The Future is Human – GenAI’s role within Communities of Practice (Part Three)
Part three of this series is going to cover the things that could be for us and our communities in the almost immediate near future
So here we are at part three. To quickly recap – in part one we covered the fact that generative AI tooling is able to replicate a lot of the tasks that we as humans are capable of. We looked at ways it can do many things faster and more efficiently than its human users can. And we reminded ourselves that just because we can doesn’t mean we have to – that we don’t have to replace our own role in relationships and communities just because technology exists that can copy it. That we can automate important human experiences to the point that they lose all value and worth (looking right at you Dear Sydney).
In part two we concentrated on things that generative AI can do to enhance our communities by doing heavy lifting tasks that a computers are better at than their human users are. Sometimes they are a good thing to do, sometimes they’re less good to do – as always, responsible use brings good outcomes, irresponsible use less so. Today in part three, we’re going to look at the now and near future…..use cases that may or may not be available in the near future that would help elevate our communities and time spent together, rather than devalue and replace it.
Facilitation: Ok before we get started, I’m NOT suggesting that we replace the role of the facilitator. I don’t want to be facilitated by a robot any more than you do. But let’s think about what could be here – think about a time where you were in a community session and the room just kind of goes…..quiet. Everyone’s looking at each other wondering where to go next, but no one can quite work out how. We feel like we’ve reached a conclusion, yet somehow no one feels satisfied with it. And as the room looks to you, you realise that you don’t really know what to say. I don’t pretend to be an expert but I would like to think that I’m at least a fairly a good facilitator, and this has happened to me plenty of times. And I bet its happened to you too. At some point, sometimes the whole room falls into the same thinking trap and can’t find a way out of it.
We’ve spent years coming up with techniques that help us think differently – there are approaches like de Bono’s Six Thinking Hats to promote different modes of thinking (which I love by the way – some of my favourite workshops use this approach), and there are approaches like a modified version of the Tenth Man Rule, where we ask someone to intentionally disagree and think differently. We as leaders and facilitators spend time and effort and energy learning new techniques to tackle this problem, but as we are ALWAYS learning, some days we find a problem that we haven’t encountered before.
So what if……what if there was a tool that could unstuck the room? What if there were something listening to the conversation, reading and interpreting the whiteboard or your Miro space or whatever tool you are using, that at the moment the room goes quiet you could ask the most human of questions?
“What are we not thinking about?”
We understand that even in their current LLM driven format, GenAI tooling is trained on a vastly greater corpus of information than you or I ever will be. We may agree or disagree on whether it is better at interpreting that data than we are, but right here we’re not asking it to interpret it or provide some greater insight than our squishy human brains could hope to accomplish – we’re asking it to give us suggestions of things we’re not thinking of. As we’ve mentioned before, we can ask a GenAI tool to assume a persona if we want – along with all that persona’s view points and biases (well, what it interprets them to be anyway) – to tailor it to provide insights and challenges that will be useful to us. In theory the technology (if not the capability) to do this is already pretty much there – a party piece I like to do when giving short presentations is to ask a GenAI tool to listen and then when I get to the end, I get it to ask a question that I didn’t cover in my material. This works to a point, because currently the majority of commonly available tools can only handle a certain size input. They find it hard to differentiate between the different voices in the same room (without the meta-data it gets from Zoom or whatever online tool you’re using). even on multi-modal tools the input windows will find it hard to handle verbal and visual inputs at the same time, and it would be really derailing if it fills its input window 5 minutes into a 20 minute discussion. And to my knowledge, I don’t know of any custom designed hardware/tools that sit in the middle/corner of the room that would perform this role for a group (well obviously there’s your phone as the hardware, but as I say I don’t know of a tool available that would do it on your phone). But if we can get to that point, think of the additive effect it would have on those discussions
Knowledge Management: Again, this is nearly there. If you use Notion like I do you’ll be aware of Notion AI – a tool that (somewhat predictably) reads everything in your Notion space and provides you with insights and information. I use Notion to host my zettelkasten, and like everything I do, its not quite perfect. I fill it with insights, I order them and link them and then, at the moment of truth when I realise I need a particular bit of knowledge, I find that my system has let me down and the bit that I KNOW I wrote down isn’t there. So I ask Notion AI to go find it for me, along with any other references that are relevant. Its really good at it.
Let’s scale this principle up a bit. One of the most valuable things a community of practice brings in a knowledge based domain is the concept of shared memory – that as a group we collectively know and understand more than any of the individual members. That as a group we all act as nodes in a collective network that supports everyone who is part of it. This has pros and cons – if someone leaves the community, the collective capability goes down. If that person is not there on a particular day, the community is less capable than it would be if they were there. Sometimes we try to write down and capture our knowledge, but then it doesn’t get maintained, it gets forgotten about, it goes unused for so long that it becomes outdated until someone actually needs it and finds out….knowledge management is hard.
What would be useful would be to have some form of tooling that is able to help manage that collective knowledge for us. Something that interprets the context of discussions, is able to recognise what that relates to, is able to offer up relevant information that already exists within the community’s shared memory. A tool perhaps that is able to automatically (or at least highlight) when parts of the community’s knowledgebase are out of date or being superseded by something new. A tool that recognises relevant gaps in the community’s collective knowledge, and suggests ways in which those gaps might be filled.
Nothing here is replacing the human involved in the process, and to my mind (although I am open to being challenged on it) there is nothing here that is devaluing the community or the human interactions and capabilities within it. What they’re doing is helping the members of the community become more effective – to do more together than they would without it. And the thing is they’re so close – all the pieces are there, they just needed to be assembled in the right order to meet the needs that we actually want them to rather than making custom emojis so you don’t have to talk to your friends and covering the meaningful moments with your children so you don’t have to stop watching Netflix. Its why, as someone who values human interaction above all else, I encourage everyone to experiment with generative AI and other emerging technologies – because we are all responsible for building the future that we want, and if we don’t take part in it and demand the use cases that will help us, someone else will do it instead.
I’ll be honest I had a few other use cases that I’d planned to write about, but this has ended up being a lot longer than I’d expected it to be. I will add a part four in the future, but I have other ideas I’d like to write about next before doing so. What I’d like very much though is that if you have any ideas of your own please add them in the comments, I’d love to hear about them!
Thanks so much for reading, if you’ve enjoyed this post I’d really appreciate it if you could share it - alternatively you could always buy me a coffee :)