Knowledge Management in Social Labs
Evolving thinking about good practice
Thanks for this provocation Hamish Lindop - great to have some further korero on this subject as it’s been awhile since I wrote this.
This is particularly salient for me now as I’m currently designing an Information Stack* for a new Lab in Chicago. (edit: read about my reflections on that project here)
*The Information Stack is the architecture of how you archive information (e.g. photographs of whiteboards from sessions), how you move it around (e.g. how does the facilitation team get the latest information from the Secretariat if they change something important), and has a big role in shaping the public communications of a Lab.
The core of the work is looking at the storage, flow and ongoing usage of data and insights being generated in the Lab. It’s an interesting design challenge, which brings me back to these musings about how best to keep the knowledge active.
What I mean by that, is that I agree there’s likely to be a significant degree of the knowledge which becomes embodied and embedded in people’s actions and projects which emerge from the Lab. For them, it may just be a matter of being able to come back to the data over time.
However it feels like there will be significant amounts of data which isn’t acted on, or adopted per se. In this case, I’m thinking about how it may be useful for other people in the future — either connected to the Lab, or not connected. How do they find about the data, and how would they receive it with enough context to make it useful?
Your point about the communities being connected enough to socialise the insights, or connect people to it, is a significant strategy in a lot of technology-enabled organisations of this information age. With tools like Google Apps, Slack, Yammer and Hylo, we can very quickly reference and share the data and insights. I was reading this article by Ursula Llabres recently which references Social curation and digital archiving as an enhanced Knowledge Management strategy.
What I’ve become interested in, is how we surface the inactive data and knowledge, and do so to the Labs networks, the change agents, and the Governments and Civil Society organisations who are also facing similar (yet locally unique) complex challenges.
Example: I’m working on a Lab in New Zealand which focuses on youth mental health. What have other initiatives around the world learnt, and shared, which could shortcut our path to success. Currently the starting point may be a literature review, desk research, or if you’re lucky — a study tour. But this is an approach which takes a lot of time and energy, and doesn’t always yield great results. How else might we connect to an open source hub of learnings of previous Labs or initiatives in this space?
My search took me into asking what kind of technology exists, or will do soon, which has the sort of power to surface insights that we’re not yet connected to through our social networks or globals search engines. I ended up considering the role of Artificial Intelligence in this space, and acknowledging this will be a game changer.
I envisage a scenario where in the future I will be able to access the data, the insights, a summary and/or the details of the people who gathered them, simply by searching the general topic. Internet search already works like this to some extent, but with the addition of AI we should be able to much more easily cut through the noise of billions of bytes of data and information being generated constantly, through some important layers of context about why you’re searching for something.
So in short, whilst I think currently the best way of activating knowledge is through a culture of sharing, coupled with interconnected communities who are constantly looking out for one another, in the future I believe we will be able to add AI to the mix to bridge the gaps that us humans don’t quite span.
