Prediction is always difficult, said Yogi Berra, especially about the future. However, it's something we do quite a bit of (have you seen our
work on election prediction - Brexit, Trump, UK 2017, Germany etc - we got them all right) so I went along to the
NESTA Futurescoping 101 event on this last night see what they had
that I could steal to offer.
There were 4 talks on various ways of predicting the future, or more accurately 4 ways of making scenarios (reading entrails of dead animals is still outre, but with the return to the
Age of Unreason we are seeing I wouln't be surprised it it makes a comeback, albeit maybe with dead plants). Anyway, in summary they covered these 4 approaches:
Speculative Design - Cat Drew
Speculative Design is primarily the use of physical things to provoke debate, rather than using documents/words/numbers etc. For example Cat did one session on blockchain visualisation using a blood transfusion drone made of felt and other blue petery stuff to stimulate thoughts of what (electronic vampire?) blood donation services may be like.
Whether you agree with the approach or not (In my experience with Tech you do often do have to build a Future Thing for people to be able to think concretely about, and this looks useful for that - but it's risky to abstract the results too far without doing the hard sums....) she also noted some things that are important to scenario building no matter what your approach, viz:
- multidisciplinary teams
- can't be fantasy, don't make it too remote
- base it on evidence of research
- Suspend belief but no trickery
Games and Simulation - Florence Engasser
Simulation and game design are more my comfort zone area, so to an extent I knew more abot this approach than the others - anyway, it was all sensible stuff and Florence noted the main problems one hits with respect to modelling complex and unpredictable things (aka most future problems), and the benefits. As she notes, simulation helps in a number of ways:
- Model the trade-offs and outcomes (and some aspects often become clear in the dynamics of the model)
- Visualisation makes it easy to see things
- Collaboration - seeing things the same way (modelling often is a good way to bring people up to speed with a situation)
- Experimentation - safe place to experiment with changing factors and assumptions
Her summary of how to make it work was good, I liked the checklist of what a simulation or game needs, not so much the first 3 which are almost a given, but the last 3 which are often neglected by techie types, and are part of the "soft factors" that are so essential:
- objectives (getting these right is non trivial in my experience)
- mechanics (wish she'd said more on what they do here)
- balance between complex and simple (again critical for model acceptance)
- narrative for the scenarios
- choices people can make
- a journey, putting it all together
What I didn't know is there are a bunch of Nesta games in existence or production:
- Innovate
- Superbug
- Consortium
Inclusive Place based futures - Harry Armstrong
This was about how to have inclusive conversations with people about changes to their cities, buildings etc. Typically top doesn solution go awry, it's better to get the locals involved for a variety of reasons and avert failure:
- Appeal to democratic/ethical notions to get buy in
- To drive collective action needs a shared vision
- Driving nclusion of a large number can show wider benefits to make the project more attractive, and show flaws and avert failure that a small group won't see
Examples used were the Newcastle 2065 future city strategy and the Island of Aruba's 2000+ strategy for itself. Looking at the latter:
- Aruba in the early noughties took at collective approach for its future strategy and engaged 60% of the island's c 100 000 population,
- They used the Appreciative Inquiry approach (Discover, Dream,Design, Deliver )
- Then went on with scenario planning approach, across 10 workstreams
What interested me about this example is that Aruba had a change of Govt during the process and teh new people wanted to change or cancel some of the streams, but concerted citizen action forced their continuation - now
that is buy in
Lessons about this approach are salutary:
- works if it's authentic,
- don't do it if you won't act, expectation raising can be risky
- needs buy in from major players
- need neutral spaces for trust
- need to manage "the usual suspects" being involved
DiY Scenarios - David Finnigan
The approach here is to acting out a scenario as a short play or event. His view is that a scenario is an Imagined vision - doesn't have to be correct, but you need a range including a best and worst. So far same old same old, but his approach is to use the play as a vehicle to slip in the assumptions and outcomes as just part of teh narrative.
This evening he acted out making a nature documentary in the future, but members of the audience had to answer assumptions on the role of nature reserves in the future, impact of tourism, and the various other assumptions about the future, using the play-acting as a vehicle to sideways slide in the assumptions of the real scenario, ie the setup conditions as part of the building the story, and the edenouemaent is anarrative end of teh reults of the various 2x2 essumption matrices.
Overall impression - the evening seemed a bit heavy on the qualitative and light on the quantitative, my experience is at some point someone with the power of decision making says "show me the numbers behind the grand vision" (which is where simulation type modelling has an advantage), so while I could see how some of the more narrative approaches could really help the envisioning.
I think - as Cat noted in the first talk - always base your scenarios on evidence of research.
