Digital Works Podcast
Talking about all the different things that 'digital' means in the arts, culture and heritage sectors. Tales of success and failure, interrogating the shiny new things and looking at what works (or not) and why, Interviews with digital folks working across the sector and beyond, in-house, consultants, funders, and more.
Digital Works Podcast
Mike Keating (Art Fund) on the collaborative development of AI policy, balancing the priorities of being both a membership and sector support organisation, and the impact of COVID on Art Fund's digital transformation
A conversation with Art Fund's Associate Director of Digital Experience, Mike Keating.
Most of our chat focused on Mike's relatively recent work in developing Art Fund's first AI policy. The collaborative, open, and pragmatic approach that Mike and colleagues took to this work feels like a useful model that other cultural organisations could borrow from.
We also talk about the benefits and downsides of being a digital generalist, Mike's feelings about technology in general, the impact of Covid on how Art Fund thinks about digital projects, and lots more.
Art Fund (artfund.org) is an organisation with three main areas of focus; they fund art "helping the UK’s museums to enrich their collections", they grow audiences through their National Art Pass membership scheme, and they advocate for museums through initiatives like their Museum of the Year award.
Hello and welcome to the Digital Works podcast, a podcast about digital stuff in the cultural sector and if you need a hand with your own digital work. I'm also a consultant who helps cultural organisations make the most of all this stuff. In today's episode, I'm joined by Mike Keating, who is the Associate Director of Digital Experience at ArtFund. We explored what digital means for an organisation that juggles everything from membership and e-commerce to sector-wide support. We talk about the challenges of wearing multiple hats, how Art Fund has shifted its approach post-COVID and, perhaps most pressingly, how they've tackled their AI policy. Mike shares how they went about crafting their AI policy, taking an approach that's practical, open and focused on what can be most useful. Plus, I think there are probably a lot of lessons that cultural organisations can learn from their process. Enjoy. Thanks for joining me today, mike.
Ash:Let's start with hearing a bit about your career and your background. You're currently at Art Fund, which is a really interesting organisation We'll hear a bit more about in a moment. How have you ended up where you are doing what you're?
Mike:doing. How did I end up here? My entire digital career is based on once upon a time being the youngest person in an office, and because I was the youngest person there, I was asked to look after the Twitter account. So I worked at a charity services agency. We did a lot of print design for charities and a big part of my job was being in InDesign every day doing mock-ups and ads and that sort of thing.
Mike:And then this thing called Twitter comes along. Someone senior gets wind of it, of it, and they're like, oh, we probably need a young person to do that, so maybe we should give the keys to I don't know that guy and yeah, that's whoever I can't even remember who it was and they're basically responsible for my entire career. Now, yeah, eventually left that agency and moved into the charity sector and did a sort of half print, half digital job back when charities especially were like maybe this internet thing isn't going to work out, so let's hedge our bets and get someone who can do a little bit of both. But yeah, after that joined Samaritans as their first digital comms manager and sort of had a really generalist role looking after what became quite a big team doing a bit of like social email marketing, digital projects, service design, kind of a lot of product stuff. And then, yeah, eventually ended up at Art Fund after that and being in the arts, yeah felt like the kind of change of scene that I needed at that point.
Ash:And your role at Art Fund. Art Fund is a really interesting organization and I'd like to hear how you define Art Fund, as I will inevitably get it wrong. What does the work of you and your teams look like, art Fund? Because I think the nature of the work that Art Fund does as a membership organization and a sort of sector support organization is very different to the focus of an in-house team at a cultural organization.
Mike:Yeah, and we're sort of both right. So I try and think of it almost as two separate organizations. Sometimes, where we are like this membership organization, we are very consumer focused and we sell a product, so we sell the National Art Pass, and a huge amount of our skills and efforts are devoted to doing that well, and then we have this whole other side where we're giving out money to museums, to galleries, to arts organizations around the country, and they both kind of inform one another, right. So the better we do at selling those passes, the more money there is to give out, and the more money we give out, the more great stuff there is for people to go and see. So it does link up. But sometimes when you're working on it it can feel like you're in this mode today and then tomorrow you're in the other mode, and it makes it really varied and interesting. But yeah, it also means your brain is switching from very different kind of perspectives quite regularly.
Ash:We've worked together a little bit and I've heard you speak at conferences and stuff and the breadth of digital stuff the helpfully elastic word digital feels stretched, especially taught at Art Fund, because you do everything from product through to content, direct consumer, e-commerce. You know there's a whole journey around how people get their art pass and then you're also working with and sort of helping the sector. You know there's been big digital learning projects. You've done stuff around ai policy. Maybe you're a bit like me and, as a generalist, that diversity of stuff is exciting and interesting, but it sounds like you're wearing a lot of very different hats and that could maybe be difficult.
Mike:Yeah, and like with this hair, I'm not a hat guy, but yeah, it is a lot. You know like you are responsible for quite a lot and with digital there are always a million different ways you can cut it right and we've cut it a certain way. But even the organization next door to us have probably got a completely different definition of what digital is, and I think so many of us who maybe started in digital roles like I did probably about 10 to 15 years ago you had to know everything. You had to know a bit of how to do literally everything, and people who came in at that time are now in starting to find themselves in roles like mine, where you're a lot more senior but you've been able to do everything for so long that it can actually make it quite hard to distinguish what you think digital should be, because you've always been told it's everything. But I think that keeps it interesting.
Mike:I would be really bored if my remit was really narrow and certainly in the last year and a half my role has really broadened from being something that was overtly around like digital projects, building a kind of user-centered design culture, and like bringing in a lot of expertise around analytics, user research and really understanding what people were doing and why. And now it's really broadened out to include, yeah, like content, social, brand and creative. But all of those things I was just talking about that were applying quite overtly to digital can be applied to all of those things too. Right, you do want to understand how your content is performing and why and then making decisions based off that. And you want to be doing the same with brand and creative and call social social, and we keep it slightly separate from content, but there'll be loads of organizations that don't do that, but the principle is the same.
Mike:You want to know, basically, why people are doing what they're doing and how you can use that information to make stuff better. And I think that's really empowering and quite disconcerting, but also really interesting, because users tell you loads of mad stuff all the time that you would just never expect. My favorite thing about my job is being wrong, because it might be. You launch a new section of a site, you change the design of a page subtly, you run a split test or you try some content that you've never tried before, and that feedback is out there and waiting. But I love it when that feedback tells me something I don't expect.
Ash:That's what keeps it interesting for me it sounds like art funds understanding of what digital means for them as an organization has perhaps shifted, evolved or matured.
Mike:It sounds like, as you said, your role has broadened and perhaps you're being brought into more conversations about what art fund does to provide a digital layer or perspective to the conversation yeah, I think one of the kind of watershed moments, certainly on the kind of grant giving and support side of the organization, was a project we ran a few years ago to look at the impact of the digital funding we'd given out during and just after covid.
Mike:Like loads of organizations needed money to keep the lights on or to keep the laptops open, essentially, and knew they couldn't open their venues anymore but needed to reach people and digital was going to be the answer to that and we gave out loads of money to help different organizations do that. But what we hadn't really been doing, certainly with digital funding, was really looking a year later what impact has that had? Has that kind of work been sustained? Has it fallen away as the fundings run out? And working with our kind of development team and our programs teams on that really sort of opened their eyes to what digital can do and made my job about so much more than just their kind of well, just the kind of e-commerce sides and making sure the tweets were doing numbers.
Ash:So, yeah, that kind of really broadened things for me from my perspective, as someone who sits very close to, but outside of, the in-house day-to-day life of the sector, that shift is really encouraging because I think, broadly speaking across all parts of the cultural sector, the shift in focus to increase the priority around digital stuff that happened during COVID hasn't really been sustained in a meaningful way beyond that. So it's really exciting and interesting to come across organizations where you can genuinely say that COVID was this watershed moment that actually changed how we as an organization talked about, thought about digital and how that mapped across everything we do yeah, and I think what that piece of research really showed us was that the organizations who were sort of doing a bit of digital already, it was much more likely to be sustained.
Mike:But those ones that you know were kind of pretty good at it anyway and maybe even had a strategy around how they use digital, those were the ones where it had been sustained. And then we sort of looked at ourselves and we're like, do we have a digital strategy? I don't know that we do. And then it was like oh Mike, that's your next thing to do. And yeah, it kind of became really interesting because we ran this research project to kind of show the sector what it could be doing differently and we learned that there was something that we should be doing differently too.
Ash:And one of the big things you've been working on has been the work you've been doing around your AI policy, which feels like a logical next thing for us to talk about and maybe came out of the self-reflection that the organization did Okay, we need to do some work on digital strategy. Actually, at the moment, ai is absolutely part of that conversation. What does the art funds? What are we calling it an AI policy? What does it say? What is it intended to do and to guide?
Mike:Yeah, good question. I think it kind of came out of like you said we did that digital strategy and then, off the back of that, we ran an internal digital skills piece that we worked with substract on, and what that showed us was that you know most people pretty good generally at using the stuff they're supposed to be using at work, but there was a lot of uncertainty and unfamiliarity around ai at that point. So this is the end of last year, end of 2023 we found about a third of people at art fund were using ai in some form in their day to day jobs. They might be using it once a month, they might be using it once a day, they might be using it once an hour. We just didn't know.
Mike:And the findings of that survey really pricked the ears of, like our like finance guy was like whoa, this feels risky, like we need to put some structure in around how people are doing this and understand what they're doing it for.
Mike:And so it kind of came out of this we need to protect the organization from risk, because there are a lot of risks associated with using AI in lots of different ways.
Mike:But then it also became about well, if we know, a third of people are using it. How do we encourage the two-thirds who aren't to maybe start to either take an interest or think about how they might want to, if they want to use it at all in their roles? Because it is such a like divisive technology in a lot of ways and there's a quite a lot of fear at least in our experience around people who would rather just not know anything about it at all and pretend it's not happening. But those people are sat right next to someone who's using it day in, day out. So for us it became like how do we strike a balance between those two types of people and how do we get that person who's really afraid to at least make a what you might describe as a more logical or logic-based decision around whether it's right for them? And then how do you kind of harness the power or creativity of the person who's using it loads to make sure that they don't, you know, end the world from art funds offices.
Ash:And this maybe sounds like an overly detailed question, but I think it's useful In terms of the form of the policy, how specific are you going? Are you saying these use cases? We absolutely encourage them, whereas these use cases absolutely do not go anywhere near?
Mike:those, yeah, and we actually started from the complete opposite direction.
Mike:So when I was briefed on this, I thought we can trust people here right to use this stuff in the right way, and we went down a really principles-based policy. So it was kind of six principles broadly around, like don't use ai to break the law, only use tools that you kind of understand. Use maybe some of these tools for these sort of specific use cases. And then there was some stuff in there really around ethics and from my perspective, like I sort of hate technology and I find it quite amusing that I've ended up doing this job, especially like in relation to AI, but it's quite important for me that we're not using it to not pay people that we might otherwise pay. I don't want it to be something that like takes jobs away from people at ArtFund, but also something that takes jobs away from freelancers that we work with regularly, and while I'm all for it helping save people time or make their jobs of slightly better quality, that sort of felt like a red line for me and that really came through in the principles, so like, if you're currently doing video editing by paying a video editor, please don't subscribe to one of these kind of like ai tools that might be much cheaper because we're not ready as an organization to move in that direction yet. But yeah, it came across really principles based, and we presented that to our smt and they were like this is great, but could you just be really specific about what you can and can't do, because ultimately you've got two-thirds of the people here who are afraid of it or don't want to use it. Can you do something that brings them along? Because what we had produced was really only speaking to people who had some familiarity with it already.
Mike:So where we are now, we have a policy that's based on those principles but is much more instructive and much more rules based. So there are some pretty hard and fast rules that kick off the policy and then we kind of go into example, use cases to make that stuff feel a bit more real. Because even having rules, if you've never sat down at ChatGBT or Claude or whatever before, knowing that you can't use it for these things and can use it for these things, doesn't really tell you how you might do that. So, yeah, rules, and then you know, here's a way you might want to use it to create a draft of a presentation, or here's how you might use ai to distill a 200 page report for you. And then, yeah, we kind of go into like all these things that you can't use it for and like we're quite prescriptive around not using it certainly around data, but also around visuals, like we're an arts organization and we got a really good steer from SMT that you know.
Mike:Ultimately, art Fund is about getting people into museums to have a real life experience and using that as a kind of almost guiding principle. You shouldn't be using AI to like, make up art or make up people or make up videos. So we have a kind of pretty strict set of rules around. You can obviously use some of those tools for draft purposes, but there is a zero percent chance they are making it outside of the building and Art Fund is never going to be publishing AI generated video or AI generated art, because that's just not what we're about weren't engaging with this stuff, have at least joined the conversation, because you've been able to say absolutely play with it in the office, but it's never going to find its way into a marketing campaign.
Ash:It will never be used to replace commissioned imagery on the website. I've often found that when you can be very specific with people who are perhaps scared of change or technology, then they go.
Mike:Actually, you've specifically addressed a lot of what my fears were related to, so now I feel like I can join in the conversation in a useful way yeah, because so much of the policy is now about, you know, chat, gpt is good at these things, claude is good at these things and gemini, yeah you know, is great for like footnoting everything. So if you're really worried about using it, that's probably a good place to start. And then, if you're using these tools, here are like five things that you could consider using them for. And when we launched the policy so we did that internally, probably about five or six months ago we did a show of hands in the room to ask if anyone had been using AI in their roles at all and we found that about half of the people in the room put their hands up. So we'd been letting them know this was coming and we'd been giving some like ad hoc pieces of guidance to teams when they came to us. But yeah, we found in that sort of period between that skill survey and it being around a third, it had jumped up to about half.
Mike:But what was fascinating about that was the look of just terror and surprise on the faces of people who hadn't used it. They couldn't believe that. You know even one of their like work best mates who they were sat next to when they didn't raise their hand. They were like, oh my God, they're using it, why aren't I using it? And it created this sort of real sense that the people who weren't using it were, in a way, like they were afraid they were being left behind or that they'd ignored something for maybe a bit too long and now couldn't afford to ignore it.
Mike:So, yeah, that felt quite revealing and off the back of that, we ran a series of training sessions, one being an intro based one and then one around kind of like marketing, and finally one around using it for data and research. We ran those sessions with jocelyn burnham, who's done a lot of work in that space, and we had yeah, I would say probably about I would say around like a third between the third and half of the organization join at least one of those sessions, and most of those were new people who hadn't used it before. I think a lot of people were like yeah, I.
Mike:I'm using AI in my way, I'll sort of make sure I'm not doing anything wrong, but I might not pay a huge amount of attention to your policy. But the policy kind of has become much more focused on getting those newbies in the door, helping them assess whether it's right for them and also just sort of being okay with.
Ash:If AI is not for them or isn't really going to make a meaningful difference to their jobs, then leave it alone and I'd like to talk a bit more about process, because it's been really helpful to hear where you've ended up in terms of focus and form, but, I think, because this is such a nascent area, that people are really there is a bit like.
Mike:I guess it looks like this, but I haven't seen one before, so maybe it doesn't, but it works for us and it feels like you're being quite open about that with your organization.
Ash:You're not going. We have squirreled ourselves away and here are the 10 commandments of AI etched in stone and they will never change. Actually, you're saying as of 2024. This is our understanding of it. That may change, and I'm intrigued to hear about the process you've undertaken to arrive at the policy as it currently exists today. Was that something that you took on individually? Was there a working group? Did you engage with external experts? How did you start?
Mike:that process. Initially it was quite a small internal group of staff working on this. There were three of us initially who came up with the principles that are now the foundation of that policy. But what we used was that skill survey and the findings in that, which told us, yeah, a third of people at ArtFund are using it in some way, but this is specifically how they're doing it. So early on we had a clear sense of like people are sort of using it to basically do copywriting and some image generation and what bits of this are fine and what bits do we feel aren't. And then we came up with these principles, looked back at the different ways people were using it and basically used that to assess whether people at Art Fund were using it in a way that was internally cool or internally uncool. And then we took that to our SMT.
Mike:They were quite engaged with this as a topic for lots of different reasons, I think some people seeing it as a huge opportunity to make people's processes much quicker. Some people seeing it as an opportunity to save some money. Some people being on the other side of the fence and just being like I don't think we should really be going anywhere near that and I do think you need people with that perspective in the room because otherwise it's all too easy to just run really fast with this stuff and get yourself in loads of trouble. But yeah, we brought that to smt. They eventually approved it and we did an all-staff session, so there's about 70 of us at art fund and that was really interesting because we got loads of really like fascinating questions people asking us about you know, how does this sit with our sustainability policy? And there's a lot out there about like the amount of power that ai uses and these data centers use. And I was quite open about not being able to answer that question because this is a work in progress. This technology and what it does will change quite a lot even over the next sort of six months, let alone several years. Kind of mitigate that or to almost take advantage of that change and that discussion.
Mike:Certainly we have an internal ai working group who review the policy every four months and yeah, when someone asked that question about sustainability, I was like, yeah, we don't know, but you can help us figure out the answer to that and thank you for volunteering to do that. Now you're in the ai working group. So yeah, we have this like group of people who are just across the organization, completely different roles, different perspectives and they all sit down now and look at the policy and sort of say, like, do these examples still make sense? Is there new stuff in here that we could be giving people a helping hand with? Has our thinking around, you know, using it for audio or using it for music or using it in this way has that changed? And, if so, we need to make sure that's reflected here.
Mike:So it's gone from being something like three of us worked on initially over a team's call, to this thing that now has a group of probably about 10 of us, all feeding in different perspectives, and that helps make it a bit more sustainable, because there's no way, like I said earlier, like I hate technology and I don't want to be keeping up with ai every day and I can't and no one really can so if you have these different perspectives, who are, all you know, plugged into different teams, all hearing about different ways of using it, that can help it feel fresh and keep it relevant and up to date but also means it's not just one person's job to do that and would it be fair to say that that approach or the model that you've landed on with this cross-organizational input, with people who are very much not in digital roles feeling that they are able and comfortable to feed into something which is ostensibly heavy quotation marks a digital policy?
Ash:do you think that's a result of the increase in digital maturity that we spoke about earlier, or is it that you know ai's in the news all the time at the moment? People feel they can have a say on it yeah, I think it's a mix of both.
Mike:I think some people in that group they would describe themselves as like very digitally literate or fluent and know how to do loads of cool stuff, and that's all cool stuff that I have no idea like I'm a I'm gonna air quote a digital expert, but like some of the stuff they're talking about I've never heard of, never even thought about.
Mike:And then, yeah, you have a group of people in that room who, you know, feel very strongly about the sustainability or the ethics side of things. And then there are people in there who are like yeah, this is like very newsworthy and I want to be involved with it, kind of. Because of that, some people definitely see it as an opportunity to learn because, like, this is probably a technology that will be with us for, I guess, quite a long time, probably a technology that will be with us for, I guess, quite a long time. And certainly people who are starting out in their careers are like how can I get in on some of this stuff now and understand how this stuff comes together? Because that will really help me out in the future.
Ash:And it feels like the dynamic that's been achieved at Art Fund feels like what so many digital folks have been sort of pushing the boulder up the hill for the last 20 years in the sector trying to achieve. You know, trying to get that sort of engagement from across the organization so you can have better conversations, a conversation that's speaking to all those different perspectives and it just so happens that ai ended up being the sort of sharp end of the spear on this but can you imagine a world in which that sort of pan-organization conversation could happen around other aspects of your digital activity?
Mike:yeah, you can definitely imagine that because, yeah, I guess when we were working on a digital strategy, yeah, we weren't getting the same level of engagement as we have done for this. I think there's something in. I think if you want to achieve that cross organizational level of engagement, you need to do a couple of things, and one, I think, with AI and certainly with how I've spoken about it, owning that you aren't sure that this is right or that this will change over time, I think makes the barrier to entry much lower. People feel much more comfortable not being an expert and getting involved in that conversation, and I'm sure there are people listening to this who will think, oh well, I actually don't want non-experts getting involved in this piece of work that I'm doing, but that perspective can be really useful, because digital is all about solving problems for people. It's not about the technology. I think the other thing that's important is almost a degree of novelty.
Mike:We've also been working on some content strategy recently, and one of the things we did with that was actually test content ideas with real human beings, so we brought a bunch of people in who we would consider to be our main consumer audience and this kind of new consumer audience that we're trying to reach and this kind of new consumer audience that we're trying to reach. And as a team, we'd workshopped a bunch of different ideas and we put them in a room and we played them some videos and we showed them some content. And it all felt quite exciting because we'd never worked that way at ArtFund before. There was definitely a lot of trepidation within the team around, like, are they going to rip apart everything that they've worked really hard to create?
Mike:And once you get over that hill and you do the sessions, everyone was like, oh, that was brilliant. And then they start to talk about it and people across the organization are like, oh, wow, that sounds pretty cool. How do I apply something like that to my job? And so I think that degree of like, novelty and something that is almost like maybe a little bit like scary in a way, does grab people's attention. If you're working on something that does feel like a bit new, maybe slightly risky, that can be a huge benefit to like getting much more people across the organization involved in a hopefully positive way. I think that degree of novelty can make all the difference. Otherwise, you know, know, with a lot of digital stuff. People are like oh well, don't we have a digital person to worry about that? So it is almost how do you market your own? Quite often, marketing work internally and yet novelty.
Ash:Yeah, I think I think that really helps and the next set of things I want to ask you about is you know the approach you took to this was very much you were open about. You were learning as you went. You were going to be collaborative in your approach. This was a evolving piece of work. I know there are lots of other cultural organizations thinking about ai policies, ai principles, ai guidelines. Is there anything that you learned that you would say to anyone who is starting down this road? You know you absolutely have to think about this. This will be way more controversial than you think. Everyone will have an opinion about this. What are the sort of hard learned lessons?
Mike:I think there were kind of two key things that would have saved me quite a lot of time, and I think one is, I guess, like not being afraid to be really prescriptive. There's probably a reason if you're working on an AI policy or a set of rules or whatever whatever you call it there's probably a reason someone has asked you to do that, and that's because they think you are the best available person to solve that problem. And I would try and feel empowered by that kind of trust that you've been given. And with that, yeah, I think remember that a lot of people are afraid of this technology and actually will really resist ever trying to get involved in it, and you need to kind of do something for the people who are afraid but interested, and the best way to do that is by being. You can use it to do this, you cannot use it to do this, you cannot use it to do this. You can use this tool for copywriting, you can use this tool for research, because that's what breaks down the barriers. If you just tell people, oh yeah, there's this thing called AI and here are some websites, that's not going to reduce People feel like they're going to do it wrong, and I guess, yeah, take that as an initial focus, like, what can you do to make people feel like they aren't doing it wrong?
Mike:The other thing that I think would be helpful to people starting out in this is like really understanding what your main area of focus is going to be.
Mike:For some organizations that's going to be we want to use this tool to save money, and that's fine.
Mike:I don't necessarily agree with that, but I can understand why different organizations might want to do that or might need to do that, and if that's your primary goal, then that gives you a very clear set of parameters around what kind of tools, what kind of things you might want to be doing with those tools.
Mike:That kind of lays that out for you. If it's to save people time, that gives you another very clear steer. Or if it's to make people's jobs of like better quality, that's also another like clear area of focus, and I think you can kind of start moving in all three of these directions, because you're trying to please a lot of different stakeholders. I think the thing that will make this easy for everyone in the long term is understanding which of maybe those three areas is most important to your organization and kind of moving in that direction and trying to leave the other two behind. If it's like a venn diagram of like saving money, saving time and making people's jobs better, which one is important to you and move that way and it sounds like certainly the art front experience was that.
Ash:And it sounds like certainly the art front experience was that inviting people into the process was of real benefit.
Mike:Yeah, I think doing that survey and finding out how people were using it initially and then hearing about different use cases in internal teams, that really helped make it real, because you know a lot of what I was saying there about like what your focus might be, all sounds kind of theoretical and, ultimately, if that doesn't align with how people are actually already using it because, let's face it, loads of people are and if you're thinking about working on an ai policy, you're probably doing it because you know people are using it and you have no idea what they're doing.
Mike:Yeah, it feels like bringing in that information, those like, whether they were like a power user or they've used it once, like what was that thing that got them in, why are they using it and how are they using it. And you know that's your user research. That's showing you, like what people are really doing and you want to create a policy that basically makes the most of the cool ways people are probably already using it and my last set of questions is not about AI, but maybe your answers will be about AI.
Ash:As we said earlier, the digital work of ArtFund is so diverse and broad and interesting. So many of the things that the teams you work with do are because ArtFund has made some really intentional choices and investments. What are you most excited to focus on over the next 6, 12, 18 months?
Mike:I think for me personally, it's been really exciting to get back into the kind of content and social space. It was something when I joined art fund and my role was very much focused on, like user-centered design, digital projects where you kind of you would hit a wall from time to time where you've designed something but you have no control over the content that goes on that thing you've designed and so, working in a much more broad experience focused role, it's been really exciting basically to get back into that sort of space where you get to think about the whole thing end to end instead of your part of the journey very much ending at a certain point, I think. For Art Fund, though, I think this AI stuff is probably one of the things that we're looking at. For the sector, we've obviously run a crowdfunding platform that actually closes at the end of this year and we have a ticketing platform, which has really helped loads of museums, and I think for a little while we were like are we going to do another? Like big, what's our next big digital thing?
Mike:And, yeah, working on that kind of research project with the sector, understanding how effective that digital funding had been, that actually showed us that there wasn't really much consensus around what people in museums thought that organizations needed digitally.
Mike:We were talking about like, do you go down a contactless or donations platform sort of route is almost like a consultancy model, something that's useful or something around content creation. And then this ai stuff sort of happened to us but has come at a really interesting time where, like you said, lots of organizations are looking at this stuff. We have done this thing slightly before, quite a lot of other organizations, and I personally think you know if someone has done some of this work already. We should be sharing that as far and wide as possible. So I'm really like interested in and open to basically sharing this pretty broadly and people being able to like pick up their version of it and then do what they will with it and that sounds hugely exciting and probably something the sector should do more of around sharing knowledge and best practice I think when I was in the more like trad charity sector, that was a really big part of the culture of that sector.
Mike:Everyone would know who everyone was in digital roles everywhere, like you could pretty reliably know someone who knew someone who did that job and it was very easy to reach out. And I think in our sector I think covid maybe broke a lot of that and for lots of reasons, lots of people either left the sector or changed jobs and those networks haven't super effectively been rebuilt yet. And yeah, I think if there's one thing I would like to do with this kind of ai policy is not necessarily rebuild all of that, but show that you know you can do this and then you can give it to other people and that's not only just fine, it's good and I think that is a brilliant note to end on.
Ash:Thanks. So much, mike. Thanks. Thanks for listening. If you enjoyed this conversation and want to hear more, you can find all episodes of the podcast on thedigitalworks, and if your organization needs help making sense of digital, you can get in touch with me via my website at ashmanco. That's man with two Ns. See you next time.
