“Our society despite its sophistication is incredibly wasteful with human intelligence”
- Nesta
On Monday, Nesta launched the Centre for Collective Intelligence Design, a new and exciting opportunity to explore how human and machine intelligence can be combined to make the most of our collective knowledge and develop innovative solutions to our tricky social challenges.
Collective Intelligence (CI) isn’t a new idea. The first Oxford English dictionary was compiled by 1000s of people who each submitted words and meanings. More recently populations have been mobilised to support scientific studies looking at nature events here on earth and astrological events in distant galaxies. But as we move further into the digital age, opportunities are emerging to combine our human intelligence with machine learning and artificial intelligence. The question is, what does the future hold for human-machine CI and how might we design for it?
The launch event which was run in collaboration with Sage publishing and saw researchers, academics, practitioners and designers coming together to discuss:
Where the filed of CI is right now
What we know about CI
Ideas around how we might advance the field
Opportunities for collaboration
I attended the event by invite, joining other designers to take part in a workshop looking at the role design can play in CI. We wanted to use the workshop to start a conversation around what a set of CI design principles, similar to the GDS Design principles, might look like.
Some of my key take a ways from the workshop discussion were:
Design can ensure we are use CI to solve the right problems
Design can bring empathy to CI. Machines don’t have empathy and AI is quite a way off plugging the gap
Design can make CI usable and accessible
Design can ensure that CI is ethical
Design enables us to understand people’s needs, desires and motivations. We know from citizen science work that people want to feel like they are helping; Looking at pictures to find new galaxies or count penguins is OK but studies show that if the stakes are too high (i.e. spotting cancer cells) people feel uncomfortable and want to participate less.
This was a successful first step towards a set of design principles and was a great opportunity to start the right kinds of conversations.
All in all it was a fascinating day spent looking at the topic through a macro lens, but as I sit on the train typing this post my mind is swirling with ideas around how we might apply the same principles to our own organisational intelligence. Taking a micro view and starting to explore the question:
I’ve been giving some thought to this question for some time. Through our localities approach we are starting to learn about our customers and communities in more detail than ever before. We are using this ‘rich information’ on an individual level, but I’m not sure we’ve managed to make the most of it at an aggregated level. The truth is that aggregating analogue, tacit knowledge, the kind of knowledge that arguably makes up 90% of our organisational intelligence but is difficult or impractical to transfer between colleagues is tricky, because it isn’t stored as hard data which can be interrogated at scale. This feels like a missed opportunity. As a service designer I’m keen to uncover ways in which we might be able to access and curate what amounts to our own CI. The insights we could uncover would be gold dust; enabling us to spot emergent trends and pick up weak signals from our communities that will ultimately help us to design better preventative services which improve outcomes for our customers whilst at the same time helping the business work smarter.
So watch this space. I’ll be writing more on the topic over the coming days . . . Once my brain stops fizzing!
