Dodging dystopia: crowdsourced foresight in ArmeniaJan 19, 2015
At Kolba lab here in Armenia, we have been testing foresight.At Kolba lab here in Armenia, we have been testing foresight.
We’re trying to gauge its potential in shaping the UN’s strategy in Armenia and in supporting the design of future development programmes.
This blog is the second part in a series aimed at sharing our rationales, experiences and results. In the previous blog post we said why we chose the futurescaper platform. We share our experiences here!
Our ambition was to create a sample map of the future of Armenia as imagined by Armenians. With futurescaper we created a questionnaire asking what participants thought were the most important trends in Armenia today, how those trends might evolve in 5 years, and then again in 20 years. We then asked how those trends might interact with the trends that other participants had identified. We also asked users what should be done to manage these trends and who should be responsible for this.
We decided to send out the survey in three phases, each one building upon the last. Phase one gave respondents open space to define the trends that they thought to be important. Phase two gave a set list to choose from, compiled on the basis of the answers from the first phase.
What did we discover? Here’s a few of our key findings to date:
1. High levels of outmigration is seen as the most likely future scenario.
2. Environmental issues are not perceived as the no. 1 challenge of the future, by anyone.
3. The government is far and away seen as the only body capable of doing anything about Armenia’s issues.
4. Corruption is an issue in all spheres.
These results are not paradigm-shaking. They’re not meant to be. Foresight is intended only to complement existing development initiatives, providing a more grounded way of thinking about the future, and using crowdsourcing platforms like futurescaper we can make development projects more inclusive to all areas of society, occasionally uncovering areas that need more work, or potential blind-spots lying around the corner.
A pilot exercise such as this has been a steep learning curve for the Kolba Lab team, but one that is informing foresight exercises in other UNDP offices across the world. Our biggest lesson came from our engagement metrics: we reached out to 26,747 people over the first two phases of engagement, of which 1,100 started the survey and only 74 completed it. The wapping gap between survey starts and completions has led us to a few conclusions on how better to crowdsource foresight exercises:
1. Incentives are important. Crowdsourcing works when the users are rewarded by their engagement with the platform. Without the analytical interface that we in the office benefit from, futurescaper is just another (albeit sophisticated) survey. This doesn’t mean that foresight models can never be successfully crowdsourced, but rather they require more open, inviting models that are able to offer incentives to the user, such as a game, in order to harness fully collective intelligence.
2. Keep it simple OR choose your target well. Either your survey is simple (and you might not gather the insights you would like) or you keep the complexity, but only involve experts (thereby sacrificing inclusiveness). Our survey didn’t take the regular online format, it took more than 15 minutes and required respondents to think hard. Anecdotal evidence suggests that this was too much for many users.
3. A captive audience is best. If you opt for the complex survey, make sure that you have a captive audience in a workshop or event that has committed an hour to participating in the foresight exercise. Whatever direction you go in, be ready to speak about the new format offline, explain foresight and futurescaper’s approach and the benefits it can bring.
4. Crowdsourcing won’t do all the work for you. This type of crowdsourced consultation on trends and their solutions might help in your work, and it might guide you and validate your tactics. Nonetheless, this method should still be considered as only one component of a larger participatory approach to development design.
Next in the series, our results from the first two phases. Watch this space for updates...