The uncertainty of the pandemic has turned into an opportunity for the implementation of technological solutions to complex issues rather than an occasion to deploy coherent decision-making processes. During the social and economic crisis caused by COVID-19, the National Development Office of Colombia, set up an unconditional funding transfer system for three million citizens. The program, called Solidarity Income, was kickstarted in just two weeks. This post analyzes what kind of social policy is Solidarity Income, what are its problems for building a fairer society, and which is the role of technology and authoritarianism in this COVID-19 emergency context.
by Joan López
Ever since the 1990s, the Colombian social policy can be understood as liberal, because it is based on targeting resources on people below the poverty line. The Colombian state has created mechanisms to identify the poor people and bring to them the limited resources available. How is this approach evolving during the pandemic, and what is the role of “big” data in this process?
Different programs
The System of Possible Beneficiaries of Social Programs (known as Sisbén in Spanish) appeared as the main instrument to target social assistance. This system rates people with scores from 0 to 100 in terms of household prosperity. To grasp the difference between Solidarity Income and more traditional social policies, we should understand how the allocation of a social benefit worked in terms of the data used to identify the beneficiaries.
Sisbén‘s targeted social programs used an examination of the conditions of each household in which citizens were considered actors in data production. The score emerged from an institutional effort to virtually search for vulnerable populations through surveys in impoverished areas. Depending on the score received, families are eligible for social programs implemented by different state agencies. The minimum score to be eligible varies across agencies, and is set independently by each program.
The Solidarity Income set up in response to the pandemic has changed the relationship between the data used to assign a benefit and the participation of people in the system. The response to the COVID-19 crisis was an experiment that involved using as much data as possible to find people who needed the subsidy but were not yet receiving other social programs. The program built a new Master Information Database, in which the National Development Office (NDO) “mixed” all kinds of administrative records, using data collected for diverse purposes and managed by private and public actors alike. These databases have quality levels, and the existence of some was even unknown to many Colombians. I argue that it is no longer a matter of finding vulnerable people in the areas affected by poverty but of taking advantage of the personal data that Colombian citizens provide in their interaction with different institutions.
The experiment ended up opening the “Pandora’s box” of the Colombian government information systems and showing its dependence on the private sector. Furthermore, the approach has appeared broken from the start: when the NDO published the list of beneficiaries, many citizens reported inclusion errors regarding non-existent and expired ID cards.
The unilateral decisions
The NDO’s response was to dismantle the database and deliver it to the National Civil Registry in charge of the national ID system for deduplication. This process resulted in nearly 17,000 records with inconsistencies, as reported on the media . After the incident, the NDO assured that the errors did not matter because the banks verify the identity of the recipient before making a transaction. Also, in the case of communities with no access to financial services, the public agency used databases of the prisons and the Forensic Medicine Institute to deduplicate IDs that were marked in those databases as deceased. This situation made clear that the state registries have serious quality problems and expose an approach to public policy that exploits databases indiscriminately.
In addition, these targeting practices imply a form of violence for individuals and families who are left out. We will never know how many people were unfairly excluded in the crosschecks with databases of uneven quality. However, we can analyze the narrative behind the Solidarity Income initiative. The bureaucracy is using these data-intensive solutions to avoid a political discussion that involves deciding who should be eligible for social redistribution in a time of crisis, what are the life consequences for the excluded, and what alternatives they might have. For example, the selection of beneficiaries in the South of the country, considering the high levels of poverty, unemployment, informality, and inequality, are the results of arbitrary data-based mechanisms. Why did the NDO draw a line between potential beneficiaries in a pandemic on 8.7 million families when there are 17 million at risk of falling into poverty? This question requires a political discussion that however is dependent on transparency and participation.
Silencing dissenting voices through data
The design of Solidarity Income makes it impossible for citizens to reclaim their rights. People will hardly be able to request that information be corrected, obtain information on decision procedures, and make a claim to challenge the results. What’s more, the system does not allow its potential beneficiaries to actively participate in the construction of the social policy that gives them agency in an emergency crisis. This is why I contend that with its recent initiatives the Colombian state is taking away people’s agency to demand their social rights and actively participate in the political discussion shaping them. Moreover, Solidarity Income is based on a wrong assumption: data does not faithfully correspond to the reality but is the representation of the politics of government and, most importantly, of the social inequalities that shape it. Communities in poverty could be easily invisibilized or misrepresented by that system.
Technocrats are hiding behind data and technological solutions to deny people the agency to participate in the state’s decisions, to claim injustice, and to claim the protection of their social rights. They reportedly dismiss citizens’ complaintsas “myths” or deny the agency of the citizens that denounce that they do not need subsidies because the databases do not lie. The official line has been in fact that “there are no mistakes”. In other words, Colombians are facing a government that unilaterally claims to know the people in need and denies their participation in the process. The government even points out how wrong the dissenting voices are: “they are being manipulated” or “they want to skip the line”. In short, it is about using technologies and data to avoid having political discussions.
In sum, Solidarity Income is an example of the gloomy future of social policy in which people have fewer mechanisms to reclaim their rights vis-a-vis the State. It is also evidence that the real beneficiaries will emerge from the data that Colombian citizens are inadvertently leaving and not as a result of an exercise in active citizenship. The Colombian government might be selling the program as an innovation, but it is nothing more than a large-scale experiment in rolling out a data-intensive social policy scheme that allows the state to “automatically” determine, through third-party data and in a non-transparent way, who deserves welfare support. Unfortunately, this is a policy designed to eliminate (so-called) inclusion errors, rather than for including citizens with agency. And this dark system will use as much data as possible to find the fewest possible beneficiaries.
About the author
Joan Lopez is a researcher in privacy and public policy at the Fundacion Karisma, a Colombian civil society organization that promotes human rights and social justice in digital environments. He is a historian and student of a master’s in sociology at Bielefeld University in Germany. Joan@karisma.org.co
To know more
Lopez, J. (2020). Experimentando con la pobreza: El Sisbén y los proyectos de analítica de datos. Bogotá: Fundación Karisma.