Group-level

Summary of group-level impacts and factors that contribute to them

There is also evidence that collective intelligence initiatives lead to group-level impacts that reveal more coordinated and cohesive collective action. Evidence from climate-smart monitoring initiatives or citizen science projects with farmers shows that being involved in data collection about agricultural impacts means they are more likely to adopt new behaviors. For example, evaluations of the Seeds for Needs project have found that participating farmers went on to use a wider variety of seeds which increased their crop yields and helped them recover more quickly from climate shocks. This may suggest that when digital solutions have a critical mass of farmers from a given region, the aggregated changes they make could result in a significant shift in behavior at the group level.

There is evidence that financial incentives play an important part in encouraging sustained changes to behavior and can provide a critical level to enable participation when communities receive payments directly. The Vietnam Forests and Deltas programme from Winrock Capital is an example of community-based adaptation: automated payments are used to reinforce community actions that lead to positive environmental impacts. Using their phones, communities log actions they have taken towards restoring the local forest ecosystem and are rewarded immediately after the activity is verified. Pre-payment to incentivize action may improve adoption of pro-environmental behaviors. A trial with rice farmers in Punjab demonstrated an 8 to 11.5 percent reduction in crop burning, a significant contributor to air pollution in the region, as a result of upfront payments.

Several collective intelligence solutions facilitate peer-to-peer interactions through digital forums or allow people to learn about differences in attitudes directly from each other through deliberation. This gives individuals direct insight into how climate attitudes and behaviors are changing among their peers and neighbors. Research has shown that observing shifts in behavior among peers or anyone from a familiar “in-group” is more likely to trigger the adoption of new behaviors by individuals.

Community-based monitoring health-surveillance projects such as the Zika Premise project and DengueChat also demonstrated the value of collective intelligence for building community resilience to crises. As a result of citizen-led monitoring and actions taken by residents to eliminate mosquito breeding sites, there was a 27 percent reduction in high risk “hotspots” for the yellow fever mosquito. An evaluation of DengueChat in Nicaragua showed 90 percent reduced transmission of mosquito-borne diseases in five intervention neighborhoods compared to a 400 percent increase in areas without intervention. Through tailored training sessions and information provision they increased the capacity of communities to take action themselves to prevent the spread of vector-borne diseases. Importantly, in the DengueChat project, monitoring and information provision is delivered by local young people who are trusted by others in the community. Another example of community monitoring – in this case of water sources in times of drought – is an initiative developed by the UNDP Kenya Accelerator Lab.