1 00:00:09,902 --> 00:00:18,764 Hello, welcome to Power of 10, a show about design operating at many levels of Zoom, from thoughtful detail through to transformation in organizations, society and the world. 2 00:00:18,805 --> 00:00:20,305 My name is Andy Perlane. 3 00:00:20,305 --> 00:00:24,726 I'm a design leadership coach, service designer, educator and writer. 4 00:00:24,726 --> 00:00:35,220 My guest today is Joel Bailey, product and service director at Arwin.ai, a four-year-old marketing technology startup that uses AI to help brands to manage and moderate their 5 00:00:35,220 --> 00:00:37,310 social media comments at scale. 6 00:00:37,560 --> 00:00:46,397 Joel brings 25 years of experience working in service design roles, leading change and building new stuff for a diverse range of organizations. 7 00:00:46,397 --> 00:00:55,205 He says if you slice him down the middle, he's 30 % total service nerd, 30 % AI and design fanatic and 30 % family man. 8 00:00:55,205 --> 00:00:57,350 Joel, welcome to Power of 10. 9 00:00:57,947 --> 00:01:01,079 So that 30%, that's like a sort of slice of Brighton Rock, is it? 10 00:01:01,079 --> 00:01:02,053 There's different sort of... 11 00:01:02,053 --> 00:01:03,245 do you know what? 12 00:01:03,245 --> 00:01:05,009 That is exactly the image. 13 00:01:05,009 --> 00:01:09,202 Although I think my family would have something to say about only getting 30%. 14 00:01:09,202 --> 00:01:10,540 But it depends. 15 00:01:10,540 --> 00:01:12,224 Maybe that's time-based. 16 00:01:12,224 --> 00:01:13,134 Obviously not love. 17 00:01:13,134 --> 00:01:15,626 ah Okay, very well done. 18 00:01:15,626 --> 00:01:26,788 look, tell us, I've talked a little bit in the intro about your background, we actually don't know how we know each other, but we've been in each other's orbit certainly from the 19 00:01:26,788 --> 00:01:29,189 service design world. 20 00:01:29,189 --> 00:01:32,473 Tell me a bit about that journey to where you are now. 21 00:01:32,940 --> 00:01:35,212 Yeah, I was trying to remember exactly how we connected. 22 00:01:35,212 --> 00:01:40,555 I think it's one of those ambient relationships that just came out of the ether, right? 23 00:01:40,555 --> 00:01:42,857 As you say, in similar orbits. 24 00:01:42,857 --> 00:01:45,059 I think it is around service design. 25 00:01:45,059 --> 00:01:53,825 So I was very lucky, I think, to stumble across service design very early on in my career. 26 00:01:53,825 --> 00:01:55,526 And I'm not a trained designer. 27 00:01:55,526 --> 00:01:57,147 I have an arts background. 28 00:01:57,147 --> 00:02:01,350 uh I didn't do any sort of 29 00:02:01,582 --> 00:02:04,042 qualifications or certificates in design. 30 00:02:04,642 --> 00:02:07,542 But I've always had a creative lean. 31 00:02:07,702 --> 00:02:17,862 And I think when I started working and I was working in organizations where I was basically being asked to solve problems, which is what lot of people get asked to do. 32 00:02:17,862 --> 00:02:20,402 If you're not doing admin, you're solving problems. 33 00:02:20,582 --> 00:02:28,822 And I was pretty frustrated with the tool set that was available, which was very kind of expert led, best practice, best best practice that. 34 00:02:29,282 --> 00:02:31,494 And I think it was... 35 00:02:31,899 --> 00:02:36,823 in one of those roles that someone said to me, what you're going towards is like service design. 36 00:02:36,823 --> 00:02:43,249 Because I come from a digital background and I remember, I called myself an information architect at one point. 37 00:02:43,249 --> 00:02:48,474 I used to work across A2 size bits of paper mapping out websites and things, right? 38 00:02:48,474 --> 00:02:51,347 And then I started looking at user sensitive design. 39 00:02:51,347 --> 00:02:57,198 If anyone remembers the Rosenfeld book with the polar bear on the front, the information architecture, but legendary stuff. 40 00:02:57,198 --> 00:02:58,967 I was about say publisher. 41 00:02:59,118 --> 00:02:59,778 All right, exactly. 42 00:02:59,778 --> 00:03:02,659 So now we're feeling old, right? 43 00:03:02,959 --> 00:03:08,798 So these books were quite seminal to me, and it was very much making it up as I went along. 44 00:03:08,798 --> 00:03:17,924 And then I got to work in, I went to work as a contractor consulting in government in the UK, and I started doing what is now known as user-centered design. 45 00:03:17,924 --> 00:03:20,294 But back then, we were just winging it. 46 00:03:20,294 --> 00:03:26,264 It was like the logic of the project I was doing, which is working on one of the big government super sites, as they were called. 47 00:03:26,264 --> 00:03:29,176 This one was businesslink.gov.uk for anyone who cares. 48 00:03:29,176 --> 00:03:31,999 It's basically a website by the government to businesses. 49 00:03:31,999 --> 00:03:39,365 And I learned that the best way to create the outcomes you wanted was by asking users what they needed. 50 00:03:39,365 --> 00:03:48,073 And the worst people to ask about what a small business owner needed was a civil servant at that point, because they were like, well, they need to out Form 20348. 51 00:03:48,073 --> 00:03:52,976 And it's like, well, do they really, you know, they might have to by law, but that's certainly not what they want to do. 52 00:03:52,976 --> 00:03:55,726 So that's when I first got into user-centered design. 53 00:03:55,726 --> 00:04:01,746 And then we fast forward, I guess, a few years and somewhere along that road, someone said service design. 54 00:04:01,746 --> 00:04:05,526 I remember going to the Wikipedia page and it was like two lines, know? 55 00:04:05,526 --> 00:04:13,966 it was like, service design is applying user-centered design to a wider scope of organizational activities, all different channels, multiple touch points. 56 00:04:13,966 --> 00:04:15,766 I was like, okay, that's kind of what I'm doing. 57 00:04:15,766 --> 00:04:22,426 Because we had telephone lines we were dealing with, we were dealing with email, we were dealing with webpages, PDFs, all that sort of stuff. 58 00:04:22,546 --> 00:04:25,446 So it was like, okay, so this is a good space to be in. 59 00:04:25,674 --> 00:04:31,377 And I guess the rest is sort of history in that I got very invested in it. 60 00:04:31,377 --> 00:04:34,869 I really got excited about service design. 61 00:04:34,869 --> 00:04:45,704 I'm really excited about two things, the design approach, which I'm sure we'll talk about, which I still use, and service and what services, which I'm, as I said, a bit of a nerd 62 00:04:45,704 --> 00:04:50,006 about service and what it is and how it works in my spare time. 63 00:04:50,006 --> 00:04:55,088 And now, if I come all the way to now, all these things kind of come together in this very unexpected way. 64 00:04:55,088 --> 00:04:59,749 So, you know, I'm running a business, I mean, but they call it product, but it's a service business. 65 00:04:59,749 --> 00:05:07,051 It's got a big digital product in the middle that uses AI to detect and remove toxic commentary from social media. 66 00:05:07,051 --> 00:05:14,673 But it also uses the same technology to, you know, have conversations with social media users on behalf of brands. 67 00:05:14,673 --> 00:05:16,682 So there is service happening there. 68 00:05:16,682 --> 00:05:25,009 We as an organization are providing a service to our clients and we have to design it continually because our users have very high standards. 69 00:05:25,149 --> 00:05:28,963 Anyway, that's very short, a long answer to your question, but that's kind how I found my way. 70 00:05:28,963 --> 00:05:32,956 And along the way I've had quite formal service design jobs. 71 00:05:32,956 --> 00:05:37,630 worked at LiveWork for a while and everyone who knows service design knows LiveWork. 72 00:05:37,630 --> 00:05:42,324 So was very grateful to be to work with Labyrinth and Ben and the others over there. 73 00:05:42,324 --> 00:05:45,132 uh And I've led service design. 74 00:05:45,132 --> 00:05:51,962 in large organizations and small, but now I'm not really doing service design as a job for the first time. 75 00:05:51,962 --> 00:05:57,064 I am applying it in a startup, which is so different. 76 00:05:57,134 --> 00:05:59,355 Yeah, well let's come to why it's different actually in a second. 77 00:05:59,355 --> 00:06:03,578 mean, it's interesting for me, you know, talked about the information architecture thing. 78 00:06:03,578 --> 00:06:08,020 I find sort of people go one way the other and sort of encounter services. 79 00:06:08,020 --> 00:06:14,143 One is they're working into interaction design and UX and they're like, there's sort of more than this. 80 00:06:14,143 --> 00:06:17,065 There's a larger ecosystem or I want to be more involved. 81 00:06:17,065 --> 00:06:19,296 If only they had come to me earlier. 82 00:06:19,374 --> 00:06:23,334 in that process and I can input it in the strategic part. 83 00:06:23,334 --> 00:06:25,014 And so they kind of do that zoom level out. 84 00:06:25,014 --> 00:06:31,094 I mean, this is why the show is named after that Eames powers of 10 film of the different levels of zoom. 85 00:06:31,614 --> 00:06:34,774 Or they go the other way, which is, I'm sort of systems thinker. 86 00:06:34,774 --> 00:06:35,934 I'm a kind of ecosystem thing. 87 00:06:35,934 --> 00:06:44,274 And I think the IA thing is, well, it's actually a good mix of the two, but there's definitely that kind of overview of how does all this kind of hang together and what is 88 00:06:44,274 --> 00:06:44,898 the kind of. 89 00:06:44,898 --> 00:06:46,607 the view of this and you sort of gone that way. 90 00:06:46,607 --> 00:06:49,628 So I can kind of see where it meets in the middle. 91 00:06:49,628 --> 00:06:56,103 there was a third option, was, I'll just stay in the website UX space with my headphones on, looking at screens. 92 00:06:56,103 --> 00:06:59,165 There were a few people that did that and I did think about that at one point. 93 00:06:59,165 --> 00:07:03,177 But I'm just too curious and I think ask too many questions. 94 00:07:03,177 --> 00:07:09,291 And then once you start asking about the call center, like what happens when people can't do this thing on the website? 95 00:07:09,372 --> 00:07:13,254 Then you end up going to the call center and talking to the manager and asking them questions. 96 00:07:13,254 --> 00:07:15,235 It's just very organic. 97 00:07:16,897 --> 00:07:19,178 But that systems theory there. 98 00:07:19,210 --> 00:07:22,952 It's fascinating to me and I'm not a systems theorist. 99 00:07:22,952 --> 00:07:27,623 I'm a systems thinker in the very basic sense and I've read enough to be dangerous probably. 100 00:07:27,623 --> 00:07:36,017 it's increasingly, you spend longer and longer in organizations of any size. 101 00:07:36,017 --> 00:07:44,210 You have to understand systems theory and you have to understand that you can't change one thing without some ramification elsewhere. 102 00:07:44,210 --> 00:07:47,171 So I'm very sympathetic to the systems world. 103 00:07:47,171 --> 00:07:48,686 It's complicated. 104 00:07:48,686 --> 00:07:49,638 hard to deliver. 105 00:07:49,638 --> 00:07:50,909 It's complex, isn't it? 106 00:07:50,909 --> 00:07:54,140 It's interrelated. 107 00:07:54,140 --> 00:07:58,602 We just said the thing about you know, you're working there and they call it a product, but I call it a service. 108 00:07:58,658 --> 00:08:06,815 you know, my endless rant that everyone's bored off by now is that, you know, everything's a service and certainly anything that's digital is. 109 00:08:06,815 --> 00:08:18,238 mean, I always say if you've ever used turned on Slack and the, um you know, the service is not working or it's, you just get a load of placeholder boxes, how you know. 110 00:08:18,238 --> 00:08:26,418 You are using an avatar to a service and anything else same goes for your banking and almost everything that is digital. 111 00:08:26,670 --> 00:08:37,210 Yeah, and the way to frame it in my mind, I remember doing presentations of FS, Financial Services audience, and it was all about, we trying to create better mortgages or better 112 00:08:37,210 --> 00:08:38,630 homeowners, right? 113 00:08:38,630 --> 00:08:40,170 What are we trying to do here? 114 00:08:40,170 --> 00:08:51,290 And in our organization, the product, sorry, the service we're after really is we want to move our clients from one place to another, from a less good place to a better place. 115 00:08:51,290 --> 00:08:52,782 And the better place is 116 00:08:52,782 --> 00:08:56,302 They're just more engaged with their community, right? 117 00:08:56,302 --> 00:08:58,182 That's what R1 is all about. 118 00:08:58,182 --> 00:09:02,302 Our mission is to make your social media more social. 119 00:09:02,562 --> 00:09:04,722 So that is all about more engagement. 120 00:09:04,722 --> 00:09:17,102 The product, one of our products, is a tool that auto-moderates all the horrible stuff, the spam, the racism, of which unfortunately there is still a bit too much of it on social 121 00:09:17,102 --> 00:09:17,816 media. 122 00:09:17,816 --> 00:09:20,727 So for me, it helps to think about service as an outcome. 123 00:09:20,727 --> 00:09:26,349 And it's about movement from A to B for anyone um in life. 124 00:09:26,349 --> 00:09:33,712 And I take it very seriously, whether it's service leadership and how I'm trying to work with others to get them from A to B in their lives and careers, even with my family, 125 00:09:33,712 --> 00:09:33,959 right? 126 00:09:33,959 --> 00:09:37,373 It's like, what can I do to serve this person to move them forward? 127 00:09:37,373 --> 00:09:41,154 With our clients at Arwin, it is very important. 128 00:09:41,464 --> 00:09:44,837 to not think that we're a rubbish removal business, because we could do. 129 00:09:44,837 --> 00:09:48,640 But that really limits your opportunity for that relationship with that client. 130 00:09:48,640 --> 00:09:56,867 When you say, yeah, we do rubbish removal over here, but actually our service is about getting you to better engagement, whether it's on your ads or on your organic. 131 00:09:56,867 --> 00:10:00,526 As a service for me, it's such a useful framework for that. 132 00:10:00,526 --> 00:10:07,246 Yeah, think, know, nine is it's a broadening of view of the ecosystem because it includes more than just the product. 133 00:10:08,026 --> 00:10:15,486 Which also obviously every time you kind of broaden the lens, I mean, there's a danger you lose yourself, but there's also this idea of, there's a different way of, we could come at 134 00:10:15,486 --> 00:10:17,366 this from a different angle as well. 135 00:10:17,366 --> 00:10:19,606 And that's often where some of the innovation lies. 136 00:10:19,618 --> 00:10:30,207 Yeah, you know, as service designers, we've all been invited to do innovation as much as just improvement, but you can't innovate, you're right, without a bigger ambition and 137 00:10:30,207 --> 00:10:31,048 service. 138 00:10:31,270 --> 00:10:43,430 But I mean, but conversely, can't, know, services I had got, I think it's probably for the reputation of some of the agencies that certainly are the big consultancies that I might 139 00:10:43,430 --> 00:10:48,370 have worked for, of delivering sort of concepts and, you know, and journey maps and blueprints. 140 00:10:48,370 --> 00:10:52,310 And then the clients run out of money, go, here you go, good luck with that. 141 00:10:52,310 --> 00:10:57,070 And obviously, you know, the real thing, reason why our book is called From Insight to Implementation is because 142 00:10:57,070 --> 00:11:00,490 You know, how things are implemented makes such a massive difference. 143 00:11:00,490 --> 00:11:03,790 I mean, you've talked about businesses filling in a form or something. 144 00:11:03,790 --> 00:11:06,510 You hear this stuff about you. 145 00:11:06,510 --> 00:11:17,570 Whenever I explain what I do to people and that's a whole thing in itself or what service design is, I, you know, I then immediately get this barrage of, you the other day I was 146 00:11:17,570 --> 00:11:21,290 trying to do X, Y and Z and this, and it's, it's tiny things. 147 00:11:21,290 --> 00:11:26,146 It's always the gaps and the transitions where things go wrong. 148 00:11:26,146 --> 00:11:27,677 and screw people up. 149 00:11:27,677 --> 00:11:32,812 And you mentioned that sort of flow chart of, know, person does this and then they go to that. 150 00:11:32,812 --> 00:11:40,858 the arrow, innocent arrow or the hairline between those two boxes on the flow chart contains a whole lot of horrors when it goes wrong. 151 00:11:41,006 --> 00:11:49,866 Yeah, and think you and I, we both had a very similar visual metaphor for this, I think yours is crossing the chasm or something like that. 152 00:11:49,926 --> 00:11:51,226 Yeah, the crevasse. 153 00:11:51,226 --> 00:12:00,246 Now I had a blog post a few years ago about crossing the chasm, I think I called it, which is that that line between two boxes on a process map actually goes across cultural 154 00:12:00,246 --> 00:12:04,326 boundaries or organizational boundaries or team boundaries or geographical boundaries. 155 00:12:04,326 --> 00:12:09,486 And in that, all sorts of things get lost, know, lots of tacit knowledge. 156 00:12:09,486 --> 00:12:14,406 And that's what service designers do is they're trying to stand in the user's point of view and say, how am I being carried from A to B? 157 00:12:14,406 --> 00:12:21,746 It looks so simple here from a business analysis point of view, but the reality is I'm suddenly being handed to someone or another part of the organization who doesn't care 158 00:12:21,746 --> 00:12:23,626 about me as much as that first bit. 159 00:12:23,626 --> 00:12:25,886 Like sales, they really cared about me. 160 00:12:25,886 --> 00:12:32,666 Onboarding, they didn't care about me so much because I'm now just a product to be processed through onboarding. 161 00:12:32,666 --> 00:12:34,546 Anyone who bought a new utility. 162 00:12:34,546 --> 00:12:35,386 Yeah, yeah, you're done. 163 00:12:35,386 --> 00:12:36,726 We've won you. 164 00:12:38,910 --> 00:12:47,373 And we'll come on and talk about startup and how it's different, but ideas implementation is obviously massively uh shrunk down in my world. 165 00:12:47,373 --> 00:12:58,347 We can have an idea and implement it in hours, which for much of my career was just not possible because the raw material of my work was other people. 166 00:12:58,347 --> 00:13:02,466 So I'd have to work with other people to develop conceptual ideas. 167 00:13:02,466 --> 00:13:08,950 and then they'd have to work with other people on committees to make change happen within the organization to make that concept a reality. 168 00:13:09,091 --> 00:13:10,392 We obviously don't have that. 169 00:13:10,392 --> 00:13:19,256 We are 15 people and we work very quickly to take an idea into reality, however quick as we want to or not. 170 00:13:19,898 --> 00:13:24,101 I, like you, probably have had large enterprises say, treat us like a startup. 171 00:13:24,101 --> 00:13:25,921 We want to be like a startup. 172 00:13:27,363 --> 00:13:29,084 Well, so what does that mean? 173 00:13:29,084 --> 00:13:33,386 And a startup, one of the things is it's not like, we're really innovative. 174 00:13:33,386 --> 00:13:36,088 And so that's kind of what they're hoping. 175 00:13:36,188 --> 00:13:42,872 But one of the things of that is a startup has often key people are wearing many hats, right? 176 00:13:42,872 --> 00:13:44,433 Or at least a couple. 177 00:13:44,433 --> 00:13:46,466 You have such a small 178 00:13:46,466 --> 00:13:50,449 group of people, the communication lines are very, short. 179 00:13:50,570 --> 00:13:59,997 Literally, I'm the person next to me or whatever, even if they're remote now, there's only a handful of people and those people are empowered to make decisions, right? 180 00:13:59,997 --> 00:14:01,859 Because it's probably their thing anyway. 181 00:14:01,859 --> 00:14:10,466 And so when you say enterprise client, you want to be treated like a startup, are you happy to get rid of most of your decision making and governance process that gets in, 182 00:14:10,466 --> 00:14:15,288 well, not governance, but kind of um gatekeeping process that gets in the way of that. 183 00:14:15,288 --> 00:14:18,519 Can we just have direct lines to someone who can make a decision? 184 00:14:18,539 --> 00:14:21,101 And, you know, can we try stuff out and be risky? 185 00:14:21,101 --> 00:14:22,001 And they're like, yeah. 186 00:14:22,001 --> 00:14:25,502 So we'd like to be a startup, but you know, not those things. 187 00:14:25,643 --> 00:14:26,253 Yeah. 188 00:14:26,253 --> 00:14:28,263 And so then they always fail. 189 00:14:28,624 --> 00:14:30,571 So I really like to kind of come back in a minute. 190 00:14:30,571 --> 00:14:36,807 I'd really like to talk about the design and AI thing, but just go back and tell us a little bit more about what Arwin does. 191 00:14:36,948 --> 00:14:39,138 Because I think it's really interesting. 192 00:14:39,138 --> 00:14:42,590 I want to ask a few questions around that. 193 00:14:42,670 --> 00:14:51,550 Yeah, so I mean a lot of people just kind of sigh a little bit when they hear the words AI at the moment and we are in that high cycle dip, right? 194 00:14:51,550 --> 00:14:52,830 And I get that. 195 00:14:52,830 --> 00:14:58,170 First thing I'd like to say is that Arwin, we have been AI from start four years ago. 196 00:14:58,170 --> 00:14:59,530 So we're pre-chat GPT. 197 00:14:59,530 --> 00:15:02,930 So it makes us really old, makes us wise like Gandalf, right? 198 00:15:02,930 --> 00:15:04,130 We're pre-chat GPT. 199 00:15:04,130 --> 00:15:08,110 We've been doing this for quite a long time in AI terms, not obviously. 200 00:15:08,270 --> 00:15:10,411 mean, AI is 30, 40 years old, right? 201 00:15:10,411 --> 00:15:18,135 But anyway, what we do as Arwen is probably easiest from the origin story from where it began. 202 00:15:18,135 --> 00:15:25,749 So the euros which are being played now, if we go back four years ago, we remember the racism that was thrown at the players who missed the penalties. 203 00:15:25,749 --> 00:15:34,524 It was kind of that point that Matt and David, CEO, CTO got together and said, we've got to solve this thing. 204 00:15:34,724 --> 00:15:36,285 We can solve this thing. 205 00:15:36,285 --> 00:15:37,888 Let's solve this thing. 206 00:15:37,888 --> 00:15:40,059 I came on board a bit later. 207 00:15:40,059 --> 00:15:48,622 And em what we built is a platform that pulls in data models and algorithms from all sorts of different providers. 208 00:15:49,143 --> 00:15:56,055 And then we plug this thing called Arwin into your social media profiles in an authorized way. 209 00:15:56,055 --> 00:15:58,296 We're authorized by the different networks. 210 00:15:58,296 --> 00:16:02,753 And then Arwin scans every single comment that you get on social media. 211 00:16:02,753 --> 00:16:12,508 And if it finds something that breaks your rules, and we set those with each client, so everybody wants to get rid of spams, or porn bots, and crypto bots, and all the fraudulent 212 00:16:12,508 --> 00:16:14,030 stuff, which can just grow. 213 00:16:14,030 --> 00:16:15,936 90 % of the internet 214 00:16:16,206 --> 00:16:17,286 My name is certainly is then. 215 00:16:17,286 --> 00:16:19,587 The networks obviously have it worse than others. 216 00:16:19,807 --> 00:16:27,939 And obviously if you're a brand and you're trying to connect with your audience, either on paid or organic, that stuff really gets in the way. 217 00:16:27,939 --> 00:16:29,790 It's a pollutant, pure and simple. 218 00:16:29,790 --> 00:16:39,633 So we remove that and we do it by studying both the content and we have probably the world's largest database of spam items in the world. 219 00:16:39,633 --> 00:16:40,963 And we do fuzzy matching. 220 00:16:40,963 --> 00:16:43,103 So we don't do like exact keyword. 221 00:16:43,103 --> 00:16:45,016 We don't use keywords at all actually. 222 00:16:45,016 --> 00:16:45,846 We do fuzzy matching. 223 00:16:45,846 --> 00:16:50,046 Basically, Arwen's saying, how close is this to every other spam item I've ever seen? 224 00:16:50,046 --> 00:16:52,448 It looks at the comment and it looks at the profile. 225 00:16:52,448 --> 00:16:54,272 So it can look at the profile's avatar. 226 00:16:54,272 --> 00:17:01,735 It can look at the different characteristics of the profile to determine and score how likely that is to be a spammer's profile. 227 00:17:01,817 --> 00:17:04,778 And then it looks at the content itself and makes a decision. 228 00:17:04,778 --> 00:17:06,600 It does all of that in under a second. 229 00:17:06,600 --> 00:17:09,761 And then it hides it if it goes over a certain threshold. 230 00:17:09,882 --> 00:17:10,786 So it's... 231 00:17:10,786 --> 00:17:12,407 That's the simplest way of describing it. 232 00:17:12,407 --> 00:17:16,890 Now we do that for spam and that's like our biggest seller because everybody wants to get rid of it. 233 00:17:16,890 --> 00:17:20,913 But then we also do it for unwanted content. 234 00:17:20,913 --> 00:17:25,857 So that is what we call in the UK lawful but awful. 235 00:17:25,857 --> 00:17:32,365 Okay, so the networks are pretty good at getting rid of illegal content and that stuff is really the unpleasant. 236 00:17:32,365 --> 00:17:33,396 they have to. 237 00:17:33,644 --> 00:17:35,835 Yeah, because they have to in different regions in different ways. 238 00:17:35,835 --> 00:17:40,606 And that's a colossal job and they do a very good job of it because we don't see things like child abuse on social media. 239 00:17:40,606 --> 00:17:42,476 So they are doing a very good job. 240 00:17:42,476 --> 00:17:54,320 The awful but lawful bit, because it's bit loose and fast in uh legal frameworks globally, even our online safety bill in the UK is a little bit fuzzy about how to deal with that. 241 00:17:54,320 --> 00:17:55,290 That's where we step in. 242 00:17:55,290 --> 00:18:02,670 So a brand basically says, so we are a, we've got a number of Formula One teams who have very premium sponsors. 243 00:18:02,670 --> 00:18:11,370 very large audiences, increasingly a female audience that they want to engage with because they've watched maybe Drive to Survive, the Netflix program, they've really engaged in 244 00:18:11,370 --> 00:18:13,070 this sport in a new way. 245 00:18:13,190 --> 00:18:21,290 And we've worked out through our analysis that these female fans are a small, they're about 25 % of Formula One fans. 246 00:18:21,730 --> 00:18:25,890 They contribute about 80 % of the vibes to the community. 247 00:18:25,890 --> 00:18:27,590 They're really positive. 248 00:18:27,710 --> 00:18:29,850 So, and yet they get all the toxicity. 249 00:18:29,850 --> 00:18:32,692 So then we start helping them to hide misogyny. 250 00:18:32,692 --> 00:18:38,144 sexism, sexual aggression, all of which occurs in sporting environments, unfortunately. 251 00:18:38,144 --> 00:18:40,445 Gaming environments, we work in a bit as well. 252 00:18:40,445 --> 00:18:45,527 So it's all about, and I go back to my earlier point about we are trying to improve engagement. 253 00:18:45,527 --> 00:18:49,979 The first step to improve engagement is to put some rules in place. 254 00:18:49,979 --> 00:18:51,980 We use the analogy of a bar, right? 255 00:18:51,980 --> 00:19:02,394 You walk into a bar and there people smashing bottles in the corner, shouting abuse, racist abuse, or uh trying it on in really offensive ways with women, whatever it is. 256 00:19:02,414 --> 00:19:11,014 We come in, I often think of that film Roadhouse, coming like Patrick Swayze, the old Roadhouse, we come in like Patrick Swayze, and we just tidy things up. 257 00:19:11,014 --> 00:19:13,334 Some people do get blocked from the community. 258 00:19:13,974 --> 00:19:16,634 We automatically identify those people. 259 00:19:16,714 --> 00:19:19,874 But everyone else just finds that you can't say these things anymore. 260 00:19:19,874 --> 00:19:23,654 We help our clients write a clear policy, put it on the door. 261 00:19:23,654 --> 00:19:30,234 And then within three months, they have got at least on average 21%, 22 % increase in engagement. 262 00:19:30,304 --> 00:19:33,784 and the number of toxic comments has gone down by around 70%. 263 00:19:33,784 --> 00:19:36,524 Just because it's just not a horrible place to hang out. 264 00:19:36,524 --> 00:19:40,558 horrible place and no one wants to be you know there's a real sheep mentality. 265 00:19:40,558 --> 00:19:42,712 It's the whole Nazi bar thing, right? 266 00:19:42,712 --> 00:19:44,223 Yeah, exactly. 267 00:19:44,223 --> 00:19:45,684 So you denormalize it. 268 00:19:45,684 --> 00:19:49,447 We talk about denormalizing toxicity, which is why we invest in speed. 269 00:19:49,447 --> 00:19:53,590 Let me give you an example about we don't got a lot of behavioral analysis on this. 270 00:19:53,590 --> 00:20:01,315 So the behaviors of uh a hater, a troll, and the behaviors of the sheep that follow them are quite obvious when you look at the data patterns. 271 00:20:01,315 --> 00:20:11,630 Someone will, so let's say client post comment, post a beautiful picture of a football ball being kicked into a goal by a female football player. 272 00:20:11,630 --> 00:20:15,530 someone comes in and comments and says, get back in the kitchen. 273 00:20:15,530 --> 00:20:17,590 We've seen all these, so I'm not describing anything. 274 00:20:17,590 --> 00:20:19,290 These aren't my words, let's be clear. 275 00:20:19,290 --> 00:20:26,570 So that someone posts that as a comment, as soon as that is seen by other people, it creates permission for other people to do it. 276 00:20:26,570 --> 00:20:31,210 So they come in and start saying, yeah, yeah, you shouldn't be doing that. 277 00:20:31,210 --> 00:20:32,710 All of that. 278 00:20:32,710 --> 00:20:38,882 Because we get rid of that first comment and we hide it in seconds, often under a second, 279 00:20:38,882 --> 00:20:46,290 then it doesn't create that wave of permission and we shorten the life of a potential toxic event considerably as a result. 280 00:20:46,702 --> 00:20:50,194 I've got a question for you, which I would imagine like everyone else is thinking. 281 00:20:50,194 --> 00:20:51,305 Yeah. 282 00:20:51,305 --> 00:20:53,937 Obviously, you know, you do this for brands, right? 283 00:20:53,937 --> 00:21:00,351 Because whatever Mercedes, AMG, Formula One team don't want to have that stuff next to their brand. 284 00:21:00,411 --> 00:21:11,519 And in fact, that's one of the most sort of best ways to kind of pressure brands to shift the way they think about certain issues is to highlight that. 285 00:21:11,519 --> 00:21:15,401 Why don't the social media platforms do this themselves? 286 00:21:15,442 --> 00:21:16,402 Why is... 287 00:21:16,402 --> 00:21:21,920 X and everyone else Y or know, Substack for that matter, talking of the Nazi Bar thing. 288 00:21:21,920 --> 00:21:23,632 Why aren't they doing it? 289 00:21:23,733 --> 00:21:24,094 Why? 290 00:21:24,094 --> 00:21:29,401 I mean, they haven't hired you yet or is it problematic at the scale they're at? 291 00:21:30,056 --> 00:21:31,788 Well, they're partly at scale. 292 00:21:31,788 --> 00:21:36,551 So it's important to think about pre-publication moderation and post-publication moderation. 293 00:21:36,551 --> 00:21:42,536 Again, I would say they do an excellent job of pre-publication moderation on illegal content. 294 00:21:42,716 --> 00:21:46,519 Very good at finding illegal content and stopping it from getting out. 295 00:21:46,880 --> 00:21:52,043 That in itself is a colossal data management job, huge amounts of data processing going on. 296 00:21:54,826 --> 00:21:56,847 Awful but lawful stuff that I'm talking about. 297 00:21:56,847 --> 00:22:00,430 There's a few reasons why it gets really hard for them to do. 298 00:22:00,571 --> 00:22:04,214 First of all, they aren't legally obliged to do it. 299 00:22:04,334 --> 00:22:12,741 Section 230 of the Communications and Decency Act, which some people will be familiar with in the US where they're all based, basically says they're not an editor. 300 00:22:12,741 --> 00:22:13,872 They don't have to edit. 301 00:22:13,872 --> 00:22:17,025 They're not responsible for what their users put online. 302 00:22:17,025 --> 00:22:20,949 And there are all sorts of challenges going on on both ends of the spectrum to that. 303 00:22:20,949 --> 00:22:22,924 Some states in the US are saying, 304 00:22:22,924 --> 00:22:25,175 You can never moderate anything pre-publication. 305 00:22:25,175 --> 00:22:28,537 It's against the First Amendment or right to free speech. 306 00:22:28,537 --> 00:22:30,628 Others are saying you have to to protect children. 307 00:22:30,628 --> 00:22:35,120 So this is playing out and has been since we started the business. 308 00:22:35,621 --> 00:22:45,937 that legally, if they start pre-publication moderation of the comments that I'm describing, then they are basically saying, well, we are an editor. 309 00:22:45,937 --> 00:22:51,610 And then they're leaving themselves open, I think, to a challenge of like, well, if you're going to do it for that thing, you've got to do it for these other things that I care 310 00:22:51,610 --> 00:22:52,152 about. 311 00:22:52,152 --> 00:23:00,429 And then we get into the really hard bit, which is one person's really toxic comment is not another person's really toxic comment, unfortunately. 312 00:23:00,429 --> 00:23:01,350 Now, some are. 313 00:23:01,350 --> 00:23:06,013 I mean, I think I'm not going to do them on your lovely show because it wouldn't be right. 314 00:23:06,013 --> 00:23:09,776 But there are some comments that I see that no one in the world would go, that's great. 315 00:23:09,776 --> 00:23:11,458 Yeah, there's nothing wrong with that. 316 00:23:11,458 --> 00:23:16,342 But unfortunately, you get into gray areas, which is why we don't set any standards on our clients. 317 00:23:16,342 --> 00:23:21,786 We work with them to work out what is your graphic equalizer to profanity to insult. 318 00:23:21,868 --> 00:23:26,430 And it's different for every client because they're different brands and they have different communities and they engage. 319 00:23:26,430 --> 00:23:31,842 So sport is going to be very different from children's entertainment, obviously, different demographic. 320 00:23:31,842 --> 00:23:36,231 And you can't expect one network to do all of that on behalf of everybody globally. 321 00:23:36,231 --> 00:23:38,405 It's it's nigh on impossible. 322 00:23:38,405 --> 00:23:41,546 And I put it, I posted about this the other day, actually. 323 00:23:41,567 --> 00:23:47,369 So I think, I think there is, there are a number of factors that prevent them from doing it. 324 00:23:47,549 --> 00:23:49,166 I also think that. 325 00:23:49,166 --> 00:23:53,926 If you do go into the pre-publication moderation world, you really take on a responsibility. 326 00:23:54,606 --> 00:24:00,686 Clearly, as a network, you're making your money out of attention, the eyeballs that see the ad. 327 00:24:00,726 --> 00:24:08,086 If you're having to put a human set of eyeballs on every bit of content, every comment before, the business model just won't stack up. 328 00:24:08,086 --> 00:24:14,606 You'll be spending so much to check everything that you won't be making enough out of the ad eyeballs. 329 00:24:14,606 --> 00:24:18,326 Human eyeballs, one side, human eyeballs on the other side, they're both costing the same. 330 00:24:18,426 --> 00:24:28,882 So I am very sympathetic to the networks because I think the other thing I would, I'm going to go one step further and say, we do expect social media to be a utopia when the 331 00:24:28,882 --> 00:24:30,243 rest of the world isn't. 332 00:24:30,243 --> 00:24:31,033 Okay. 333 00:24:31,033 --> 00:24:40,079 Now I know we can look at the algorithms around ranking, although Metra has done some great changes that our clients benefit from, that positive interactions get higher, ranked 334 00:24:40,079 --> 00:24:41,609 higher than negative interaction. 335 00:24:41,609 --> 00:24:43,020 So they are working. 336 00:24:43,020 --> 00:24:46,240 But I think we've all seen that the drama. 337 00:24:46,240 --> 00:24:48,432 is what the ranking algorithms go for. 338 00:24:48,432 --> 00:24:51,615 And drama is often where toxicity lives. 339 00:24:51,615 --> 00:24:56,398 So people are pushed into places where there is toxicity. 340 00:24:57,239 --> 00:25:10,671 we can't, know, a lot of our clients, if you go to a store or an event or you hang out with the CEO, they probably all got security at the front door. 341 00:25:10,671 --> 00:25:12,893 They've got security in a drive that drives them around. 342 00:25:12,893 --> 00:25:14,616 If they fly or do something, 343 00:25:14,616 --> 00:25:19,568 They have extra levels of insurance and care and protection on themselves and their buildings. 344 00:25:19,568 --> 00:25:22,910 uh And really, that's no different on social media. 345 00:25:22,910 --> 00:25:27,412 uh So I think we've just got to be careful about the networks. 346 00:25:27,412 --> 00:25:30,724 They've got to make the human race just much nicer to each other. 347 00:25:30,724 --> 00:25:32,022 It's really hard. 348 00:25:32,022 --> 00:25:45,472 Yeah, I think it probably says the thing you're talking about eyeballs says something more, I think around, I would suggest broken, certainly, or toxic or difficult business 349 00:25:45,472 --> 00:25:46,113 models. 350 00:25:46,113 --> 00:25:46,523 Right. 351 00:25:46,523 --> 00:25:55,760 You know, that's the problem as you know, the cardinal sin of the internet is that it lacked micro payments and that created advertising or ad tech. 352 00:25:55,760 --> 00:25:56,020 Right. 353 00:25:56,020 --> 00:25:58,622 So then everything kind of follows on from there. 354 00:25:59,086 --> 00:26:00,908 I'd like to move on a little bit. 355 00:26:00,908 --> 00:26:03,429 You talked before about something I want to circle back to. 356 00:26:03,429 --> 00:26:14,968 You said, know, obviously when I was doing other stuff, it involved a kind of group of people and the pathway from idea to trying something out was much longer, know, weeks, 357 00:26:14,968 --> 00:26:15,878 months. 358 00:26:17,060 --> 00:26:19,882 in some cases, lots of expense to an infrastructure. 359 00:26:19,882 --> 00:26:22,594 And now you are saying, you know, that's much, shorter now. 360 00:26:22,594 --> 00:26:25,998 We can come up with an idea and try it out very, very quickly. 361 00:26:25,998 --> 00:26:36,022 How much is kind of that because of the AI aspect of it or how much is it, know, what role is technology playing in there and how much is it to do with your culture as a startup? 362 00:26:36,022 --> 00:26:39,564 Well, I mean, definitely the culture of startup helps. 363 00:26:39,985 --> 00:26:41,276 It's all experiment, right? 364 00:26:41,276 --> 00:26:44,869 The whole business is an experiment live in the world. 365 00:26:46,210 --> 00:26:56,969 But if I look at any department, I say department, we don't really talk about departments, but like we have, you we've got engineering and product, we've got marketing, sales, it's 366 00:26:56,969 --> 00:26:58,720 all ongoing experiments. 367 00:26:58,720 --> 00:27:01,038 And the first thing you learn 368 00:27:01,038 --> 00:27:07,538 when you're working in a startup is that most of the books are wrong or they were right for a certain context, but they're wrong for your context. 369 00:27:07,618 --> 00:27:11,218 And so you quickly realized that you needed it. 370 00:27:11,218 --> 00:27:13,618 The most important thing you need is an experimental framework. 371 00:27:13,618 --> 00:27:25,978 So I'm working with Tushar, who works in our marketing team on a range of marketing experiments, which is where I guess the AI also comes in, not our own AIs, but other AIs 372 00:27:25,978 --> 00:27:27,458 out in the world that we're working with. 373 00:27:27,458 --> 00:27:30,446 So we're working with a couple of different AI 374 00:27:30,446 --> 00:27:43,357 products that allow us to not just to take our kind of experimental DNA of a startup, bring AI into that, and it then accelerates the experiment itself. 375 00:27:43,357 --> 00:27:51,664 So things like research, secondary research, primary research, less so, but people keep trying to tell me that avatars are going to do primary research. 376 00:27:51,664 --> 00:27:58,254 I don't think trust is there yet for qualitative research, but hey, but quantitative research, it's amazing. 377 00:27:58,254 --> 00:28:05,514 I can get an AI to go and find out lots of facts for me very quickly and compile them. 378 00:28:05,514 --> 00:28:12,054 You've obviously got to look out for hallucination, but the thing you've got to remember in a startup and in any business is all you need is a hunch. 379 00:28:12,054 --> 00:28:13,634 It's a Rory Sutherland thing here. 380 00:28:13,634 --> 00:28:19,734 He says, we're not doing quantitative research for like Elsevia or some university or something. 381 00:28:19,734 --> 00:28:21,694 We don't have to be 100 % right. 382 00:28:21,694 --> 00:28:24,974 We just have to be right enough or righter than the next person. 383 00:28:24,974 --> 00:28:26,082 And one of the things that 384 00:28:26,082 --> 00:28:32,694 that I was blessed with as a service designer in previous roles was lots of good data, like qualitative data and quantitative data. 385 00:28:32,694 --> 00:28:34,404 I could go out and speak to customers. 386 00:28:34,404 --> 00:28:37,465 I could go out and do research projects that last weeks. 387 00:28:37,465 --> 00:28:39,522 We probably can't do that so much anymore. 388 00:28:39,522 --> 00:28:41,766 I things have changed budget-wise. 389 00:28:41,766 --> 00:28:43,417 But that was a real luxury. 390 00:28:43,417 --> 00:28:47,468 In a startup, you're very data poor, very time poor. 391 00:28:47,468 --> 00:28:54,818 uh So the experimental framework plus AI allows you to overcome the time piece, but also bring in the data. 392 00:28:54,818 --> 00:29:04,557 And you just accept the fact that you might get errors in the data because you've just got to be faster at getting to the hunch and then sitting down and going, it's good enough, 393 00:29:04,557 --> 00:29:08,570 we're going to push the green button and we're going commit to this as an approach. 394 00:29:08,574 --> 00:29:13,250 You're not generating content, is where, you know, that can be... 395 00:29:13,250 --> 00:29:13,863 Quite well. 396 00:29:13,863 --> 00:29:15,331 We have a second prod. 397 00:29:15,331 --> 00:29:17,348 We'll talk about that separately. 398 00:29:18,232 --> 00:29:27,135 Well, putting content out in the world, that's where it's pretty problematic, particularly with AI as you know, you've seen this kind of weird thing going on where companies would 399 00:29:27,135 --> 00:29:39,559 fire an employee, a customer service employee if they said that kind of thing in a chat thing, but obviously they just kind of plug a chat bot in and let it go crazy and with 400 00:29:39,559 --> 00:29:43,230 some crazy results too and not great results for them. 401 00:29:43,534 --> 00:29:52,574 But you with the moderation thing, can also, you know, this is a very well known thing that part of the problem that happens with moderation is if for example, a person of color 402 00:29:52,574 --> 00:29:59,394 is talking about experience of racism that they've had, gets flagged up because they're using the words that the racists are using and it gets flagged up as content. 403 00:29:59,394 --> 00:30:02,714 And so those marginalized voices get further marginalized. 404 00:30:02,714 --> 00:30:05,014 How do you deal with that aspect? 405 00:30:05,014 --> 00:30:11,274 Because there is a, you know, it's still quite, it's very, very complex, obviously. 406 00:30:11,274 --> 00:30:12,514 I think there's a lot of the... 407 00:30:12,514 --> 00:30:14,866 there's just a black boxy, we don't really know what's going on. 408 00:30:14,866 --> 00:30:18,881 Even the people have kind of put it together, you know, once it's got up and running. 409 00:30:18,881 --> 00:30:20,392 But how do you balance that? 410 00:30:20,430 --> 00:30:21,411 You're absolutely right. 411 00:30:21,411 --> 00:30:32,484 You know, this is one of the risks of AI's who's built it how they built it on what data has it been trained etc I mean we just distinguish between LLMs which will come on to And 412 00:30:32,484 --> 00:30:40,914 how they work and how they've been trained versus the various models that we've been using Pre-charge GPT and continue to use really effectively They have all been built and trained 413 00:30:40,914 --> 00:30:42,876 by experts in this field, right? 414 00:30:42,876 --> 00:30:49,670 So they are detection algorithms and they are benchmarked for bias and error rates 415 00:30:49,706 --> 00:30:53,667 So around, you know, white supremacism, bigotry, racism, all these things. 416 00:30:53,667 --> 00:30:54,508 Okay. 417 00:30:54,508 --> 00:30:59,390 And I could go into quite a lot of detail about why we're confident in how they make decisions. 418 00:30:59,390 --> 00:31:03,761 So, so clearly that's something to keep an eye on. 419 00:31:03,761 --> 00:31:11,594 It's, think when you get into the LLMs bit where it feels like a bit more of a black box, I can tell you how the other ones work and I can tell you how they were trained and how 420 00:31:11,594 --> 00:31:12,326 they were built. 421 00:31:12,326 --> 00:31:14,848 there is some rickets behind that. 422 00:31:14,848 --> 00:31:16,259 Providence and rigor. 423 00:31:16,259 --> 00:31:23,264 LLM is, it feels like, you know, they've just created something and it's just gone, it's just gone out to the world and hoovered everything up and it's coming out with something 424 00:31:23,264 --> 00:31:26,907 quite useful, but is it entirely true and right? 425 00:31:26,907 --> 00:31:32,764 So we do use large language models and we do use generative AI. 426 00:31:32,764 --> 00:31:34,532 So I've talked about the moderate product. 427 00:31:34,532 --> 00:31:36,293 We have an engaged product. 428 00:31:36,293 --> 00:31:43,668 So like I said earlier, our service mission is to make our clients more social, make their social media more social. 429 00:31:43,746 --> 00:31:52,249 So once you've got rid of all the bad stuff and that bar is now great and everyone's hanging out, having a great time, now you want to talk more to your community. 430 00:31:52,249 --> 00:31:55,696 It's safe, it's lovely, it's got all the people in there that you want in there. 431 00:31:56,137 --> 00:32:03,504 The most surprising thing to me about social media, so $270 billion got spent on social media last year, sort of globally. 432 00:32:03,504 --> 00:32:04,744 Someone came up with that number. 433 00:32:04,744 --> 00:32:05,766 It's really big. 434 00:32:05,766 --> 00:32:10,769 And it roughly sounds about right when I hear about some of the social media advertising budgets. 435 00:32:11,394 --> 00:32:15,535 You put that content out there, that content on social media will be responded to. 436 00:32:15,535 --> 00:32:16,799 You will get comments. 437 00:32:16,799 --> 00:32:19,681 Clearly, I've talked about the negative ones, the toxic ones. 438 00:32:19,681 --> 00:32:20,552 Negative is different. 439 00:32:20,552 --> 00:32:22,804 Toxicity, we get rid of it. 440 00:32:22,804 --> 00:32:30,119 But you're going to get negative comments, you're going to get questions, you're going to feedback, people going, yay, I love this. 441 00:32:30,119 --> 00:32:34,373 The amount of brands that do nothing with those comments just astounds me. 442 00:32:34,373 --> 00:32:38,496 You spend all this money advertising essentially is trying to get someone's attention. 443 00:32:38,576 --> 00:32:40,684 You've got their attention, they're asking you. 444 00:32:40,684 --> 00:32:42,584 something, they don't do anything. 445 00:32:42,584 --> 00:32:44,435 It's like the orphan child. 446 00:32:44,435 --> 00:32:47,896 Everyone's all about, create more blog posts, create more blog posts. 447 00:32:47,896 --> 00:32:50,847 So we use large language models to help down at comment level. 448 00:32:50,847 --> 00:32:54,918 So if someone's looked at your ad and says, great, where can I buy this watch? 449 00:32:55,799 --> 00:33:02,614 You can't scale a team where you can, it'll cost you a lot of money to answer every comment on every social media channel in real time. 450 00:33:02,614 --> 00:33:05,742 You've got to do it within an hour and to get into that buyer moment. 451 00:33:05,742 --> 00:33:06,982 Oh, Arwen can do that. 452 00:33:06,982 --> 00:33:12,504 Now to go to your point about the fears that we all have about hallucinations and stuff like that. 453 00:33:12,504 --> 00:33:24,027 So the latest technology that we're using, which is called retrieval augmented generation, lovely phrase, rag retrieval augmented generation basically says you're a large language 454 00:33:24,027 --> 00:33:24,567 model. 455 00:33:24,567 --> 00:33:28,708 You've learned off all this stuff, some of it good, some of it bad. 456 00:33:29,248 --> 00:33:32,769 But I have a load of content here that I know is good. 457 00:33:32,769 --> 00:33:33,119 Yeah. 458 00:33:33,119 --> 00:33:34,300 It's the company policy. 459 00:33:34,300 --> 00:33:35,766 It's the brand voice. 460 00:33:35,766 --> 00:33:37,167 It's the rules and regulations. 461 00:33:37,167 --> 00:33:38,987 It's the opening times of all the stores. 462 00:33:38,987 --> 00:33:40,228 They're facts. 463 00:33:41,969 --> 00:33:47,271 And I want you to refer to those things when you're making a consideration generating a response. 464 00:33:47,271 --> 00:33:54,955 So what Arwin does is it goes to the large language model and says, person, the large language model goes, this person's asking a question about a watch. 465 00:33:54,955 --> 00:34:01,618 um And then the rag element looks at the rules and says, they're looking at this watch. 466 00:34:01,618 --> 00:34:02,722 It's this ad for. 467 00:34:02,722 --> 00:34:06,094 this watch, yes, you can buy it here, here's the URL and it connects them through. 468 00:34:06,094 --> 00:34:06,924 Okay. 469 00:34:06,924 --> 00:34:18,831 So what we're trying to do with RAG and it's a meta originated technology because they're obviously fighting this kind of, all this crap firing across the internet from AI is like, 470 00:34:18,831 --> 00:34:20,231 we've got to put rules around it. 471 00:34:20,231 --> 00:34:21,952 You've to put control around it. 472 00:34:21,952 --> 00:34:31,697 And for us, it's so important because if Engage is going to be having conversations with people online and delivering service, let's be honest, that's what it's going to be doing. 473 00:34:32,691 --> 00:34:41,257 then it has to be accurate or the lawyers will never sign it off because we've all heard about, I don't know what brand it was, a car brand in the US selling a car for a dollar 474 00:34:41,257 --> 00:34:44,009 because the chat bot, they managed to get it to do that. 475 00:34:44,009 --> 00:34:47,311 No legal team is now going to sign off a chat bot AI. 476 00:34:47,471 --> 00:34:49,753 We're not even rolling it out as fully automated. 477 00:34:49,753 --> 00:34:51,274 We're like, it's semi-autonomous. 478 00:34:51,274 --> 00:34:52,675 It's a co-pilot. 479 00:34:52,675 --> 00:34:57,230 So our AI reads the question, reads the comment, whatever. 480 00:34:57,230 --> 00:35:02,150 and then generates three alternatives and then the manager can go in and just choose which one they want to use. 481 00:35:02,150 --> 00:35:11,914 Okay, but the key thing is this rag technology allows you to put guardrails in so that the AI doesn't just freak out and promise people like a new car. 482 00:35:11,914 --> 00:35:15,415 So talking of co-pilots, I'm not going to talk about Microsoft co-pilot. 483 00:35:15,415 --> 00:35:21,257 As we are speaking, and this will probably come out in a couple of months, so as we're speaking, Figma have just shown all their new stuff. 484 00:35:21,257 --> 00:35:24,018 There's a lot of AI tools in there for design. 485 00:35:24,018 --> 00:35:35,211 um I had a dream, a frequent sort of daydream as a kid that I had a robot me, duplicate me that went into school and did lessons and all the boring stuff. 486 00:35:35,211 --> 00:35:37,982 I stayed at home reading comics and eating sweets. 487 00:35:37,982 --> 00:35:39,458 um 488 00:35:39,458 --> 00:35:44,169 The question is, it's a part of me when it looks at some of that stuff that it can kind of very quickly generate. 489 00:35:44,169 --> 00:35:52,062 there was some stuff I saw the clip where it's where you've got a whole, instead of having some lorem ipsum text, it just sort of generates a load of actual sort of placeholder text 490 00:35:52,062 --> 00:35:53,202 and all that stuff. 491 00:35:53,202 --> 00:35:59,324 And obviously it's going to do a lot and sort of make prototypes really quickly, um go from some idea to prototype. 492 00:35:59,324 --> 00:36:00,975 And part of me is like, you know, that's amazing. 493 00:36:00,975 --> 00:36:03,485 That takes a lot of drudgery away. 494 00:36:03,485 --> 00:36:05,706 And then the other part of me is, yeah, but. 495 00:36:06,030 --> 00:36:10,150 Design isn't just design, as in the end artifact. 496 00:36:10,150 --> 00:36:20,190 Designing is a process of thinking whilst you're designing and actually that process of prototyping of, you know, even sketching on paper actually, there's a talking to Eva 497 00:36:20,190 --> 00:36:26,150 Lottelam in some comments of a thing she did the other day, which is teaching people to sketch wireframes again in paper. 498 00:36:26,330 --> 00:36:30,070 There's a lot of thinking that goes on in the designing. 499 00:36:30,158 --> 00:36:31,558 And I really kind of worry about that. 500 00:36:31,558 --> 00:36:34,678 I worry less about the AI taking people's jobs. 501 00:36:34,678 --> 00:36:39,718 So there's clearly a lot of, there will be a lot of sort of low end product managers who go, oh, this is great. 502 00:36:39,718 --> 00:36:40,938 I don't need designers anymore. 503 00:36:40,938 --> 00:36:47,538 I can just kind of write in a prompt and, and it will send some stuff to engineering, which is how they treat design anyway. 504 00:36:48,798 --> 00:36:54,698 Rather than I want to have this kind of trio and have this kind of good conversation and understand so that the good ones do that. 505 00:36:54,698 --> 00:36:56,146 So I can see the kind of. 506 00:36:56,146 --> 00:36:59,722 the advantages of that, but I do worry about that side of it. 507 00:36:59,722 --> 00:37:00,653 What's your view on it? 508 00:37:00,653 --> 00:37:03,670 Talking about that sort of going from idea to prototype very quick. 509 00:37:03,670 --> 00:37:10,034 Well, we've both worked in consulting design, well, businesses and agencies. 510 00:37:10,034 --> 00:37:18,449 And I think we've all seen over the years that what is pushed out as original work is often just a repeat of like, you want a website? 511 00:37:18,449 --> 00:37:21,261 Well, we did that with one, we'll kind of use a version of that. 512 00:37:21,261 --> 00:37:29,966 So I think for me, comes down to like, what is the job of inventing a wheel of actual invention? 513 00:37:29,966 --> 00:37:34,485 is going to have to remain a part of the designer's core skill set. 514 00:37:37,546 --> 00:37:44,286 I think there's lots of reinvention of wheels going on out there and being sold as, well, you want a website, it's 100,000 pounds. 515 00:37:44,286 --> 00:37:46,166 But we've done 14 of them. 516 00:37:46,166 --> 00:37:48,166 We're just going to repackage this one. 517 00:37:48,166 --> 00:37:49,966 There's a lot of that going on. 518 00:37:49,966 --> 00:37:55,146 And I think, to be honest, look at it, it's same people sitting down. 519 00:37:55,146 --> 00:37:58,318 A website is now, I'm using that as an example, but you could take anything. 520 00:37:58,318 --> 00:38:02,438 is a very well thought out, very well understood artifact object. 521 00:38:03,038 --> 00:38:07,378 clearly you want to make it right for that brand. 522 00:38:07,378 --> 00:38:14,498 But for me, we're talking a sort of co-pilot logic here, which is get me to a good decent first draft so it's all structured and labeled right. 523 00:38:14,498 --> 00:38:19,718 And there's no like stupid mistakes where the site map just doesn't connect and has broken ends to it. 524 00:38:19,718 --> 00:38:25,658 And then let me go in and add in how this is going to work for this brand and this particular use case. 525 00:38:25,658 --> 00:38:27,060 I just think that 526 00:38:27,060 --> 00:38:38,223 Design has been doing a lot of recreating of things and treating that as creativity when not necessarily the case, when some of these things are already well-invented, 527 00:38:38,223 --> 00:38:41,895 well-understood, and it hasn't really done us any favors. 528 00:38:41,895 --> 00:38:50,777 Equally though, the best briefs are the ones where, right, we're struggling in this market, everybody's things look like this, everybody's things look like this. 529 00:38:50,777 --> 00:38:52,844 We need something that's different. 530 00:38:52,844 --> 00:38:53,674 Right. 531 00:38:53,674 --> 00:38:55,736 And again, it comes back to your point about just the client. 532 00:38:55,736 --> 00:38:58,134 I used to say, they say we want innovation. 533 00:38:58,134 --> 00:39:02,930 I'd say, okay, do you actually mean you want to invent something new or improve the thing you've got? 534 00:39:02,930 --> 00:39:07,823 Because if it's improving the thing you've got, I do think AI has a role to play there. 535 00:39:07,823 --> 00:39:16,668 As I said about testing things, researching things, understanding things, coming up with options, potentially then designing that and the evolution of that thing. 536 00:39:16,668 --> 00:39:21,090 But if you want something brand new, like very inventive, I totally agree. 537 00:39:22,270 --> 00:39:26,573 I wouldn't say never because I just don't know how this is going to change. 538 00:39:26,653 --> 00:39:36,950 But I'm with the lady who said, and it was a lady, think he said, I want AI to be doing the dishes and washing up so I can do the art, not the AI doing the art. 539 00:39:36,950 --> 00:39:38,502 So I have to do the washing up, right? 540 00:39:38,502 --> 00:39:41,744 I'm very much in that zone, but I do think we can't help. 541 00:39:41,744 --> 00:39:50,946 But some of the drudge work, not the drudge work, because some people love doing boxes and AI and IA, sorry, and information architectures. 542 00:39:50,946 --> 00:39:54,569 But let's be honest, when I did information architectures, I always forgot about little bits. 543 00:39:54,569 --> 00:39:55,639 I have to go back and do them later. 544 00:39:55,639 --> 00:39:59,512 The joy of an artificial intelligence is it generally is complete, right? 545 00:39:59,512 --> 00:40:01,573 It doesn't finish the job till it's finished. 546 00:40:01,894 --> 00:40:06,397 So you'd expect me to be a bit pro at it, and I am quite pro at it. 547 00:40:06,397 --> 00:40:11,061 I think that designers have peddled a lot of design that isn't really creative work. 548 00:40:11,061 --> 00:40:18,146 It is just taking something else and putting a slightly different skin on it, on patterns that are very well understood. 549 00:40:18,146 --> 00:40:21,400 which is maybe a spicy take, but that's the one I'm giving it. 550 00:40:21,400 --> 00:40:26,435 So my response to that would be though, I think that is a systems effect of the environments they're working in. 551 00:40:26,435 --> 00:40:33,395 In that the agile digital product kind of thing has been very, very, it's been great for so many things, right? 552 00:40:33,395 --> 00:40:45,833 It's really improved the ability of teams to get past all that sort of uh waterfall stuff and big brands, enterprise brands that actually, most of my banks having had really, 553 00:40:45,833 --> 00:40:47,032 really awful. 554 00:40:47,032 --> 00:40:50,143 kind of apps and stuff now have kind of reasonably decent ones and things like that. 555 00:40:50,143 --> 00:40:53,628 I, you know, that's definitely because of that. 556 00:40:53,668 --> 00:41:02,847 On the flip side is I tweeted or I didn't tweet because I don't tweet anymore, but I tweeted the other day and I put it on LinkedIn, which is a sort of AI is kind of the wind 557 00:41:02,847 --> 00:41:04,938 tunnel of creativity, right? 558 00:41:04,938 --> 00:41:13,248 But you know, there's some very famous silhouettes of cars out there, you know, small cars, sedans, know, SUVs and... 559 00:41:13,248 --> 00:41:16,401 In the silhouette, they all look the same and that's because they've all been designed in a wind tunnel. 560 00:41:16,401 --> 00:41:21,306 And at some point everyone optimizes for pretty much the same stuff and everything starts to look the same. 561 00:41:21,466 --> 00:41:31,797 In my experience, whenever I've been using a chat GPT or whatever it is, it gravitates towards that sort of mediocre middle and chat GPT therefore sounds always like kind of a 562 00:41:31,797 --> 00:41:37,502 management consultant because it's like very average stuff spoken with amazing confidence. 563 00:41:37,642 --> 00:41:46,700 And what I'm saying about design is I think in an environment where that was a sort of lean and agile thing where speed and velocity without much thought is always held up as 564 00:41:46,700 --> 00:41:49,312 the most important thing because it comes from that startup world. 565 00:41:49,312 --> 00:41:52,655 in other areas, it doesn't make so much sense. 566 00:41:52,655 --> 00:41:59,300 When everyone is working very, very fast or under pressure to work very, very fast, they'll lean into what the tools do well. 567 00:41:59,621 --> 00:42:01,282 And so they'll use... 568 00:42:01,366 --> 00:42:10,492 that particular what used to be, know, rave posters all look the same because they all had the same flash shot filter or, um you know, in the rise of flash and all the vector stuff. 569 00:42:10,492 --> 00:42:13,754 It's all vector stuff because that's what the tools did well. 570 00:42:13,775 --> 00:42:15,616 They all leave their signature. 571 00:42:15,616 --> 00:42:21,180 And now, you know, with Figma, you can always tell, you know, this has just been a kind of design pattern that's been pulled down. 572 00:42:21,180 --> 00:42:25,903 And in some cases, obviously, the design system, which the designers are just kind of pulling on. 573 00:42:25,903 --> 00:42:30,356 there's not really that, as you're saying, there's not really that much original work being done. 574 00:42:30,734 --> 00:42:39,174 kind of feel like that is that's not because designers come forward, it's because they're under pressure to operate really quickly. 575 00:42:39,174 --> 00:42:45,746 I worry that the sort of AI kind of say the AI Figma stuff just kind of perpetuates that and just makes it even worse. 576 00:42:46,382 --> 00:42:47,102 I it will. 577 00:42:47,102 --> 00:42:47,482 I think it will. 578 00:42:47,482 --> 00:42:48,442 I think there's two pressures here. 579 00:42:48,442 --> 00:42:51,822 One is like a sort of general capitalist, neoliberal pressure. 580 00:42:52,442 --> 00:42:56,542 You know, make it as lean as possible and scrub everything out. 581 00:42:56,762 --> 00:43:01,502 But there's also a pressure the other way, which is people like familiarity, right? 582 00:43:01,502 --> 00:43:09,322 And do I want the copy explaining something to me about what I should do as a small business to be written by a copywriter? 583 00:43:09,322 --> 00:43:09,942 Or do I... 584 00:43:09,942 --> 00:43:11,862 It's just instructional in that sense. 585 00:43:11,862 --> 00:43:12,682 It could be written... 586 00:43:12,682 --> 00:43:15,138 As long as it's written in plain English for... 587 00:43:15,138 --> 00:43:20,079 the average age of 10, which is the average reading age for the most of the UK. 588 00:43:20,079 --> 00:43:21,409 And most corporates don't do that. 589 00:43:21,409 --> 00:43:31,543 And I was surprised when working on copy stuff that people still write copy for people who are like, you know, reading age of like 15, 16, like the economist, you know, and people 590 00:43:31,543 --> 00:43:32,113 don't, right? 591 00:43:32,113 --> 00:43:39,405 So you can tell an AI that I want you to write this for the reading age of average UK reader or whatever country you're in. 592 00:43:39,405 --> 00:43:40,785 And it will do that. 593 00:43:40,785 --> 00:43:42,686 And it will do that repeatedly. 594 00:43:42,718 --> 00:43:43,686 And 595 00:43:43,966 --> 00:43:46,227 Sometimes you don't want creativity in there. 596 00:43:46,227 --> 00:43:48,926 You just want, and I'm talking about service stuff here. 597 00:43:48,926 --> 00:43:50,199 mean, marketing is different. 598 00:43:50,199 --> 00:43:51,959 Marketing, you're trying to capture attention. 599 00:43:51,959 --> 00:43:53,550 You've to have something creative in there. 600 00:43:53,550 --> 00:43:56,121 I think creatives are reasonably safe in some of that stuff. 601 00:43:56,121 --> 00:44:00,713 I saw the Toys R Us little video that someone's put out that saw a creative. 602 00:44:00,713 --> 00:44:08,216 I think there's a way to go with capturing attention and delighting the soul of another human via AI. 603 00:44:08,216 --> 00:44:09,377 I think there's a way to go. 604 00:44:09,377 --> 00:44:13,312 But a lot of the stuff we're talking about is 605 00:44:13,934 --> 00:44:21,914 Um, it's, it's, it's just a lot of work that I used to do as service designer is like, well, we just got to get into the terms and conditions and we've got to get into the 606 00:44:21,914 --> 00:44:22,854 instructions on this page. 607 00:44:22,854 --> 00:44:23,994 And do we have to have those there? 608 00:44:23,994 --> 00:44:26,594 And if we are, can we make them really much simpler, please? 609 00:44:26,594 --> 00:44:28,614 And, I'd have to work with copyrights to do all that. 610 00:44:28,614 --> 00:44:35,074 And I'm not having a go at copyrights here, but I think everybody wants to bring creativity to a project that often doesn't need it. 611 00:44:35,334 --> 00:44:38,734 Um, but we, we, we need creativity in the right place, right? 612 00:44:38,734 --> 00:44:41,614 I'm not denying that because your point about everything. 613 00:44:41,614 --> 00:44:46,534 All those rayflies were the same until they weren't because somebody said, hold on, I'm going to do something different. 614 00:44:46,534 --> 00:44:48,994 And I don't think there'll be any different here. 615 00:44:49,014 --> 00:44:51,714 AI already is making everything very generic. 616 00:44:51,714 --> 00:44:54,474 And so then something else will have to change. 617 00:44:54,474 --> 00:44:57,034 And it will always be a creative decision to make that change. 618 00:44:57,034 --> 00:45:02,234 is a lot of very generic, mean, lot of the, I don't know, I had like three or four websites open for different stuff the other day. 619 00:45:02,234 --> 00:45:05,294 And I looked at them and I was like, wow, these, they're all using the same typeface. 620 00:45:05,294 --> 00:45:08,314 They all use the same hierarchy, you know, as it was all. 621 00:45:09,994 --> 00:45:11,414 It wasn't bad. 622 00:45:11,414 --> 00:45:17,154 I wrote this essay a little in my newsletter, the last newsletter it was called, it was called On Mediocrity. 623 00:45:17,154 --> 00:45:24,614 And you know, it was like, well, it's just H &M t-shirts, you know, everything's like H &M and it's kind of fine. 624 00:45:24,686 --> 00:45:26,508 but it's not very exciting either. 625 00:45:26,508 --> 00:45:29,199 No, and I think that's it, right? 626 00:45:29,199 --> 00:45:33,961 And a lot of organizations settle for it's fine. 627 00:45:33,961 --> 00:45:39,854 And lot of managers will and workers will settle for it's fine because it makes their life easier. 628 00:45:39,854 --> 00:45:41,834 If you can do eight hours work in one hour. 629 00:45:41,834 --> 00:45:47,467 mean, you know, people do gravitate towards that sort of, you know, decision making. 630 00:45:47,467 --> 00:45:56,030 I think that's why AI is so disruptive inside organizations because you want the quality there and who determines what quality looks like when everybody has access to something. 631 00:45:56,118 --> 00:45:57,319 like this. 632 00:45:57,319 --> 00:46:08,063 think AI within the organization and having proper guardrails on that so that people are creating good quality right for this brand, right for this organization, whether it's 633 00:46:08,063 --> 00:46:13,905 internal comms or external customer comms, whether it's in a service that's outward facing or inward facing. 634 00:46:13,985 --> 00:46:18,677 there's so many, you know, it takes me back to almost like the early days of the dot com, right? 635 00:46:18,677 --> 00:46:20,168 It's like, this is all new. 636 00:46:20,168 --> 00:46:21,048 Where do we start? 637 00:46:21,048 --> 00:46:21,789 What's important? 638 00:46:21,789 --> 00:46:23,558 And the perennials are still the same. 639 00:46:23,558 --> 00:46:25,474 Like if you're trying to capture my attention, 640 00:46:25,474 --> 00:46:28,495 You've got to be interesting and I've got to love something about this. 641 00:46:28,495 --> 00:46:30,955 But if you're just trying to tell me to do something, just give me the facts for you. 642 00:46:30,955 --> 00:46:32,287 But in fact, get out of the way. 643 00:46:32,287 --> 00:46:36,239 And the promise of AI obviously is to get totally beyond the interface, right? 644 00:46:36,239 --> 00:46:42,508 Is that I'm just like, hey, em AI thingamajig, I need a holiday next year. 645 00:46:42,508 --> 00:46:44,743 You kind of know what my family likes. 646 00:46:44,943 --> 00:46:46,194 Come back some options. 647 00:46:46,194 --> 00:46:48,105 know, like we talk about body doubles. 648 00:46:48,105 --> 00:46:51,086 I'd like to send a version of myself off into the world. 649 00:46:51,086 --> 00:46:55,826 as a gopher and it will come back and say, well, I found three holidays and they're in this sort of price range. 650 00:46:58,006 --> 00:46:59,826 That's very attractive. 651 00:47:00,906 --> 00:47:04,746 The question we might come onto is that what does that mean for a designer? 652 00:47:05,286 --> 00:47:07,026 Because in a way, I'd like to be a designer. 653 00:47:07,026 --> 00:47:12,286 could go off and do secondary research for the day as a body double, come back, tell me what you've learned. 654 00:47:12,286 --> 00:47:15,854 But I still want to be the person who synthesizes it and goes, oh. 655 00:47:15,854 --> 00:47:16,674 That's the thing. 656 00:47:16,674 --> 00:47:23,574 I think there's a thing I read the other day, is, you know, what AI doesn't have is sort of common sense discernment and taste. 657 00:47:23,634 --> 00:47:33,114 know, I think one of the things that does, and it's interesting actually, because I looked up the etymology of intelligence today, because I was to make a snarky comment on 658 00:47:33,114 --> 00:47:33,974 LinkedIn. 659 00:47:34,294 --> 00:47:35,634 But it was, and it's that, right? 660 00:47:35,634 --> 00:47:37,094 It's pretty much that. 661 00:47:37,534 --> 00:47:42,914 And so, you know, artificial intelligence is such a sort of misnomer. 662 00:47:42,914 --> 00:47:44,896 I think one of the things that 663 00:47:44,896 --> 00:47:52,800 what you just described does then highlight is the, differentiates really good ideas from the kind of craft dazzle, right? 664 00:47:52,800 --> 00:47:55,852 And I think that that sort of evens that out. 665 00:47:55,852 --> 00:47:57,032 We are actually coming up for time. 666 00:47:57,032 --> 00:48:08,668 So there is one final question, the one small thing question, is what one small thing is either overlooked or could be redesigned that would have an outsized effect on the world? 667 00:48:08,992 --> 00:48:10,833 Okay, you talk about a thing. 668 00:48:10,833 --> 00:48:16,306 I'm going to go right back to the beginning of the conversation because it's a bit of an attitude really. 669 00:48:16,306 --> 00:48:30,254 um I think it's an attitude to serve that I've designed into all sorts of organizations or tried to, and I've certainly tried to do it in ours, which is service and service to 670 00:48:30,254 --> 00:48:37,237 others, whether it's people that you work with, or whether it's a customer that's giving you some money for some exchange of value. 671 00:48:37,237 --> 00:48:38,420 But for me, 672 00:48:38,420 --> 00:48:41,412 It's a real anchoring concept. 673 00:48:41,412 --> 00:48:48,877 um I've been a service designer, I know service designers, but I don't think most people really think about service as a concept and what they're trying to do. 674 00:48:48,877 --> 00:48:54,461 But for me, it lifts my entire life, which is why it's connected with religion. 675 00:48:54,461 --> 00:48:58,083 And I'm not religious, but I can see why that connects. 676 00:48:58,104 --> 00:49:05,519 So for me, if you're doing any sort of design, you're thinking about a service, don't just think about the service as the noun, right? 677 00:49:05,519 --> 00:49:07,680 Think about the verb, the doing of it. 678 00:49:07,686 --> 00:49:12,027 And what is the, what are you trying to move forward here? 679 00:49:12,706 --> 00:49:16,977 Is it, it's not necessarily you're trying to create a widget or a product or anything like that. 680 00:49:16,977 --> 00:49:19,489 It's like, what is the outcome you want to achieve? 681 00:49:19,489 --> 00:49:21,080 Now that's a bit abstract. 682 00:49:21,080 --> 00:49:28,652 It's not a thing, but it is very meaningful to me that I am trying to serve the world in a better way. 683 00:49:28,652 --> 00:49:34,113 And therefore that anchors me down to what does this person need to move forward? 684 00:49:34,113 --> 00:49:34,714 I don't know. 685 00:49:34,714 --> 00:49:36,054 I need to find out. 686 00:49:36,802 --> 00:49:38,573 but it's helped me through my design career. 687 00:49:38,573 --> 00:49:46,948 And it just so happens to be helpful because the majority of businesses in Western countries where I tend to work are service industry organizations. 688 00:49:46,948 --> 00:49:49,390 And I'll be honest, they don't really understand what that means, right? 689 00:49:49,390 --> 00:49:57,895 They have forgotten because of their scale that their service organizations and helping them to remind, and everyone knows, like I used to start my workshops and you probably do 690 00:49:57,895 --> 00:50:00,637 something similar by saying, right, I just want to go around the room. 691 00:50:00,637 --> 00:50:02,316 Just tell me the best services. 692 00:50:02,316 --> 00:50:03,560 Yeah, service. 693 00:50:03,560 --> 00:50:04,740 Or tell me the worst. 694 00:50:04,740 --> 00:50:06,061 Yeah, tell me the worst. 695 00:50:06,061 --> 00:50:06,921 And everyone knows it. 696 00:50:06,921 --> 00:50:09,181 Everyone's like, my God, and they'll never forget the worst one. 697 00:50:09,181 --> 00:50:10,232 They'll never forget the best one. 698 00:50:10,232 --> 00:50:13,073 But then they go back into the service organization, so they forget it. 699 00:50:13,073 --> 00:50:18,474 So I think just rekindling that little flame, and I have it on every aspect of my life. 700 00:50:18,474 --> 00:50:19,015 I try to. 701 00:50:19,015 --> 00:50:21,715 There'll be people listening to this going, John, he doesn't do that for me at all. 702 00:50:21,715 --> 00:50:22,976 But I am trying. 703 00:50:22,976 --> 00:50:31,064 And I just think it really helps to create an integrity to the design process, to whatever you're trying to do. 704 00:50:31,064 --> 00:50:34,476 So that's the one small thing I'd ask everybody to take into account. 705 00:50:34,476 --> 00:50:35,988 I think it can change the world, right? 706 00:50:35,988 --> 00:50:43,723 I think service is a, I actually heard Keir Starmer talking about it in his speech, a return to service. 707 00:50:43,723 --> 00:50:46,305 King Charles did it in his speech, all about service. 708 00:50:46,305 --> 00:50:47,419 No one's really getting it. 709 00:50:47,419 --> 00:50:48,757 So I think it's a communications issue. 710 00:50:48,757 --> 00:50:49,360 I got it. 711 00:50:49,360 --> 00:50:51,569 So I'm the one person going, yeah, I get it. 712 00:50:51,569 --> 00:50:53,230 Because I think it's really profound. 713 00:50:53,230 --> 00:50:54,590 That's very fine answer. 714 00:50:54,930 --> 00:50:55,930 Thank you very much. 715 00:50:55,930 --> 00:50:57,710 Where can people find you online? 716 00:50:57,710 --> 00:51:00,014 Arwin is arwin.ai. 717 00:51:00,014 --> 00:51:03,914 Arwin.ai is where you'll find our service and what we do. 718 00:51:03,914 --> 00:51:04,994 You can find me on LinkedIn. 719 00:51:04,994 --> 00:51:09,394 I'm probably mostly there these days because we're a B2B software as a service business. 720 00:51:09,394 --> 00:51:10,934 That's where we live. 721 00:51:11,094 --> 00:51:12,974 I used to have blogs and things. 722 00:51:12,974 --> 00:51:17,494 I am on X, I am on Instagram, I am on all these places because it's my business to know how they work. 723 00:51:17,494 --> 00:51:22,234 But LinkedIn, otherwise arwin.ai or joel at arwin.ai. 724 00:51:22,286 --> 00:51:22,929 Thank you very much. 725 00:51:22,929 --> 00:51:25,319 Thank you for being my guest on Power of 726 00:51:25,396 --> 00:51:25,770 much. 727 00:51:25,770 --> 00:51:26,973 It's been a pleasure. 728 00:51:27,448 --> 00:51:29,579 You've been watching and listening to Power of 10. 729 00:51:29,579 --> 00:51:38,437 You can find more about the show at pelain.com where you can also check out my leadership coaching practices, online courses, sign up for my very irregular newsletter, Doctor's 730 00:51:38,437 --> 00:51:39,128 Note. 731 00:51:39,128 --> 00:51:42,471 If you have any thoughts, put them in the comments or get in touch. 732 00:51:42,471 --> 00:51:47,575 You can find me as atapelain at pkm.social. 733 00:51:47,575 --> 00:51:50,457 I'm on LinkedIn, my website, you'll find it everywhere. 734 00:51:50,457 --> 00:51:53,060 You Google, all the links are in the show notes. 735 00:51:53,060 --> 00:51:56,162 Thanks for listening and watching and I'll see you next time.