though they're in a sense pushing in opposite directions.

So, you know, one is reinforcing and the under is undermining, but it doesn't matter. It no good comes from telling. Or sharing these predictions, which is interesting because it says something then about having grades and having formal assessments. So instead what we do is something very, very simple, but profound.

We send, particularly in the work we've done with families, we send a single message home every day. Here's the one thing you can do today. Parents that will have the biggest impact on your child's life. Wow. And then we send it again tomorrow, a new message-driven by what we've learned about your child that day.

And then we send it again the next day and the next day and the next day. 

Jonathan Levi: That's brilliant. And what did these tips, or I don't know if you would call them tips, but action items. Give us an example of what one of them might sound like.

Dr. Vivienne Ming: So we call them interventions and happy to go into a little bit of what it took to actually build this out.

But a very tangible example for a young child would be, Hey dad, Maria's really interested in sea horses right now. Take 15 minutes and talk to her about seahorses. So this was a highly targeted recommendation. We picked up on dad. Involved in a lot of families, things, not that involved in education, the system explicitly signals him.

Maria's really interested in seahorses. This is from pilot data. We collected from kindergartners, where there were microphones and cameras in the classroom. And we actually picked up on her interest. She was talking about it over and over again. But it wasn't part of the course curriculum. The teacher wasn't bringing it up.

This was something that Maria was endogenously interested in. It turns out that is a huge predictor of life outcomes. Wow. So now imagine you're Maria. Five years old. Dad's typically not very chatty about school. You get home around the dinner table, he glances at his phone and then turns to you. And for 15 minutes you have a conversation about seahorses, like magic out of nowhere.

Huge. Then the rest of it's constructed as well. So we'd love for him to talk for an hour. We'd love for him to buy a ticket and take her to the Monterey Bay aquarium with the population we were initially working with that just wasn't going to happen. So part of. The engine, which is a little reinforcement learning AI, it learns, Hey, a most likely outcome is 15 minutes.

It's the best trade-off between what Maria needs and dad will do. And, you know, for example, we didn't signal reading about seahorses that makes it less likely to happen. We signaled or acute him to just talk so highly targeted. It seems so simple, but if you can do it over and over again, Create those behaviors in the parent, model it for the kid, and create experiences of value.

And you can see over and over again in the research literature that, I mean almost every week, new findings come out in science and nature and the proceedings international Academy about. New little interventions, the recent one was telling math stories to your kids and we have that body of literature driving our intervention.

Jonathan Levi: Right. That's incredible. Although it does, I have to say, remind me a little bit of an episode of black mirror where, you know, someone passes away and they plug in all of his emails and are able to completely recreate his personality.

Dr. Vivienne Ming: So now we can get into why I don't use Facebook anymore. 

Jonathan Levi: It's alarming actually. I mean, you say you could literally predict people's life outcomes. 

Dr. Vivienne Ming: I mean, I don't want to either over or under salad, you really can't. And when you think about the insurance industry and actuary tables, when you look at the power, probably the most famous experiment in this domain would be the marshmallow experiment with little kids.

Oh yeah. So, you know, you put a marshmallow in front of a four-year-old and you tell them you'll be back in 10 minutes and if they don't need it, they'll get a second one. How long do they wait before they eat it. Turns out to be a pretty robust predictor of education attainment income later in life health outcomes, you look at the grit literature at the mindset literature.

You look at predictors from a general cognitive ability like working memory span from emotional intelligence, and creativity. In fact, there's this broad swath of what my wife and I have called metal learning. Uh, this broad swath of these mental learning abilities or dementia or attributes, these are all robustly predictive of life outcomes.

It doesn't say you couldn't overcome a limited working memory span and be successful, but you are definitely working against the odds there. Right? So what we're interested in is what can we intervene on there? Can we in younger children literally increase working memory span? And it turns out that you can, can we improve perspective-taking, which is a form of empathy.

It turns out you can, and you can even do it in adults. Can we change someone's zip code that they were born in? Well, no. I can't intervene in that, but it turns out it's a great predictor of life outcomes. That's pretty depressing. So what's really depressing and scary to me is how much we accept as fixed.

Versus how much is actually changeable in someone's life. So it's much less about our predictions of their life outcomes than those little trajectories. So for the geeks in the audience, we're doing gradient ascent in massively high dimensional spaces, but we're ascending on people's lives. 

Jonathan Levi: Interesting. I guess I'm not enough of a geek to understand that one. 

Dr. Vivienne Ming: Let's just throw that out there for the people in the world that are enough that love their optimization algorithms. 

Jonathan Levi: Yeah. Dr. Ming, you mentioned, I like it. You described neuroprosthetics because you said, you know, I want to stick something in your brain and see if I can make it perform more.

I got to know more about that. I don't know how to phrase the question, but I really want to know what's going on in the field of neuroprosthetics right now. 

Dr. Vivienne Ming: So just to give a clear definition of a neuroprosthetic. The only one that is in standard common use today would be a cochlear implant. So this is essentially a hearing aid.

Where they literally drill out. If you have profound, peripheral deafness, they can literally drill out the cochlea, the structure in your ear. That turns waves in space into auditory signals and they wire that hearing aid directly to your auditory nerve, your eighth cranial nerve. And as a result, if you do this with a little kid, When they grow up, it can be hard to tell that they were ever deaf.

I shouldn't acknowledge by the way that in the deaf community, this is a little controversial, but it is a powerful statement as to at least what's possible in live experiments with humans today, you have retinal implants. So people that can't see because the retina is, are damaged or have congenital disorders, certain types of diabetes can be an example of this.

Right now we can restore at least a perception of light and dark and, you know, regions of space. And there really is good reason to think. With those kinds of sensory neuroprosthetics that we will one day truly be able to, uh, create, uh, a fairly robust sensory signal. Wow. Very exciting. Today is motor neuroprosthetics.

So if you watch the world cup, you may have seen when someone kick a soccer ball. Not a very exciting thing in the world, competition soccer, but one of those people did it wearing an exoskeleton and that exoskeleton was driven by a set of wires that were literally connected to his motor cortex. Wow. To the parts of his body that would normally be essentially driving his biological legs.

But those like didn't work because he'd broken his neck. Wow. Which player was this? By the way? Oh, not a player. I'm afraid this was a demonstration. Okay. Okay. So it was out of the lab of Nicholas local theaters, and many other people are doing great work. Andy Schwartz and Donahue, Brown and others are doing this amazing work.

One of my favorite, if you search BrainGate, you'll find a set of videos on YouTube. For example, one of my very favorite is this woman drinking. From a thermos of coffee again, so modest, but she's profoundly paralyzed. What you see in the video is a robotic arm, not even attached to her, just is on the table.

Next to the thermos. The arm picks up the thermos rotates around. She takes a drink from it. By thinking about reaching out and picking up the thermos. Wow. It's incredible. It's amazing stuff. So here's the final frontier to me, cognitive neuroprosthetics. So the only human research on this right now is called deep brain stimulation.

And it is kind of exactly what it sounds like. Take a bunch of wires and jam it up into the middle of your brain and just structures like the basal ganglia, the vagus nerve, which goes down into your guts. No one understood why for a long time, but it turns out if you do that and you give it a current, a little stimulus.

It can treat depression and it can treat Parkinson's disease, and traumatic stress. So the US army is putting a bunch of money into this research right now to really advance our understanding of it. But here's where I come in on my website for years and years, it has said what if it was 20 plus or minus two?

Yeah, this is a reference to this famous paper in the fifties titled the magic number seven plus or minus two. Right? And this is an admittedly very simplistic, but still informative bit of research on working memory. What some people call short-term memory. So, you know, w why is it? We can only remember a limited set of things.

Turns out. There's some very good reasons. And so very, roughly speaking seven is something like, you know, you can only here pay attention to a very limited number of things. Sure. Keep a limited number of things in mind, the complexity even argument is limited by this, which was really interesting is that plus or minus two, If you're a nine, you have a huge advantage in life, right?

If you have five, it's going to be a struggle. Doesn't mean you can't succeed, but it will be harder because again, the complexity of an argument, how much you can pay attention to it's high correlation with life outcomes. So what if it was 20. What if it was three times as high as the average, you know, twice as high as the smartest person, you know, you're fundamentally higher than the most intelligent person that you will ever meet in your life is average.

Wow. It's a point of faith, right? For me. I want to live in that world. I truly think it would be a better world, but I don't know. Cause it's wild extrapolation by the way. It's not because I think people are better if they're smarter. I just think if everyone were smarter, Together collectively, it would be a better world.

Right? So that's a description. I think the coolest research right now is in going on in those world of what's called neural dust and neural nets, neural webs. These are technologies that go beyond the classics, which are. EEG, you know, how do I put a bunch of electrodes on the surface of your skull and pick up on brain activity?

That's not very exciting to me. I have to say, nor is what's called a transcranial electrical or magnetic stimulation. There's neat work going on in that space, but it's kind of like getting excited about solar power 20 years ago. Great concept. But the reality is the technology isn't there. But things like neural dust.

So these are little nanobots. That has been developed. The work is being done with animals. You can sprinkle it over. Literally, they take off their skull. I know it sounds weird tasks, but these is early days. Literally sprinkled this thousand of these things all over their brain and then put the skull back on.

And it turns those neuro signals into RDI AF or a hyper sound or any other type of signal that's that can easily pass through the brain. And now listen. I know what word you're thinking, even if you're not saying it, I know that you're looking at, uh, neural nets or another incredibly exciting world where these self unfolding networks that can be injected via a physical network, I should say, as opposed to the algorithms that can be objected via syringe and they unfold across the surface of the brain.

And there they can not only read out there's good evidence. They might be able to do input, which isn't even harder task, but, you know, imagine the brain-computer interface that comes to me, really knowing what's going on in detail in your brain. Wow. It's scary. But I think every technology, what we need to do is think what is the benefit and what is the cost and how can we maximize.

That benefit to cost ratio recognized no technology comes without risks and takes that seriously. So what I think is the biggest risk with cybernetics or cognitive neuroprosthetics is I don't think we're going to live in a world where it's 20 plus or minus two. I think we're going to live in a world where the wealthiest people can buy the best prosthetics.

And they'll look at the rest of us. Like we have down syndrome. Wow. And that doesn't need to be a dystopia for it to not be a world that we don't want to live in where other people make decisions for us, because frankly they should. And there's genuine research, animal work being done on this preliminary work with humans where I think we need to stop treating it as science fiction and really decide as a society.

I'm not worried about AI's taking over the world. I'm worried about 20 to 30 years from now, the definition of what it means to be human is fundamentally changed. Sure. I think 

Jonathan Levi: AI gets so much attention because it is this big scary thing, but yeah, nobody's talking about the fact that we could have super-intelligent humans who have the same capability as this kind of doomsday singularity scenario.

Dr. Vivienne Ming: Exactly it is in essence, the same concern, but here it's one, that's one to me, much more proximal and realistic. And two is a reinforcement of some of the very discussions we're having right now. Want to know one of the predictors. I already mentioned it of life outcomes, and zip code, and that's largely well, yeah, of course so.

Well, your parents are a meaningful predictor of forgiving such a generic term, but your intelligence. Yeah. And what happens when, you know, the causal strength of that predictor is increased by orders of magnitude. So. That's I don't want to be there. My goal is to build the world. I want to live in. I want a world where everybody is fully realized, not just those people that can afford it.

Jonathan Levi: I studied sociology at Berkeley. Go bears by the way. And so I'm right on the same page with you. 

Dr. Vivienne Ming: I actually think part of this is also about long-term outcomes. I realize we're talking singularity here. So who knows what happens afterwards, but in a funny way, I want to put the selfishness back in philanthropy.

I know it's never been there, but we're going to somehow figure out how to stick those letters in there because I've done the economic modeling on so much of this work. We all benefit, you know, right now may be the real potential of civilization is at best driven by 1% of our population. And I think that's a tragedy for all of us.

Imagine if we could just tap 10%. You know, the real creative potential, the real productivity of 10%, what a transformation that would make in our world, certainly in terms of literal dollars and cents, but also just in terms of the world that we live in, everyone laments that we don't have our flying cars and so forth.

Well, I don't know that I'm interested in those specific details, but the world that could deliver that sort of life is the one that comes from. All of us contributing. 

Jonathan Levi: Absolutely. Me. I want to touch on something that you said about these neural nets and the idea of you briefly mentioned that it can potentially be used for inputting information.

Now, I remember reading years and years ago about an experiment where two mice on opposite sides of the planet were put through a maze. One was put through it before essentially they transmitted knowledge of the maze. Across the world. And we're able to teach this mouse who had never solved a puzzle, how to solve it.

What is the likelihood, I guess what I'm trying to ask is that we'll be able to essentially transmit memories and knowledge without actually having to experience them, you know, sit a kid down and plug them in in some way. And do you think that's a goal that we should be reaching for? 

Dr. Vivienne Ming: Somewhat like my reference to AGS and TMS earlier.

So there's some co-work Raj Rao at the University of Washington has gotten a lot of press, for example, for the sort of brain reading over internetwork, which is well-deserved. But at the same time, it's not. Quite what people probably appreciate, which is to say it's a lot less about really putting in a full, formed memory and about leveraging some of the things we know about the human brains.

So for example, probably the best illustration here are the rescue rats. So these are rats that have a little mobile system. Implanted in their brain. It's like a mobile chip and we can control their reward centers, not sort of bliss reward, but the centers that control how we learn, how to do things, the reinforcement dopamine as a reward, again, for those of neuroscience in the world.

And. By then giving them right. Well awards at right time. But I want the rat to go left. I want them to go, right. We can provide these little signals, which then essentially bias them in a certain direction. I see. I mean, that is legitimate control. If you did that in a human being, it would be wildly, unethical, and profoundly potent in controlling their behavior.

But it's not quite the same thing as what we imagined someone means when they say kind of mind-reading. So for example, we can do a very robust using something like FMI and definitely another technology called econ, which is essentially a during brain surgeries, putting EEG right on the surface of the brain underneath the skull.

I can tell what pictures you're looking at. I can tell what words you're thinking. So that's the reference I made earlier. So you can truly read out robustly if you have that fine-grain resolution of being in contact with the brain directly, by the way, there's a lot of engineering and physics issues that need to get worked out for that to be a long-term, but it is realistic.

Very real. The write-in is a different issue entirely so we can exploit certain types of right-in. So I referenced cochlear implants earlier by wiring that to the auditory nerve, we can create an actual perception of sound, but if you tried to wire that into the auditory cortex right now where, you know, our higher-level sound perception takes place.

Okay. It would be terrible. You know, we simply don't understand these things well enough or have finely grained input capabilities that can right. A true percept into the brain, as opposed to, you know, again, I can stimulate a part of your motor cortex that will cause you to reach out. I can just randomly stimulate a part of your temporal lobe of your brain.

And all of a sudden you'll be thinking about your grandma. Wow. You know, you can evoke these sorts of things, but it's wildly uncontrolled. You know, the map is not the same across individual people. So there's a huge amount of work that needs to go into writing in, or as we call it coding. Right. But the deep coding portion, the write-out portion that can truly be done very robustly.

And I think that early forms of brain-computer interfaces will involve detail. Decoding coupled with, you know, uh, feedback. So you can imagine you're doing really robust readout and then you have something kind of like, Ooh, glass that gives you the feedback back. You know, it provides auditory signals.

It provides visuals. You could incorporate into that. Some other, the simple brain tricks I'm referring to, but it's going to be longer before we do the write in portion 

Jonathan Levi: robustly. Mm. So you don't see really a future. I mean, also because you're involved in building education solutions, you don't see a future in which, you know, kids are able to sit and put on a helmet and learn the day's lesson.

Dr. Vivienne Ming: I see a future and will, which we can, again, we can exploit the reading of their minds and we can leverage the stage so we could know right now, maybe right now is exactly the moment to give them this piece of information or whoops. That piece, we just presented. We read the state of the brain at that moment.

We know it hasn't been encoded. We need to go back and do it again. Interesting. So in that sense, there is an enormous amount to be leveraged, but the idea of near future, I'm saying 10, 20 years' time. Certainly, 10 years time that we will be able to just say, you know, upload let's do the matrix. You know, now I know Kung Fu yeah.

That's not going to happen based on any of the existing technologies we have today. Well, 

Jonathan Levi: I have to say I'm a little bit relieved because that means I have a job at least for the next 10 to 20 years.

Dr. Vivienne Ming:. I think what we can do is make your job so much more effective, so much more targeted, right. That perfect student that you have that gets everything the first time and is, you know, as a, such a fast and engaged learner.

My goal is to create that in every kid. Yeah. 

Jonathan Levi: Well, that's a good segue because as someone who spends most of their time, teaching people. How to learn more effectively and how to store memories a little bit better. I can never resist the temptation to ask a neuroscientist the same question and hopefully learn something new about my own kind of top area of interest.

So I want to ask how can we learn more effectively?

Dr. Vivienne Ming: So here's one of the core things we do at Socos. And this also comes from, I have had a database of 122 million people working as professionals. And I looked at what predicted career success. And you see the same things come up over and over again, I'm going to use my own particular terminology, which is endogenous motivation.

So endogenous motivation. Is that interest that comes from within you? Yes. A drive that comes from within. Exogenous motivation is a sensitivity to rewards and to punishments, uh, you know, you want to show off, you want to please people you don't want people to think badly of you turns out. In an educational context, that endogenous motivation is an overwhelmingly positive predictor.

Whereas exogenous is in fact a negative predictor, absolutely. In terms of learning in the moment. And one of the main things that I think is useful is to understand that I'm not a huge fan of gamification. I'm not a fan of educational games. Now building games as a form of education, I think is incredibly cool.

And the reason is this is because you're being driven by that endogenous motivation, right? There's an incentive system in those experiences, which isn't the same as you wanting to learn. So there's this disconnect and we are amazing human beings are amazing at exploiting that misalignment, right? And back there's an, a word for it in educational technology is called slicing, you know, figuring out.

How you can get through the experience as quickly as possible. Reap has many rewards is void as many punishments without actually having learned anything. So that's the one, and that sounds like a bit of a platitude, but. What I found is any time that a teacher and this could be a self teacher as well.

You can find your own meaning in the learning experience. So instead of maybe doing rote learning or engaging in, you know, I really want to learn this because I have some other motivation. It's find the actual meaning. So I will give myself as an example. I was a terrible student and quite frankly, generically speaking, I still am.

And I routinely wouldn't do homework and wouldn't engage in class. You know, uh, most of the time I was asleep for half of my high school classes. When I finally went back to school and I was taking seven classes a quarter and, you know, rushing through doing two research projects at the same time and still getting straight A's and everything.

It wasn't because I figured out how to regiment myself and all these other things. It was because it didn't matter what the topic of the class was. I sat up front and I thought, how can I use this today? I didn't literally have the words maximize human potential, but if I did, it would have been that I'm in a Supreme court case.

They're talking about Plessy versus Ferguson. How can I leverage this today to maximize human potential? 

Jonathan Levi: I'm so glad you said that. Yeah. Yeah. Literally, that's an example. Very, very close to an example. I give in my course where, you know, we recommend that everyone preread, which is basically looking through the text and saying, How does this apply to my life?

Where do I agree or disagree? How am I going to use this? I mean, uh, we're, I'm totally on the same page with you. 

Dr. Vivienne Ming: I'm so glad you said that the other, I think is to recognize that those moments that you are truly engaged, they're different for everyone and they can be fleeting. So let's be clear arrest and taking breaks.

Don't get trapped in procrastination traps and those sorts of behaviors. That seems obvious, but. You know, some of the things I've worked on in the past are systems that specifically track how engaged people are not to assess them, but to in fact, do the exact opposite. Hey, you know what, take 15 minutes go to shoot some baskets.

When you come back, we'll actually be more effective, right?

Jonathan Levi: My kind of Pomodoro time, uh, paradox.

Dr. Vivienne Ming: Exactly. And so whether you're using a fixed system like Pomodoro or. You know, people like me are developing things that are highly targeted and personalized either way. You're trying to reach that same thing, which is the recognition that it is those internal goals.

You've set that matter. Not so much how you get there. And I want to deliver that and, you know, let me put it differently. We experimented with systems in universities where, for example, we've found one population of students. Regardless of what grade they got did better. If they got hard, tough love feedback from the faculty.

Wasn't a huge effect, but it was very real. Another population, even bigger though. Didn't just do worse on the project. They didn't do worse than the class. They were 80% more likely to drop out of the entire degree program if they got harsh feedback, even if they were passing. So in that case, what we experimented with were systems for the faculty.

Where literally, as they were grading, it would pop up much like our messages for the parents, with Sarcos and muse. This is essentially muse for faculty and it said this person, Maria needs more gentle feedback. Right there in the moment that you're writing the feedback. And if you clicked on it, it would say why students like Maria that receive harsher critical feedback are 80% more likely to drop out.

You get out to give her a B why sabotage that by hugely increasing the chance that she will never reap the benefits of your course. So for those of you that are teachers and managers, here's my line. And again, it sounds like a line, but I build algorithms. So this is truly realizable. Don't get focused in aligning your employees.

With your business or aligning your students with some set of fixed outcomes, figure out how to align your business with your employees. What is the thing that's going to make this resonate for them? Why did they get out of bed in the morning? Right? I'm not saying you can only teach people about Buffy the Vampire Slayer because it's their only interest in the world.

No, but if you can make it relevant to Buffy the Vampire Slayer, they will learn it better. 

Jonathan Levi: Yeah, it's the start with why, you know, the TedTalks so much and it's the Malcolm Knowles stuff. Adults need to connect to their existing knowledge and they need to have a pressing need and immediate applicability.

Otherwise, why do I care?

Dr. Vivienne Ming: You know, you know, we actually this paper that we wrote a white paper or my wife and I coined the term, meta-learning, we included in that a subtitle, which is, it's not what you know, it's why you know it. And we see that. Over and over again, when I analyzed that 122 million person database, the college, you went to the grades that you had for that matter, your gender, your race, all those sorts of things.

None of those were predictive in meaningful, useful ways, but neither were the skills, you know, of course, you know how to program if you're a programmer, but it takes real detailed analysis. For knowledge of someone's skills to actually be predictive of how successful there'll be inside an organization as a software developer.

And this goes so deep as to say a bachelor of computer science at Stanford, we found only be a very modest admittedly though, positive predictor that someone is a good software developer. So instead we see things like if they're tweeting out at two in the morning, Oh, salary is awesome. You know, to their eight followers.

That turns out to be a strong predictor. Why? Because our algorithm automatically mining through these tweets said, Oh, they're almost certainly referring to salary. The multiprocessing toolkit for Python. And if they know the salary, now we have this fancy machine learning probabilistic graph that says if they know salary, they probably know Radice or rabbit MQ.

They're probably using it for flask or Jengo even though they never used the word Python. Imagine what it says versus they wrote the word Python on their resume. And furthermore, what made it really predictive is celery is awesome. They could have said salary sucked. What mattered is that they had passion about it.

It gives you an insight into why they do what they do instead of what it is they do. And that turns out to be the most important thing. In fact, I have a pretty strong recommendation to a lot of people, which is okay. Hire based on cultural fit and personality and motivation. And then if you can afford to do it, take weeks, take months, train them how to do the job.

Jonathan Levi: Yep. Skills can be taught and culture can not 

Dr. Vivienne Ming: exactly. Now that's the point of what you really want? What I call a good liquid skills market, where people can quickly go out and learn to do new things. That's powerful and it needs to be there, but you've got to have. You know that craftsmen there to make use of those tools.

Jonathan Levi: I love that. I really love that. Especially, you know, as someone who has changed industries so many different times and came into podcasting or book writing or online course teaching with no skills and just that passion and that willingness to learn, it resonates with me quite a bit. 

Dr. Vivienne Ming: Well, it's been something that I brought together.

People look at the work that I do, and it's sometimes it feels disjointed and all over the place. To me, it's very coherent, you know what makes it great life is something that we can actually produce. Everywhere from three-year-olds to 30-year-olds to 90 year olds. And I just want to be a part of all of those pieces.

Jonathan Levi: I love it. Dr. Mink. I know we're running out of time here. I just want to ask you a couple of really quick, short-form questions. If you have a couple more minutes. Absolutely. Awesome. First question. What hundred dollars have you spent recently that most impacted your life?

Dr. Vivienne Ming: You know, this is going to sound almost trivial, but I have a nexus nine tablet and I bought the wireless keyboard for it.

And it has been, you know, freeing me to stick my tablet in my purse. And be productive anywhere has been really useful to knock out those emails, even write a little bit of code, you know, write long-form anywhere I am. It sounds like such a small thing, but I have to admit. It's been a big deal and I've become kind of a convert to this idea of getting off your computer and being mobile.

Jonathan Levi: I love it. That's a solid one. Question. Number two. What book or books have you most recommended or given as gifts? 

Dr. Vivienne Ming: So, you know, the one that I have recommended often because it captures part of what I want to do is a book called the diamond age. And it's about this, uh, this man who builds. An AI that's meant for this princess to optimize her life, to make her as good as she can ever be.

But then he ends up making three and one goes to the princess. One goes to his daughter and one goes to this orphan girl on the street. And then the story, which is complex and involved from Neal Stephenson, the author of snow crash and other books is very complex. But this core idea is that you could build something.

That would literally transform these three women's lives. Yeah, I was in this space already in my head, but it codified it. And you know, in a very real sense, muse is exactly what I've tried to build. Is that primmer from that book. 

Jonathan Levi: I love it. Muse being the headband. 

Dr. Vivienne Ming: No, no, no. I'm so great. Muse being the name of our product at Socorro's.

Okay. So press news. So this is this thing for parents, where we literally can take pictures of the children's writing. We can take an audio snippet of you having a conversation with your kid. We ask one single question a day, and then we can send to those parents. That one thing that will have the biggest impact in your child's life, that night amazing.

And it's all packed up and all you need. We have an app, but all you also need is text messages. We can do this anywhere in the world. If you're a mom and rural Liberia. And you've got a flip phone. You can get the exact same system. And in fact, we're distributing it around the world for free starting early at the end of this year.

So it is enormously exciting. I love it. 

Jonathan Levi: One last quick, short form question possibly too. We like to give our audience, uh, homework every week that they can do to act on the things that they've learned today during the episode. So what, one piece of homework, whether it's a reading assignment or an exercise or anything else, would you like to assign to our audience this week?

Dr. Vivienne Ming: Well, listen, I would be a terrible business woman. By the way I am. If I didn't say go to soccer, starting.com and get muse and do it please. Yes, absolutely. Let me give you a different thing. It will sound like we're off topic, but part of what I describe as my life changing moment is living a life of substance.

And that often means doing something because you know, it will make the world around you better. Even if it's harder, even if it means it will make you a little less happy in the moment. So here's my assignment to people this week. Find that one moment where you can live a life of substance. If you see someone.

That looks alone, go up and make their company. If you see someone that is, you know, they're in their muse, they're geeking out on whatever it is. Go celebrate it with them. You know, so many times in life, we see little moments where we know we could have done something to make someone else's life a little bit better, and we walk past them for good reasons.

We're busy. Our job is making our kids' lives better. All of these things. Here's my one homework assignment. Pick a moment this week, do an act of substance. 

Jonathan Levi: I love it. That's a beautiful point to end on Dr. Ming, where can people learn more? We're going to put the link obviously to Socos, but if people want to learn more about what you're working on or get in touch with you, where should we send them?

Dr. Vivienne Ming: Absolutely. So, uh, Socoslearning.com is where you can find all about my work there. If you go to my personal page, the vivienneming.com and you've got a friendship, find that Vivian. Then you can reach me directly off of that site. You can reach me off the Socos site and you will learn about the work that I'm doing with bipolar disorder, with diabetes in labor, and talent modeling.

And so many other things. I get to travel around the world and speak and share all this stuff. I'd love to come and visit any of you out in the audience and share. I, Almost never say no, especially when it involves a big donation that helps bring news to more kids around the world. 

Jonathan Levi: Excellent. On that note, I'm going to see what I can do about getting you to come out here to Tel Aviv and lecture. Cause I know Israel is really, really hot on edtech and of course, uh, you know, anything involving big data. 

Dr. Vivienne Ming: I would absolutely love it. 

Jonathan Levi: Awesome. Dr. Ming, it's been such a pleasure. Thank you so much for your time and we'll make sure to link everybody up. To both of your websites. 

Dr. Vivienne Ming: And thank you. It's been my pleasure. I've really enjoyed this, Jonathan. 

Jonathan Levi: Me too. Take care.

Dr. Vivienne Ming: Bye.

Jonathan Levi: All right. Superfriends. That's it. For this week's episode, we hope you really, really enjoyed it and learn a ton of applicable stuff that can help you go out there and overcome the impossible.

If so, please do us a favor and leave us a review on iTunes or Stitcher, or however you found this podcast. In addition to that, we are. Always looking for great guest posts on the blog or awesome guests right here on the podcast. So if you know somebody or you are somebody, or you have thought of somebody who would be a great fit for the show or for our blog, please reach out to us either on Twitter or by email or email is info@becomingasuperhuman.com. Thanks so much. 

Closing: Thanks for tuning in to the Becoming Superhuman Podcast. For more great skills and strategies, or for links to any of the resources mentioned in this episode, visit www.becomingasuperhuman.com/podcast. We'll see you next time.