 My name is Dr. Connor McGinn. I'm an assistant professor in the School of Engineering at Trinity College. As a kid I enjoyed kind of transformer cartoons and a lot of machines kind of got my interest at that stage. And I think from an early age I knew I wanted to be an engineer. As I started to study engineering I learned a little bit more about robotics and I kind of saw how robots can combine kind of machines which I really enjoyed with AI and machine learning and these kind of things. And I was really excited by the possibilities of what might happen if you put these things together. Then I also kind of noticed that robotics can really help solve some big problems we face in the world. So I guess all of these things together sort of confirmed it for me that this was what I wanted to do with my life. The core mission of our research group is to build technology that can empower people. We see a responsibility there to be able to use our understanding of science, to be able to create things that can help people and make their lives better. We see robots as a quite unique way of doing that. This is a technology that I don't think we've seen before. With a robot it's like a computer which just kind of sits there and we have to go and approach it. It's somewhat passive. A robot is able to move around, it's able to actually act in the world. Am I able to combine, you know, to take computers and to be able to extend them, combine them with physical machines to be able to develop new approaches in sensing, to be able to understand the world around it and then to be able to take that information and do things that are useful from it. This is an exciting thing that we've never really seen before. And really what our group is trying to do is to understand, you know, with that power of what you're going to use it for. We spend a lot of time, for that reason, working very closely with the people we think that technology can help, trying to get them involved in the design process so that what we create reflects, you know, the needs that they actually have and they feel as opposed to unfortunately quite often what happens is where we come up with some cool science and then we try to figure out how we can apply it. The main project that we've been working on over the last over the years is, as you mentioned, Stevie. Stevie is what we call a social assistive robot. It's a robot that can move around, it's got arms, it's got a head, it's able to interact through social interaction as opposed to using a kind of a tablet or remote control. We think this is potentially going to be very useful for many different types of problems. You know, because it's somewhat shaped like a person and it has some of the features that people have, it's very adaptable. So whether that's, you know, being able to do things physically, that might be to go and get an object. It might be to open a door or control something. These are applications we see happening down the line. But maybe in the shorter term it's able to do things that have more of a social function so it can remind you to take medication perhaps. One of the areas we've seen, you know, a huge amount of positive feedback is in its ability to play games and try to keep people entertained quite often. The older demographic that we test this technology with, they can be quite lonely and quite bored. So being able to provide that kind of social simulation is something that we think has huge potential. It's very difficult to know when you design a robot if people are going to like it or not. When we build robots to do tasks, it's not that difficult. If we want to have a robot, we want to develop a robot that can pick something up. There's lots of mats we can use and there's lots of techniques we can use to figure out exactly what sort of motors we should use, what sort of materials we should use. These are kind of logical decisions we can make. When it comes to more subjective things like if people are going to like the robot, it's going to be fun, how they're going to perceive it. Is it going to be threatening? Is it going to be something that they trust? These are much harder things to design for. For us, the way in which we try and get past this is by trying to involve the users in the design process. So we run workshops, we run focus groups, we show them some of the things we're working on, we get the feedback on it. Through taking an iterative approach over time, what we create, we help reflects what people want in the technology. With the new machine that we've built, it's taken us nearly two years to develop it. We've probably gotten feedback from more than 2,000 people in total if we were to count. As a team, we work very closely with each other, we're very interdisciplinary. Ultimately, what happens is that we've managed to develop the technical aspects of it. So this new robot has got far more sensors, the computing is there to be able to do really sophisticated things, to be able to utilize the state-of-the-art machine learning and AI. At the same time, we feel that the aesthetic of the robot, how it appears, how it expresses itself, this really addresses the more subjective aspects of the applications we're going after. Equally, we think the applications it's doing, we're deploying it to do, addresses needs that are quite underserved by either existing technology or existing resources within retirement communities, which is kind of our key market. I think everyone who's working on robotics in the university is a dreamer somewhere. So certainly, I have a vision of what the future might look like. I think in the best case scenario, we'll be able to use robots and AI to solve some pretty fundamental problems we face. With a robot like Stevie, we see a rapidly aging population. We see very few people, well, relatively speaking, we see very few people of a working age who are going to be able to look after people who are living longer. When those people get older, their healthcare needs increase. We see this as being a huge healthcare challenge. If we don't do something about it, something, I think, quite, if we don't do something radically different from what we're currently doing, we're going to have healthcare systems across the world just buckle at the demand. So things like this, I think, are really good applications of robots. Other applications where I think robotics is really exciting that I can see radical changes would be in areas like where people maybe are paralysed. We can see exoskeleton technology that's able to maybe help them walk again. This is exciting technology that the potential of is pretty profound. On the other hand, I think that if we're not careful, if the right sort of steps are taken to prevent the misuse of the technology, we see kind of weaponry which can be lethal because of this technology. We can see the potential for mass unemployment as a result of automation that is purely driven by capital means. And I think there's responsibility on researchers and also on people who run companies to make sure that what they're building is a world that they want to see and that's something that makes people money. And I think that if we're not realistic about what these things are doing, if we're not knowledgeable and reflecting on what the consequences of actions are, then that's problematic. So what I try and do and what I think our team tries to do is to kind of be the change that we want to see and to focus on the development of the technology that makes a positive difference while being quite vocally and proactive in speaking out against the misuse of the technology. It's really exciting at the moment and I remember when I was kind of starting out in the area when I was starting out to learn about AI and to learn about robotics. I of course was looking around to see who was doing things here and compared to other places in Europe and the world, there wasn't much going on and to see how much things have changed in a relatively short period of time. People are saying that Dublin is now the AI capital of Europe. They're comparing it to Silicon Valley in terms of the activity that's going on here in the space. It makes it an incredibly exciting place to be. It's incredible to be able to see what has grown to be a very active community. There's multiple times a month now, there's meetups and there's events where you can go and network with people, professionals in the area with students, with academics who are really interesting to work in the science. I think that as we project forward over the next couple of years and we see more and more companies start to come out and do interesting things, the opportunity to collaborate will really start to become apparent. When you see the kind of things that are, Dublin has gone for it, we're a very social species, we live very close together. Our universities are in close proximity. These are things that I think many bigger countries that might have, at least in theory, better universities, better everything. They struggle to be able to work together. We consider what this kind of future of interdisciplinary AI, machine learning, robotics, what this sort of looks like, being able to have the right people in the right place at the right time is a critical ingredient and it seems to me that Dublin just might be that place. We spend so much time in the university here, we're engaged in conversations with each other, whether it's with students, whether it's with colleagues, whether it's conferences, whether the researchers, we really get the opportunity to engage with the general public. What I'm excited about doing at Predict is being able to share some of the research that we're doing here. Not only that, but being able to share some of the exciting results that we're getting from deploying these robots in real-world environments. Quite often we see fancy YouTube videos of robots doing interesting things, but rarely do we see them interacting with people, especially people in real environments. I think that what we hope to show and predict will be some evidence that what we're building works and what we're building has a real impact. I think that when we get around to that time we'll have some results that are going to open people's eyes to the technology stuff that maybe they thought was a little bit further down the line is actually maybe a little bit closer to hand. I think we'll be able to talk and demonstrate how real use cases of social robots and be able to show that what we're not doing is replacing people's jobs. What we're not doing is often perceived to be trying to purely reduce costs. What we're doing is we're building a technology that's able to extend the capabilities of people. This is a force multiplier. This enables people to do more with less. I think if ever there was a need and a time for a technology that could do this in the healthcare space, now is it.