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AI for societies
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AI for societies
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2022-04-28T00:00:00.0000000
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Language: EN.
Segment:0 .
JORIS ROULLEAU: Good afternoon, everyone. You can't talk about technology without talking about AI. But there's new applications coming up all the time. But what's in it, really, for societies? Is AI even relevant at all? Well, societies, as we've seen, need to face a number of challenges. One of them is revenue. Most societies have fewer valuable revenue streams. And those viable revenue streams are under threat, be it member fees or conference attendance or publishing with Plan S which is being discussed next door.
JORIS ROULLEAU: Another challenge is some members do question the value they get from societies. This is a comment that was on a Nature post. And it says, "I honestly don't get much out of being a member of the few societies I am in, besides discount on meeting registration and a few publications." That may sound a bit unfair, but we do know that societies are addressing these kind of issues, and trying to provide more value to their members.
JORIS ROULLEAU: There's no denying that member expectations have been increasing offline probably. And there's a lot of projects that societies have engaged with to try and deliver more online, as well. Expectations are driven by the likes of Google, Amazon, Facebook, Apple. Societies do pale in comparison, from what I've sampled, from what someone said earlier this morning as well.
JORIS ROULLEAU: The user experience is not really in a position to attract members there. So what does it have to do with AI? Well, I believe that AI is part of the solution to these challenges. There's tremendous potential for AI to deliver more value to members in the way of new benefits, new services, in the way of better user experience.
JORIS ROULLEAU: So what it means in terms of business? It means you can increase member retention, member engagement. You can strengthen and diversify revenue streams. So let's have a look. Concretely speaking, what can AI do? One example is personalisation. There's been talks about personalisation this morning as well.
JORIS ROULLEAU: But when people talk about personalisation, they're really talking about segmentation of their membership. We need to go one step beyond that. Iris.ai operates in the content discovery sphere. So what they do is they take in a natural language input, so text that someone, a human's, written. They process it. And they give you your personalised reading list based on that.
JORIS ROULLEAU: They use AI to do this. And you can train. You can train the results. You can train the AI to just keep getting better and better results over time. So say, for example, you've got your research grant. Feed it into the machine. That's all you have to do. It's been analysed.
JORIS ROULLEAU: And then content that's relevant to that, to you, to that research grant you've written, comes back. Not all of it might be perfect. You get the opportunity to say, "This is correct. This is not. I'm not interested." And then the results keep on improving. And then they do other thing that can refine their list a bit further.
JORIS ROULLEAU: But that gives you an idea of the level of personalisation you can get with AI. Grip is another example. I like their tagline, "Intelligent Event Matchmaking Software." Essentially, it's eHarmony for conference attendees. [CHUCKLES] But what they are doing is personalised networking. And again, they use AI to deliver that.
JORIS ROULLEAU: So I don't know exactly how they do it, but you can see they're putting the right people together who will have the meaningful conversations at conferences. You can also equally imagine how you can create a personalised conference program for your members without even asking them what they're interested in. If, as a society, you know what they work on from the data, you can deliver just the sessions they'd be interested in.
JORIS ROULLEAU: It also shows that AI applications are not online only. This is an application that's happening in conferences like these. To give you another example of where you can get personalised information is Research Professional. So what they do, they provide funding insights, again personalised.
JORIS ROULLEAU: What do societies do to help their members navigate grants and funding opportunities, for example, is one question you could be asking. Another area where AI is making strides and is solving problems is in transforming content into knowledge. What better example than the heavily regulated industries for this. If we take the example of banks or banking, banks can get up to 200 regulatory changes a day.
JORIS ROULLEAU: Now just imagine the amount of time and effort it takes for humans to track it, read it, understand it, process it, find out who's going to work on the relevant bits in your organisation. It's a massive burden and a massive risk for these organisations. Well, we see the regulatory technology industries come up with some AI solutions for these which do all of that or a lot of that automatically.
JORIS ROULLEAU: So you've got AIs that track the regulatory changes or the new regulations. They understand it, if understanding is the right term. But I mean, they process it, analyse it, identify what's relevant to an organisation, and what's relevant to different people, different departments, in an organisation, and just send the right-- notify the right people of the right things that are of interest to them.
JORIS ROULLEAU: It can sometimes also put that into context to help make decisions about what actions need to be taken about a particular change. So we can see here that we're again solving problems for people. We are helping them get more out of their day, basically. We've got content. We've got masses of content that it's just difficult to get through, difficult to understand.
JORIS ROULLEAU: AI does it for you. You can focus on what you're going to do with that knowledge, instead of having to go through that whole content. At 67 Bricks, we've mapped these benefits, the types of benefits you can get from AI into what we call a data maturity model. So what it shows you is the best charter of added value you can deliver to users and to members.
JORIS ROULLEAU: So most organisations will start with some raw content and raw data sets. And like I said, say, if it's regulation, you've got to read the whole thing and figure out what's relevant to you. And then you can, if you develop your ability to capture, store, and manage your data in certain ways, you can start providing additional value to your members, to your users, at the same time you reduce your users' effort in their daily job.
JORIS ROULLEAU: So you've got raw content, raw data. Then you add a level of granularity. You get smart content, if you got the right data and you do the right things with it. And then you can move on and get some personalisation features which I talked about earlier. And beyond that, you refine your data model, and you apply artificial intelligence to it, and you can get knowledge from your content.
JORIS ROULLEAU: And beyond that, you're getting to the top of the pyramid here. You get insights, which really what our insights is, they're predictions and prescriptions, so tell you what will happen, what's likely to happen in the future, and what you need to do about something, about a piece of knowledge, a piece of information you've got. So right there, you've got-- you've delivered the most value to users.
JORIS ROULLEAU: What's important to note here-- so it's all very well to decrease the user effort. But there's a price to pay for this obviously, and that's our role on the left hand side. It takes time and effort to build those data models, takes time and effort to move from one issue on to the next, capture the right data, analyze it, and transform it into something that delivers value. As I said earlier, the potential benefits for organizations like societies are tremendous.
JORIS ROULLEAU: I've listed briefly personalisation for members, and getting knowledge rather than content, so I focused on the member. But it's worth pointing out that the back office functions in societies can benefit greatly from it. If I just pick one example that came up this morning at the roundtable, we're talking about what would we do about an aging membership in a society.
JORIS ROULLEAU: And someone said, "Well, my first problem is I might notice it, but I have no hard data to understand it, to quantify it, and to understand it." Well, if you do, you can get much, much deeper knowledge about your members than you have now, which will drive better decision making. Other examples, I know CPD learning and so on, are big aspects of a lot of societies.
JORIS ROULLEAU: AI is promising in adaptive learning products, in predicting education need. It gives you better visibility of what to expect in the future. You can identify trends in your area of work or in your membership, so these are just a few examples of AI applications. Now AI is unleashing new possibilities in all areas, in all industries.
JORIS ROULLEAU: It is not a transformation that can be ignored. It is something that needs to be understood and harnessed, much in the same way that some companies transitioned successfully from film photography to digital photography, or Fuji film. AI will become something that will be expected because it delivers benefits, delivers value to users. And it will be implemented everywhere.
JORIS ROULLEAU: There's the various organisations I mentioned, and loads more which are applying it to your constituencies, to your members. Elsevier is gathering vast amounts of data and selling it as AI-ready. So that move to getting data, turning it into AI-driven value, is happening. So for organizations like learned societies and others, the challenge is to understand where the value lies, how they can harness AI to deliver that value to their members.
JORIS ROULLEAU: If they don't, well, members will go turn to, say, ResearchGate, Facebook, LinkedIn, maybe ZAPlit for their online community needs, then turn toward the organizations which provide these-- we know that they're questioning the value they get from AI. To remain relevant, yeah, AI is part of the solution. So how do you get started?
JORIS ROULLEAU: It can be daunting. You're like, well, first, it's technology. It's not something we typically do. And well, the stakes are high. Well, it doesn't have to be quite like this. I think like Charles said, first you want to start from understanding the member's need or your business need, anyway, as an organisation. AI is not a strategy.
JORIS ROULLEAU: Doing AI is not a strategy. You've got to understand how you can improve your organisation, how you can deliver more value. And by doing that, you've got to really take a holistic, unfiltered view of your members. It's too easy to be-- to have that kind of filtered view, and say, "All right, I know what my members want, they want to be able to download that PDF," right?
JORIS ROULLEAU: And not go the step beyond, say, "Why is it they need to download that PDF? What are they getting out of it?" for example. So really understand that. And then, don't be afraid of breaking the rules. Because organizations have been doing things in the same way for a long time, doesn't mean it has to be. That's why AI-based platforms are popular is because they do things differently.
JORIS ROULLEAU: They provide a different type of value, different type of service. You've got to facilitate experimentation if you want to-- you're not going to get it right the first time necessarily, if you try to change your whole organisation and implement AI everywhere. You've got to take it one step at a time and try something small scale.
JORIS ROULLEAU: And think about your data, as well, as I said earlier. AI is reliant on data. They're coming together at the top of that pyramid. You get to the top of the pyramid by marrying data and AI, essentially. So think about your organisation. Think about where you could add the most value to your members. And try something. How would you get there?
JORIS ROULLEAU: Do you have the data you need to try something different? Do you need to capture that data? And start small. Start with a proof of concept, a small capability that you can then expand on. See if it works. If it doesn't, try something else. So it doesn't have to be daunting. And I think this holds some of the keys of the future of societies, if they want to retain those members, in particular those newer generations which get value elsewhere.
JORIS ROULLEAU: Thank you. [APPLAUSE]