00:00 You’re going to find a lot more robots
00:02
00:02 in your life in different situations,
00:04
00:04 whether it’s at work, in the office, in
00:06
00:06 your leisure time.
00:06
00:06 >> They’re robots that look like people
00:08
00:08 that will be cooking your cheese
00:10
00:10 omelette. They will be looking after
00:12
00:12 your granny in hospital. They will be
00:14
00:14 integrated within our society.
00:16
00:16 >> The potential for healthcare is huge.
00:18
00:18 There’s things that exist right now that
00:19
00:19 they that could be used by the NHS all
00:22
00:22 over the UK and be making a huge
00:23
00:23 difference. I think that’s the biggest
00:24
00:24 thing that we need to do over the next
00:26
00:26 few years is is really turn our
00:28
00:28 attention to how are we going to live in
00:30
00:30 this world with with robots and humans
00:32
00:32 working side by side.
00:35
00:35 >> Welcome to tomorrow the future forum
00:37
00:37 podcast. I’m Victoria Usher
00:39
00:39 >> and I’m Ollie Barrett and here at the
00:42
00:42 future forum we’re all about bringing
00:43
00:43 very different people together from
00:45
00:45 completely different industries and
00:46
00:46 walks of life to shape the future
00:49
00:49 together. Now, Victoria, today’s guest
00:51
00:51 is someone who leads a fascinating
00:53
00:53 organization. I’m already intrigued
00:55
00:55 called the National Robotarium.
00:58
00:58 >> That’s right. Stuart Miller, CEO of the
01:00
01:00 business, fascinating guy looking at
01:03
01:03 what robotics is, what it’s going to be,
01:06
01:06 and how it’s going to be integrated
01:08
01:08 within the workplace, within our homes,
01:10
01:10 within hospitals. We have got such a
01:12
01:12 fantastic conversation to have
01:13
01:13 >> and and I already feel like I’m going
01:14
01:14 back to into the classroom here. When we
01:16
01:16 talk about robots, are we talking like
01:18
01:18 C3PO Star Wars here? Oh,
01:20
01:20 >> is it is it in the car factory?
01:22
01:22 >> So much more. This is the next
01:24
01:24 generation of of robots. So, these are
01:25
01:25 humanoids. So, people uh again, you see
01:29
01:29 people, they’re not people. They’re
01:30
01:30 robots that look like people that will
01:32
01:32 be cooking your cheese omelette. They
01:34
01:34 will be looking after your granny
01:36
01:36 hospital. They will be integrated within
01:38
01:38 our society just as a whole population
01:42
01:42 within themselves. So, it’s going to
01:43
01:43 completely blow out the water. anything
01:45
01:45 we’ve experienced with AI. This is the
01:48
01:48 next wave of innovation.
01:49
01:49 >> Right. So, we’re all ears. Let’s get
01:50
01:50 ready to welcome uh today’s guest.
01:53
01:53 >> Let’s dig in and find out. So, Stuart,
01:57
01:57 can you please give us a glimpse of the
01:60
01:60 future? What are we going to be looking
02:01
02:01 at in say 10 years time? What can we
02:04
02:04 expect in our workplace, in our homes?
02:06
02:06 What is it going to look like in a world
02:08
02:08 of robotics?
02:09
02:09 >> Well, it’s going to be a lot different
02:10
02:10 from what it is today. Um, you’re going
02:13
02:13 to find a lot more robots in your life
02:15
02:15 in different situations, whether it’s at
02:17
02:17 work, in the office, in your leisure
02:18
02:18 time. Um, they’re going to range in
02:22
02:22 type, uh, from very simple, very robot
02:25
02:25 looking things to humanoid looking and
02:28
02:28 behaving robots. Uh,
02:32
02:32 the the development uh, of this kind of
02:35
02:35 technology is moving incredibly rapidly.
02:38
02:38 I’m sure we’ll get into that a little
02:39
02:39 bit later, but um as a result uh a
02:43
02:43 number of companies around the world are
02:45
02:45 investing heavily in developing this
02:47
02:47 technology and bringing it to the
02:48
02:48 market. And we’ve seen huge advances
02:51
02:51 just in the last 18 months or so uh
02:53
02:53 particularly around humanoids that are
02:56
02:56 pointing towards
02:58
02:58 uh assistance at home helping with
02:60
03:00 domestic chores, helping with uh looking
03:03
03:03 after the children, helping with
03:04
03:04 security uh and being able to most
03:07
03:07 importantly interact with the world that
03:10
03:10 we created for ourselves without them
03:12
03:12 having without us having to adapt the
03:14
03:14 world to them. So giving them all kinds
03:16
03:16 of capabilities, walking, talking, being
03:19
03:19 able to identify objects, being able to
03:22
03:22 touch things, pick things up, move them
03:24
03:24 around, use the kind of tools that that
03:27
03:27 we currently use uh without having to
03:29
03:29 adapt those tools for the for the robot
03:32
03:32 to use. And that type of technology
03:34
03:34 because of its flexibility and because
03:36
03:36 of its ease of use and its cost point is
03:40
03:40 going to become incredibly accessible.
03:42
03:42 Um, so I think in 10 years time you’ll
03:46
03:46 see almost as many robots in your life
03:48
03:48 as you see humans at the moment.
03:50
03:50 >> And that is just mindblowing. All of
03:52
03:52 those things that you’ve just put there,
03:54
03:54 the home, the boring jobs, the potential
03:58
03:58 for having a population that basically
04:00
04:00 mirrors our own is huge. And I I think
04:02
04:02 we want to take uh our time here to
04:05
04:05 unpack all of those. Um, what I’d like
04:08
04:08 to do as well is take a a look in the
04:10
04:10 rear view mirror and ask what do we know
04:13
04:13 now about robotics that we didn’t know
04:15
04:15 then 10 years ago. So, what’s what’s
04:17
04:17 happened in that that time? Where why
04:19
04:19 are we here where we are now?
04:23
04:23 >> I think the biggest thing that’s changed
04:24
04:24 and it’s only been in the last couple of
04:26
04:26 those 10 years has been the bringing
04:29
04:29 together of artificial intelligence and
04:32
04:32 physical robotics. If you’d asked me
04:34
04:34 four or five years ago to describe what
04:36
04:36 a robot was, I would have probably told
04:37
04:37 you it was some kind of a autonomous
04:39
04:39 system capable of making sense of the
04:42
04:42 world for itself and on that information
04:44
04:44 making decisions for itself to carry out
04:47
04:47 tasks. Some of those were mobile, some
04:49
04:49 of them were static, some of them had
04:51
04:51 arms, some of them had different types
04:53
04:53 of ways of interacting with the world.
04:56
04:56 Now I think increasingly what we’re
04:57
04:57 seeing is still a mixture of physical
05:00
05:00 forms but very much artificial
05:03
05:03 intelligence based uh platforms that are
05:07
05:07 able to train and learn from example uh
05:11
05:11 and repetition that we can interface
05:14
05:14 with through voice command uh and
05:17
05:17 general conversation in a much more
05:19
05:19 sophisticated way than we were ever able
05:21
05:21 to do a few years ago. So that
05:23
05:23 introduction of artificial intelligence
05:24
05:24 means that now that the definition of a
05:26
05:26 robot is very much the physical
05:28
05:28 embodiment or the physical manifestation
05:30
05:30 of artificial intelligence.
05:32
05:32 And actually I I personally have seen
05:34
05:34 some of these humanoids.
05:36
05:36 They I find them a bit freaky. I I
05:38
05:38 remember seeing at CES the big uh
05:40
05:40 consumer electronics show um in the west
05:42
05:42 coast of America. You had the the dogs.
05:45
05:45 This is a couple of years ago and and
05:47
05:47 they were they were actually quite
05:49
05:49 frightening looking. And it’s quite
05:50
05:50 interesting to conceptualize the fact
05:52
05:52 that, you know, I I have a four people
05:54
05:54 in my home. I will have four other kind
05:58
05:58 of humanoids in my home. It feels it
06:00
06:00 feels a little bit freaky, I have to
06:02
06:02 say. So, um, so they’re going to be
06:04
06:04 doing all of the boring jobs. Is that
06:07
06:07 what you’re saying here? So, I’ll have
06:09
06:09 somebody in my home as a personal chef
06:11
06:11 that’s going to be cooking my dinner.
06:13
06:13 >> Yeah. Yeah. And, um, it won’t be just
06:16
06:16 the boring jobs, but it will certainly
06:18
06:18 be the boring jobs. and other things. So
06:21
06:21 really those if you think about what
06:23
06:23 we’ve done over the last few decades in
06:25
06:25 terms of introducing new appliances into
06:28
06:28 our homes for convenience everything
06:30
06:30 from tumble dryers to dishwashers
06:33
06:33 um and you go back far enough fridges
06:36
06:36 and freezers those have all been labor
06:38
06:38 saving devices to to use a generalism.
06:41
06:41 Um the introduction of robotics into the
06:44
06:44 home is the same. We’ve already seen
06:46
06:46 quite a solid uptake of floor cleaning
06:49
06:49 robots and lawn mowing robots. Um, but
06:54
06:54 those are very much simple robots able
06:57
06:57 to do one task. What we’re going to find
06:59
06:59 is coming along next is more
07:02
07:02 sophisticated robots able to do multiple
07:04
07:04 tasks. Uh, and to be able to make sense
07:07
07:07 of the world in a much more
07:08
07:08 sophisticated way than your Roomba does
07:11
07:11 right now. that allows them to then
07:14
07:14 interact not just with physical objects
07:16
07:16 but with people as well uh and become
07:19
07:19 part of the family.
07:20
07:20 >> Two years ago, we couldn’t have imagined
07:22
07:22 what AI could do. I imagine we’re going
07:25
07:25 to see the same thing happen with
07:26
07:26 robotics. Um and from what you’re
07:29
07:29 saying, the AI is going to learn. So
07:32
07:32 that’s the component that’s changed
07:34
07:34 here, right? So you’ve you’ve probably
07:35
07:35 always had the ability in the hardware,
07:37
07:37 but it’s actually getting that AI
07:40
07:40 capacity in so I can say to my robot in
07:42
07:42 my home, make me a cheese omelette and
07:44
07:44 this is how I want it cooked and it will
07:47
07:47 then learn from that and I can program
07:48
07:48 it effectively.
07:51
07:51 >> Yeah. Exactly. Exactly. So the the
07:54
07:54 introduction of artificial intelligence
07:55
07:55 has really done a number of things for
07:58
07:58 robotics. Uh in one sense it’s improved
08:01
08:01 the control of the robot uh and its
08:03
08:03 ability to sense and and make sense of
08:05
08:05 the world. But then the big step change
08:09
08:09 really is that very few robots now are
08:12
08:12 handcoded or require u teams and teams
08:15
08:15 of people to write thousands and
08:17
08:17 thousands of lines of code for it to be
08:19
08:19 able to move its right arm in a
08:21
08:21 particular way. These are now learning
08:23
08:23 machines that are learning from either
08:27
08:27 real world situations where someone’s
08:29
08:29 demonstrating what they want them to do
08:30
08:30 or they’re learning from video or
08:33
08:33 they’re learning in some cases a lot of
08:36
08:36 increasing number of cases they’re
08:38
08:38 learning in uh simulated environments.
08:42
08:42 So the the artificial intelligence is
08:44
08:44 actually learning in a simulated world,
08:46
08:46 making its mistakes in that world and
08:47
08:47 learning how to carry out the tasks that
08:49
08:49 you wanted to do before then being
08:51
08:51 introduced into physical form.
08:53
08:53 >> Um what I’d love to get is just even
08:56
08:56 more snapshots if you like if we look
08:58
08:58 around the world as it is today. Forget
09:01
09:01 what’s coming uh towards us whether
09:04
09:04 that’s in hospitals, it could be
09:06
09:06 factories, it could be the home, uh it
09:08
09:08 could be a school. just help us
09:10
09:10 understand with a few more snapshots of
09:12
09:12 what’s currently happening. Take take us
09:14
09:14 to the edge of what’s already possible.
09:18
09:18 >> So right now there are um AI enabled
09:22
09:22 robots working in a number of different
09:24
09:24 large
09:25
09:25 um factories. They tend to be in uh
09:29
09:29 automotive. So Mercedes, BMW and Hyundai
09:32
09:32 have declared uh partnerships with
09:34
09:34 various humanoid manu uh robotic
09:37
09:37 developers and those robots particularly
09:40
09:40 uh figure robot has been working for
09:42
09:42 nearly a year now in a BMW factory.
09:44
09:44 >> Ju just help me understand though what’s
09:46
09:46 different in that last year because I
09:48
09:48 would have thought you’d say we’ve had
09:50
09:50 robots in BMW factories for decades. I’m
09:53
09:53 missing something here. So, the
09:55
09:55 difference is we’ve had robots, but
09:58
09:58 they’ve tended to be quite expensive.
09:60
09:60 They tended to be single use, so
10:02
10:02 painting or welding. Yeah.
10:04
10:04 >> Um or lifting heavy loads to to help
10:07
10:07 someone, for example, put the wheels on
10:08
10:08 and things like that. Um these robots
10:11
10:11 now are doing much more dextrous tasks,
10:14
10:14 ones that required humans in the past to
10:17
10:17 identify objects, place them in
10:20
10:20 particular ways. Um, the kind of
10:22
10:22 examples have been shown is loading up
10:24
10:24 an automated welding machine to weld
10:26
10:26 three pieces of metal together and then
10:28
10:28 removing that, putting it into a stack.
10:30
10:30 Um, but there’s also been demonstrations
10:32
10:32 of robots sorting through uh parcels,
10:36
10:36 the kind of thing you would you would
10:37
10:37 find in a in a distribution warehouse.
10:40
10:40 >> Yeah. And these when you say dextrous,
10:42
10:42 you’re talking about some of those fine
10:43
10:43 motor skills where the lazy conclusion
10:46
10:46 would have been, well, I think the
10:47
10:47 plumbers are safe. Your point is if a
10:50
10:50 hand can do it, a robot can do it.
10:52
10:52 >> We’re getting towards that. Yes. And
10:54
10:54 there’s a lot of research going into
10:55
10:55 dexterity all around the world because
10:57
10:57 the the key to robotics really being
11:00
11:00 useful is dexterity.
11:02
11:02 >> I can imagine a listener is already
11:04
11:04 thinking, look, if a system is growing,
11:06
11:06 you know, increasingly intelligent, is
11:08
11:08 iterating on all of the processes that
11:10
11:10 it has been undertaking? It’s one thing
11:12
11:12 to come up with a more sophisticated
11:14
11:14 answer in an LLM about a request that
11:18
11:18 you’ve put through or a prompt. It’s
11:20
11:20 another ball game entirely to then
11:22
11:22 perform a whole different set of actions
11:24
11:24 in the real world. And that comes with a
11:27
11:27 whole different set of gate gateways and
11:29
11:29 thought processes if we’re going to
11:31
11:31 green light that.
11:33
11:33 >> Correct. It’s very much a neural network
11:36
11:36 based approach as opposed to what most
11:39
11:39 people might be familiar with in terms
11:40
11:40 of LAR language models and the kind of
11:42
11:42 things that they may be interfaced with
11:43
11:43 in chat GBT and the like. This is a a
11:45
11:45 different type of AI.
11:46
11:46 >> In fact, actually, I want to take a step
11:48
11:48 back and find out a little bit more
11:50
11:50 about your role and where you’re coming
11:52
11:52 from um in all of this. So, so tell us a
11:55
11:55 little bit more about your role as a CEO
11:57
11:57 um at the National Robot. Um what are
12:00
12:00 you doing? What’s your remitt? What’s
12:02
12:02 your vision? uh would love to know in
12:04
12:04 the context of everything we’ve been
12:05
12:05 talking about.
12:07
12:07 >> Yeah, sure. So, we were set up just over
12:10
12:10 four years ago to try and move the dial
12:13
12:13 on robotics in the UK. So, the National
12:15
12:15 Robotarium National is is for the whole
12:17
12:17 of the UK and that’s
12:20
12:20 uh found itself taking four main forms.
12:23
12:23 One is helping companies that are
12:26
12:26 looking to adopt and use robotics in
12:28
12:28 their in their operations. And that’s
12:30
12:30 not just companies that includes health
12:33
12:33 care and social care and agriculture and
12:35
12:35 all you know basically all sectors of
12:37
12:37 the economy. So a practical support and
12:40
12:40 help bringing expertise uh connecting
12:43
12:43 them to suppliers making sure that they
12:46
12:46 know how to test and validate what
12:48
12:48 they’re doing and get to the point where
12:50
12:50 they didn’t have a robot but now they do
12:52
12:52 have a robot. Alongside that we do a lot
12:55
12:55 of work with robot developers,
12:57
12:57 particularly those that are uh moving
12:60
12:60 into building the robots for the first
13:02
13:02 time. Uh we have resident companies here
13:05
13:05 at the National Robbitarium at the
13:07
13:07 moment uh 10 or 11 who are doing exactly
13:10
13:10 that and we have a wider network that we
13:11
13:11 support that are not actually based here
13:14
13:14 but draw on the facilities and the
13:17
13:17 engineering expertise that we’ve got.
13:19
13:19 And then alongside that we uh pull
13:23
13:23 through research as and when it’s
13:24
13:24 required and encourage research in
13:27
13:27 certain areas uh as we’re seeing demand
13:30
13:30 from those adopters. And then finally
13:33
13:33 and very importantly, we try and raise
13:35
13:35 awareness of robotics in the public in
13:37
13:37 general, particularly with school
13:40
13:40 >> uh engagement, but also just with
13:42
13:42 general public engagement. helping
13:44
13:44 everyone to realize in part what we’re
13:46
13:46 talking about here, what’s on the
13:48
13:48 horizon, what the impacts of that might
13:51
13:51 be so that they can think about those
13:53
13:53 for themselves and really try and make
13:56
13:56 sure that we are as a nation better
13:59
13:59 equipped for what is inevitably going to
14:02
14:02 come which is this mix of humans and
14:03
14:03 robots living side by side in future. I
14:06
14:06 mean it feels like I don’t feel like we
14:08
14:08 were prepared for the large language
14:10
14:10 models and how it’s it has hit quite
14:13
14:13 dramatically. I know people are
14:15
14:15 underplaying it but it has you you can
14:17
14:17 see how it’s hitting across industry and
14:19
14:19 I know before we spoke uh Stuart about
14:21
14:21 one of your jobs is to educate on what
14:24
14:24 is coming up so that there’s a
14:25
14:25 preparedness here in society and in
14:28
14:28 business for what we can expect to see
14:31
14:31 once we have this robot population that
14:33
14:33 comes in. So, can you just talk to us a
14:35
14:35 little bit more about that and and what
14:37
14:37 you feel needs to be done to get us to
14:38
14:38 that point?
14:40
14:40 >> It’s really important that as a society
14:43
14:43 in the UK and and right around the
14:45
14:45 globe, but you know, our remit is to to
14:48
14:48 try and help the UK. It’s really
14:49
14:49 important that I that society has a
14:52
14:52 better understanding of what not so much
14:55
14:55 the technology, but what the
14:57
14:57 implications of the technology are.
14:59
14:59 We’ve seen it with a number of different
15:00
15:00 technologies. We can talk about mobile
15:02
15:02 phones. Um, we can talk about the
15:04
15:04 internet. We can talk about social
15:06
15:06 media. They they all come with their ups
15:09
15:09 and downsides. Um, and I think what we
15:12
15:12 found with the introduction of these
15:13
15:13 technologies in the past is we haven’t
15:15
15:15 prepared the population as a whole early
15:18
15:18 enough to understand and be able to ask
15:21
15:21 the right questions, understand the
15:23
15:23 answers that they’re getting and make
15:24
15:24 decisions for themselves about how they
15:26
15:26 want to embrace that technology. And
15:28
15:28 that’s why, for example, we’re seeing
15:30
15:30 that retrospectively, we’re bringing
15:32
15:32 legislation about the age of people that
15:34
15:34 we want to be able to use phones and
15:36
15:36 whether we should be using them in
15:37
15:37 schools, etc. We’ve had smartphones for
15:42
15:42 18 years now.
15:44
15:44 Um, so it seems a bit late in the day to
15:47
15:47 be doing, not saying we shouldn’t be
15:48
15:48 doing it, I’m just saying that it seems
15:50
15:50 a bit late in the day that we’re
15:51
15:51 catching up with that technology now.
15:53
15:53 And it would be good to think that we’ve
15:55
15:55 learned enough from all of those
15:56
15:56 examples to do more
15:59
15:59 >> so that when the robots arrive, we’re
16:02
16:02 ready for them.
16:03
16:03 >> Well, on that, Stuart, you could say
16:05
16:05 that we are just catching up in using
16:08
16:08 those technologies or educating around
16:10
16:10 them. Um, somebody watching this might
16:13
16:13 say, “Yeah, we’re catching up by banning
16:14
16:14 them.” um which is exactly the opposite
16:17
16:17 of what we could be doing which is
16:20
16:20 empowering a generation to use and
16:22
16:22 understand them. Um it seems to me
16:24
16:24 there’s a contradiction from time to
16:26
16:26 time that says on the one hand we need
16:28
16:28 all of the next generation to be fully
16:30
16:30 fluent in things like robotics and
16:32
16:32 artificial intelligence and step one on
16:34
16:34 that journey is to ban them from using
16:35
16:35 it.
16:36
16:36 >> Yeah, I think I think it’s really
16:37
16:37 important that we recognize that the
16:40
16:40 world we live in today has got a lot of
16:41
16:41 new technologies coming along. It’s not
16:43
16:43 just in in robotics. Um, you know, we’ve
16:48
16:48 already talked about AI and even if it’s
16:50
16:50 just those two, that’s a that’s a huge
16:52
16:52 change in the future. But then you you
16:54
16:54 throw in the potential with quantum, you
16:57
16:57 throw in what’s happening in life
16:58
16:58 sciences and the the pace and extent of
17:02
17:02 change over the coming years is going to
17:05
17:05 be quite huge. Probably something we’ve
17:07
17:07 never actually experienced before. And
17:10
17:10 again, that makes me think that we need
17:12
17:12 to try and help everyone be prepared.
17:14
17:14 Now, it’s by no means an easy task, but
17:17
17:17 I do think that we need to put more
17:19
17:19 effort into helping the the population
17:23
17:23 at large to understand what questions to
17:27
17:27 ask if if nothing else, but also how to
17:29
17:29 make their own mind up about how they
17:31
17:31 want to use these technologies rather
17:33
17:33 than it being, you know, state imposed
17:37
17:37 uh after bad experiences, which is what
17:39
17:39 we’re tending to see at the moment.
17:40
17:40 >> Yeah. And Stu, let’s just see if we can
17:42
17:42 um let’s um let’s pick on Victoria here
17:45
17:45 because uh just as a tiny experiment,
17:48
17:48 she’ll kick me afterwards. When you
17:50
17:50 described seeing that robotic dog, and I
17:53
17:53 think we know the one that’s being
17:54
17:54 talked about here. I think it’s made by
17:56
17:56 Boston Dynamics. You use the word freaky
17:59
17:59 >> and I just want to understand it. And
18:01
18:01 sorry, Stu, I want you to come in on
18:02
18:02 this, but what if that dog was quietly
18:07
18:07 247 without the need presumably to be
18:09
18:09 paid? Yeah. um prowling the perimeter of
18:12
18:12 your house, looking out for you, keeping
18:14
18:14 you safe, sounding the alarm if it’s
18:17
18:17 spotted something, I don’t know, warding
18:19
18:19 off, you know, the n do wells cats. That
18:23
18:23 doesn’t sound freaky to me.
18:25
18:25 >> I agree. I think it’s again we’re we’re
18:27
18:27 it was so naent when we were seeing
18:29
18:29 those types of robotics and I think some
18:31
18:31 of this is already being addressed by
18:33
18:33 Stuart, which was it was actually the
18:34
18:34 way it was moving.
18:36
18:36 >> It was like something out of a science
18:38
18:38 fiction movie. So it was very unhuman.
18:41
18:41 So it was something in a form of
18:43
18:43 something lovely and gentle and soft and
18:45
18:45 cuddly that we all know a dog yet it
18:49
18:49 actually moved like a spider.
18:50
18:50 >> Yeah.
18:50
18:50 >> It was kind of like it was it was
18:52
18:52 repulsive actually in the way the action
18:54
18:54 and that’s why they’ll get this right
18:56
18:56 I’m sure with robots so that they’re
18:58
18:58 actually moving in a much more fluid way
18:59
18:59 so you don’t have that repulsion to them
19:02
19:02 because there is a chance you will have.
19:04
19:04 >> Well I mean presumably there’s a fork.
19:06
19:06 Well, two things, Stuart. There’s an
19:07
19:07 opportunity and a threat here for the
19:09
19:09 robotics industry, if I can put it like
19:12
19:12 that. One is that if it pulls on the
19:15
19:15 wrong threads of our memories, um, then
19:17
19:17 it can trigger us in the wrong
19:19
19:19 direction. Right.
19:20
19:20 >> Um, on the other hand, the future is
19:22
19:22 still to be written on this. All I would
19:24
19:24 notice about your two dogs, Victoria, is
19:28
19:28 um there’s another fork in the road by
19:30
19:30 moving towards the most realistic
19:33
19:33 possible, which could Stuart be exactly
19:36
19:36 the wrong thing to do because you end up
19:39
19:39 getting that slightly freaky almost
19:41
19:41 human quality when you might have been
19:42
19:42 better heading off in a deliberately
19:44
19:44 different direction.
19:46
19:46 It’s actually a very live debate uh
19:50
19:50 around those that are designing and
19:51
19:51 developing robots, but also those that
19:52
19:52 are concerned about how humans and
19:55
19:55 robots are going to coexist in the
19:57
19:57 future. Is whether
20:01
20:01 psychologically we want our robots to
20:03
20:03 look like robots and it’s obvious it’s
20:05
20:05 not human or do we want them to be more
20:08
20:08 human or more dogike. Um, and I think
20:12
20:12 from our experience of the thousands of
20:14
20:14 visitors we have every year. I think the
20:17
20:17 younger generation takes to robotics
20:20
20:20 just naturally doesn’t really think very
20:23
20:23 much about whether that dog looks like a
20:26
20:26 dog. They kind of get that it’s it, you
20:28
20:28 know, they’re comfortable with
20:29
20:29 identifying as a robot or identifying as
20:31
20:31 a dog. They’re they’re not phased. uh
20:34
20:34 older generations I think see the
20:37
20:37 potential for robotics and are really
20:39
20:39 quite pleased about how that might not
20:41
20:41 only assist them but be futures for
20:44
20:44 their children and grandchildren. Um but
20:47
20:47 I think the generations in between are
20:49
20:49 the ones that have yet to be convinced
20:51
20:51 about whether having a robot that looks
20:54
20:54 like a uh like a human is better than
20:58
20:58 having a robot that looks like a robot.
21:01
21:01 um albeit it might still you know have
21:03
21:03 two arms, two legs and a torso and a
21:05
21:05 head and still do the very same things.
21:08
21:08 And I think that is one of the barriers
21:09
21:09 to full adoption and acceptance of
21:12
21:12 robotics is how we how we as humans want
21:16
21:16 our robots to not only look but how we
21:19
21:19 want them to behave and what how far we
21:22
21:22 want them to impinge on our uh way of
21:26
21:26 life and where we would like that to
21:28
21:28 stop. And again, that’s why I think it’s
21:30
21:30 really important that we have a live
21:32
21:32 debate around these kind of things and
21:34
21:34 are able to explore this um in enough
21:38
21:38 time to be able to make decisions around
21:41
21:41 what we really want. And is there is
21:43
21:43 there a forum or anything that’s set up
21:45
21:45 to do that? Because we’ve you know we
21:47
21:47 we’ve talked we touched on AI and
21:49
21:49 there’s obviously concerns that there is
21:51
21:51 no kind of governing body that companies
21:53
21:53 are independent countries and companies
21:55
21:55 are going off independently and just
21:58
21:58 developing it because they want to get
21:59
21:59 ahead. They don’t want other countries
22:01
22:01 to get ahead of them. It’s it sort of
22:03
22:03 feels like the same argument here. What
22:05
22:05 what’s being done on a kind of
22:07
22:07 international level? Is there anything
22:09
22:09 being done on an international level to
22:11
22:11 discuss some of these points that you’re
22:12
22:12 talking about?
22:15
22:15 >> There are various forums, but they’re
22:17
22:17 not
22:19
22:19 they’re not widespread and and probably
22:21
22:21 not listened to as much as they should
22:23
22:23 be. So, the whole area of human and
22:25
22:25 robotic interaction is is a recognized
22:27
22:27 discipline within research and within
22:30
22:30 academia.
22:31
22:31 um is less recognized by the developers
22:34
22:34 of robots as being a barrier to what
22:37
22:37 they want to do. However, what we have
22:40
22:40 seen is the developers of robots who are
22:45
22:45 um enlightened enough to take this this
22:48
22:48 aspect into account are very aware that
22:50
22:50 their products will only sell if people
22:52
22:52 are prepared to to you know live and
22:55
22:55 work alongside them. Um so they do look
22:58
22:58 at these human and psychological
23:01
23:01 elements and try and make sure that
23:02
23:02 their robots are good to be accepted.
23:05
23:05 And just on that um well firstly
23:08
23:08 presumably there’s an interesting middle
23:10
23:10 ground where robot meets human I’m
23:13
23:13 talking about more assistive
23:14
23:14 technologies um exoskeletons
23:18
23:18 support for the elderly in firm I don’t
23:22
23:22 know forgive my ignorance does that
23:24
23:24 classify as robotics is there a middle
23:26
23:26 ground there
23:27
23:27 >> yeah no I think that that is still
23:29
23:29 robotics um and I think that
23:33
23:33 augmentation and support for for the you
23:37
23:37 know the human form to be able to lift
23:39
23:39 things or protect um in extreme
23:43
23:43 environments is an area that again has
23:46
23:46 advanced in the last few years
23:48
23:48 >> doesn’t tend to use artificial
23:50
23:50 intelligence in the same way but uses
23:52
23:52 different types of robotics in some
23:54
23:54 cases soft robotics uh and in other
23:57
23:57 cases more traditional forms of robotics
23:59
23:59 >> yeah funny enough I interviewed and a
24:01
24:01 fascinating woman Sarah Deagard a couple
24:04
24:04 of years ago with a prosthetic arm which
24:06
24:06 has incorporated only thanks probably to
24:09
24:09 organizations like your own thanks to a
24:12
24:12 whole mesh of startup technologies
24:14
24:14 working in tandem um to embody that in
24:18
24:18 her in her hand.
24:19
24:19 >> Yeah. Yeah. Can I can I ask though when
24:22
24:22 you walk the floor of uh the National
24:24
24:24 Robotarium, what excites you at the
24:28
24:28 moment in terms of what you’re actually
24:29
24:29 seeing on the ground? Cuz it sounds like
24:31
24:31 you’re attracting a whole range of types
24:33
24:33 of company, right?
24:35
24:35 >> Yeah. I think I think of all the four
24:39
24:39 areas that I mentioned before, the most
24:41
24:41 inspiring is is the robot developers.
24:45
24:45 You know, those companies that are in
24:48
24:48 the early stages with a vision for how
24:50
24:50 their robotic device can benefit
24:53
24:53 society, can be of use to people and are
24:57
24:57 trying to make that not only work but
25:00
25:00 make it acceptable and find a market.
25:03
25:03 And you know, I I have huge ad
25:06
25:06 admiration for anyone who’s running a
25:07
25:07 startup. Uh the amount of things that
25:09
25:09 they have to juggle and the difficulties
25:12
25:12 they have to overcome to to just
25:13
25:13 survive, let alone thrive. So we don’t
25:16
25:16 we don’t mind um when our guest name and
25:18
25:18 fame uh on the on the show say any
25:21
25:21 anyone that we should be looking up
25:23
25:23 afterwards feel free to shine a light
25:25
25:25 around a bit. I think a couple I would I
25:27
25:27 would highlight and so one is touch lab
25:30
25:30 who are developing skin for robotics the
25:32
25:32 sense of touch um with the aim to
25:36
25:36 basically have that sense available to
25:39
25:39 robots not just in the fingertips which
25:41
25:41 is where they’re predominantly working
25:43
25:43 at the moment but across the whole body
25:46
25:46 >> um and Bio Liberty who are working on uh
25:51
25:51 a stroke recovery device which is based
25:53
25:53 on robotics and AI to help people regain
25:56
25:56 the control of their hands and as a
25:58
25:58 result then be able to regain control of
26:00
26:00 the rest of the body following a stroke
26:03
26:03 and they’re seeing uh a lot of interest
26:06
26:06 in the states and are are starting to
26:09
26:09 spend more time in the USing than they
26:11
26:11 are here in the UK.
26:12
26:12 >> Amazing. We uh we commend to you our
26:14
26:14 viewer previous episode of tomorrow with
26:16
26:16 Dr. Laura Salsbury from NIT regen on
26:19
26:19 stroke rehabilitation. Maybe we should
26:20
26:20 introduce them to that we’ve just
26:22
26:22 mentioned. Yeah,
26:24
26:24 >> you can’t when we talk robotics, I’m
26:26
26:26 literally thinking humanoid, but the
26:29
26:29 applications for this are going to be
26:30
26:30 immense, aren’t they? Just you
26:31
26:31 mentioning that going to health, you
26:33
26:33 know, you can see it going, we haven’t
26:34
26:34 even talked about the office, what the
26:36
26:36 office is going to look like, but you
26:37
26:37 can see across in fact, can we do that?
26:39
26:39 What what is our what’s the office of
26:41
26:41 the future going to look like, Stuart?
26:44
26:44 >> Well, again, like all the other
26:46
26:46 environments, there’ll be more robots in
26:47
26:47 it than there are today. I think in the
26:49
26:49 office environment, the applications are
26:51
26:51 a little bit limited. Um but certainly
26:54
26:54 you know moving things around um
26:57
26:57 retrieving things and and being able to
26:59
26:59 assist in office activities is the is
27:03
27:03 going to be the general approach. I
27:04
27:04 think the area where the there’s massive
27:07
27:07 potential is in healthcare particularly
27:09
27:09 in hospitals. Mhm.
27:10
27:10 >> Um, and we’re starting to see the green
27:13
27:13 shoots of that now, not just with new
27:16
27:16 robotics devices being developed, but
27:18
27:18 with attention being paid to that
27:20
27:20 increasingly by the more mature robotic
27:22
27:22 developers and an understanding that uh
27:27
27:27 there’s huge gains to be made. So, we
27:30
27:30 look at the NHS, there’s huge gains to
27:31
27:31 be made in in the adoption of of
27:33
27:33 robotics. And that’s been identified in
27:35
27:35 the 10-year NHS strategy recently. Uh
27:39
27:39 it’s about now making that real and
27:41
27:41 getting some traction on it to start to
27:44
27:44 break down the the barriers to
27:47
27:47 introducing these kinds of technologies
27:48
27:48 into into healthcare. And that’s not
27:51
27:51 just about, you know, robot nursing
27:54
27:54 assistants uh that look like humanoid
27:57
27:57 nurses. It’s more about simple things
27:60
28:00 like cleaning floors and cleaning
28:02
28:02 windows and moving vast amounts of
28:04
28:04 laundry around every day, moving uh vast
28:07
28:07 amounts of drugs and other equipment
28:10
28:10 around. Uh a lot of that is done
28:13
28:13 manually at the moment. It suffers quite
28:15
28:15 a lot from u labor shortages and and
28:18
28:18 people not really want to do the job.
28:20
28:20 Uh, and so there’s ways to use robotics
28:24
28:24 to just make the the hospital run more
28:26
28:26 efficiently. And then as we extend that
28:29
28:29 into the home, social care at home,
28:31
28:31 having a a robot carer that’s there
28:34
28:34 24/7. Um, that’s able to raise the alarm
28:39
28:39 if you’re in difficulty, but more
28:40
28:40 importantly give you a bit of
28:42
28:42 companionship and at the same time make
28:43
28:43 sure that if you’ve got physio to do,
28:45
28:45 you’re doing that. Or if you’ve got
28:47
28:47 medicines to take, you’re make you’re
28:48
28:48 taking your medicines.
28:50
28:50 And it and one of the things
28:51
28:51 interestingly when we’ve discussed that
28:53
28:53 kind of thing with people is they like
28:55
28:55 the idea of having the reassurance that
28:57
28:57 if they have a family member that needs
28:59
28:59 care at home that there’s something not
29:03
29:03 necessarily someone but something that’s
29:06
29:06 able to be looking after their family
29:08
29:08 member on their behalf. And I think
29:11
29:11 that’s a big area that um that we’ll see
29:14
29:14 a demand coming in the future.
29:16
29:16 >> Yeah. I’ I’d love to get a bit more of a
29:18
29:18 sense of the breadth of the sorts of
29:20
29:20 organizations that you’re working with
29:22
29:22 and would like to work with. And on a
29:25
29:25 slightly geekier note, my apologies, how
29:28
29:28 is that work being funded and how will
29:30
29:30 you as the person leading it measure
29:32
29:32 whether it’s a success?
29:37
29:37 Well, the the kind of things that we’re
29:39
29:39 trying to do is to
29:42
29:42 fundamentally
29:44
29:44 have a positive impact on the economy
29:46
29:46 and have a positive impact on society
29:48
29:48 when we introduce robotics. So, we’re
29:52
29:52 doing a lot of awareness raising to help
29:56
29:56 people, not just in businesses, but the
29:59
29:59 public at large, but particularly in
30:01
30:01 businesses to understand what’s possible
30:04
30:04 with robotics. And then we work very
30:06
30:06 closely with them to then uh identify
30:09
30:09 the applications of robotics in their
30:11
30:11 particular business and then hopefully
30:14
30:14 take that through into actual
30:15
30:15 implementation.
30:16
30:16 >> Who who would you like to reach more of
30:19
30:19 >> in terms of sectors you mean?
30:21
30:21 >> Yeah.
30:22
30:22 >> Um healthcare
30:25
30:25 just the potential for healthcare is
30:27
30:27 huge.
30:27
30:27 >> Yeah.
30:28
30:28 >> Uh and we’d be all day talking about
30:30
30:30 what the barriers are at the moment but
30:32
30:32 uh the potential for healthcare is huge.
30:34
30:34 There’s things that exist right now that
30:36
30:36 they that could be used by the NHS all
30:38
30:38 over the UK and be making a huge
30:39
30:39 difference. Um, we just need to find a
30:42
30:42 way to get healthcare to start embracing
30:45
30:45 this technology and making making that
30:47
30:47 difference.
30:48
30:48 >> I mean, you can see people that have got
30:49
30:49 elderly parents at home. This is
30:51
30:51 immediately what I’m thinking of when
30:52
30:52 you’re saying this. It’s three grand a
30:53
30:53 week in a care home, I think, sorry,
30:55
30:55 month. It’s it’s it’s horrendously
30:57
30:57 expensive. And, you know, people that
30:59
30:59 have worked all their lives lose their
31:01
31:01 home in the last two years of their life
31:03
31:03 often. So depending on the price point
31:05
31:05 of course for something like this, this
31:07
31:07 could really replace that having that
31:10
31:10 that kind of end of life care situation
31:14
31:14 um in a really neat way where somebody
31:15
31:15 could actually stay in their home and of
31:17
31:17 course you know you wouldn’t have to
31:18
31:18 have the daughter or the son being with
31:20
31:20 them 24 hours a day 24 hours a day care.
31:22
31:22 Is that the sort of thing that you
31:24
31:24 envision here in addition to the
31:25
31:25 hospitals and so on?
31:27
31:27 >> Yeah, eventually. Yes.
31:29
31:29 >> Yeah. being
31:30
31:30 >> exactly that.
31:31
31:31 >> And the thing and we have to touch on
31:32
31:32 it, don’t we? Um because it’s important
31:35
31:35 the thing that uh a listener will be
31:37
31:37 wrestling with is that there’s a circle
31:40
31:40 to be or a square to be circled here if
31:42
31:42 you like which is um there are huge
31:45
31:45 numbers of vacancies in some of these
31:47
31:47 professions. Um some of that because as
31:50
31:50 you’ve said um you know certain
31:53
31:53 individuals do not wish to perform these
31:55
31:55 jobs. On the other hand, we have surging
31:58
31:58 unemployment, especially amongst young
32:01
32:01 people. Um, and yet somewhere in the
32:03
32:03 middle, we have a whole generation of
32:06
32:06 new, newly enabled uh robots, some of
32:09
32:09 them humanoid robots, which can perform
32:11
32:11 these tasks. And we need your help in
32:14
32:14 helping us to navigate between these
32:17
32:17 three things, I suppose.
32:19
32:19 >> Yeah, it’s an interesting conundrum,
32:20
32:20 isn’t it? and that
32:22
32:22 um
32:24
32:24 some people would say that as we bring
32:26
32:26 robotics in that that going to be a
32:28
32:28 threat to jobs and I think
32:31
32:31 uh and therefore it would add to the
32:32
32:32 problem of unemployment. I think like
32:35
32:35 any technology it will initially be
32:37
32:37 disruptive and we might see some and
32:38
32:38 probably will see that kind of impact. I
32:40
32:40 don’t think we should and that’s one of
32:42
32:42 the reasons why I think we need to have
32:44
32:44 that public discourse because I think
32:46
32:46 people need to understand that this
32:48
32:48 there is initially an you know uh an
32:51
32:51 inevitable consequence of that but then
32:54
32:54 as we embrace the technology it’s been
32:57
32:57 proven and a lot of studies has been
32:58
32:58 done and published around the fact that
33:01
33:01 the technologies themselves don’t
33:03
33:03 actually in the long term lead to
33:06
33:06 further unemployment. In fact, in a lot
33:07
33:07 of cases, they lead to higher
33:09
33:09 employment. Um, and I think robotics has
33:11
33:11 got a huge potential for for doing
33:14
33:14 exactly that. Um how how we use this in
33:19
33:19 the mix is really an interesting
33:22
33:22 conversation to be had between the
33:24
33:24 shortage of people in the workforce that
33:27
33:27 if we use robotics to to fill that gap
33:30
33:30 then you know productivity would go up
33:33
33:33 overall GDP would go up everyone as a
33:36
33:36 result would be better off
33:38
33:38 >> um but does that actually help us get
33:40
33:40 humans into the workforce? Um, and I
33:44
33:44 don’t think I don’t think there’s an
33:45
33:45 easy answer, but I do think the three
33:47
33:47 things need to be in play as opposed to
33:50
33:50 what we tend to talk about now, which is
33:51
33:51 vacancies and numbers of people
33:52
33:52 unemployed and how do we get people who
33:55
33:55 are unemployed into filling those
33:56
33:56 vacancies. Well, now we’ve got something
33:58
33:58 else in the mix, which is robotics.
34:00
34:00 >> Yeah. And of course, one of the
34:02
34:02 challenges to what you’ve uh said very
34:06
34:06 clearly is that one of the issues with a
34:08
34:08 lot of that research is that it was
34:10
34:10 quite literally based on the past. And
34:12
34:12 if you talk about a conundrum that saw
34:15
34:15 um pre-industrial workers, cart horses
34:19
34:19 um being replaced, you know, we just
34:21
34:21 need to be careful that the humans we’re
34:23
34:23 talking about aren’t the car horses in
34:25
34:25 that equation because those car horses
34:26
34:26 didn’t go and get other jobs, did they?
34:29
34:29 >> No. Indeed. Indeed. And I think that
34:32
34:32 again just underlining my point from
34:34
34:34 earlier that’s why we need to have that
34:36
34:36 open public discourse.
34:39
34:39 >> And and and just briefly on that and I
34:41
34:41 know we want to get through um some more
34:42
34:42 things sometimes and in lots of
34:44
34:44 situations you know um it’s important to
34:47
34:47 think about what the message is and then
34:49
34:49 who the messengers could be and very
34:51
34:51 often uh government departments and
34:53
34:53 you’re certainly not one of those um
34:55
34:55 aren’t best placed. So, who would you
34:57
34:57 like to see, to Victoria’s point
34:59
34:59 earlier, coming together to help really
35:02
35:02 raise the um the old phrase be like the
35:05
35:05 national discourse on this, the national
35:06
35:06 conversation? Who who who who would you
35:08
35:08 like to see gather around the table?
35:12
35:12 I think that the industry leaders have
35:14
35:14 got a lot a part to play. both those
35:18
35:18 that are embracing robotics and taking
35:20
35:20 them into their businesses but also
35:21
35:21 those that are developing robots at
35:23
35:23 scale to actually engage in in this
35:26
35:26 discussion um and help people understand
35:30
35:30 what the pros and cons could be. So I
35:33
35:33 think that’s definitely one area or one
35:35
35:35 group. Uh government definitely is
35:38
35:38 another group. Um but maybe not best
35:41
35:41 place to explain and and help raise
35:45
35:45 understanding and awareness. Um and then
35:48
35:48 I think you know in this day and age um
35:51
35:51 there’s lots of different
35:53
35:53 uh people and types of people that that
35:57
35:57 influence different generations and
35:59
35:59 different audiences. So I think making
36:01
36:01 use of that uh to be able to raise
36:04
36:04 awareness is is really important as
36:05
36:05 well.
36:06
36:06 >> Yeah. And bringing I think you’re in
36:08
36:08 such a great position which you’re
36:09
36:09 already doing to bring those different
36:11
36:11 people together, some of those
36:12
36:12 developers, some of those entrepreneurs
36:14
36:14 with those storytellers with those
36:16
36:16 creators themselves to inspire each
36:18
36:18 other and to tell those stories to
36:19
36:19 spread that word.
36:20
36:20 >> Yeah, indeed. Very much so.
36:24
36:24 >> I’m going to ask you a question
36:25
36:25 actually. Um again taking a complete
36:28
36:28 step back. Um, and it’s really something
36:31
36:31 we do on uh the Tomorrow podcast. Uh,
36:34
36:34 something that Future Forum likes to
36:35
36:35 think about, which is leaving a memo for
36:39
36:39 the future. So, what I would like you to
36:41
36:41 do is tell us what your message would be
36:44
36:44 for somebody that’s 10 years in the
36:46
36:46 future. Um, so what can you tell them
36:49
36:49 about robotics and the choices that we
36:51
36:51 need to be thinking about today and uh
36:55
36:55 moving forwards?
36:57
36:57 I guess firstly I’d say to them I hope
36:59
36:59 you’re enjoying your life with lots of
37:00
37:00 robots in it. Um
37:03
37:03 and I hope that we have embraced the
37:08
37:08 complexities of robotics not so much in
37:10
37:10 terms of technology but more to do with
37:12
37:12 its impact on society in such a way that
37:15
37:15 we’ve
37:17
37:17 laid the groundwork that means that that
37:19
37:19 integration has gone smoothly. Um, I
37:22
37:22 think that’s the biggest thing that we
37:23
37:23 need to do over the next few years is is
37:25
37:25 really turn our attention to how are we
37:27
37:27 going to live in this world with with
37:29
37:29 robots and humans working side by side.
37:31
37:31 >> That is such a clear answer. Thank you
37:33
37:33 so much, Stuart. And we can uh tell us
37:35
37:35 other than by looking it up on our
37:36
37:36 search engine of choice. Where can we
37:38
37:38 find out more about the National
37:39
37:39 Robotarium?
37:41
37:41 >> Um, we have a very lively LinkedIn feed.
37:45
37:45 So, find us on LinkedIn. Uh, you’ll find
37:48
37:48 us you’ll find our website. Um, you’ll
37:51
37:51 also find us occasionally on Instagram.
37:53
37:53 Um, so yeah,
37:55
37:55 >> and presumably
37:56
37:56 >> predominantly we communicate through
37:57
37:57 LinkedIn.
37:58
37:58 >> Amazing. And and you’ve got some amazing
37:59
37:59 space obviously um up there um in
38:02
38:02 Edinburgh. Um
38:04
38:04 access to that events, gatherings, that
38:07
38:07 sort of thing, or is it is it is it a
38:09
38:09 little more um sort of uh a little more
38:12
38:12 closed than that?
38:14
38:14 >> No, it’s very much open. Um so through
38:17
38:17 our website and through our LinkedIn
38:19
38:19 people will be able to find uh events
38:22
38:22 that are open to the public but also
38:23
38:23 specialist days that we have looking at
38:25
38:25 particular subjects. Um and
38:30
38:30 uh they’ll also be able to hear about
38:32
38:32 things that we’re involved in more
38:33
38:33 widely that are not necessarily just
38:35
38:35 here.
38:36
38:36 >> Amazing. Such uh a fascinating glimpse
38:40
38:40 into the future. Stuart Miller, thank
38:41
38:41 you so much for joining us on tomorrow.
38:43
38:43 >> Thank you Stuart.
38:45
38:45 Oh, fascinating. That was absolutely
38:48
38:48 that took us into place I wasn’t
38:50
38:50 expecting.
38:50
38:50 >> We have such amazing guests on this
38:52
38:52 program.
38:52
38:52 >> We’re very fortunate here. I I I knew
38:54
38:54 we’d start with the factory. I had a
38:57
38:57 suspicion we’d go into the chef.
38:59
38:59 >> Yes.
38:59
38:59 >> Robot, but actually so much broader.
39:01
39:01 >> Absolutely. I mean, the the caring
39:03
39:03 element of it was something that I
39:04
39:04 hadn’t actually considered. And you can
39:07
39:07 see how in hospitals around the world,
39:10
39:10 you’re going to be integrating this
39:11
39:11 human touch and this robotic touch. you
39:13
39:13 can see how it’s going to make quality
39:15
39:15 of care so much better for all of us.
39:18
39:18 So, um and and you know, it’s an
39:20
39:20 interesting point about the job
39:21
39:21 displacement. Um so, Stuart brought that
39:23
39:23 up himself. Um but you can see how some
39:26
39:26 of these jobs people you can’t get
39:28
39:28 people to do them. So, it’s actually
39:29
39:29 putting robots in where we actually need
39:32
39:32 the assistance.
39:33
39:33 >> And also creatively, especially for
39:36
39:36 entrepreneurs and innovators, you can
39:38
39:38 see how every single step on a journey
39:40
39:40 like this, there are going to be
39:42
39:42 questions. There are going to be ethical
39:44
39:44 dilemmas, serious conundrums and yeah,
39:47
39:47 it is also important to just let that
39:50
39:50 creative what if imagination flow.
39:52
39:52 >> Absolutely.
39:53
39:53 >> As we explore what’s what’s already
39:55
39:55 happening, what’s possible.
39:57
39:57 >> Yeah. I hadn’t when when we when we’re
39:59
39:59 looking at AI, we’re all so ingrained in
40:02
40:02 AI and how that’s changing our life, we
40:04
40:04 we’re actually just ignoring the whole
40:05
40:05 robotics thing that’s that’s happening
40:07
40:07 in the background.
40:08
40:08 >> Really good really good point. Really
40:09
40:09 good to see it embedded there. Right. um
40:12
40:12 you know in Edinburgh National
40:14
40:14 Robotarium serious funding behind it as
40:16
40:16 well.
40:16
40:16 >> Yeah.
40:17
40:17 >> Um I know we ran out of time slightly.
40:19
40:19 What do you wish we’d asked him if we
40:20
40:20 >> I wanted to ask you about defense cuz
40:23
40:23 I’ve got Return of the Jedi in my head.
40:24
40:24 You know when you see the the re you
40:26
40:26 know it harks back to the Second World
40:28
40:28 War but you can see these ranks of
40:31
40:31 soldiers and that’s the image I’ve got
40:33
40:33 in my head and that’s what Stuart was
40:34
40:34 saying. Yes, it’s going to be completely
40:36
40:36 feasible um to have that. So that’s
40:39
40:39 going to again turn things on its head
40:41
40:41 in a way that we’re seeing at the moment
40:43
40:43 with warfare and drones. So this is the
40:46
40:46 next stage in that,
40:46
40:46 >> right? Well, whether it’s defense or
40:48
40:48 other industries, how does a robot doing
40:51
40:51 something change what we feel about what
40:55
40:55 we ask them to do,
40:56
40:56 >> right?
40:56
40:56 >> The choices we make,
40:58
40:58 >> how we make those decision. We’re going
40:59
40:59 to need another episode, aren’t we?
41:00
41:00 >> We are. It’s going to be like, no, you
41:02
41:02 have the night off to the robot. I’ll
41:04
41:04 make dinner tonight.
41:05
41:05 >> Exactly. Right.
41:07
41:07 The robot strikes back. Right. Okay.
41:10
41:10 Thank you, Victoria. Another excellent
41:11
41:11 guest. We’ll see you next time. Thank
41:12
41:12 you. Well, that’s it for this episode of
41:15
41:15 Tomorrow. We’d love to hear what you
41:16
41:16 thought of it. Very grateful uh to
41:18
41:18 Stuart Miller from the National
41:20
41:20 Robotarium for being our brilliant guest
41:22
41:22 and to you for tuning in today and for
41:24
41:24 helping us to spread the word. Uh I’m
41:27
41:27 Ollie Barrett and with my brilliant
41:28
41:28 co-host Victoria Usher. Until next time,
41:31
41:31 goodbye.
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