An ongoing study by the University of Ghent in Belgium revealed that back in August, only 33% of Flems were willing to comply with the COVID-19 health measures, compared with 81% in March. The concept of complying or cooperating also evolves with time - it has ranged from hand-washing, social distancing, respecting the curfew, isolating, and recently, installing the contact-tracing mobile app provided by the government.

This lack of motivation is a serious issue, suppose that everyone around you decides not to follow any measures, and by doing so, it will put everyone at risk, increasing the number of infected and death numbers. This situation is called “tragedy of the commons” in social dilemmas, when acting in self-interest affects the common good - in this case, public health. Theoretical and experimental work on cooperation in social dilemmas, provide insights into how cooperation can be sustained. Understanding these principles may help policy-makers in making impactful choices.

Coronalert

The inclusion of technology (in this case the Coronalert, the contact-tracing app created for Belgium) might also affect our desire and motivations to cooperate (See studies from Rahwan et al & Crandall et al). Moreover, we as humans shape the behavior of these systems, both by providing the data but also by designing these algorithms and handling these data. Cooperating by installing an app on our smartphone and sharing our personal information such as location data also follows the social dilemma principle described earlier. A survey by the Kenniscentrum Data & Maatschappij reveals that 78% of the respondents believe that the data collected by Coronalert will end up in the hands of other organizations or companies, posing a risk for our privacy. Despite the mistrust, 51% of those surveyed are willing to install the app, however this cooperation rate drops to 34% after the corona crisis (which interestingly is the same cooperation rate as the survey by the University of Ghent revealed back in August).

According to some of the participants of the UGent study, reasons for this decrease in motivation vary from lack of straightforwardness from the authorities to the feeling that the fear for the virus is gone. Maarten Vansteenkiste, professor of Motivational Psychology at UGent argues that people might decrease or even lose their motivation to cooperate with time, because it is demanding: i.e. is energy consuming, and it’s seen as more of an obligation rather than an act of solidarity with society. The decrease of cooperation observed by Prof. Vansteenkiste is thus self-selecting for even less compliance.

How to tackle uncertainty?

Adding to the challenges of this pandemic, the responsibility to contain the virus still relies on how we coordinate our actions throughout an uncertain amount of time. This means that neither governments nor citizens know how bad the catastrophe is going to be, and for how long is going to last until an effective cure is found and distributed widely.

It has been shown experimentally that in crises such as climate change, participants failed to reach the predetermined goal when they were not informed about how long the experiment was going to last or how much effort was required. Recently, work by AI Lab Brussels’s (VUB) Elias Fernández Domingos, Prof. Jelena Grujić and Prof. Tom Lenaerts showed how timing uncertainty leads to generous contributions at the beginning. Yet, the same uncertainty also leads to inequity and polarization, requiring the inclusion of new incentives handling these societal issues.

This issue with uncertainty is reflected in this COVID-19 crisis where according to Prof. Vansteenkiste “it is important that the population gets perspective, that the government indicates in concrete terms where we want to go”. Indeed, having clear goals has been proven to increase cooperation in collective actions, or as a testimony by a respondent put it: "People are tired of it, it was promised that things would get better now" (Anja, 49).

By now, most of the population experienced some kind of behavior change: whether it was by peer pressure that we ended up complying with the regulations, or we became frustrated by seeing other people not cooperating. We as individuals must know that our own actions shape others’ actions and vice versa, since we all look for signals that validate or confront our own behavior. Work by AI Lab’s Prof. Jelena Grujić has shown that in general, people’s first instinct is to cooperate (as was confirmed by Prof. Vansteenkiste’s data at the beginning of the COVID-19 crisis). However, their context can shape their expectations and motivations (whether is to positively reinforcing it, or lead to frustration).

Going back to our society, it is the network of contacts that not only influences the spread of the disease, but also the “spread” or strengthening of cooperation. The work of Prof. Tom Lenaerts has shown that both, the shape of the network and the contact dynamics determine cooperation8. Therefore, it is possible to model the spread of the disease in conjunction with the spread of cooperation as this immediately reveals whether regulations have a chance to lead to the anticipated outcome.

Lessons learned from the crisis

In complex systems like public health, where people interact with each other, with technology and authority figures that regulate these interactions, taking a holistic approach to policy making is key especially in a fast-paced crisis like this one. The OECD recently published an extensive review of how policy-makers can benefit from the knowledge of behavioral insights, or how humans behave. In this review, the OECD stresses the importance of understanding the dynamics of behavior change and collective action. Since governments have a variety of methods to increase compliance, like hard measures and punishments or softer alternatives like information spreading, incentives and guidance, successful collective action depends on the knowledge on how these methods affect human decision-making.

Since all these measures are created having a model of human behavior in mind, with their assumptions and generalizations, policy-makers can risk losing people’s compliance. If for example, they assume people are “strictly self-interested” as traditional economic theory predicts and thus non-cooperative, while reality points to the fact that people are willing to cooperate for the common good, if the conditions permit them to do so.

Another lesson the policy review by the OECD, is that to increase trust in the authorities, they must be open with information spreading and knowledge to the population, avoiding the assumption that people will not understand or will panic if the information is shared openly. This is demonstrated by an effort of the Belgian government when they opened Coronalert contact tracing protocols for the public scrutiny, to ensure that different parties, like security experts, privacy advocates and the general public can give their input on the app.

Of course, applying this knowledge on human behavior is not without challenges. The AI Lab at the VUB is developing a project which has demonstrated how cooperation is harnessed differently among age groups, genders, cultural background, to mention a few. Ultimately, a lack of trust, both in the autorities and in other citizens, affects people’s motivation.

The efforts from the Belgian government to increase people’s motivation seemed to have worked, the same study from UGent in a more recent iteration showed that even with a second wave and stricter restrictions, the motivation to follow the health measures increased to 65% among the survey respondents. Interestingly, they argue that voluntary motivation is a better predictor of persistence than the obligatory motivation “(moet)ivation” as they call it, referring to the Dutch word “moet” meaning must. Trust is essential to achieve cooperation in this and all other social dilemmas, especially in future measures and the future of the pandemic will depend on how much we trust the regulators and each other.