COVID-19 and the Citizenry: the first 120 days.
Findings using Artificial Intelligence to understand citizen trends and scenarios to exit the crisis.
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This technical note exposes case studies evidencing that understanding the needs of citizens is an indispensable condition to generate innovative responses to such needs.30% of the total conversation at the beginning of the COVID-19 crisis centered around topics relating to the pandemic.Once the initial moment was surpassed, the crisis continues to strongly affect citizens, but through diversified categories. |
Scenarios to exit the crisis: 5 initial conclusions.
1. Today’s citizens are putting tomorrow’s political agenda on the table. The evolution of citizens’ concerns reflects how, during the first weeks of the pandemic, the conversation was predominantly centered around the collapse of the healthcare system. A few weeks later, this conversation became fragmented into various social concerns, such as mental health and community hygiene.
2. Sustainable decisions are not made by responding to perceptions, but by structuring needs. Health emergency alerts (Section II) and innovations in the technology sector (urban mobility, tourism) are characterized by designing solutions to real needs, rather than responding to perceptions. These perceptions hide unmet needs, which must be codified. This last step is achieved thanks to the integration of Human Intelligence (HI) methodologies combined with Artificial Intelligence (AI).
3. Perception generates reality. Why is it relevant to recognize perceptions in time? People perceived a shortage of food. This perception was reported massively and instantly by social networks, which caused the emptying of supermarkets. Understanding these information networks, also generated in times of emergency, helps to contain the negative impacts of this perception. These trends can be very useful for measuring the impact of public policies, identifying needs, narratives and opportunities. CivicLytics, as a model of ethical Artificial Intelligence, can identify flourishing productive sectors. We saw an example of this in Peru, where a trend in a change in food consumption habits is identified as a result of the sanitary conditions of urban markets.
4. Citizen changes do not come from the media, but from structural changes. It is not enough to program the theme detector of a conversation; the situation requires one more step. In the case of Black Lives Matter, thanks to CiviClytiCs, we saw that throughout Latin America and the Caribbean there were testimonies of frustration due to an event that occurred during the confinement that many people considered racist. Many of these frustrations, which were developing in an “invisible” way, needed a great media event to bring it to light.
5. Big data (dis) connects us through segmentation: The virtual universe segments citizens in indecipherable ways (for now): There are social problems that are affect a certain sociodemographic group that another group in the same territory totally ignores.
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