Learning Bit by Bot
7th February 14
Posted in robotify.me
Tyrell: Would you … like to be upgraded?
Batty: I had in mind something a little more radical.
Tyrell: What … what seems to be the problem?
Blade Runner, 1982
Robotify.me – what we did, what we learned and what we’re doing now
In December 2012 we launched robotify.me, an experiment to test our hypothesis that seeing social media behaviour visualized could actually influence and change those behaviours. Perhaps, we asked ourselves, data visualisation might reveal surprising nuances of social media behaviour which might otherwise be overlooked?
How would it feel to compare activity – likes, links, retweets, checkins, photos – with the rest of the group’s data? Would the transparency of the visualisation cause any changes in social behaviour? Would inveterate retweeters be shamed into posting more original content? Could we encourage more checking in, more posting of photographs, more liking by visualising the effect that it had on the robot?
Robotify.me was also another opportunity to learn and experiment with process. Could we create a service rather than a campaign? Could we work fast and lean and create a mvp? Could we create a product without a brief, without a client?
A little over a year on, the answers to some of these questions are in. The first thing to say is thanks. Thanks to the team who worked so hard (and gave their time so generously) on robotify.me and thanks to everyone who took part in this project. Thousands of you created robots and we loved seeing the project come to life, reading the tweets, hearing your thoughts and feedback on this thing we’d made.
Much of what we learned is displayed in the infographics accompanying this post and some of our early learnings were incorporated into changes we made live on the robotify site in the early go-live days and weeks. Perhaps our major learning was to do with storytelling – if we wanted people to learn a little about themselves we should, perhaps, have shown more, and told more explicitly. Knowing when to intrigue and when to explain is something we will take with us in the future.
We also learned that when you have a team with demanding day jobs it’s impossible to schedule daily scrums and the focus and scheduling required for an iterative workflow are not easily applied to side projects. When we plan future Labs experiments (and more on that very, very soon) we’ll definitely be thinking about the sorts of projects that lend themselves to a leaner approach. Stretch is good, but restraints will help define scope from the very beginning.
So, we’re going to be pulling down the shutters on this particular garage and disassembling the robotifier, cleaning down the work surfaces and wiping down the whiteboard in preparation for a new swathe of Labs experiments, robotify learnings fresh in our minds. We’ll be keeping the service up in it’s current form for another month, so you can still create a new robot, revisit your robot mirror-self or download and print out your robots for your digital files.
Finally, thanks again for supporting our Robotify.me experiment.
Bleep. And out.