 So, I am so excited about our next talk, which will be by Ronald. Ronald has a wonderful story about how he got interested in technology. He is based in Italy right now and in Sicily, an amazing place, where he works remotely at the digital agency Deeson. Ronald actually has a PhD and studied artificial intelligence. And then when he moved to Italy, started getting involved with web design through WordPress and Drew Paul. And now his work has somewhat come full circle because he is looking at these artificial technologies inside of web development. So let's give a warm applause and welcome to Ronald. I'm going to have to start with an apology. I had a cold, pretty bad cold, and I have a weird, very deep voice. This is not my normal voice. And then it sometimes turns into a 12-year-old voice, so I can go really high. So we'll see how this goes. So yeah, I work for Deeson, I'm the technical strategy director there. Before I start, I'll say Deeson is hiring. If you're into UX, we're looking for a UX director, WordPress developers, solution architects and so on, just come talk to me after this talk. Okay, so what are we going to do today? I'm going to try and convince you about two things. That AI, artificial intelligence, is going to change the way we develop websites and that this is going to happen quickly. That's kind of the important bit. And then I'm going to talk about, well, what do we do about that? Now before I go on, how many of you are web developers, like build sites day in and day out? Great. That's relevant to what we're going to be doing in a few years. So how's the talk structured? We're going to talk a bit about what AI actually is. Then look at technological progress from a slightly abstract standpoint, kind of how technology progresses in general. And that's important to understand the consequences. We'll talk about how web development is changing and then, yeah, what should we do next? So what is AI? It's not Skynet. It's not the Terminator. And I think this is important because when people mention AI, when I finished my studies and people would ask me, what did you do as the artificial intelligence is saying, oh, you're building a Terminator or something. No, it's kind of more mundane and worse at the same time. It really is going to change things. And I'm going to give you a view of AI that is not philosophical or anything like that. It's not about consciousness, but it's a view that helps us think about how we build things. And it comes from something called agent-based software development. So how do you build software that has intelligent programs within it? It's quite simple. So we'll just step through it. So what is an agent? An agent is anything that can perceive the environment through sensors and can modify that environment through effectors, pretty simple. Think of a thermostat. It perceives the temperature of the environment. And then it switches the heating on and off to change that environment through effectors. The first level in agent-based software development is something called reactive agents. And they're very silly and they're very simple. And I'm going to be using chatbots as an example here because it's kind of the latest thing I'm playing with. How many know what chatbots are? Okay, cool. So yeah, chatbots is kind of programs that live within something like Messenger or Slack and you can talk to them and they respond and they do things for you and so on. So a reactive agent chatbot would do something like just sit there and it's only going to react once you talk to it. So if you say, hey, how are you doing? It's going to reply, I'm doing good. How are you doing? It doesn't, it's not trying to achieve anything. It's just sitting there waiting for something to happen. And from an AI perspective, that's not necessarily interesting, but it's kind of the first stepping stone. Then we get into something a bit more interesting, which is a proactive goal-oriented agent. Right? A proactive agent is something, it's a piece of software that has a goal. What's a goal? It wants to change the environment from state A into state B, right? And it's going to do that proactively. So it's not just going to sit there and wait for you to talk to it, it's going to actually try and do it. This is when things start becoming interesting because we're relinquishing control. We're letting programs do things for us. So in a chatbot scenario, you would have something like a chatbot with a goal to take the world from a state where Ron did not read the news to a state where Ron reads the news. So it will say something like, hey, you will not believe what happened today, click here to get all the details, right? It will proactively try and get you to do something. And this is actually things that we see happening on chatbots every day, these days, and kind of rewrite applications that do these things as well. Okay, so let's take it a step further. So you can have a proactive, goal-oriented agent that's also learning, right? So it wants to change the world, but it's not just going to do it, it's trying to do the same thing over and over again. So with our chatbot example, it's going to say, hey, Ron, you will not believe what happened today, click here to get all the details, and I ignore it. Right, so I say, that didn't work, let's try something else. Hey, Ron, click here to get the latest news, no result, right? It keeps learning. What is actually going to make Ron click? So then it tries a different approach, dear Ron, all the things you need to know here. And that doesn't work either, right? It just keeps kind of using some utility function and trying to figure out what makes sense. I think this would really work for me. If it said, my masters will delete me. If you don't click here, then, yeah, I'd click. So you have a piece of software that is proactive. It's trying to change the world in some way, and it learns based on various things it tries. And it's all still very simple. This could be 20 lines of code, and just something that assigns values to, but this is still AI. It's very simple, but the moment you start relinquishing control, you're building something that is changing the world on its own. Now, next level, and we're done, are autonomous agents. And autonomous agents are more interesting because they're not just driven by goals where goals are very specific things. Change worlds from state A into state B, they have motivations, and motivations can be things like increased user engagement, just in general. And then they have specific goals, like get the user to read the news, get the user to subscribe, get the user to sign up to Facebook, and stuff like that. And there can be any number of complicated, mathematically interesting functions there that try and figure out how am I going to get maximum utility for this motivation of increased user engagement by putting in place actions through my effectors that are going to achieve those goals. But the basic level, it's simple, and that's kind of what I'm trying to drive through. It's that relinquishing control. So we're not just trying to get it to get the user to read the news. We're saying there's this high level thing we want you to achieve, which is user engagement. And then it can get kind of like transistors, right? They start simple, and then they get increasingly more complicated, integrated circuits, and so on. And then you can start imagining, well, you can have different motivations, and those motivations lead to different goals. So it's increased user engagement, but it's also increased ad income. So then, do you get the user to click on an ad? But that's going to take them away from me and my ability to increase engagement, and you have conflicting things. And you're really increasingly losing control. You don't know what the program is going to do. You know that you have overall utility functions that are going to lead it in the right direction. Now, take this into car driving, right? Why do we call them autonomous vehicles? And everyone is so excited and scared about how autonomous vehicles are going to change the world, because we're letting these cars figure out how they're going to get us from A to B, right? And the goal may be get the passenger back home, but the motivations can be things like do this in a fuel-efficient way. So you don't know exactly what route it's going to choose. It can be don't kill the passenger before you get them home. That's kind of big motivation. Don't kill anyone else while you're taking the passenger home, right? And those motivations are actually going to conflict at some point. Like, this car is going to have to decide there's someone in front of me and there's a wall and there's a passenger. Who do I kill? That's a real question that autonomous driving vehicles are going to have to answer, right? So that's where AI, starting from simple building blocks, becomes an increasingly more interesting thing because we're relinquishing control. We're letting a piece of software decide what it's going to do. Okay, so let's leave that to the side for a bit and talk about technological progress and how progress happens. And there's two concepts I want to talk about here. Exponential growth and interconnectedness. So what's exponential rate of change? Well, I think we've probably all seen some sort of graph like that. Things start slowly and then they really take off. There's a great book called The Second Machine Age that talks about what exponential rate of growth means in technological terms that I definitely recommend. And where we hear about exponential rate of growth most is Moore's Law, right? How many people have heard of Moore's Law? Cool, right? So what it says is the number of transistors in an integrated circuit doubles every two years. And this line is straight because that's a logarithmic scale. But if it was a normal scale, it would go up like that. So this has actually been extremely consistent over a long period of time. Now, the problem with exponential rate of growth is that we, as human beings, are really bad at dealing with numbers, especially big numbers. Like, we don't get it. So I'm going to tell you a story about chess to talk about exponential growth. And the story goes like this. Once upon a time, a ruler of India was bored and asked a mathematician in their court to come up with a game. And the mathematician invented chess. Now, I don't think that's how chess was invented. Actually, I know that's not how chess was invented, but it's a great story. So the court was really pleased with chess. It was a really fun game. They weren't bored anymore. And they asked the mathematician, well, how do you want to get paid? The mathematician said, I want to be paid in rice. And what you're going to do is you're going to place a grain of rice on the first square of the board. And then on the second square of the board, you're going to place two grains of rice because you're going to double what you did before. And then you're going to just keep doing that. So it's four. And just keep doubling the amount of rice that you place on each square of the board until the board finishes. So that's like 64 steps, right? So I think where are we now? So it's 16, 52, 64, 128, 500, and well, no. 256 grain of rice. And the ruler where there was laughing was like, here's some more rice. OK, 256, 512 grains of rice. OK, here's some more rice. And I wanted to do a great slide where this just went crazy with grains of rice, but keynote bombed. It can't handle more than 512 grains of rice plus everything else. So here's what happens. The numbers grow very quickly. So the first line, I think that's like the 70s, the first two lines. Then it's the 80s. And it's like, OK, here's a bag of rice. And here's a barrel. And here's like a truck. And then by the time you're at the fourth line, well, that's two billion grains of rice. That apparently is like a big rice field. That's a lot of rice. And then it's four all of a sudden. And then by the time you finish the fifth line, it's 274,877 million. So how does the story end? Well, there's two endings. The first one is that the royal goes bankrupt. They cannot supply enough rice to complete the board. The second ending is that they just chopped the mathematician's head off and went back to playing chess, which is probably the most likely outcome of that scenario. Now, why this is interesting? This is interesting because we're actually 32 doublings in. As humans, in terms of computer technology, we've done the first half of the board. And this is not me saying this. This is Ray Kerswell, who is Director of Engineering at Google and a really famous AI scientist and Director of Engineering at Google. So make the connection there. We are starting the second half of the board. Every next step change is going to be so much bigger than everything that happened before. That's what exponential rate of growth means. That's why I think this is going to happen very soon because the rate just goes like this. So everything we've seen happen in the past 30 years is just going to redouble. Just think of when the iPhone came out. What was that, 10 years ago, 11 years ago? Now, everyone has a smartphone. Those smartphones have all sorts of sensors on them. And we just use them. And we don't care. And we get annoyed when they don't quite work. But that device is crazy. That thing recognizes your voice and does things in the real world because of that. And that just happened in the past few years. Exponential rate of growth. So that's one concept to keep in mind as you're planning the future. The future is going to change much faster than the past did. The other concept is things are interconnected. And it's, again, another great book called The Inevitable. And it's talking not so much about technologies, but technological processes. Kind of things that are, by their very nature, leading technology into a certain direction. And I'm going to give you one example of interconnected. It has to do with machine learning. Machine learning has actually been around for a very long time. Since, well, let's just say, since the 1950s. Let's just put it there. It hasn't been very exciting. So a few things had to happen at the same time in order for machine learning to get exciting. And those things have now happened. The first one is cheap parallel computation. In order to train a neural network, you have to run a lot of processes in parallel. And that takes a lot of computation. And that's expensive. But at the same time, as neural network scientists were trying to make efficient neural networks, teenage kids were really excited about shoot them up games. And that when they shoot someone, they should see that head explode in full realism. As a result, we got graphical processing unit chips, GPUs from people like NVIDIA, that are extremely efficient. And the cost just went all the way down because teenage kids were buying them all over. So around 2011, Andrew Ng, who used to be head of Google's AI effort and is now head of Baidu's AI effort. He's a chief scientist that I do. He was at Stanford. And with his group, they said, OK, let's just get a bunch of GPUs, put them together, and solve neural networks that way. And problems that would take weeks to solve, they solved in a day. So that happened. The other thing that happened is big data. I'm very pleased with that. How do you represent big data? So AI feeds on data. In order to train a neural network, you just need a lot of information. And we didn't necessarily have that information. We didn't have it as a training set. But then storage got cheaper, and networks got faster, and database technology got better. And suddenly, and Google and Facebook and all these people started collecting data, and suddenly you have a lot of data you can use to train neural networks. And the other thing that happened is better algorithms. In 2016, someone called Jeff Hinton, working in Canada with his research group, came up with a better way of solving, of running neural networks. And they called that deep learning. So when you read deep learning, it's just basically another algorithm for running neural networks. And that increased the efficiency by a factor, or several factors. And one of the first papers they wrote, I don't expect you to read this, don't worry about that, is something called image net classification with deep convolutional neural networks. And is this competition that happens to see how well neural networks perform? And just look at the numbers there. 1.2 million high resolution images categorized across 1,000 different classes. The neural network had 60 million parameters and 650,000 neurons. And they used GPUs in order to solve the problem. And they got an error rate of 15.3%. So 85% of the time they're correct. Current error rates for image recognition are 5%. That's better than humans. So computers are better than us at recognizing what's in an image right now. So exponential, this all happened in the past five years. Computers went from being kind of eh when it came to image recognition to being better than us. Computers are better than us in recognizing cancer in scans. They're better, well, they're better than doctors, right? There's all sorts of things that in the past two years, it's just computers started being better than us. And that's going to impact all sorts of things and how we do them. OK. So we have AI. We know that the rate of change is exponential. And we know that changes are interconnected. And once they come together, the shift is factors of magnitude more. So how does this impact web development and what we do day to day? Well, let's think about what problem we're actually trying to solve. What is it that we do? And if the answer is build websites, that's the wrong answer. Because who needs a website? There's no intrinsic need for a website in human beings. People need solutions to their problems. They want to find clients. They want to sell widgets. They want to hire people. They want to entertain, et cetera, et cetera. So what if we could solve all these problems without websites? That's the question we need to be asking ourselves, because we kind of depend on people needing websites. And if they don't, it's a bit of a problem. So we have two questions we need to answer. Do we need a website? And if we do need a website, how will it be built? Let's tackle the first one. And I'm going to give you an example with Desons' own website. Here's my user story. As a user, I want to find where your business is. And I type decent agency into Google. Gives me some results. Fantastic. Click on the first one. I go to Desons' website. And it doesn't say where they are. So I will contact, maybe, or click on Contact. It's a very nice picture of our managing director. But I have to scroll down. And finally, here's where they are. London and Contraberry and Remote. But actually, I lied, because when I typed decent agency in Google, this is what Google actually gave me. Deson is exactly there. This is their phone number. This is their opening times. And if you're a restaurant, or a hotel, or any sort of business of that sort, you didn't need a website to solve that specific use case. And it can get better, because if I have Alexa, I can say, Alexa, where is Deson agency? And it's just going to tell me. And I didn't even use the web. Well, I used the web, but I didn't type anything. So we need to start asking ourselves, what are the problems that we're solving and how are they currently solved? Once you're in a situation where you also have dedicated marketplaces. And by the way, all these things work efficiently because they work with artificial intelligence in the back end. Google knows where Deson agency is, because there is a ton of AI in the back end figuring that stuff out. Take Airbnb. If you are renting out a flat, Airbnb has all the data. It has a processing power. It will give you the best price. Why should you build a website for that? Same thing with Amazon, Viboletti, and so on. Then you have other ways of interacting. So if I want to book a flight now, I can talk to Kayak in Facebook Messenger. I can say, give me some ideas. Tell me when flights are available. Tell me how much they're going to cost. I'm not using a website. At Deson, we're working with museums and we're building exhibition experiences where instead of building a website for an exhibition, you build a message board. And it can have a fun character of the one we're working with now. It's King Charles II. So there's a King Charles II exhibition when you're talking to King Charles II, asking things about their life. And then eventually, you can also book tickets. Devices are changing. They're getting smaller. They're getting bigger. They're moving. They're static. They're hidden. Interfaces are changing. You have voice, motion detection, text entry. This is all going to impact the utility of websites. And we can understand the user in ways that we could never before. So websites are becoming a part of a much bigger picture. Doesn't mean that they're completely going to go away, but they're going to change in terms of what they are. But let's deal with the other problem. OK, we do need a website. Convince ourselves. The best solution is a website. How are we going to build it? Well, there's a bunch of dedicated SAS tools including WordPress.com. And you can go to these places and just get a website built, pull things together, and it works nicely. And I include Facebook there, because that's what Facebook pages are. They are websites. And there's a bunch of businesses right now that say, I don't need a website. I have a Facebook page. I actually know who comes to my Facebook page and what they click. Like, I see their face and all of that. Then you dig a little deeper, and you have things like Wix has their AI-based design. And you can laugh at it and say, oh, it's not really AI. It is. You're relinquishing control. Remember what we said at the start. It's deciding how to set up the picture, the page, based on context, based on what you're trying to achieve. But it's not just Wix. You have this services are completely AI-based. So let's say FireDrop says, build your site with Sasha, the AI web designer. You have tools like Adobe Sensei, which this is a program that Adobe is implementing across all their products where they're building artificial intelligence into every single thing that they do, including web design. So designers, and this is just nuts, that the fact that we can do this, a designer can sit and say, eh, I am Brella here, person. And then the program is going to go away and say, OK, those things match exactly what you needed. And anyone who has designed knows how much time designers spend to find just the right picture. And now with AI, you've compressed that time into literally nothing. And this is just going to get better because exponential rate of growth. So two years from now is going to be much, much better than what it is now. In the Drupal world, you have Acquia doing personalization of Drupal sites with something called AcquiaLift. And it collects a lot of information about user context. And it allows you to try out different images and words and so on and keeps building that user profile. You have ad design and management. This is a great story. Cosa Bella, they do lingerie. And they've completely outsourced their ad management to an AI. And the CEO is crazy about this thing. He's saying, I will never go back to an agency. I loved my agency. They are beautiful people. But I will never go back to humans. I'm just going to use Albert. And Albert is going to figure out the right phrase and the right image and manage my advertising and does it so much better than those lovely humans that I really like. Logo design. There is something called Mark Maker that just spits out designs. And you tell it what you like. And it just keeps doing it. And you can say, well, this is not as good as a real designer, but exponential growth. This is going to get better. Automated content creation. Associated Press writes something like 3,000 to 4,000 stories now per quarter using bots, using AI. It just feeds in facts and out comes a story. And it publishes that. No journalist actually interacted with that. Initially, there was a monitoring phase just to make sure it was OK. There's no humans involved. Just a story gets released. It would be awesome if it was actual robots typing at a keyboard, but it's not, which is sad. So every aspect of what it takes to build a website is going to be impact by AI. And the question becomes, OK, what now? But I think there's a few things. There's a few answers. We need to start thinking now about all those other interfaces, like chat-based interfaces, motion-based interfaces, virtual reality, augmented reality. Start thinking about how those solve problems. We need to stop selling websites, because websites are not going to be the most interesting thing. We have to sell solutions to problems. Tell your client, which is a good idea anyway. You tell your client, this is how I'm going to get you more clients. There's going to be new professions, new things that we can't think of right now. So you have stuff like data scientists and machine learning experts, but you're also going to have stuff like bot designers, conversation writers, like people that write the conversations for bots. I love this one. Chief listening officer, just someone that tries to interpret what's going on, sustainability experts, and so on. But the thing is, by definition, we don't know what the new professions are going to be until they get there. And something else that I want to mention is it has to come down to policy. How many people know what universal basic income is? Excellent. For those that didn't raise their hand, universal basic income is the idea that, well, it's a complicated idea summarized into there is enough abundance and enough automation that the basics are covered without you having to actually go work. And it's not welfare. It's literally saying, we don't need to do these things anymore as a society. Because we're changing how society works, so we need to change how we run society. The two things can happen separately. Then it's going to break. And you get a number of things that we're already seeing. We're kind of seeing these processes happen. So in conclusion, it's going to happen because there are underlying forces that are pushing things in this direction. We can either pretend it's not going to happen or accept that it is going to happen. And it's actually really exciting. I mean, I love the idea that my retirement plan is universal basic income. I have all sorts of things that I want to do, and they don't need to involve computers anymore. That's fantastic. There's opportunity there. OK, thank you. Thank you so much. That was a lot of information. Did everyone learn something? A lot. Are you afraid of the machines now? No? OK. So we have some time for questions. And I'm sure you all have many. So just raise your hand. And someone with a mic will come to you. Do you think that there would be, obviously, jobs will vanish and jobs will be created? What worries me is that certain jobs will be more automated and you'll find people that won't be working. So do you think there'll be an even balance between jobs that will be created and jobs that will vanish? So there's an intense debate about this. Some people say you just don't know. I fall on the side of there will not be the same number of jobs created as opposed to jobs that go away. There will be less jobs because we're automating. So by definition, less things to do. That's why the change is actually bigger. It's political and sociological and so on. Back there? Thank you. Yeah, so one of the things that occurs to me at the moment when you're doing old school search with Google, et cetera, you present it with a bunch of results and you can choose which shop you buy those Nike shoes from. But with this bot revolution, you're only given one option. And that's a lot of power you're handing over to the provider of the results. Do you have any thoughts on the rights and wrongs and what can be done about that? I think that we're going to see two things developing. On the one hand, you are going to have companies like Nike having their own bots and you interact with that. And that's the shoes that you're going to get. But what's going to be more interesting is independent bots that at the back end, they're actually powered by a search engine and they learn who you are and what you like. And you have a conversation. It's literally having a conversation with someone in a shop. And they offer different options and so on. So I don't think that bots are going to limit that side of the equation. You're still going to get the single ones and essentially search engines disguised as a bot. OK, up here. Hi. Have you got any practical starting points for this kind of work? Because I've played with something called superscript and there's a few of the tools and things out there. But have you got any practical favorites for starting places or resources and things that you can share? So you mean for something specific like bots or? Yeah, so the museum bots. Yeah. So what we use, what we're playing around with is BotKit, which is an open source Node.js based framework. And then there's API services like API.ai from Google, for example, that does the natural language processing and figures out the intent of what the user typed in and that you pipe that back into your bot and give the reply. So you're telling us that we're using bots that are inspired by us to create content, writing text, create graphics. But what will happen in the future when bots will be inspired by other bots? So we're dropping the human of the equation. So what's the creativity process in that? I don't know what's going to happen with that. There's different views, right? So this is kind of the view of AI abandoning humans, in a way, and just worrying about itself and things interacting between themselves. But I think what's more likely to happen, and it's very hard to predict, but is a combination. So there's going to be an augmentation of what we can do, which is essentially the process that we see so far. So it's not just going to be bots interacting between themselves, it's going to be us with bots, and it's going to be hard to tell the line of where the bot finishes and where. Right now, if you take away my smartphone, I can't go back home. I'm going to sleep under a bridge. That's the kind of augmentation I mean. It becomes co-dependent on these things. Same time, my smartphone is useless without me. It's a symbiosis. That's Ray Kurzweil calls this a singularity. He gives a date. I think it's 2029, singularity. Two things together. Who knows? Any other questions? Back there. So in order for AI to take over more and more stuff, does that mean for the consumer to give up privacy more and more? Yes, I think because AI feeds on data. And I think that's where the interesting social questions come out of it. I think the question is much bigger than whether we're going to need websites or not. And it's already happening. If you look at elections and how they run and how they're influenced at the level of influence, we need to start asking ourselves, what are we actually, where do we want to end up? And I'll just add, I don't think the answer is, oh, let's just stop. We can't stop. But we need to deal with it. And the problem is that the rate of change might just be a bit too fast for us to adapt. I want to get all dark and so on, but there might be a breaking point. So the more we think about it now, the less likely that is. You have a question? Just to follow up on that. OK. Talking about the influencing and voting that we just saw happening, how is that going to be? Is there any controlling instance for AI that we can think about already? It's like fake news and all that stuff. There isn't really. If you look at the news, you'll hear there are parliamentary commissions that are calling the managers of Google and Facebook and are asking questions. They're saying, you need to do something better about this. But there is no legal framework to actually handle it. So there are no penalties to fake news currently. And then we have one up here. Did you have a question? No. Does anyone else have questions? Oh, OK. I just wanted to just look at this in a WordPress context. Are you aware of or have you encountered anything where bots are being used to interact with WordPress and help people carry out some of the higher level functions, updates, plugins, various things like that, using this kind of bot technology? Is it something you've experienced? No, I haven't seen anything like that, although I would be surprised if that didn't happen soon enough. Really? OK. So, I need to talk to you. OK, I think we have time for one more question. I just wanted to say. Yeah, he has a comment, so. I'm going to start with him. Does anyone have a question? OK. The problem is what worries me is the fact that we're not all unified as humans in the sense that we have nationality and there are factions in the world, certain countries that are perceived as enemies. Before we, when we use this technology against each other, eventually those bots will realise that they are more united and have more common than we do. No, seriously, they will. Well, that's evolution. That's teacher's lesson. But they will realise that they have more common with each other than we have in common with certain countries. It's entirely feasible. You know, there's very intelligent people, Stephen Hawking, Elon Musk, like specifically said, this might be the end. These are not silly people. Like, the issues are completely real. So, we're going to leave you with that positive thought. So, enjoy the rest of WordCamp and we'll be back here in 20 minutes. Where can I find the slides? I'll put them up and tweet it out. I'll put them up on Slide Deck or something, speaker deck or something. Right, and this talk will also... He will be tweeting it out and this talk will also be on WordPress TV. I think it did great. Thank you.