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Chapter 1: What is the vision for future robot-human interactions?
Hello. Let's start with a quick test. If I ask you to conjure up an image of a useful and reliable robot helper, what springs to mind? Some of you might be thinking of those industrial robotic arms used in car assembly lines, or perhaps an explosive ordnance bot, the remote-controlled devices used by bomb disposal teams. Others might be focusing on fictional robots, R2-D2 from Star Wars perhaps.
Not just a tool, but a machine that can actually interact with humans. One that is communicative, responsive and even trustworthy. In fact, those sorts of relationships are the focus for today's guest. Helen Hastie is a professor of human-robot interaction and head of the School of Informatics at the University of Edinburgh. Her mission is to develop robots that don't just think, but connect.
Systems that will competently perform their tasks, but which can also hold a natural conversation and explain themselves clearly to their human colleagues. Although, as we'll hear, that's not quite as straightforward as Star Wars made it seem.
Helen's career has taken her from developing early dialogue systems, the ancestors of today's generative AI, to working on sophisticated bots that can serve coffee with a side of small talk, teach struggling kids with empathy, or provide calm and confident decisions as triage nurses. She's also driven some of the UK's flagship robotics initiatives, not least as co-lead of the National Robotarium.
Ultimately, her ethos is robotics for all, shaping a future where robots aren't just in our world, they're part of it.
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Chapter 2: How has Helen Hastie's career shaped her views on robotics?
Ideally, a welcome one. Professor Helen Hastie, welcome to The Life Scientific.
Thanks for having me.
Now, Helen, a big part of your work is getting people to trust and welcome robots in everyday settings. What would you say is the biggest misconception people have that might put them off having a robot colleague?
So we see in the media and in sci-fi movies, these robots that are highly functioning, that can do many, many jobs and are social and cognitively quite intelligent. Now, we are far from that. We do have some robots that can perform very, very well on specific tasks, but these tend to be very narrow tasks. So we are quite a long way from these all functioning, intelligent robots.
I suppose a lot of us hear the word robot and do think of those humanoid versions from sci-fi movies that can do everything, including take over the world, of course. But I gather there are actually quite a few issues with making robots in human form.
Sure. So robots that generally look like humans, not necessarily those with legs, but in some kind of human shape, can be really useful for certain settings. But we have to be really careful. There's a phenomenon called the uncanny valley.
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Chapter 3: What misconceptions do people have about robots?
And as robots become closer to looking like humans, particularly in terms of detailed looks, this can actually be quite unsettling. So it's good that robots look a bit like us, but Not too much like us.
I mean, so is there a sweet spot of how human a robot should look if it's going to be accepted?
Yes, most definitely. And it's very dependent on the task. So robots in the home, maybe it's good they look a bit like us. But robots working in factories or warehouses or stacking shelves, it's actually better if they look like they know what they're doing in terms of the function that they're designed to do.
So having wheels, for example, rather than legs.
Exactly.
Yes. Yeah. Thinking about trustworthiness in robots does make me wonder about the current concerns around over-reliance on large language models, like chat GPT, for example, having influence over vulnerable youngsters or isolated individuals. Is there an element of risk to making robots more trustworthy, as in the more we trust them, the greater the risk of manipulation?
So it's very important that we install the appropriate amount of trust.
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Chapter 4: Why is the appearance of robots important for trust?
So it's important not to overtrust robots and it's also important not to undertrust them. For example, a robot that's used in surgery that is highly accurate, maybe more so than a human. It's really important that we do adopt these robots if they are capable of performing properly.
So in some cases, we should trust them because they've been designed to do something better than we can.
But it's also important not to overtrust. So you shouldn't overtrust an autopilot in a ship, for example. It's important that you always have the human eye on it.
Yes, indeed. So, Helen Hastie, do you remember where this fascination with AI and robots first started for you? Were you particularly into tech or sci-fi as a kid?
Well, I grew up in a house that had early computers. My father was an early adopter. We had Commodore PC, for example, in the house. And he was always putting together computers. So I think from an early age, I was surrounded by tech.
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Chapter 5: What challenges exist in creating trustworthy robots?
You grew up in Aberystwyth in Wales. Tell me a bit about your family.
My father was a lecturer in international relations and my mother in classics. And I'm the youngest of four. Most of us have PhDs in the family, to put it like that.
But across a wide range of disciplines, clearly. I gather you felt rather lost at school because you love both science and languages. And it didn't feel like there was a way to follow both paths. But then a lightbulb moment. Tell me about discovering linguistics.
So when you're 16, you have to decide what three A-levels you're going to do. And I wanted to do all the languages and all the sciences. And I think my father could see a bit of a conflict inside me. So he bought me this encyclopedia of language. This really caught my attention.
Chapter 6: How do robots learn to interact with humans effectively?
And linguistics being the science of language really kind of found a sweet spot with me.
Okay. So off you went to study AI and linguistics at Edinburgh, followed by a master's in computational linguistics at Georgetown University in the United States. What drew you to America?
So I'm a half American, so I wanted to study out there. And I was given a fellowship for, believe this or not, Welsh females studying science at master's level in America.
Excellent.
Very niche. I'm not sure there was many of us. So I got that fellowship and off I went to Georgetown.
Right, right. You returned to Edinburgh to do your PhD in speech and language technologies. Then you decided to take a year out.
I married Stuart in the year 2000 and we took a year-long honeymoon, which we were very fortunate to do, travelling around the world, which included going over land in a truck across Africa and then Asia and Australia. And then we stopped off in the States having a degree in technology.
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Chapter 7: What insights were gained from the Robo Barista experiment?
I thought I'd be quite quick to get a job. But unfortunately, that was the time of the dot-com bubble burst. So everything was basically shuttered up. On the west coast of the US. So then we moved over to the east coast. And that's when I got a research position at AT&T Research Labs.
One of your biggest projects there was called How May I Help You? One of the first truly interactive voice response systems. First of all, what was it designed to do?
So IVRs, as we call them, were pretty terrible back then. Basically, most of them would allow you to say things like say one for billing, say two for technical support. So not a very rich interaction, not much more benefit than pressing the button on the phone. So how may I help you was different in that it was an open question.
And so the system had to understand a whole range of different responses and then channel the customer to the appropriate department. What I was doing was I was working with Marilyn Walker and we were looking at how we evaluate these systems.
Chapter 8: How can robots improve quality of life for the elderly?
I mean, that advance was quite revolutionary at the time, an ancestor, if you like, to the voice assistants we use today, you know, like Siri and Alexa and so on. But doing this 25 years ago, what sort of difficulties did you run into?
So we called them spoken dialogue systems, and we would divide them into different parts. So you would have the speech recognizer understanding the words, and then you need to convert those words into meaning and decide what to say next, and then what the words would be, and then turn that into a computer voice.
Nowadays, it's all one big end-to-end system, and it's trained on much data, large compute. So it's tackled in a different way, but back then we had to divide into each component, and each component had their own challenges.
And I mean, we should say this sort of voice assistant technology is quite different from today's all singing, all dancing, large language models. Correct. Can you explain how?
We didn't have the data back then. We were using language models, but they weren't large.
OK, well, a couple of years later, Helen, you joined Lockheed Martin, also in New Jersey on the East Coast, and you developed an onboard AI assistant for ships called Suzy. Tell me about that.
At Lockheed Martin, it was all about applications and putting these systems where they would be used and adopted. So one of these was on a ship and it was using the intercom and it was sensorised. So you could call up Susie on the intercom and it would tell you, for example, the starboard engine temperature. So the important thing here was the equipment was in situ and it may be of use.
OK, well, having a named AI assistant like Susie helping you control a vehicle does have slight overtones of hell from 2001 A Space Odyssey. I'm afraid I can't do that, Dave. That's my best hell voice. So do you have any reassuring words for people concerned that we're hurtling towards that sort of AI dystopia?
So in critical situations, we put in certain guardrails. It's important that we test them properly. But the technology is advancing so rapidly that we really have to think about this now.
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