In today's episode, I talk with one of the most influential voices in technology in the last 20 years - Kevin Kelly. Kevin is the author of "What Technology Wants" and "The Inevitable", co-founded Wired magazine, and is now leading the charge of optimism as it relates to the future. Today's episode is sponsored by Rollbar. With Rollbar, you get the context, insights and control you need to find and fix bugs faster. Rollbar is offering Developer Tea listeners the Bootstrap Plan, free for 90 days (300,000 errors tracked for free)! Head over to rollbar.com/developertea now for the free 90 day offer.
In today's episode, I talk with one of the most influential voices in technology in the last 20 years - Kevin Kelly. Kevin is the author of "What Technology Wants" and "The Inevitable", co-founded Wired magazine, and is now leading the charge of optimism as it relates to the future.
Today's episode is sponsored by Rollbar. With Rollbar, you get the context, insights and control you need to find and fix bugs faster. Rollbar is offering Developer Tea listeners the Bootstrap Plan, free for 90 days (300,000 errors tracked for free)! Head over to rollbar.com/developertea now for the free 90 day offer!
I want you to take a second and ask yourself what your job title is. And I don't want to use the terms developer or strategist. I want you to think about what your real job is. What value are you providing? And in today's episode, we're going to talk about how this is changing. We're talking with editor and author Kevin Kelly. Kevin wrote What Technology Wants, and more recently he wrote The Inevitable. Kevin is also the senior Maverick editor at Wired, which he co-founded in 1993. This is the second part of my interview with Kevin, by the way. Go and check out the first part if you missed it. You can find it at spec.fm. And of course, if you're subscribed in whatever podcasting app you use, it should be the one right below this. Or above this one, however you have it laid out. But Kevin is a voice of reason, and he's also a voice of optimism when it comes to the future of technology. And the future of technology is going to look, well, it's going to echo very similar things from the past. Some of our job titles are going to change. Some of the things that we do on a day-to-day basis to create value in an economy, those are going to change as well. And we're going to talk about that in today's episode. I'm Kevin. I'm Kevin. I'm excited to be joined by Kevin. Make sure you subscribe in whatever podcasting app you use while you're listening to this episode if you don't want to miss out on future episodes. Let's get into the interview with Kevin Kelly. I have this struggle of telling people what I do. And it's already that way, right? We're already beginning this kind of strange path of brand new jobs that, you know, my parents didn't even have in their perspective when they were my age. And continuously, that's becoming more and more a thing. And obviously, you know, before 2007 or so, somebody like a social media strategist, nobody even knew what that meant, right? And some of the fundamental concepts are still the same. You have to understand communication. You have to understand, you know, one-to-many or many-to-many or whatever it is that you need to understand. But those titles and the specifics of the job, they become new, constantly new versions. And it's so interesting to hear that kind of wrap-up that ultimately becomes, let's find ways to hire new technology. That's kind of what it is, right? Exactly, right. So, yeah, I'm not really worried. I'm not that worried as many people are about employment and automation because I think, like you said, we will invent entirely new job careers, titles. We can't even think of right now, you know, like, I don't know, artificial intelligence strategist, right? I was like, there's somebody or, you know, like an AI whisperer, somebody who's really good at understanding how AIs work and their AI repair person or AI psychiatrist. You know, there's just so many new niches that are going to come along. At the same time, they may have evolution, that are very hard to to imagine and they seem kind of ridiculous to us as as you were saying that most web designer you know uh mortgage broker these these wouldn't even make sense to the farmers 150 years ago whose jobs have have all gone um and so i i think we're not gonna these new jobs aren't gonna make sense to us now yeah i think uh you mentioned the uh the the web designer or or rather a ai whisperer job and i think this is actually going to um the way that this will will affect us earliest and you cross check me again you wrote the book on this but um i think this is going to begin by web developers kind of the people hiring web developers or software developers uh adding new bullet points to that requirements list right and saying okay well if you're going to be a software developer here then yes you need to know java and x y and z but you also need to have experience with machine learning or you also need to have experience with this you know whatever ai platform api thing that that that is out in the wild um i think that's kind of the start of that because you know as we saw with software developer titles in the beginning it's software developer because there's really only three languages right there's assembly and c and and you know evolution evolution evolution evolution evolution evolution evolution evolution you know, whatever other thing that existed. And then it continued to branch. It continued to grow and expand. And as it expanded, each of those individual areas got large enough to justify a person that is solely dedicated to that thing, right? And so now we have people who are even subdivided inside of a given programming language or subdivided inside of a given tool set that are really focused on one particular aspect of that software development process, whereas previously it was really all one title. I think that's going to continue that direction. Right. I think so too. So you talk about AI and you mentioned a few times this term bots. And because I've read your material, I know what you mean by this. I think some people listening may be envisioning the Boston Dynamics robots. You know, coming in and being cashiers. I want to kind of correct that perspective and talk about this concept you use the word smartness to describe or or cognifying cognition to describe AI. Can you kind of walk out what a cashier bot would look like? Yeah. So the main concept I think is important to put out is the concept of AI. Yeah. And I think that can begin or be done at the beginning with a very simple thing of just talking about AI in the plural. So it's AIs. That what we're going to basically invent is a whole zoo of different types of thinking, different types of minds, different types of artificial minds. And I use the word bots to mean both AIs, which don't have a body and robots, which do have a body. So bots for me includes AI chatbot. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. Yeah. that the image that you want to have your mind is of many many different species of thinking and some of these are just types of smartness that don't have consciousness they they're maybe they're kind of like vegetal vegetable level they're they're smart but they don't have very many dimensions your calculator is smart in their rhythm ticket smarter than you or an arithmetic and you know the GPS navigation is really smart and spatial navigation but it doesn't have anything else but we will also make more complicated and complex varieties and so it'll be like you know like a whole ecosystem of different types and some may have very large amounts of consciousness and maybe they aren't so smart or there will be you know a a! that are extremely perceptive or you have great perception there may be a little bit of of language recognition and they've got you know a little bit of spatial but they're their memory short whatever so so the idea is is that there are many many many different types of these species of thinking and there's some set of primitive elements of cognition which were in the process of identifying and will invent more of them that can be recombined and remixed in many different ways and that each of these will be engineered to specific uses and the ones that are in a kind of a car driving may not want to be conscious we may find that it's a total distraction to have consciousness in a car because that's what we have and we're distracted and so no you you you these are just some of the things that we're bringing together these are conscious free drivers and then they're other places were were you you know may be someone some bot that's making mortgage decisions or something you want to have some sense of empathy with people may may may may may may may may may may may may may may may may may may may may consciousness there um and i uh so it's plural there's ais and there'll be thousands of different types yeah and and what's so interesting about this concept to me is the idea that you know that we're trying to replicate uh some human form is really uh short-sighted in in that there's so much more that we can do if we remove certain uh limitations that the human can't remove right um so so and and you mentioned this i believe in your south by southwest uh talk um but you you discuss this concept that okay well the thinking portion of the human or the learning process is really the part that matters and and the thing that we want to utilize uh is is that or or the thing that we want to mirror perhaps is is the learning process but not the uh the humanity side of it right because you know a human um has quite literally physical limitations that we may not want to impose on uh let's say alexa for example right um very very interesting opportunities that begin to show up when we say okay no we don't want to make this more human we just want to take the good part and uh and then lean on the things that the technology can do that a human cannot do the things that the technology can do better than a human could do right the the other aspect is is that um we don't need to make humans because they're they're pretty easy to make right now and um for me the chief benefit of ais is this because they think differently than us and that there are certain problems like in science or in the world that we're not able to solve that are so going to be so difficult maybe quantum gravity whatever it is that that our own intelligence is alone working alone may not be sufficient to solve us so we have to invent other kinds of thinking it's not that we want them smarter than humans because i think you know like smarter than humans is probably still going in the same direction that we're going you want something that's coming very different approach so you want you want a different type of thinking that um would help us solve some of these problems so we're going to solve in a kind of a two-step thing or first invent another kind of thinking that together working with us can can solve that so i think um it's it's um when we're trying to be innovative and and and uh thinking different that uh it's actually very hard to do thinking different it's very hard to do when you're connected to everyone else all the time when seven billion people are connected continuously day and night there will be groupthink there will be it will become really difficult to come up with a truly different idea um and i think ai can actually help in that assignment of even spurring us to keep thinking different and working with them to together to think differently when we have this massive super organism of all the humans together in this kind of converging global culture um it's going to be a challenge to keep coming up with wholly different ways of of of of a problem and i think the differences of ai the non-human aspects of them will help us do that yeah and in a way it could assist with our creativity and the inefficient things that we do need to continue with uh those are the things that are truly unique right so the future of you know software programmers i think is going to be there going to be a lot of ai going on where you're going to be working with some kind of a system that may be proposed to you different um solutions you know whatever it is uh i don't know how you call it you know codes systems loops all this kind of stuff it may you may work with it and it's and it's uh um going to be proposing uh things as a colleague might um or completing things that are going to be proposed to you and bringing together these human players and bringing together these human players and bringing together these human players and bringing together these human players and bringing together these and bringing together these human players and bringing together these human players and bringing together these human players and bringing together these human players and bringing together these human together these human players and bringing together these human players and bringing together these human together these human players and bringing together these human players and bringing together these human players together these human players and bringing together these human players and bringing together these human players together these human players and bringing together these human players and bringing together these human players together these human players and bringing together these human players and bringing together these human players together these human players and bringing together these human players together these human players team of human plus AI working on a problem. And some people will do that better than others. But then some people will be involved in making these AIs that are, you know, more creative in a certain direction than others. And you, you know, might come to favor, like, I really like working with, you know, Prospect over here because Prospect, you know, is a good complement to the way I think. And your fellow colleague is really, you know, going to work with this other AI because it suits her approach better. And I think working with the bots is going to be how we're going to end up. It's not that they're going to replace everything we do. I think we're going to end up working as a team. We're going to take a quick sponsor break and talk about... That's today's sponsor, Rollbar. And we'll get right back to the interview with Kevin Kelly. Today's episode is sponsored by Rollbar. Rollbar is an excellent service for those of you who write software on a daily basis and you have people that are actually using your software. That's going to be most of the people who are listening to this podcast. That software is going to have bugs. I hate to break it to you. You're going to have bugs at some point. And in fact, you're going to have bugs that you don't find until after they've shipped. To production. Now, the problem is tracking these bugs down can be expensive and it can be very difficult. In fact, it can also be costly because sometimes you're even relying on your users to tell you about those bugs. And that's a worst case scenario because by that point, you probably already lost money. You may have even lost that user entirely. On top of that, you're going to end up going and digging through your logs, writing extra code to track. You're going to have to try to do some of the things that Rollbar is actually going to do for you. And that's exactly what Rollbar has specialized in. They're going to help you track your errors better than you could in your own custom way. That's because Rollbar has thought of pretty much everything. They integrate with all of your existing services. For example, you can send error messages to email. Of course, you can send it to email, but you can also push it to Slack or you could push it to Trello. You can push it to pretty much any service. You can imagine really the list is very long. We're not going to cover the whole thing here. But imagine integrating all of the errors in your production applications directly into the channels that you're already looking at when you're working on those projects. That's what Rollbar is going to do for you. We use it at Whiteboard. I highly recommend it. Go and check out what Rollbar has to offer. Rollbar.com slash developer T. That'll get you started on the bootstrap plan for free. Free. That's zero dollars for 90 days. You can get started tracking your errors today for free for 90 days. Rollbar.com slash developer T. Thanks again to Rollbar for sponsoring today's episode of developer T. Yeah. Yeah. Collaborating with both other humans and other bots in that the word you use in the book is beginning this global kind of system together. Really a very exciting prospect. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. Right. They create the bad. And really, that's not the picture of the future that we're looking for here. Instead, it's connecting humans better together and connecting humans with intelligence that can assist them. I actually have lightly coined this term because I'm not a futurist. I'm not writing books about this. But this term of assistive intelligence. Assistive or assisted? Assistive. And what do you mean by that? Effectively, the idea that the intelligence of that thing is pointed at providing assistance to a human. Yeah. Specifically, rather than solving something on their own, it's solving something only when interacting with another person. Yeah. And there are probably going to be a couple of different modes that works. One is where they're proposing. It's like brainstorming. Yeah. Where they are kind of brainstorming with you on these things. And you may be kind of doing the curation. Like a caddy. Like a what? Like a caddy almost. Yeah, yeah. Exactly right. Why don't you try this? Or why don't you try that? Or how about this? Or wow, this is a crazy idea. And then you're kind of working with that. And then the other way they could do it is like an assistant where they're kind of finishing some of the details that you work with where you kind of do a broad outline. And they do that. And there also might be ways in which there's more of a conversation about, say, like the structure of something where you are in a conversation about, well, I think we should do this. And it's like, well, what about, you know, or do you remember the other thing is, well, what about, like the thing about AIs is they can have a complete mastery. Yeah. It's like, well, you know, when Samuel Johnson did that in 1870, it didn't go so good or whatever. And so there could be this historical viewpoint. It didn't have to, you know, I mean, I can obviously in programming, there's going to be other more recent examples. But they could say, you know, over, you know, Tim over in Trinex, he, that loop worked. But the problem with that loop was. This X and Y. And that kind of a comprehensive command of what had been done would be also make you smarter as well. So I think we could kind of imagine a bunch of different ways in which that assistive AI would work. Just even just in your own little industry of, you know, coding and programming. It would, you know. And I would imagine that could be one of the first industries that would use the assistive AI. Almost certainly. Yeah. And we like to build our tools for ourselves. So why would, other than maybe, you know, monetary or commercial reasons that are compelling. Are you aware of anybody who's doing that now? That's a good question. I know that some, there are some things like, for example, the Google drawing tools. These are things that use machine learning to try to figure out what you're, the shapes you're trying to draw. There are some layout tools that as you begin to create an interface, I can't quite remember exactly what they are. They're still very much in their infancy. But they aren't, they're not conversational. They're not, the cognizance of these things is not visible. It doesn't feel like AI. It feels more like a tool, honestly. I know that Facebook has claimed that they're using. Some of their AI to design other AI. And I don't know exactly what that means translated into an operational practical way. Yeah. But that is, that is a claim. Yeah. There's, there's some, there are some groups that are working on finding, you know, consistent algorithms that as you're writing your code, the, the, the machine is trying to figure out, okay, where are the weak spots most likely to be? Yeah. There's some. It's like grammar checking. It's like, it's like we're checking your grammar as you go along. More like structural. Right. Grammar is structure. Testing. Yeah. Yeah. Yeah. So very powerful possibilities, obviously in that arena. And, you know, it's very interesting to know as a developer, some of the pieces of the puzzle that make this stuff tick. And it's, and it's exciting and, and really, I know, I know we're on the very beginning of this bell curve. For, for AI specifically in machine learning and those kinds of things. And it is very exciting. And the future is, is looking, you know, you, you discuss this idea that AI is going to be a service that is offered, you know, in large and that's already happening. That's immediately, it started happening already. We, we have image recognition technology that's available through an API. You hook it up and basically give it an image and it'll tell you what's in that image with, with level. Yeah. Yeah. Yeah. Yeah. You have levels of confidence. You have things like video monitoring or checking the video to see what items are in that video. You, you can find locations and all kinds of things. And they are available to developers today for, for pennies, you know, per image already. And it's only going to increase that level of, of kind of contextual AI. Yeah. The best. To complete the, the actual thought for the benefit of the readers who haven't seen the book. The idea was, was that. Because the industrial revolution made artificial power beyond the natural power of muscles of a human or an animal. And we could extend our reach with making things with artificial power to build, you know, skyscrapers or railways across continents and factories churning out miles of, of cloth all because of artificial power. That power was distributed on a grid and it became a commodity. so that anybody could buy as much artificial power as they wanted or needed and to do whatever they wanted and to invent new ways, you know, electric pumps, harnessing that artificial power. And now we're going to do the same thing with artificial intelligence, which certain varieties of that will be delivered on the grid called the cloud to anybody who wants to buy as much AI as you want or need. You don't have to generate it yourself. You can just purchase, you know, TensorFlow, whatever, or go to Microsoft or IBM, and it'll become a commodity. It'll become a utility, maybe is a better word, that's available to anybody to, you know, plug and play. Yeah, it's so exciting because, you know, and one of my questions that I had for you in my – I have a very long list of questions, certainly didn't get to all of them today, but, you know, we could have this conversation for – or days on end probably, but one of the questions that I had for you regarding this specific subject, you know, you talk about 30 years, but for developers who are listening to this today, what does 2018 look like? What can we do to begin to bring this optimistic, you know, I really think developers are kind of at the ground floor of this, as we already discussed. What can we do? What can we do to start thinking, at least, towards this optimistic view of the future? You know, I think we kind of hinted at it. I think start to tinker with these new tools. There are no AI experts, given where we'll be in 30 years. I mean, there are some highly paid people now who know more than other people. There's a lot of money being diverted into. AI, just to take one example. But there are no AI experts compared to where we'll be in 30 years. We know nothing, really. We're just at the first hour, the first day of figuring out the business. So you're not late. You have a chance to become that expert. And it's going to be, you know, like tinkering around with the stuff that some of the biggest breakthroughs are going to be found. It's very similar to the state of – In the Delphi Revolution, we had all these amateurs with their – fooling around with electricity. Just – I mean, we forget that people had no idea what electricity was in the beginning. They didn't know natural force. They didn't have an idea of electrons. There was this amazing thing, and people are tinkering, figuring it out. And we're in the same stage with intelligence. We really don't know what intelligence is. And people figure – tinker around with artificial intelligence. And artificial intelligence will be one of the ways that we're going to figure out this. And it's – as I said, you can buy some now cheaply, and you can start to mess around with it and do stuff because it can be done. And that is the – I think that's where all the big breakthroughs are going to be found. The easy-hanging fruit are just sitting there waiting for someone to come along. And people – the gray beards and 20 – Mm-hmm. Mm-hmm. Mm-hmm. And 47 will look back and say, oh, my gosh, I wish I could have been alive and young in 2017 when nobody knew anything. And all these things were just waiting to be grabbed. And so it's – there's no better time ever in the history of the past because the tools exist now. And compared to what we're going to future, this is really the best time ever to make something happen. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. Mm-hmm. It should be an empowering thing, and I'm really excited for the future. I'm really excited for seeing that 2047 moment come to life and recognizing, hey, some of these people actually did take advantage of that opportunity. Kevin, thank you so much for joining me on the show. Yeah. I really enjoyed it. Thanks for having me and for the great questions. Absolutely. And, of course, people can buy The Inevitable pretty much anywhere, right? In fact, I just posted a picture of it. I found it. It was found in Costco at the discount book table, the new paperback version next to the Stephen King novel. So, yeah, anywhere, I think, at this point. Yeah, you're right. Excellent. Yeah. Thank you again, Kevin. Okay. Bye-bye. Thank you so much for listening to the interview with Kevin Kelly. I hope this has challenged your thinking and excited you about the future, but also created a roadmap in front of you of a lot of work, a lot of exciting work that you and I get to engage in on a daily basis. Thank you again to Kevin for joining me on Developer Tea. This is the second part of my interview with Kevin, by the way. Go and check out the first part if you missed it. You can find it at spec.fm. And, of course, if you're subscribed in whatever podcasting app you use, it should be. The one right below this one or above this one, however you have it laid out. But thank you so much for listening. Thank you again to Rollbar for sponsoring today's episode of Developer Tea. Of course, you can get started with the bootstrap plan for free for 90 days by going to rollbar.com slash developer tea. And you can get started tracking your errors in any production environment. Go and check it out. Rollbar.com slash developer tea. Thank you so much for listening. And until next time, enjoy your tea. See you next time. Thank you.