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Episode 23: Flawless Predictions for the 2020s
11 Plays4 years ago
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Transcript
Introduction and Show Overview
00:00:15
Speaker
Welcome to the Cognition podcast. I'm your host, Rolf Nelson, and with me as always is Joe Hardy. Hi. On today's show, we are going to do instead of a year end wrap up, we're going to look ahead towards the future and we're going to think of the next decade ahead. So what's going to happen between 2020 and 2030? Well, we've got some predictions for you.
00:00:43
Speaker
We've got stunning predictions, stunning, absolutely stunning. And you know, we're going to, we're going to lay those on you.
Audience Engagement and Festivus Plans
00:00:52
Speaker
Uh, before we get into that though, I just want to help, uh, get people oriented to how to reach us. If you have any feedback or just comments or you have a guest that might want to be on the show, you can reach us at cog nation podcast at gmail.com. We'd love to hear from you.
00:01:09
Speaker
You can also check out our Facebook page, Cognition Podcast on Facebook. I'm also reachable on Twitter, JL Hardy PhD. And I am available on Twitter at roflnelson. But I think the best way to get us is the email. So if you really want to catch us quick, definitely email us and we'll get back to you as soon as we can.
00:01:38
Speaker
All right, so end of your podcast. It's getting to be holiday times. Are you thinking about the holidays? The holidays? Yeah, we're going to have a Festivus party. I'm excited about that at the Festivus for the rest of us. Are you really doing that? Are you going to air your grievances? We're going to air our grievances. We're going to have a Festivus poll. There might be some wrestling involved. I want to know how the grievance ring actually goes.
00:02:09
Speaker
I think it's just, you know, you get up there and you're like, I have a lot of problems with you people. Yeah. And you just kind of get into it. You work it out. You just work it out. That sounds, I'd love to try Festivus sometime. Yeah. I mean, I have a lot of problems with a lot of people, so that could take a while. It's a way to cleanse the system. It is. It's a, it's a yearly ritual that the rest of us can participate in. And, uh, it should be a lot of fun.
Humor and Serious Futurism in Predictions
00:02:37
Speaker
So so we're going to talk about each of our 10 predictions for things that may come true within the next 10 years. So those of you listening to the show in the year 2030, you can get out your tally and see how we score on these. Yeah, this is fun because, you know, the futurism is is part of the show. I mean, that's part of what we're we're getting at is like what's going to happen in the future?
00:03:05
Speaker
based on what we know about where we are today and what's happened in the past. And of course, you know, there's always a little bit of humor when it comes to the futurism stuff, because, you know, there's this balance between things that are kind of obvious and kind of lame predictions that are like, of course, it's going to come true. We're gonna have a couple of those. But then there's the more interesting ones where
00:03:27
Speaker
It's probably not going to happen, but if you say it and it happens, you're going to sound really smart in 10 years. So we're going to try to do some of those as well. And there's no doubt that a lot of crazy things are going to happen and people are not going to predict most of them. Obviously predicting the future is hard. If we could predict the future easily, well, we wouldn't have to invent. We wouldn't actually have to invent anything. We just think about the stuff we're supposed to invent. Right. Exactly. Exactly. Yeah.
Media and Time Travel Discussions
00:03:57
Speaker
The, uh, have you seen the show dark? Oh, you know, I just started watching that Netflix. Yeah. Yeah. It's pretty good. It's, it's, you know, it's this whole time travel thing and they bring up all the different paradoxes and so on and so forth. Um, pretty, pretty good shows. It is very dark, but it's a good show.
00:04:18
Speaker
I think at some time we may have to do a show on time travel tropes and maybe even go through the movie Primer. Have you seen Primer? I don't think so. Oh, it's a great movie for insanely complex and sort of gritty, realistic time travel. Maybe we can look at that someday. Yeah, no, that'd be fun.
Autonomous Vehicles and Future Tech
00:04:42
Speaker
No, time travel is a good one. I don't think time travel is happening in the next 10 years.
00:04:47
Speaker
I don't think so either. So it's not going to, we can't really get into that today. It didn't make the list. So we, so we are traveling into the future with our predictions cause they're going to be spot on. Well, mine will be spot on. We may have some disagreements about some of these. We do. I think we do. I think we do. So yeah. Yeah. So what are some of your predictions?
00:05:09
Speaker
OK, so let's take the topic of autonomous cars and where that goes, because everybody has a prediction about autonomous cars. And everybody's predicting, oh, there'll be X here that autonomous cars will come out. But I think there are all kinds of other things that might happen as a consequence of development to these two. So here's one. So autonomous vehicles on farms, I think, are going to be a much bigger deal.
00:05:37
Speaker
because I think that's going to be the thing that moves towards almost fully automated farming. Once you have cars that are able to transport things and get around the farm and efficiently manage all these resources, I think you could
00:05:58
Speaker
Well, I guess it could depopulate the rural areas, unfortunately. It's not a good thing for small hobby farmers, but that kind of stuff seems like it could be more or less automated. Yeah, the agribusiness is a big story that doesn't get talked about much from the past couple of decades, really.
00:06:20
Speaker
I mean, just the advances in technology with tractors and harvesting equipment. And of course, all the animal husbandry stuff that's happened so far, I think your point is well taken. I mean, the next logical step would be you don't even need a person driving the tractor at all. And you could have huge swaths of land essentially farmed with machines. It's so much being done with drones and other sensing technology as well.
00:06:49
Speaker
Yeah, I mean, we're able to produce a ton of food with very little human input. Yeah, and I guess maybe it's not the most dramatic thing to say that that'll just be on the increase. And you can think about more things that AI would be able to take over, that people still have to operate on some level for kind of overseeing the whole thing, but probably certainly less manual labor.
00:07:18
Speaker
Right. I mean, maybe someone's in the driving around in the tractor just because, you know, why not? It's just kind of someone out there, you know, so they don't have to really do anything. Yeah. Yeah. Yeah. I had a prediction. You know, one of my predictions was self-driving cars are a real thing. Flying cars and jet packs are not so. So if you look at, you know, the futurism from the past, the fifties or whatever. Yeah. By now, 2020, we're supposed to have flying cars.
00:07:49
Speaker
Well, yeah. And we're not going to have we're not going to have flying cars in 2030 either. It just inefficient. Doesn't make sense. I might have to disagree with you on this. I guess I think we have to define then a few terms like what is self driving car being a real thing mean? And what is having flying cars and jet packs? OK, sure. You can have a flying car. I mean, you could have had a flying car in 1950 as well. If you define like like, you know, you just make a plane that is like a little bit better.
00:08:18
Speaker
suited for driving around but it's not the same as everybody people aren't using it yeah people are using it to get around full of flying cars and everything yeah exactly that's not gonna happen it's just impractical it's just impractical you end up running into each other because managing managing the airspace becomes a huge hassle
00:08:40
Speaker
Well, but I mean, that's a hassle that could be figured out with A.I. I mean, it's right. But it's another demand. I mean, aren't there those flying cars and what is it Abu Dhabi? That are planned to I mean, they were planned to have been up already this year that they'd be like drones that can carry a couple of people and they can fly up to the top of skyscrapers if you need to. You can just go right through the traffic. Isn't that like a helicopter?
00:09:08
Speaker
Uh, yeah, maybe it's more like, I mean, they call them drones, but I guess it's, maybe it's just like a helicopter, but they're, they may need a human pilot down on the ground, like overseeing them. So that doesn't, I don't know if that counts as fully automatic. No, I think that's fine. I think that's fine. I, I, yeah, I think so. Sure. The technical, I mean, there's always this question of like, you know, helicopters, are they like, you know, what's a drone? What's a helicopter? What's a flying car?
00:09:38
Speaker
You know, if a helicopter can, you know, has wheels, instead of flying car, you know, now we're just playing with semantics here. Now we're playing. Yeah, exactly. But you know, people aren't going to like go to their driveway, get in a vehicle that flies and fly off to work. That's just not going to happen in 10 years or ever really. Probably. This is not the right way. It's not the practical way to do it. It's not efficient. Hmm. It's way more efficient to like put someone in a tube.
00:10:06
Speaker
The bigger point here with the self-driving car thing is it's not the tube thing, but it's the same concept. The problem you're trying to solve is you need to get everybody lined up. It's all about getting people lined up and going in the same direction at the same time, at the same velocity. Acceleration is your enemy when you're trying to manage traffic of any kind, whether it be air traffic or street traffic or foot traffic, any kind of traffic.
00:10:35
Speaker
It's when there's just different changes in velocity across different, you know, actors in the, in the, in the world there. So like a car is going at constant velocity on the highway are able to interact very smoothly. It's just the problems when everyone slows down.
00:10:54
Speaker
Well, this is my pet peeve too that when you're at a stop sign and the person in front of you takes like their delay is a little bit and then the other person in front of you has a little delay. And I would think if you just all just follow each other at the same time, if you'd start at the same time, which you could coordinate
00:11:11
Speaker
Yes, a little drum roll, please. Yeah. Yeah. You could coordinate through automatic driving. You would get a lot more people through that stop sign, and then I wouldn't be the last one sitting there waiting at the rest. No, absolutely no. And it's a super good point. And the big distinction is between what you might call smart highways and self-driving cars. Self-driving cars are just whatever.
00:11:40
Speaker
They don't really help you that much. The person driving the car maybe gets a little bit more rest. Maybe they can spend, you know, they have another half hour to like scroll, you know, their social media, which is like, is that advancing anything? Really? I don't think so. So Tesla kind of does this now. I mean, you have cars that can do this now, basically autopilot, right? Doesn't really help you that much.
00:12:04
Speaker
this to be a real major advancement so that people get where they're going faster and more people get where they're going faster with fewer accidents, the cars need to talk to each other. Yes, absolutely. That's the part that's missing right now. And that's the part that I think is going to be hard. And the reason why it's hard, it's not technical. And this is the big theme of my whole top 10 was that it's not the things that
00:12:30
Speaker
are hard to do in 10 years are not the technology things. We can do so much with technology. We have so much technology now that's just sitting on the sidelines anyway. The hard thing is coordinating it, especially at the level of society, getting people to work together to use the technology in a smart way. That's the problem.
00:12:50
Speaker
So because there's too many there's too many people trying to make autonomous cars all with their own particular way of doing it, their own communication systems, they need to have some standardization. Yes, exactly. Exactly. And that requires, you know, something at the level of, you know, the society. I mean, you could imagine an industrial standard that would that would solve it, but it would be
00:13:21
Speaker
I would predict that that doesn't happen in 10 years. The only way you could solve it in 10 years is if the government came in and said, this is the standard. These are the sensors we're going to use on the highways. This is how cars need to talk to each other. Obviously, you're going to need all the technologies coming from industry, but you need some sort of regulatory body to coordinate that. Because Elon Musk has no interest in
00:13:46
Speaker
you know, giving Ford the keys to his technology, right? Why would he do that? Right. He wants everyone to drive a Tesla. So, okay. So maybe, so now the question is, it's different than is the technology there.
00:14:04
Speaker
Right. Now the technology is totally going to be there in 10 years, a hundred percent. Well, okay. That's basically there now. That's what I would say is the tech is in 10 years we can have good automated flying drones that we ride in. Right. Yeah. Taxis like, so if you were to take, if you were to take them out to the middle of Nevada or something like that, it would respond just fine. It would be a problem if you were in a city cause you know, airspace and
00:14:35
Speaker
Right. So you'd have all these, you know, if you, that's the problem. You start getting these, yeah, exactly. Same with self-driving cars, the same problem they're going to run into, which is that the rule sets for the different self-driving cars are going to start to conflict. So at the end of the day, it results. If everyone is, there's, there's too many cars and they're all
00:14:57
Speaker
operating on different rule sets, the net result is still just a traffic jam. I mean, everyone's just still sitting in their cars in a parking lot, right? It's the same problem we have today. It doesn't solve the actual problem that we're trying to solve, which is, I mean, putting my hands on the steering wheel and using my feet to do the grass gas and brakes. I don't, I don't, I don't mind that. That's great. I'm totally cool with that. I just don't want to sit in traffic. Well, if it's more, I mean, at the very least it could be an issue of safety.
00:15:26
Speaker
Right, it is. I think it won't be very long if we're not already there that self-driving cars are safer than human-driving cars. I would definitely trust an algorithm over my brain for driving and the sensors that would come with it too, like what a self-driving car is going to be able to see and pick up on. See it all behind you, to the sides,
00:15:52
Speaker
No, I mean, it's definitely there. I mean, certainly in 10 years, they will definitely be safer. There's no question. I think they will be safer enough and it'll be efficient enough that people will be using them. A lot of people will be using them. They'll be all over the place. OK, so let's get a specific prediction, Joe. So what?
00:16:14
Speaker
I'd say the majority of cars on the road will be self-driving cars. In 10 years, over 50%, you would say. Have that capability. Not that they will always be in that mode, but
CRISPR and Genetic Enhancements
00:16:28
Speaker
they will have that mode. Okay. That's a prediction. Okay. We'll fact check that in 10 years. Yes. We'll come back in 10 years on episode 5,000 of the show.
00:16:39
Speaker
And my modest prediction is that you'll have well-performing autonomous flying drones that you could use in remote locations, but probably won't be able to use in cities. OK. And if it comes true, I will be flying one of those. I'll be moving to Nevada. Well, maybe it's more the kind of thing where you go to Vegas and it's like an activity that you do between your time at the casino.
00:17:09
Speaker
You can go shoot AR-15s, or you can go fly one of these autonomous drones. Well, Vegas seems like a great place to be the first place to have autonomous. Let's have a pile on prediction that the first place that this will be popular in the US is in Vegas. People who are looking for something new, something novel, they're also totally drunk. Yeah, they're not going to be flying the drone. That would be unsafe. Yeah. OK. Well, there it is. They're wasted.
00:17:39
Speaker
Flying taxis in Las Vegas. Okay, that's my end prediction. Flying taxis in Las Vegas. All right, so let's move on from autonomous cars. What else do we have here? Let's talk about CRISPR. Let's talk about CRISPR. So my prediction about CRISPR is that people are going to start trying to use CRISPR to enhance intelligence.
00:18:01
Speaker
So they're gonna be trying to like cut out little pieces of DNA, replace them with different pieces and try to make people smarter. And there are gonna be problems. Okay, details. Well, you know, this whole thing with CRISPR is, you know, you've got the sort of mainstream CRISPR that's happening in labs in like a methodical scientific, you know, reasonably
00:18:33
Speaker
reasonably safe and- Laboratory, lab-level equipment. Yeah, yeah. And people, you know, just trying it first on mice and then trying it on larger animals and so on and so forth. And then you've got the Yahoo's at home who can buy a kit for like a thousand bucks on the dark web and do their own CRISPR at home. And people will be trying to hack their brains. And I predict there will be some pretty significant
00:19:01
Speaker
Side effects. Negative side effects. There'll be some Darwin Awards handed out for that. Yeah, exactly. I mean, if you just look at how much people are zapping their brains today with electricity, and we've talked about that. I mean, it's probably pretty safe, actually. But it's kind of dodgy.
00:19:23
Speaker
And you don't really know what you're getting yourself into. I mean, if there's so many people willing to do that, I'm sure they're a smaller percentage, but still a lot of people willing to try CRISPR to make themselves smarter. And I think eventually that is a thing that will be possible. And that's going to be a whole topic, but in the next 10 years, I don't think it will actually work efficiently and well. So it's just going to be a lot of weird Darwin award type stories.
00:19:49
Speaker
Um, more details again. So what like extra eyes like, uh, Well, I think there's going to be, yeah, it's going to, you're going to have weird mental problems. That's really what it is. Yeah. Yeah. You're going to have people who are, you know, you know, having strange effects of like, for example, if you, if you enhance memory in a certain way where you can like be very, you can very clearly remember certain events.
00:20:19
Speaker
But that might have other knock-on consequences to the rest of your cognition that are hard to predict. Right. So we know, I mean, this seems to show up in brain research all the time that usually an enhancement in some area leads to a deficit in another area. And for the most part, something like photographic memory is not a useful thing for people to have because it ends up being more confusing than it is helpful and not a good way to organize information.
00:20:48
Speaker
Right, it can be distracting. You'll have this very vivid memory that will pop up in a situation that may not be helpful and that memory can be quite distracting. So what we may see is people trying out CRISPR and more kind of seeing what kind of benefits they can get and what kinds of horrible side effects they'll have. That's right, exactly. Exactly. Well, we can learn from that.
00:21:18
Speaker
Yeah, no, I mean, it's going to be interesting. CRISPR is super interesting from that perspective. Just the fact that you can start to really, you know, design your own DNA or design a being's DNA is, you know, it's going to be it's going to be big. Let's just say that the consequences are going to be enormous over the next 10 years. Well, I have two predictions that I think would relate to CRISPR because I'm sure that's on everybody's future list.
00:21:48
Speaker
Yeah, of course, you have to have something about CRISPR. So the first one is a bold prediction that the first commercially available genetically modified food is going to be released in England, and it will be called CRISPR chips made from modified potatoes.
00:22:08
Speaker
So that's a specific prediction. That's like really specific. Whoever decides, whoever wants to do that, I'm just throwing that idea out there. You can even have the brand too. Crisper chips. No, no, no trademark here where this is open source. Modified by CRISPR to be CRISPR.
00:22:29
Speaker
And then the other one that I had was thinking about, I think CRISPR probably plays into genetically modified foods and probably into whatever comes next for fake meat, right? Right, right, right. Fake meat is a big topic. Yeah, I like this one. It's hard to imagine
00:22:56
Speaker
I don't know if everybody's going to go towards plant-based food in 10 years. I think that's way too early. What I'm thinking is just more genetic modifications on fatter and fatter chickens. Maybe you can take out their cortex. Well, that's an interesting thought, right? I mean, if you could basically, for example, right, I mean, we think about,
00:23:24
Speaker
Well, anyway, my first thought when I think about fake meat is you're growing muscle tissue in a Petri dish, which is like the thing that people are doing. And that's, you know, right now it's very expensive to do, but people are doing it. You can do it. I make sense for hamburger, right? You know, for hamburgers, you know, you're just, it's kind of mashing that stuff up anyway.
00:23:44
Speaker
Doesn't really matter how it's all organized together. As long as you've got the right kinds of proteins and it looks basically like the right color. Uh, I'm thinking you might need, you might need some kind of other, besides muscle, I think some other parts of the organism. Maybe you've got, you know, fat circulatory system. Yeah. You need blood. Yeah, for sure. All of that kind of stuff, but you have it controlled. You don't need to have it controlled with a cortex. I don't know.
00:24:14
Speaker
Yeah, exactly. And then the interesting question for me as you bring this up is if you take out the cortex so that the animal no longer has a brain. Yeah. Does that assuage some of your concerns from an ethical standpoint about the fact that you're housing this living being and like a totally horrific, you know, I can't help but think so Mad Max kind of environment that they live in.
00:24:42
Speaker
I mean, well, I don't know, actually, these kinds of things, these kinds of horror scenarios always sound like, I mean, you can't really go right either way, but I guess I would, I know, but the horses, just to be clear, the horse scenario that I'm talking about is current, the current farming practices around like animals. Yeah.
00:25:01
Speaker
Right. I mean, like how how chickens are currently farmed today. Yeah. It's horrible. Yeah. So it's actually disgusting. So I look I look this up and according to estimates are somewhere around 23 billion chickens in the world. OK, that's a lot.
00:25:19
Speaker
And also, strangely enough, there are about 65 billion chickens that are eaten each year, which sort of tells you something about the lifespan of a chicken. Not very long. So it goes through that fairly quickly. So I would have to imagine that if what you're really concerned about is the suffering of a creature living in one of these horrible factory farms, you're going to reduce the suffering by
00:25:43
Speaker
reducing the conscious experience. And if you can take out a brain, I think you're, well, I mean, I don't know if you're ethically in the clear, but at least you should be moving in the right direction. You're moving towards, I mean, there's this whole thing about, I mean, right. Some people would argue, and I think it's not crazy, that all things have some sort of consciousness. Panpsychism, yeah.
00:26:12
Speaker
And even more people would argue that all living things, at least, have some consciousness. And so as you get into that, lettuce, what's the consciousness of a lettuce? But you're moving, I mean, I think just in terms of how we feel about it, I think we all pretty much, not everybody, but almost everybody feels a little bit better about the lettuce than they do about the chicken.
00:26:43
Speaker
And you're moving the chicken towards the lettuce. If you take the brain out, you're definitely getting closer to lettuce. And you grow it in the Petri dish, and you're much, much, much, much closer to lettuce. I think you bring up, I think that you've got, that's a perfectly stated goal. We want to move from chicken towards lettuce. With the deliciousness of chicken. In terms of sentience that we, in terms of the sentience that we're farming.
00:27:07
Speaker
Yeah. The brains of lettuce with all the deliciousness and flavor of chicken. Yes. And protein. Perfect. Yeah. Yeah. That's where we're going. So where are we going to be in 10 years on that?
Challenges in Harnessing Technology for Society
00:27:23
Speaker
My prediction is we just have more bigger chickens.
00:27:31
Speaker
So we just have, I think we're not moving. We're not, we're probably not. We're not moving in a positive direction, basically.
00:27:38
Speaker
I think it'll come, maybe come eventually, but I think we're just going to have, you know, ridiculous looking chickens that have huge, huge, like bigger breasts and wings and everything. And, and, uh, maybe they're dumber. That would be a bonus, but, uh, but I guess, yeah, I don't see, I don't see us moving to a meat free.
00:28:05
Speaker
That's not happening yet. That could be in some ways in the future. And I think this speaks back to the previous point, which is, again, I think a big theme of this whole thing is the technology to make the world better is going to be there. And not much of it already is, but we won't use it because we're dumb. And the way that we're dumb specifically is it's hard for us to get together on things. It's hard for us to agree on things.
00:28:32
Speaker
Right. It's like we were looking at the world, not as like, uh, what's the best thing for everybody altogether on average, or even like in total, but rather like, am I doing better than the next guy? And that's going to be, that continues to be the problem. Well, and that, that gets me to one of my predictions. Oh, okay. Which is, so what people continue, this is number, this is prediction number eight.
00:28:58
Speaker
So we each have 10 predictions. We're kind of going through them in different. Yeah, we'll go through kind of more on topic because I think it's like hard to like, it would be kind of boring to just like go through one, two, three, four, because we have some of the same ones, but we have different takes. Yes. Okay. So your next prediction, Joe. Number eight is people continue to be dicks to each other, even though they don't need to anymore. Wow.
00:29:25
Speaker
We're going to file this under not very bold. Not a bold prediction, but... I feel very confident on this prediction. I think the interesting part of this is the don't need to anymore part, right? Yeah, so flesh this one out.
00:29:39
Speaker
Because the fact that people are going to be dicks to each other, I mean, that's the easiest prediction in the world. I can make that prediction for 20 million years from now if there won't be people. But as far into the future as there will be people, they're going to continue to be dicks to each other. And the reason that they don't need to anymore, it gets actually back to your topics around farming. We already produce more than enough food to support everybody on the planet. If we were smart about it,
00:30:08
Speaker
and we were kind to each other and we were thoughtful, everyone could eat. Everyone could eat. Yeah, this is, okay, so this is a bit of an inequality issue. It's a- The inequality distribution topics, exactly. Hoarding, you know, waste, throwing stuff away. And in 10 years, we're gonna have, it's gonna be super efficient and cheap to feed everyone on the planet. Easy.
00:30:37
Speaker
Easy. The distribution would be possible. You know, productivity is going to be there and it would be inexpensive relatively to everything else that we're doing to just make sure that no one went hungry. Everyone ate.
00:30:51
Speaker
I guess this is sort of in the topic. I mean, you know, there's all this stuff that's gaining traction now around universal basic income and just sort of thinking of a way to allow for a basic set of things that we can provide for every single human on the planet. Right. That everyone should have, you know, you know, we have human rights that we consider basic in America and a universal set of basic human rights.
00:31:20
Speaker
I think so. As progress continues, you want to be able to have that progress benefit everybody. I think so. I would like to see that. And I think food is one for sure. That's the number one. And then a place to live, stable, safe, secure, a place to live. It doesn't have to be fancy. It doesn't have to be big. Just a place to lie your head and put your shit.
00:31:45
Speaker
And, uh, some healthcare, you know, some basic healthcare, right? Everyone should have all that stuff, you know, but we won't, we won't, we won't do those things and we could, just like we could have car, you know, highways that are smart and all the cars officially move around each other in a, in a fast and safe way. We're not going to do that either. Well, your future for the same reason, your future seems to be kind of a bureaucratic, uh, nightmare.
00:32:14
Speaker
The future is gridlock at the level of cooperation and getting along and tremendous growth in terms of technological capabilities. But yet inefficiently distributed.
00:32:35
Speaker
inefficiently distributed. And the inefficiency of the distribution is what prevents a lot of these technologies from really achieving positive outcomes, or the most positive possible outcomes. Okay. How about, have we covered that topic? Yeah, I think that's the big point.
00:33:00
Speaker
Okay, I have one in the area.
AI's Role in Efficiency and Education
00:33:04
Speaker
So my number six on here is office use of artificial intelligence will increase. So this is a boring one, I guess.
00:33:14
Speaker
I would imagine, I mean, what I can see is there are so many people that have boring drudgery office jobs, right? And I could see a lot of that stuff algorithmized. Just being able to take any of the repetitive stuff that's done day to day, filing paperwork, making appointments, all of that stuff,
00:33:40
Speaker
I think you're going to have, you know, digital assistants that are going to be smart enough so that they can handle that stuff more seamlessly. And the job of someone working in the office is really just going to be higher level and less repetitive stuff. That's what I mean. That's the hope.
00:34:02
Speaker
I could see that. You know, the dream, I mean, like the dream for AI is that it gets you out of doing the boring stuff. And be nice to see some of that happen. And I mean, as a matter of economics, it seems like it should be happening in in office, office settings. And there's certainly the incentive to do it because it costs less.
00:34:24
Speaker
I think thinking about your job, Rolf, as a professor, it feels like the most boring part of that job, from my experience anyway, is grading papers. You're not wrong. Yeah. So do you think AI is going to be grading your papers in 10 years? That's an interesting question.
00:34:46
Speaker
I could see the demand to do AI grading, but I could see students being really not happy with that. I don't think, I mean, if I had access to AI to grade a paper, then students could also have access to that same thing. And they should have access to that thing. Get the key, and then it's just a matter of, yeah, plugging it into the key.
00:35:15
Speaker
they should be able to use AI as much as you know as much as anyone else and but yeah I think that's one thing I can see a lot of areas in education and teaching where it seems like things would have been algorithmatized but they haven't been I think online teaching is has has really failed
00:35:38
Speaker
You know, it had tons of promise. People thought that traditional brick and mortar colleges were just gonna disappear, but there's so many issues with online education that it's just, it's not going away, that real education's not going away anytime soon. You're gonna need teachers, I think. Yeah, no, I agree, I agree.
00:36:03
Speaker
Or if you think about just from the AI perspective within the office space as it kind of relates to papers specifically, in some ways, like spell check and grammar check are like a very sort of, it seems trivial now. I mean, kind of pretty deep use of that that we're doing already. Yeah. Right. I mean, like you write a paper and, uh,
00:36:32
Speaker
You know, when I was writing my thesis, this was not that long ago. Like, what was it? 2002, I guess I got my PhD. It's now quite a long time ago, actually. I think about it. But, you know, spell check was there. That was a thing. Didn't work very well. Didn't really use it that much. Grammar check was pretty garbage. We had, you know, we obviously, we had word processing, so that was an advantage.
00:37:03
Speaker
But nowadays, I never learned how to spell properly. I never did. I still don't. I still don't know how to spell. I don't. I just never learned. And then all of a sudden, technology came to the point where you just don't need to anymore. You don't need to, Adam, or you just need to have the thought.
00:37:19
Speaker
Yeah, I know. And so I never learned it and never have to learn it. I will never learn it. And I'm totally fine. It's never, it used to be a problem for me. It was like a problem. I would, I would do like relatively poorly on spelling tests, for example. I mean, compared to, I mean, I was, you know, not, I mean, I might be exaggerating a little bit, but like, I wasn't a great speller and especially relative to other things that I was doing and.
00:37:45
Speaker
You know, it just was like a problem, but because I looked dumb when I misspelled some obvious word, but now it just, you know, doesn't come up. This literally hasn't come up in years.
00:37:55
Speaker
Yeah, and it's interesting to really think about what the set of capabilities that AI are going to have that can take over these things that people, you know, used to think are related to being smart or cognitive capabilities. Like, you know, it's hard to say that playing chess well is a valuable skill in everyday life because
00:38:22
Speaker
You know, you'll never beat a computer. Yeah, exactly. You'll never beat a calculator either. Yeah.
00:38:32
Speaker
Right. I mean, the chess thing, I never I never would have bought into that, that that was like really a thing. I never believed in that. But like, yeah, a lot of people did a lot of people did. And now it's like hard. It's hard to maintain those arguments to your point because of the ease at which AI beats people now. Yeah. And I think that I think the spell check example is a really good one, because I think that's a perfect example of one that's already here. And
00:38:56
Speaker
We think about the future as being super exciting, but we don't think about spell check as being super exciting. But it's impactful. It's impactful. It's impactful, exactly. I think there'll be a lot of other things like that that automate lower level tasks so that you're just spending less time on anything that's repeated. Right. I saw a couple of examples here that just extending this a little bit.
00:39:25
Speaker
One area that I think will be massively, basically solved in 10 years. I predict this will be solved. Microsoft Word, if it's still a thing, which I mean, it's amazing that it still exists. You have to think that it probably still will be a thing in 10 years.
00:39:38
Speaker
It was a thing in like, what was it? What did they come up with word like 90, 90 or 89? Even in the late eighties, I think. Yeah, I don't know. But I mean, it's been around for forever. Yeah. Or ever. And so you imagine like Microsoft Word will have really robust grammar checks. I mean, it does still now, but to the point, I mean, really robust to the point where the Senate structure suggestions will be basically perfect.
00:40:06
Speaker
where style will be codified. So not just that it's not grammatically incorrect, but that your style is optimal for the purpose that you're trying to do. Now, this brings up a big point, which is the deep point here is that the English language continues to evolve
00:40:36
Speaker
Uh, you know, as all the languages evolve, but the rate at which it's evolving in the written form is slowing and it will come to an almost complete stop at the point where you've codified style into an algorithm. Because if you can define it at that level, just the way like spelling, spelling has completely stopped evolving for all intents and purposes.
00:41:06
Speaker
Spelling, if you think about from old English to middle English to modern English, spelling just massively changed, massively changed of all kinds of words. That evolution has completely stopped. And a lot of it now starts with writing and then dictionaries. And then when the dictionaries are automatically included in the input device,
00:41:34
Speaker
Now there's no even opportunity to miss quote unquote misspell something. Right. Hmm. And so there's no evolution of spelling this is just stops.
00:41:46
Speaker
I guess this plays into your idea of organizing by having common languages, say between automated cars or between computers on the way that they treat information so that it's all standardized. So I have a related
00:42:07
Speaker
I think this is related to your predictions too. So thinking about AI, one of my predictions is applications will be developed exclusively for artificial intelligence interfaces. So I guess to stick with Microsoft Word, I
00:42:28
Speaker
Maybe this is totally off base, but you could develop a version of Microsoft Word that can interface much better with, say, a digital assistant. Say if you had a digital assistant like Siri that also had a visual interface that you could interact with and that could interact with Microsoft Word to create a document and could
00:42:54
Speaker
interface with Excel to create a spreadsheet and all of this stuff so that you could have better integration with your assistant, which I guess is the advantage of being an artificial intelligence is that you can quickly interface and get data in this digital form in a way that a person can't. So that's my prediction. You're going to get apps that are developed specifically for interfacing with artificial intelligence. Maybe it will be in the background, but I think you'll see more of that.
00:43:24
Speaker
You certainly have some of that already with Alexa, right? But I think you'll do that increase greatly with productivity kinds of things. You see the big tech companies all believe this. I mean, they're Google, Apple, Amazon. Right. We've got an assistant. They've all got an assistant that they could think of as just continuing to expand.
00:43:50
Speaker
Right? So everyone wants you to talk into it, right? I think that speech text will be solved in 10 years.
00:43:59
Speaker
That's a prediction. It will be solved. It will work basically perfectly. To the logical extent of which it can be that you could call it perfect, because people say things that aren't really words. Well, as good as a person. As good as a person. As good as a person. As good as a person hearing it, the computer will hear it as well and be able to transcribe it as well as a person could.
00:44:23
Speaker
Yeah, that's, I think we're actually pretty close. I mean, this might be even like two years from now, three years from now, but it's, it's taken longer than I would have predicted in 2010 that by 2020 we would have that. I think most people in the field would have predicted that by 2020, we would have had that in 2010 and we're not, it's harder than we thought. But I've got to say Alexa and Siri and all that 20 years ago, which seemed like magic, right?
00:44:50
Speaker
Yeah. Oh yeah. That's what I'm saying. Yeah, exactly. I'm agreeing. What we have now is so much better than what we had 20 years ago. It was just garbage 20 years ago. And what we have now basically kind of works for a lot of things and you kind of use it a little bit now here and there. Yeah. And 10 years, you could use it if you wanted to everywhere. Now the limitation will just be places where you don't want to be making noise around other people. That's the limitation right at the end of the day. It's just like,
00:45:16
Speaker
The interfaces where speaking won't be the interface are just only places where it just doesn't make sense. Also, typing is fast, actually. You can actually type faster than you can talk, right? Isn't that right? I mean, if you're fast typist, I guess, what, 120 words a minute or so? I think that's a lot. It's a lot. Yeah. I think it's at least as fast, if not faster, to type than to talk.
00:45:44
Speaker
But you can also have a visual kind of interface, too, that presents a lot of information to you, where you can deal with it without regular language. So I think the prediction is a dyad there. Text-to-speech will be perfect in 20 years, as good as a human. And people will still type. People will still type. OK, I'll go with that. I think people will still type.
00:46:16
Speaker
I had something kind of related to this, uh, AI and neuroscience continue to converge. What do I mean by this? So the specific prediction is that AI models will continue to be more related to the way that the brain works or our understanding of the way that the brain works. You remember back to our storyline about, you know, the AI winter and this period of time starting in the nineties when people lost faith
00:46:46
Speaker
in neural networks as a solution for solving real problems. And then, you know, the 2014 and on when we started to see, you know, neural networks and deep learning models, you know, be victorious in all kinds of different contexts for solving real problems with computers.
00:47:09
Speaker
Uh, these are neural, these are, these are systems that are inspired by our understanding of the way the brain works. And I continue to believe that as we understand how the brain works, we will get increasingly better algorithms through that inspiration. That's my prediction. It's a little vague. It's a little vague.
00:47:33
Speaker
No, but I don't think it's vague because I think it really could go both ways. It could be that, you know, and this is what a lot of people had thought, I guess, is that, you know, the brain has essentially nothing to do with neural networks, that there
00:47:52
Speaker
that they're so radically different that you can't really use one to say much about the other. Even though that was their original intent, they were built as these mathematical structures. Turns out they were good at certain kinds of supervised learning, but nothing like the brain.
00:48:10
Speaker
I think your prediction is interesting in that way, that you're really saying that there's going to be more inspiration. We have a lot to learn about how the brain works in teaching us how to create something artificial. Yeah, exactly. And it gets to this point that the brain is really complicated and amazing at how it performs tasks. The human brain is really amazing.
00:48:38
Speaker
And we haven't begun to understand it even a little bit. And all the learning and technology that we've made advances in in chemistry, biology, physics, we're so advanced in some of these areas. We're still babies in our understanding of neuroscience, just babies. Little tiny babies. Little tiny babies.
00:49:06
Speaker
I mean, you get to this question of like supervised learning is an interesting one because with AI, it starts to get really advanced. Building a good AI model depends so much on having well labeled data. I mean, data that is well organized and well labeled. That's right. Yeah.
00:49:31
Speaker
The labeling itself is still absolutely 100% a human endeavor. It has to originate from a concept or a category that a person has. It's a human concept, yeah. What is the origin of that concept or that goal? What is the initiative that produces that? That is the thing that we just have no idea about how to think about.
00:50:00
Speaker
Give an example of that. What do you mean? Well, so I mean, I'm talking about consciousness fundamentally. Right. So you have the idea that you want to build an algorithm that detects, you know, when, you know, the price of potatoes is going to go down so that you can, you know,
00:50:25
Speaker
build your CRISPR business. What was the impetus for that? Where did that idea come from? How did those sets of electrical chemical signals in your brain manifest into this notion or idea that you wanted to do that? And then the experience of that, where does that come from? We don't know. We have no idea.
00:50:55
Speaker
Nope, we don't. So the mystery will be there. The mystery of consciousness will still be there. We won't have solved consciousness in 10 years. That's a bonus. That's a bonus throwaway one, because I guarantee that's true. I think that's a safe bet. That's a safe bet, no.
Cryptocurrency and Tech Industry Shifts
00:51:11
Speaker
All right, let me throw another one out. Totally different topic. So I have as number 10 on my list that it's a prediction about Bitcoin.
00:51:22
Speaker
Whoa. All right. Get your Robin hoods out. Everyone get their trading apps out.
00:51:30
Speaker
I don't have a lot of faith in ... This is not investment advice. No, this is not investment advice. I don't have a lot of faith in Bitcoin as a long-term thing. I know there's diehards and they'll probably take offense at this, but my prediction, to make an interesting prediction, I predict that Bitcoin's going to crash at least to the level where it may get consolidated in some form. I predict it crashes to a pretty low level.
00:51:58
Speaker
some actor buys them all up and they get used for some other corporate purpose. Bitcoin, it's going to be like Disney Bitcoin or something like that. That's my prediction. What about Facebook? Do you think Facebook's going to... Facebook's cryptocurrency?
00:52:20
Speaker
Look, I mean, Mark Zuckerberg is going to be our fearless leader in 10 years. He's going to be the czar of, you know, America, Stan. Oh, I don't want that. I don't have anything against I don't have anything against leaders of tech companies, but I don't think a ruthless dictators.
00:52:47
Speaker
Yeah, I do. I guess now that you say that, I do have something against ruthless dictators. So what's your prediction about Bitcoin? Good question. I don't have one, but I'll speculate. I'll speculate. It's something I have thought about, but I just really, really don't know where it's going. I just have no intuition. It seems like almost a coin toss, whether it'll go up to an insane amount or go down to nothing. Yeah. And I think
00:53:16
Speaker
I think there's two questions that are interrelated, but very, very different in terms of where they're going to go. One is cryptocurrencies and the other is Bitcoin specifically. And then you could have, you know, you could draw a four quadrant thing and say, you know, up, down, you know, for each of those.
00:53:37
Speaker
And all possibilities are there. Cryptocurrency could be huge. Bitcoin could be the winner. Cryptocurrency could be small. All those things are possible. So what's your take? What do you think? Where do the arrows go?
00:53:51
Speaker
Well, I think that Bitcoin itself is nothing special. I don't see anything special about it when it was one of the first ones. And so I think that's the only thing it offers really. That's the only thing it offers. It has some cred because it was the first one. But I think I think the winning. All right. Here's a prediction. The winning cryptocurrency will be backed by something. All right. There you have it.
00:54:19
Speaker
Right. So in other words, like right now, crypto, like Bitcoin's not backed by anything. Right. Which means, and this is not backed by the full faith and credit of Mark Zuckerberg's, you know, seaside ranch, you know, or whatever, you know, like somehow you have to put some something, some collateral behind it. Right. Whether that be like the full faith and credit of the US government or
00:54:44
Speaker
or our stock and, you know, uh, equity in Facebook or, uh, you know, crisper chips or whatever it is, you know, it's gotta be backed up by something. Well, I think that once you've got that, then you've got something, you got something. Uh, if, if somebody in some, in the, the interesting thing about, to me about cryptocurrencies, interesting thing is, is an international and international topics, because when you can,
00:55:14
Speaker
pay somebody in a foreign country using a currency that is not intermediated by the governments of either country, that is a real value. There's clearly value. There's clearly value there. Especially because it's difficult sometimes to create these transactions. There's a lot of barriers put up
00:55:37
Speaker
Here's the problem with that, though, is that that seems like the kind of thing that if you wanted that, you would also want a really stable currency because you're looking to you're looking to reduce transaction costs and keep your money. Right. But the problem with Bitcoin is it's extremely unstable and you can't know from one day to the next what your risk is going to look like from having Bitcoin. So, you know, what you would you know, what a lot of people would do is
00:56:05
Speaker
Buy bitcoins with dollars, trade in bitcoins and then sell bitcoins in dollars, which is not a sustainable system. That's not a good way to make transactions, I think.
00:56:15
Speaker
I mean, it's the same reason why Bitcoin, it's the reason why Bitcoins are popular is because people want to make ton loads of money off of them. So people at the same, the reason people buy Bitcoins is, is the hope that it'll make them tons of money. So they're hoping that it's going to be in high fluctuation. So investors, you know, there's, there's sort of, it's a kind of a catch 22, I guess.
00:56:44
Speaker
People that are pouring money into it are causing high fluctuations and people that want the currency as an actual thing for legitimate reasons would like something that's stable. And I think like you say, you have to have something that backs it. Isn't there some coin that has a backing to it, I forget? I'm sure there is. I don't know.
00:57:05
Speaker
I don't know. I'm sure. I'm sure these business models were not the first people to have thought about. Right. No, no, no. Yeah. This is where we're at the like first stages of thinking about this. But I, I personally don't have I don't have faith in Bitcoin as a long term stable currency. No, I think you point out a really, really important fundamental piece, which is the same thing that you're using as a
00:57:34
Speaker
you know, to speculate on with hope of future gain should not be the same thing that you use to buy your milk. Exactly. Yeah. Or pay your developer or, you know, whatever it is like. That's right. Your currency should be different. Your developer needs to buy milk. Your currency should not be where the risk is. No, exactly. That's not. But I mean, the the the the the ability to I mean, to circumvent, if you will,
00:58:04
Speaker
to transcend, really, international bullshit is profound. I mean, if you start thinking about the way that we're working today already, especially in tech, especially anything that's software-based, hardware-based stuff too, but especially software, it doesn't really matter where you are at all. As long as you speak a common language between the group of people who are talking or working together,
00:58:34
Speaker
Even if that language is like, you know, C plus plus, right? You can work together. And if that creates a huge incentive for people, there's a huge pressure for the work to flow to places where there is an M a relative imbalance between how
00:58:58
Speaker
much things cost and how well educated people are. So in the US, things are expensive and people are well educated relatively, you know, in places like parts of Eastern Europe, for example, are a lot of really well educated people on things are cheap. And so just makes sense for efficient. It's just sort of like a more efficient market for for the barriers to that are are the corrupt governments in between.
00:59:28
Speaker
Part of it's just straight corruption and part of it's vested interests and not having free trade because you want to whatever protect your industries. But that currency is a big piece of it. And a payment system, so trying to run a credit card in a foreign country can be a big problem if you're not actually there yourself.
00:59:50
Speaker
Um, and if you had a system for transacting, I mean, that's Bitcoin does that now. You can do that now with Bitcoin, but your point, the reason why it's not more popular for that is that it is unstable. Yeah. So, uh, my prediction specifically to Bitcoin, I guess that I don't, I wouldn't say anything about any other blockchain technology, maybe something else will pop up, but I say Bitcoin, Bitcoin's going to fall.
01:00:19
Speaker
Okay. Bitcoin is going to fall. All you guys out there with Bitcoin, Roth is saying sell now. Or sell before 2030 anyway. Sometime between now and 2030. Whenever you feel it's the best time to sell before 2030. That's a bold prediction. Okay.
01:00:38
Speaker
What else do we have? We have. Okay. Let's see. I, all right. I'm going to bring things back up in terms of positivity and say, I think there is going to be a resurgency in techno optimism.
01:00:51
Speaker
Oh. Yeah. So all of the hate people are feeling towards Facebook and Google and some of that stuff. Right. I don't think Facebook's going, people are going to like Facebook more in the future. I know I wouldn't predict that people are going to like Facebook more in the future. I don't necessarily think people are going to leave Facebook. I think it's just going to continue to be one of those things that's there and you hate it.
01:01:15
Speaker
So maybe some creative destruction, there'll be some new stuff that will solve some real problems that people actually want to have solved and they actually make them feel better. And this kind of relates to one of my other predictions, which that technology will transform mental health care. I think this is one of the areas where, you know, there's a real opportunity to
01:01:39
Speaker
use technology to help people by delivering things like behavioral health care, therapy. You have all these apps now for guided meditation and things like that. I think that type of technology will move forward in advance. We'll see some impact. We'll see some impact. Yeah, that's a prediction. But the techno-optimism piece in particular is
01:02:05
Speaker
you know, a return to a group of people, a significant group of people really believing that they can use technology to make the world better and promoting that strongly and getting some real buy-in and having structures built
01:02:27
Speaker
that support that, that aren't necessarily only just for-profit venture-backed firms, but are other structures that maybe they're cooperatives, maybe they're not-for-profits, whatever they may be, that support people really trying to use technology to help people in deep ways, not just get your toaster faster.
01:02:55
Speaker
with a drone from Amazon. But in some deep way, really making the world a better place. OK, so return of techno. So that's just sort of the temperature of the mood in Silicon Valley, I guess, comes back. Well, I don't think it's necessarily going to come from Silicon Valley either. Maybe not. Yeah, maybe it comes from somewhere totally different. I think that's another prediction too, is that increasingly Silicon Valley as a technology hub is
01:03:27
Speaker
Silicon Valley is now and will increasingly become the center for money and capital for development of new technologies, but not necessarily and increasingly less so the center of real innovation. So the way that New York and London are the financial market centers or capitals of the world in terms of just like financial transactions and banks,
01:03:56
Speaker
Silicon Valley from San Jose to San Francisco will basically become the banking center for technology and less so the actual
01:04:08
Speaker
developers of new innovations. Yeah, and I guess this fits with your prediction about having a common language or common currency so that you can collaborate on this stuff across the globe so that it's easier to do a project in a number of different places at once.
01:04:29
Speaker
Yeah, great ideas for new technologies are going to be coming from everywhere. We already see this. Yeah, open. So collaborative, open ways of doing these kinds of things. What else? What do you got?
01:04:41
Speaker
All right, so I have one more nerdy one specific to academia.
Academic Publishing and Cancer Treatment Predictions
01:04:48
Speaker
So I'm thinking about, so there's a lot of change going on in publishing in academia, or at least people talking about change a lot in academia for journals for publishing academic research.
01:05:04
Speaker
One of the things that I think is going to happen or I'd like to see happen, predict it'll happen, is that we're going to get a sort of comprehensive academic way of doing peer review in journals where it benefits the academic system as a whole and not publishers so that it can be done
01:05:28
Speaker
Fairly, people that are doing peer reviews aren't overburdened and they get compensated for it some way. This is one of the problems with peer review systems recently is that there's lots of demand for reviewers, but nobody really wants to do it. Yeah, I've got so many journals and so many papers being written and every paper needs two or three reviewers. Yeah. And so for every paper written, there's two or three or four as many
01:05:59
Speaker
people that need to actually read it before it gets, plus the editor. And the depth of their comments are going to make a big impact on how good the science is going to be. So if you kind of brush it off, you're degrading science in a way. So hopefully there's a way to patch this system up. And this would be an optimistic thing, too, is that the academic community gets together and figures out a common system that may take use,
01:06:29
Speaker
some use of AI so that this can be done in an efficient way. People may have reputation scores and
01:06:39
Speaker
peer reviewing becomes an integrated part of publishing and it all becomes part of one kind of system that again is for academia and not necessarily for publishers and it means more open science would be available to people so that research results would be published in a totally open access form and it would be
01:07:03
Speaker
in databases so that you could compare research much better too. So kind of consolidating and getting stuff together so that research is searchable and sort of streamlined. That's what I think the whole area of science is ripe for and that's what I predict. Yeah, no, I hear you. There's a lot to unpack there actually because there's a bunch of different pieces to that.
01:07:31
Speaker
I mean, the big problems you sort of point to is like two whole sets of things, but fundamentally the problem you're sort of pointing to is that there is these for-profit publishers that are providing the service of aggregating and also credentialing the work of academics. Meanwhile, academics don't get paid that much and
01:07:59
Speaker
The research is paid for by taxpayers, fundamentally. And so taxpayers, if they want to read the articles, really can't unless they're at a university. Universities have to pay too much. It's it's a drag. And then, you know, you don't get really any kind of benefit or credit for reviewing these papers. Yeah. So it's kind of it's kind of just like a it's kind of a lame system in a way. I mean, it basically works and sort of why it continues. But it's sort of unfair and kind of lame.
01:08:29
Speaker
And there are some, I mean, there are journals who are taking a stab at this and, you know, small bits, you know, small groups that are trying to do something to reform things. But I think it'd be nice to see a more comprehensive system that works for everybody. Yeah. I mean, you can see one of the things with this is just the open access topic. I mean, you can see this already where, you know, you've got like things like SciHub where, you know, I've heard
01:08:58
Speaker
you can access journals that are not open source pretty efficiently and easily, just with like, you know, one redirect on your URL, for example. And then I thought I would advocate doing that or have done that, but I've heard that you know, the institute academia is generally friendly to those kinds of things.
01:09:24
Speaker
Academia is friendly to that. Now, the publishers are not because the publishers, you know, that's their business. They have to make money, too, and they have to support their business. So, right. So, I mean, I think as the cost of actually producing the publications goes to zero, basically. That's right. Yeah. You know, then then it becomes the impetus of like, all right, how do we work together, guys? Like, let's get together on this. Let's figure this out.
01:09:53
Speaker
We don't need a publisher. I mean, the only reason why nature is still
01:09:59
Speaker
able to be the big business that it is, is that it's got the name, it's got the brand. That's the only reason. The problem with academics is that the idea of brand building is just anathema to the whole way people get along in academia. Because what you need to do is you need to build, if you wanted an academically oriented, for academics, by academics, that was open source,
01:10:27
Speaker
publication, I'm sure these exist, but I don't know about them, which is the whole point. People would have to get together and get along in a way that they just don't today.
01:10:41
Speaker
Do you think that will happen? Do you think people will get it together in that way? Or do you think, where would that come from? Is that going to come from? That's my prediction. That's my prediction is that it will happen. And I think it'll come from academics who choose to spend their time working on this rather than research. It's almost a crusade kind of thing. It's smart people working together that have access to lots of other smart people will figure out a system for this.
01:11:11
Speaker
I believe that, I believe that, you know, it seems like that would be a fun project to work on the, uh, and I believe that there are enough people will do that. That's a good prediction. What else do you have left? Okay. So it seems like we've got two others. Um, one we can probably just hit real quick, which is that we actually had different opinions on, which is the, uh, prospective on prognosis for cures for major neurodegenerative diseases.
01:11:42
Speaker
And I believe this is the one where you are pretty negative. I believe in a brighter future and I think you're just looking at all the negative possibilities.
01:11:55
Speaker
Yeah, I mean, we've just seen so many failures, especially in Alzheimer's disease and Parkinson's disease. I don't know. This is tough. I don't know what I don't know what in me is predicting this because 10 years probably isn't a lot of time. And there's there've been plenty of 10 years since we've started having problems with them.
01:12:13
Speaker
I just want to make one optimistic prediction that we will cure. We will find a cure for one major neurodegenerative disease. That would be awesome. Lou Gehrig's or multiple sclerosis or something like that. One of the predictions that I made is actually not even really even a very bold prediction that's related to this in terms of curing diseases is that cancer treatments
01:12:42
Speaker
will be massively improved in 10 years, like massively improved. Especially they've, they've improved so much in the last 10 years. I think it's unbelievable. The leaps forward have just been incredible. And there's a whole conversation that I think probably better not for this wrap up to get into too deeply, but there's a whole conversation of why cancer treatment is relatively easier than treating neurodegenerative diseases. Um, which is, I don't actually know the answer.
01:13:10
Speaker
That's a good potential topic. It is a good potential topic because it does seem to be the case that we're making tons of progress in cancer and not in these neurodegenerative diseases. And why is that? I don't know. Maybe we'll find out. Maybe it'll change. Maybe it'll just be that inflection point. There's been just a few little things with cancer that have made those inflection points. Maybe, yeah, I guess that's your prediction. We'll get one of those for neurodegenerative diseases. That would be awesome. That would be huge. That would be huge.
01:13:39
Speaker
All right, the last one, and last but not least. Your predictions? Of my predictions is the Robopocalypse. The Robopocalypse. The Robopocalypse.
01:13:52
Speaker
All right, so flesh this out. As we know, there are lots of ways the Robopocalypse will happen. So you can be non-specific, you could just say a Robopocalypse will happen. Or do you want to be more specific? Well, let's put it out there. I mean, I'll say.
01:14:12
Speaker
And I'm just putting this one out there. This is one of those ones where, actually, if you really were being pedantic, you could say, well, Joe, if the Robopocalypse hits, some of your other predictions, you can't be sure. Yeah, exactly. I was thinking that. I was thinking that. This kind of goes above all of the rest of your predictions. You should have had that. No. And so each one is independent. Each prediction is independent. I'm not saying all of these things are going to happen. OK. I'm making a prediction for each one.
01:14:39
Speaker
Each one is an independent prediction. And I'm not assigning any probabilities to them. I'm just saying, I believe, more likely than not, 50.0000001%, this is gonna happen. Though neither of us could possibly know these things, we still have some belief in them anyway. That's right, exactly. And so I don't think it's not 100% prediction, it's not even a 90%. This is a 50.00001% prediction that the Robopocalypse will happen in the next 10 years.
01:15:10
Speaker
probably towards the end. And it's going to be the kind of thing where basically it's not like robots are going to come in and really start just shooting you with blazers. So get away from that idea. That's right. People put that out of your minds.
01:15:37
Speaker
Don't worry about the lasers. The lasers are not the problem. All right, so look at the predictions. There's a stack of predictions in here because laser weapons, handheld laser weapons will not be a thing in 10 years. Okay. No. Subprediction A. Yeah, subprediction A. No laser, handheld laser weapons in 10 years. Commonly available. So the robots aren't going to be walking around with lasers.
01:16:06
Speaker
Okay, so they're not gonna shoot us. What are they gonna do? Prediction number two. Well, they're not gonna shoot us with lasers. Prediction number two, they won't be walking around at all. This is not how this goes. The ways in which technology is going to try to successfully copy humans will include copying our brains and the way that our brains process information. That will not include the way that we walk, because the way we walk is fucking dumb. Okay.
01:16:36
Speaker
Right? It's super inefficient. They spent so much time trying to get robots to walk on two legs, which is dumb. Dumb. You don't have to. If you didn't have to do it that way, in any given context, you would totally not do it that way. Okay. Right? You could have a drone. You could have been flying around untethered from the ground entirely. Okay. Right? So why would you be walking? So no walking around shooting you like
01:17:03
Speaker
fucking terminator type thing, right? That's not what it's gonna be. What it's gonna be is you're gonna have all these interconnected systems that I was talking about being net benefit and important, like the roads, like the financial system, and all of these things are gonna be networked, and at some point,
01:17:24
Speaker
Some A.I. will get it in its A.I. head. Not that it will necessarily even have that. Not that it has a head. Doesn't have a head, but it is little processor that it's going to fuck with it. It's just going to bring it. It's going to burn it all down because for whatever reason, it's got that imperative. It doesn't even have it doesn't. You don't need to presuppose the concept of wanting to do that or like any kind of malice or any of that. It's just for whatever reason.
01:17:54
Speaker
That's going to be its next goal. There's an AI that has a goal to just burn it all down. And it's going to make a significant amount of progress in that direction. Like shit is going to get screeched to a halt. Like your farm equipment, your networked farm equipment autonomous is going to like screech to a halt. Highways are going to screech to a halt.
01:18:14
Speaker
And this is going to be a problem. People are going to die. It's going to be ugly. Not everyone's going to die. This is not going to be the end of the world apocalypse. This is going to be like a minor apocalypse. It's going to be the warning shot across the bow before everybody starts trashing their computers and goes back to agrarian societies.
01:18:37
Speaker
But this is the canary in the coal mine thing. This is like worse than 9-11, but not as bad as the Black Death. Somewhere in between those. Somewhere between 9-11 and the Black Death. Somewhere between 2,000 deaths and a third of humanity.
01:18:58
Speaker
Okay. That's a, that's, I mean, it's a very specific error bars on there. It's a very specific criterion. Okay. And so your, your, your prediction is that the Robopocalypse in that form will happen. My prediction is a very simple one in that that will not happen. So one of us will be right. You took the other side of the bet. I like that. That's good. That's good. That's, that's fair and, and, and, and healthy. So shall we say a thousand Bitcoins?
01:19:31
Speaker
All right. Well, all right. We should we should buy them now because who knows what the fuck they're going to be like, you know, in 10 years. Yeah. Well, maybe that's the whole bet. Is that because you think it's going to go down. I think it's going to go down. I'm not going to buy them now. Yes, I'm not worried about.
01:19:46
Speaker
You're not buying them now anyway. You don't care if you lose the bet or win the bet. You win the bet. Great. It's nothing. You lose. Who cares? Fair enough. Fair enough. Well, I think that seems like maybe a good place to wrap it up now that we've gotten to the Robopocalypse part of the show. I think I've gotten my main ideas out there for future generations to evaluate. So get out your red string. Get out your push pins.
01:20:16
Speaker
You know, type these things out, get them, get them printed out, put them on a board, put them on a map, you know, figure out, read the tea leaves, figure out like what's what, you know, this, this is prophecy here. You know, you really gotta take this stuff seriously. Well, we just, well, we just broke down here. And then afterwards, put it in a time capsule. That's right. Bury it in your backyard. We'll see where we are in 10 years. All right. Well, I think that's it for our show today. All right. Thanks everyone. And we'll talk to you soon.
01:20:46
Speaker
Talk to you in 2020.