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The A.I. Race (2017)
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(mystical music) [Female Robotic voice] Hi, how are you feeling? I just checked your health data. Your last meal contributed 60% of your daily nutrients. And you've completed 11,000 steps towards your daily fitness goal. So you can take a seat now. I've got something for you to watch. And I'll be watching, too. Tonight, you're going to see humans take on the robots that might replace them. There will always need to be experienced people on the road. From truckies to lawyers, artificial intelligence is coming. Actually it's already here. I didn't realize that it would be just be able to tell you, hey, here's the exact answer to your question. We'll challenge your thinking about AI. [Male Robotic Voice] Same category, 1600. The AI's going to become like electricity. Automation isn't going to affect some workers, it's going to affect every worker. And we let the generation most affected take on the exerts. I think that the younger generations probably have a better idea of where things are going than the younger generations. (laughing) Tonight, we'll help you get ready for The AI Race. (upbeat music) (mellow music) Australian truckies often work up to 72 hours a week and are now driving bigger rigs to try to make ends meet. I've seen a lot of people go backwards out of this industry and I'm seeing a lot of pressures it's caused them, their family life, especially when you're paying the rig off. Now a new and unexpected threat to Frank and other truck drivers is coming on fast. Last year this driverless truck in the US became the first to make an interstate delivery. it traveled nearly 200 kilometers on the open road with no one at the wheel, no human that is. The idea of robot vehicles on the open road seemed ludicrous to most people just five years ago. Now just about every major auto and tech company is developing them. So what changed? An explosion in artificial intelligence. (mellow music) There's lots of AI already in our lives. You can already see it on your smartphone every time you use Siri, every time you ask Alexa a question. Every time you actually use your cellphone navigation, we're using one of these algorithms you're using some AI that's recognizing your speech, answering questions, giving you search results, recommending books for you to buy on Amazon. They're the beginnings of AI everywhere in our lives. (gentle music) We don't think about electricity. Electricity powers our planet. It powers pretty much everything we do. It's going to be that you walk into a room and you say, room, lights on. You walk and you sit in your car and you say, take me home. (whistles) A driverless car is essentially a robot. It has a computer that takes input from its senses and produces an output. The main senses are radar, which can be found in adaptive cruise control. Ultrasonic senses, and then there's cameras that collect images. And this data is used to control the car, to slow the car down, to accelerate the car, to turn the wheels. There's been an explosion in AI now, because of the convergence of full exponentials. The first exponential is Moore's Law. The fact that every two years we've had a doubling and computing performance. The second exponential is that every two years we've had a doubling of the amount of data that we have. Because these machine learning algorithms are very hungry for data. The third exponential is that well we've been working on AI for 50 years or so now. And our algorithm are starting to get better. And then the fourth exponential, which is over the last few years, we've had a doubling every two years of the amount of funding going into AI. We now have the compute power. We now have the data. We now have the algorithms. We now have a lot of people working on the problems. (engine turns) It could be you just jump into the car. You assume the car knows where you need to go because it has access to your calendar, your diary, where you're meant to be. And if you did not want the car to go where you're calendar says you ought to be, then you need to tell the car, oh, by the way, don't take me to the meeting that's in my calendar, take me to the beach. [Host] But Frank Black won't have a bar of it. I think it's crazy stuff. You've got glitches in computers now. The banks are having glitches with their ATMs and emails are having glitches. Who's to say this is going to be perfect and this is a lot more dangerous if there's a computer glitch. There'll always need to be experienced people on the road, not machines. Frank is going to explain why he believes robots can never match human drivers. (mellow music) Okay then, let's do it. But Frank is off to a rocky start, Driverless trucks in Rio Tinto Mines in West Australia, show productivity gains of 15%. Frank needs to break every five hours and rest every 12. Oh and he needs to eat and he expects to be paid for his work. Robots don't need a salary. Trials also indicate that driverless vehicles save up to 15% on fuel and emissions. Especially when driving very close together in a formation called Platooning. And at first glance, driverless technology could dramatically reduce road accidents because it's estimated that 90% of accidents are due to human error such as fatigue, or loss of concentration. Robots don't get tired. But hang on, Frank's not done. He's about to launch a comeback using 30 years of driving experience. If there's something, say like a group of kids playing with a ball on the side of the road. We can see that ball starting to bounce towards the road. We anticipate that it would be a strong possibility that that child will run out in the road, you know, after that ball. I can't see how a computer can anticipate that for a start and even if it did, what sort of reaction will it take? Would it say, swerve to the left, swerve to the right? Will it just break and bring the vehicle to a stop? What about if it can't stop in time? In fact, right now, a self-driving vehicle can only react according to its program. Anything unprogrammed can create problems. Like when this Tesla drove into roadworks barrier, after the human driver failed to take back control. And what if some of the sensors fail? What happens if something gets on the lens and people doesn't know where it's going? It's true, currently heavy rain or fog or even unclear road signs can bamboozle driverless technology. And then there's the most unpredictable element of all. Human drivers. Stupidity always find new forms. Quite often you see things you've never seen before. That's why there are no plans to trial driverless trucks in complex urban settings right now. They'll initially be limited to predictable multi-lane highways. You also still need a human right now to load and unload a truck. And a robot truck won't help change your tire. If someone's in trouble on the road, you'll usually find that a trucker will pull over and make sure they're all right. Finally there are road rules. Australia requires human hands on the steering wheel at all times, in every state and territory. Hey Frank. You won the race. One for the human beings. (laughing) (upbeat music) But how long can human drivers stay on top? Nearly 400,000 Australians earn their living from driving, any more when you add part-time drivers. But the race is on to deliver the first version of a fully autonomous vehicle in just four years. And it might not be hype. Because AI is getting much better, much faster every year. With a version of AI called Machine Learning. (mellow music) Machine learning is the little part of AI that's focused on teaching programs to learn. If you think about how we got to be intelligent, we started out not knowing very much when we were born and most of what we got is through learning. And so we write programs that learn to improve themselves. They need, at the moment, lots of data. And they get better and better and in many cases, for setting narrow focus domains, we can often actually exceed human level performance. When AlphaGo beats Lee Sedol last year, one of the best Go players on the planet, that was a landmark moment. So we've always used games as benchmarks, both between humans and between humans and machines. And a quarter century ago, chess fell to the computers. And at that time, people thought, well Go is going to be like that. Because in Go, there are so many more possible moves. And the best Go players weren't working by trying all possibilities ahead. They were working on kind of the gestalt of what it looked like and working on intuition. And we didn't have any idea of how to instill that type of intuition into a computer. (mesmerizing music) But what happened is we've got some recent techniques with deep learning where we're able to do things like understand photos, understand speech and so on and people said, maybe this will be the key to getting that type of intuition. Sp, first it started by practicing on every game that a master had ever played. You feed them all in and it practices on that. The key was to get AlphaGo good enough from training it on past gains by humans sot hat it could then start playing itself and improving itself. And one things that's very interesting is that the amount of time it took the total number of person years invested is a tenth or less than the amount of time it took for IBM to do the chess playing. So the rate of learning is going to be exponential. Something that we, as humans, are not used to seeing. We have to learn things painfully ourselves. And the computers are going to learn on a planet-wide scale, not on an individual level. (mesmerizing music) There is this interesting idea that the intelligence would just suddenly explode and take us to what's called the singularity, where machines now improve themselves almost without end. There are lots of reasons to suppose that maybe that might happen, but if it does happen, most of my colleagues think it's about 50 years away, maybe even 100. (robot gasps) I'm not convinced that how important intelligence is. So I think that there's lots of different attributes and intelligence is only one of them and there certainly are tasks that having a lot of intelligence would help. And being able to compute quickly would help so if I want to trade stocks then having a computer that's smarter than anybody else is going to give me a definite advantage. But I think if I wanted to solve the Middle East crisis, I don't think it's not being solved because nobody's smart enough. But AI experts believe robot cars will improve so much that humans will eventually be banned from driving. (dramatic music) Big road blocks remain, not the least of which is public acceptance. As we found out after inviting professional drivers to meet two robot car experts. How are you doing, Maria? Straight away the first thing is to be safety. You definitely have to have safety paramount. And obviously efficiency. So the big question, when is it going to happen? In the next five to 10 years we will see higher autonomous vehicles on the road. If you want to drive from city to Canberra, you drive to the freeway, activate autopilot or whatever it will be called at the time and by the time you arrive in Canberra, the car will ask you to take back control. There are predictions that in 20 years time, 50% of new vehicles will actually be completely driverless. What makes us think that these computers in these vehicles are going to be fool-proof? Well we were able to send rockets to the moon and you know, I think that there are ways of doing it and you can have backup systems and you have backups for your backups and, but I agree. Reliability is kind of a big question mark. But we're not talking a phone call dropping out or an email shutting down, we're talking about a 60 ton vehicle, in traffic, that's going to kill people, there will be deaths if it makes a mistake. I think we need to accept that there will still be accidents and a machine can make a mistake, can shutdown, can fail and if we reduce accidents by, say 90%, there will still be 10% of the current accidents will still occur on the network. Who said it's going to be 90%? How do you work that out? 90% is because 90% of the accidents are because of human error. And the idea is if we take the human out we could potentially reduce it by 90%. Have any of you ever driven a car available on the market today with all this technology, autopilot and everything in there? It's absolutely unbelievable how safe and comfortable you feel. I think people will ultimately accept this technology because we will be going in steps. I would say, for me as an Uber driver, we're providing a passenger service and those passengers, when they're going to the airport, a lot of luggage. If it's an elderly passenger, they need help to get into the car, they need help getting out of the car. The human factor needs to be there. I would argue that you can offer a much better service if you're not also driving. So the cars taking care of the journey and you're taking care of the customer. And improving the customer experience. And I think that there's a lot of scope for improvement in the taxi and Uber customer experience. You could offer tax advice, you could offer financial advice. (laughing) It's unlimited. Then we go back though, they're not fully driverless vehicles anymore, we've still got a babysitter there, a human being to look after the cars. So what are we gaining with the driverless technology? Well, the opportunity to do that. Yeah, but, that's-- Are you trying to reduce cost by not having to drive in the vehicle? Well, it depends on what people are paying for, okay? And if you are in business, you are trying to get as many customers as possible. And if you're competitor has autonomous vehicles and is offering, you know, daycare services or looking after disabled, you probably won't be in business very long if they're able to provide a much better customer experience. For my personal use, I like to drive my car. I want to enjoy driving. Well I think in 50 years there will be special places for people with vintage cars and they can go out and drive around. (all laugh) (drowned out by laughter) Someday driving our vintage car when these autonomous vehicles have got our roads. I mean, in the future when all the cars are autonomous, we won't need traffic lights. Okay, because the cars will just negotiate between themselves when they come to intersections, roundabouts. Can I ask you a question? If we would do a trial with high automated platooning of big road trains, would you like to be involved? Yes, I would be involved, yeah, yeah, Why not? You convinced Frank, yeah. If you can convince Frank, you can convince anybody. Do you want to come out with us and I bet Frank's the same as well, if you want to come for a drive in the truck and see exactly what it's like and the little issues that would never have been thought of, I mean, my door is always open, you're more than welcome to come with me. Oh definitely, I think it's-- It's time for a road trip. (all laugh) The drivers aren't the only ones trying to find their way into the AI future. (mellow music) Across town, it's after work drinks for a group of young and aspiring professionals. Most have at least one university degree or studying for one. Like Christine Maibom. I think as law students we know now that it's pretty tough even to like get your foot in the door. I think that at the end of the day, the employment rate for grads is still pretty high. Tertiary degrees usually shield against technological upheaval, but this time AI will automate not just more physical tasks but thinking ones. (dramatic music) Waiting upstairs for Christine is a new artificial intelligence application. One that could impact the research typically done by paralegals. We invited her to compete against it in front of her peers. Adelaide tax lawyer, Adrian Cartland came up with the idea for the AI called Ailira. I'm here with Ailira, the Artificial Intelligent Legal Information Research Assistant. And you're going to see if you can beat her. So what we've got here is a tax question. Adrian explains to Christine what sounds like a complicated corporate tax question. Does that make sense? Yep, yeah. Very familiar? All right, ready? I'm ready. Okay guys, ready, set, go. (upbeat music) And here we have the answer. So you've got the answer? We're done. That's 30 seconds. Christine, where are you up to with the search? I'm at section 44 of the income tax assessment guide. (laughing) Maybe it has the answer, I haven't looked for it yet. (laughing) You're in the right act, so now do you want to keep going or do you wanna give some more time? I can keep going for a little bit, yeah, sure. (upbeat music) No pressure, Christine. We're at one minute. (laughs) Okay. Whew, I might need help on this one. This is, you know, really complex tax law. Like I've given you a hard question. You were in the income tax assessment act, you were just doing research, what is your process? Normally what I would do is probably try to find the legislation first and then I'll probably look to any commentary on the issue. Yep. Find specific keywords so for example, consolidated group and and accessible income obviously there. That's a pretty standard way. That's what I would approach. If you put this whole thing into a keyword search, it's going to breakdown. Keyword searches breakdown after about four, five, or seven words. Whereas this is, you know, 300-400 words. So all I've done is I've entered in the question here, copied and pasted it. I've clicked on submit. And she's read through, literally, millions of cases as soon as I pressed search and then she's come through and she said, here is the answers. Oh wow. She's highlighted in there what she thinks is the answer. Yeah, I mean, wow. I mean even down to the fact that it can answer those very specific questions, I didn't realize that it would just be able to tell you, hey, here's the exact answer to your question. It's awesome. I think obviously, for paralegals, I think it's particularly scary because I mean we're already in such a competitive market. Adrian Cartland believes AI could blow up lawyers monopoly on basic legal know how. And he has an astonishing example of that. My girlfriend is a speech pathologist who has no idea about law and she used Ailira to pass the Adelaide University tax law exam. Oh wow. Automation is moving up in the world. Here's Claire, a financial planner. It's estimated that 15% of an average financial planners time is spent on tasks that can be done by AI. What kind of things do you see it ultimately taking over? I would say that everything except talking to your clients. Yeah. Here is Simon. He used to be a secondary school teacher. One fifth of that job can be done by AI. Simon's now become a university lecturer, which is less vulnerable. I think there's huge potential for AI and other educational technologies. Obviously it's a little bit worrying if we're talking about making a bunch of people redundant. And did I mention journalists? I hope you enjoyed tonight's program. The percentage figures were calculated by economist Andrew Charlton and his team after drilling into Australian workforce statistics. For the first time, we broke the Australian economy down into 20 billion hours of work. And we asked, what does every Australian do with their day? And how or what they do in their job change over the next 15 years. I think the biggest misconception is that everyone talks about automation as destroying jobs. The reality is that automation changes every job. It's not so much about what jobs will we do, but how will we do our jobs because automation isn't going to affect some workers, it's going to affect every worker. But if there's less to do at work, that's got to mean less work or less pay or both, doesn't it? If Australia embraces automation, there is a 2.1 trillion dollar opportunity for us over the next 15 years. But here's the thing. We only get that opportunity if we do two things. Firstly, if we manage the transition and we ensure that all of that time that is lost to machines, from the Australian workplace is redeployed and people are found new jobs and new tasks. And condition number two is that we embrace automation and bring it into our workplace and take advantage of the benefits of technology and productivity. But Australia's not doing well at either. Right now, Australia's lagging. One in 10 Australian companies is embracing automation and that is roughly half the rate of some of our global peers. Australia hasn't been very good historically at transitioning workers affected by big technology shifts. Over the last 25 years, one in 10 unskilled men who lost their job, never worked again. Today, four in 10 unskilled men don't participate in the labor market. (dramatic music) We asked a group of young lawyers and legal students, how they felt about embracing AI. The contrasts were stark. I often get asked, you know, do you feel threatened? Absolutely not. I'm confident and I'm excited about opportunities that AI presents. I think the real focus will be on not only up-scaling, but re-skilling and about diversifying your skillset. I think for me, I still have an underlying concern about how much of the work is going to be taken away from someone who's still learning the law and just wants a job part time where they can sort of help with some of those less judgment based high level tasks. how much software is there out there, AI for legal firms at the moment? There's quite a lot. There's often a few competing in the same space so there's a few that my law firm has trialed in. For example, due diligence, which are great for identifying certain clauses. So rather than the lawyer sitting there trying to find an assignment or a change of control clause, it will pull that out. How much time do you think using the Ai cuts down on that kinda, just crunching, lots of documents, lots of numbers? Immensely, I would say potentially up to about 20% of our time in terms of going through and locating those clauses or pulling them out, extracting them. Which of course delivers way better value for our clients which is great. Well, I think the first reaction was obviously like very worried, I suppose. You just see the way that this burns through these sort of banal tasks that we'd be, you know, doing at an entry level job, and yeah, it's quite an intuitive response, I suppose, that we're just a bit worried. And also, it just was so easy, like, it was just copy and paste, and so it means that anyone could do it, really, do you don't really need the sort of specialized skills that are getting taught to us in our law degrees, it's pretty much just a press a button job. AI is like Tony Stark's Iron Man suit, it takes someone and makes them, you know, into Superman, makes them fantastic. So you could suddenly be doing things that are like 10 times above your level and providing that, you know, at much cheaper than anyone else could do it. Lawyers might, the legal work of the future might be done by social workers, psychiatrists, conveyances, tax agents, accountants, they have that personal skill set that lawyers sometimes lack. Yeah, I always wonder just how much law school should be teaching us about technology and new ways of working in legal workforce, because, I mean, a lot of what you guys are saying, I've heard for the first time. I certainly agree with that statement. This is the first time I've heard the bulk of this, especially hearing that there is already existing a lot of AI. Unfortunately, our education system just isn't keeping up. Our research shows that right now, up to 60% of young Australians currently in education are studying for jobs that are highly likely to be automated over the next 30 years. It's difficult to know what will be hardest first. But jobs that help young people makes ends meet are among the most at risk. Like hospitality workers. So, the figure that they've given us is 58% could be done by versions of AI. What does that make you feel? Very, very frustrated, that is really scary. I don't know, I don't know what other job I could do whilst studying or that sort of thing. Or as a fallback career, it's what all my friends have done, it's what I've done, it sort of just helps you survive and, you know, pay for the food that you need to eat each week. It may take a while to be cost-effective, but robots can now help take orders, flip burgers, make coffee, and deliver food. Young people will be the most affected by these changes because the types of roles that young people take are precisely the type of entry level task that can be most easily done by machines and artificial intelligence. But here this evening, there's at least one young student who's a little more confident about the future. So, Aniruddh, how much of your job as a doctor do you imagine that AI could do pretty much now? Now? Not much, maybe five, 10%. But artificial intelligence is also moving into healthcare. Watson. What is Sauron. Sauron is-- Watson. What is leg? Yes, Watson. What is executor? Right. Watson. What is shoe? You are right. Same category, 1600. Answer. So, in the earliest days of artificial intelligence and machine learning, it was all around teaching computers to play games. Yes, Watson. What is narcolepsy? But today, with those machine learning algorithms, we're teaching those algorithms how to learn the language of medicine. We invited Aniruddh to hear about IBM research in cancer treatment using its AI supercomputer, Watson. Today, I'm going to take you through a demonstration of Watson for oncology. This is a product that brings together a multitude of disparate data sources and if able to learn and reason and generate treatment recommendations. This patient is a 62 year old patient that's been diagnosed with breast cancer and she's presenting to this clinician. So the clinician has now entered this note in, and Watson has read and understood that note. Watson can read natural language, and when I attach this final bit of information, the ask Watson button turns green, and at which stage, we're ready to ask Watson for treatment recommendations. Within seconds, Watson has read through all the patients records and doctor's notes as well as relevant medical articles, guidelines and trials. And what it comes up with is a set of ranked treatment recommendations. Down at the bottom, we can see those in red that Watson is not recommending. Does it take into account how many citations a different article might have used, say, the more citations, the more it's going to trust it? So, this is again where we need clinician input, to be able to make those recommendations. Natalie, you've shown us this, and you know, you've said that this would be a clinician going through this, but the fields that you've shown, really, an educated patient could fill in a lot of these fields from their own information. What do think about that approach, the the patient's essentially getting their own second opinion from Watson for themselves? I see this as a potential tool to do that. AI's growing expertise at image recognition is also being harnessed by IBM to train Watson on retinal scans. One in three diabetics have associated eye disease, but only about half of these diabetics get regular checks. We know that with diabetes, the majority of vision loss is actually preventable if timely treatment is instigates, and so that if we can tap into that group, you're already looking at potentially incredible improvement in quality of life for those patients. How could something like that happen? We could have a situation where you have a smartphone applications, you take a retinal selfie if you like. That then is uploaded to an AI platform, analyzed instantly, and then you have a process by which instantly, you're known to have high risk or low risk disease. How long does it take to analyze a single retinal image using the platform? Very close to real times, it's in a matter of seconds. I mean, this is obviously very, very early days, but the hope is that one day, these sorts of technologies will be widely available to everyone for this sort of self-analysis. Just like law, AI might one day enable patients to DIY their own expert diagnosis and treatment recommendations. Some doctors will absolutely feel threatened by it, but I'd come back to the point that you want to think of it from the patient's perspective, so if you're an oncologist sitting in the clinic with your patient, the sorts of things that you're dealing with is things like giving bad news to patients, and I don't think patients want to get bad news from a machine. So it's really that ability to have that intelligent assistant who's up to date and providing you with the information that you need and providing it quickly. We like to use the term, augmented intelligence. I think one interesting way to think about this is, I mentioned 50,000 oncology journals a year. Now, if you're a clinician trying to read all of those 50,000 oncology journals, that would mean you'd need about 160 hours a week just to read the oncology articles that are published today. Watson's ability to process all of this medical literature and information and text is immense. It's 200 million pages of information in seconds. Wow. Need a bit of work on myself then. IBM is just one of many companies promoting the promise of AI and healthcare, but for all these machine learning algorithms to be effective, they needs lots of data, lots of our private medical data. In my conversations with my patients, and the patient advocates that we've spoken to, you know, they certainly want the privacy protected, but I think it's actually a higher priority for them to see this data being used for the public good. But once it has all the data, could this intelligent assistant ultimately disrupt medicine's centuries old hierarchy. They should have more general practitioners and less of the specialty. So, doctors, they all have more time to have a better relationship with you, maybe they'll be talking about your overall health rather than waiting for you to come in with symptoms, and if they do have to, you know, analyze an x-ray and look for a disease, they'll have a computer to do that, they'll check what the computer does, but they'll be pretty confident that the computer's gonna do a good job. (mellow music) When we first talked to you, Ani, in Sydney, you said you thought that in terms of the time spent on tasks that doctors do, that AI might be able to handle maybe five, maybe at the outside 10%. How do you see that now? Definitely a lot more. I tell you, it can go up to 40, 50%. Using it as a took rather than taking over, I'd say it's gonna happen. The percentage for doctors is 21%, but that's likely to grow in the coming decades as it will for every profession and every job. We've been through technological upheaval before, but this time, it's different. One of the challenges will be that the AI revolutions happens probably much quicker than the industrial revolution. We don't have to build big steam engines, we just have to copy code, and that takes almost no time and no cost. There is a very serious questions, whether there will be as many jobs left as before. (mellow music) I think the question is, what is the rate of change, and is that gonna be so fast that it's a shock to the system that's gonna be hard to recover from. I guess I'm worried about whether people will get frustrated with that and whether that will lead to inequality of haves and have nots. And maybe we needs some additional safety nets for those who fall through those cracks and aren't able to be lifted. We should explore ideas like universal basic income to to make sure that everyone has a cushion to try new ideas. What to do about mass unemployment? This is going to be a massive social challenge. And I think ultimately we will have to have some kind of universal basic income. I don't think we're gonna have a choice. I think it's good that we're experimenting and looking at various things, and you know, I think we don't know the answer yet for what's gonna be effective. The ascent of artificial intelligence promises spectacular opportunities, but also many risks. To kickstart a national conversation, we brought together the generation most affected with some of the experts helping to design the future. You will have the ability to do jobs that your parents and grandparents couldn't have dreamed of. And it's going to require us to constantly be educating ourself to keep ahead of the machines. Actually, first of all, I wanted to say that I think the younger generations probably have a better idea of where things are going than the older generations. (laughing) We won't take that personally. Sorry, sorry, but I think-- So where have we got it wrong? Well, I think the younger people, they've grown up being digital natives, and so they know where it's going, they know what it has a potential to do, and they can kind of foresee where it's gonna go in the future. We all hate that question at a party of, like, what do you do? I think in the future, you'll be asked instead, what did you do today or what did you do this week? Because I think the, we all think of jobs as a secure, safe thing, but if you work one role, one job title at one company, then you're actually setting yourself up to be more likely to be automated in the future. The technology in the building game is, is advancing. Kind of worry if you're a 22 year old carpenter for example. I think there's often this misconception that you have to think about a robot physically replacing you, one robot for one job, and actually, it's going to be, in many cases, a lot more subtle than that. In your case, there'll be a lot more of the manufacturing of the carpentry happens off-site. That happened between the start of my apprenticeship and when I finished, it was while moving sort of all the frames and everything we build off-site, and brought to you, and you do all the work that used to take you three weeks in three days. I mean, there is one aspect of carpentry that I think will stay forever, which is the more artisan side of carpentry. We will appreciate things that are made that have been touched by the human hand. I think there will be a huge impact in retail in terms of being influenced by automation. Probably the cashier, you probably don't need someone there necessarily to take that consumer's money. That can be done quite simply, and that's me. That's what you're doing? (laughing) But at the same time, just from having a job, there is a biological need met there, which I think we're overlooking a lot. I think we might not have a great depression economically, but actually mentally. AI is clearly going to create a whole new raft of jobs, so there are the people who actually build these AI systems. I mean, if you have a robot at home, then every now and then, you're gonna need somebody to swing by your home to check it out. There will be people who need to train these robots and there will be robot therapists, there will be obedience school for robots and other kinds of, so, it's not, I mean, I'm not joking. What should these young people do today or tomorrow to get ready for this? There really is only one strategy, and that is to embrace the technology and to learn about it, and to understand, as far as possible, what kind of impact it has on your job and your goals. I think the key skills that people need are the skills to work with machines. Don't think everyone needs to become a coder, in fact, if artificial intelligence is any good, machines will be better at writing code than humans are, but people need to be able to work with code, work with the output of those machines and turn it into valuable commodities and services that other people want. I disagree that we're gonna necessarily have to work with the machines. The machines are actually gonna understand us quite well. So, what are out strengths, what are human strengths? Well, those are our creativity, our adapitability, and our emotional and social intelligence. How do people get those skills? (laughing) Well, if they're the important skills. Well, I think the curriculum at schools and at universities has to change so that those are the skills that are taught, those are the skills that are barely taught, if you look at the current sorts of curriculums, you see you have to change the curriculum so that those have become the really important skills. A lot of these discussions seem to be skirting around the issue that really is the core of it, is that the economic system is really the problem at play here. It's all about ownership of the AI and the robotics and the algorithms. If that ownership was shared and the wealth was shared, then we'd be out sharing that wealth. The trend is going to be toward big companies like Amazon and Google. I don't really see fragmentation because whoever has the data has the power. Data is considered by many to be the new oil because as we move to a digital economy, we can't have automation without data. What we see as an example is value now moving from physical assets to data assets. For example, Facebook. Today when I looked, the market capitalization was about 479 billion dollars. Now, if you contrast that with Qantas who has a lot of physical assets, their market capitalization was nine billion dollars. But you can go a step further, and if you look at the underlying structure of Qantas, about five billion dollars can be contributed to their loyalty program, which is effectively a datacentric asset that they've created. So, the jobs of the future will leverage data. The ownership of data is important because, you think about Facebook. Over time, Facebook learns about you, and over time, the service improves as you use it further, so whoever gets to scale with these datacentric businesses has a natural advantage and natural monopolistic tendency. In 20 years time, if big corporations like Google and Facebook aren't broken up, then I will incredibly worried for our future. Part of the reason why there are so many monopolies is because they've managed to control access to that data. Breaking them up, I think, will be one of the things we need to do to be able to open the day traps so that all of us can share the prosperity. But the global economy is not, is very rich and complex, and so, you know, you can't just, Australia can't just say, oh, we're opening the data. Well, I just also think we're leaving a section of the population behind, and some people in our country can't afford a computer or the internet or a home to live in. It'd be a bit crazy to just let it all go, free market, just go crazy, because we don't know if everyone is on that make the world a better place type thing. I personally don't want to be served by a computer even if I am buying a coffee and things like that. I enjoy that human connection, and I think that human connection's really important for isolated people. And that job might be really important for that person and creating meaning in their life and a purpose in their life, and, you know, they might not be skilled enough to work in another industry. My first thought is that if it is about human interaction, why do you need to have a, be buying a coffee to have that human interaction, why not just have the machine do the transaction and people can focus simply on having a conversation? Perhaps part of that is to simply say, it is a productive role in society to interact, to have conversations, and we can remunerate that and make that part of people's roles in society. It could be, a lot of things around caring, interpersonal interactions, the type of conversation you were talking about, I think they'll become an increasingly important part of the way that we interact, the way we find meaning, and potentially the way we receive remuneration. I think we all have choices to make, and amongst those are the degree to which we allow or want machines to be part of our emotional engagement. Will we entrust our children to robot nannies Algorithms can be taught to interpret and perceive human emotion. We can recognize from an image that a person is smiling, we can see from a frown that they're angry, understand the emotion that's set in text or in speech. And you combine that together with other data, then yes, you could get a much more refined view of what is that emotion, what is being expressed. But, does an artificial intelligence algorithm actually understand emotion? No, not presently. We're in the early days of emotion detection, but this could go quite far. You could certainly see emotional responses from algorithms, from computer systems in caring for people, in teaching, in our workplaces. And to some extent, that's already happening right now as people interact with bots online, ask questions, and actually feel like oftentimes, they're interacting with a real person. (calm music) When Tay was released in the U.S. with an audience of the 20 to 25 year olds, the interactions that Tay was having on the internet included hate speech and trolling. And it only lasted a day, but it's a really fascinating lesson in how careful we need to be in the interaction between artificial intelligence and its society. The key thing is, what we teach our AI that reflects back to us. First, you know, you'll kind of want the robot in your home because it's helpful, next minute you'll need it because you start to rely on it, and then you can't live without it. I think it sounds scary, to be honest, the thought of replacing that human interaction and even having robots in your home that you interact daily with like a member of the family, I think, yeah, really human interaction and real empathy can't be replaced, and at the end of the day, the robot doesn't genuinely care about you. Well, I think you certainly can't stop it, I mean, we're in, there's not way to stop it. Software systems and robots of course can empathize, and they can empathize so much better than people because they will be able to extract so much more data and not just about you, but a lot of people like you around the world. To go to this question of whether we can or cannot stop it, we're seeing, for example, in the United States already, computers, algorithms being used to help judges make decisions, and there, I think, is a line we probably don't want to cross, we don't want to wake up and discover we're in a world where we're locking people up because of an algorithm. I realize that it's fraught, but all of the evidence says that AI algorithms are much more reliable than people, people are so flawed and they make many, you know, they're very biased, we discriminate, and that is much more problematic, and the reason is that people are not transparent in the same way as in AI algorithm is. Humans are deeply fallible. I more veer on the side of saying that yes, I do not necessarily trust judges as much as I do well-designed algorithms. The most important decisions we make in our society, the most serious crimes, we do in front of a jury of our peers, and we've done that for 100s of years, and that's something I think we should give up only very lightly. Well, Nathan, what do you think? Well, I think ultimately, I don't know far you want to go with this discussion. (laughing) Like, how far into the future, because ultimately what's gonna end up happening is that we're gonna become the second intelligent species on this planet, and if you take it to that degree, do we actually merge with the AI? So, we have to merge our brains with AI, it's the only way forward, it's inevitable. But we won't be human then, we'll be something else. Superhuman. Superhuman. There's a choice. Do we not value our humanity anymore? We started off talking about jobs. But somehow, artificial intelligence forces us to also thing about what it means to be human, about what we value and who controls that. So, here we are, on the precipice of another technological transformation. The last industrial revolution turned society upside down. It ultimately delivered greater prosperity and many more jobs, as well as the eight hour day and weekends. But the transition was at times shocking and violent. The question is, can we do better this time? We don't realize that the future is not inevitable. The future is the result of the decisions we make today. These technologies are morally neutral, they can be used for good or for bad. There's immense good things they can do, they can eliminate many disease, they can help eliminate poverty, they can tackle climate change. Equally, the technology can be used for lots of bad. It can be used to increase inequality, it can be used to transform warfare. It can be used to make our lives much worse. We get to make those choices. (soft music) |
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