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Blog By María Beatriz Jiménez
On Wednesday, November 24, 2021, the Digital Welfare State and Human Rights Project hosted the ninth episode in the Transformer States conversation series on Digital Government and Human Rights, in an event entitled: “Chosen by a secret algorithm: A closer look at Colombia’s Pandemic Payments.” Christiaan van Veen and Victoria Adelmant had a conversation with Joan López, Researcher at the Global Data Justice Initiative and at Colombian NGO Fundación Karisma about Colombia’s pandemic payments and its reliance on data-driven technologies and prediction. This blog highlights some core issues related to taking a top-down, data-driven approach to social protection.
The System of Possible Beneficiaries of Social Programs (SISBEN in Spanish) was created to assist in the targeting of social programs in Colombia. This system classifies the Colombian population along a spectrum of vulnerability through the collection of information about households, including health data, family composition, access to social programs, financial information, and earnings. This data is collected through nationwide interviews conducted by experts. Beneficiaries are then rated on a scale of 1 to 100, with 0 as the least prosperous and 100 as the most prosperous, through a simple algorithm. SISBEN therefore aims to identify and rank “the poorest of the poor.” This centralized classification system is used by 19 different social programs to determine eligibility: each social program chooses its own cut-off score between 1 and 100 as a threshold for eligibility.
But in 2016, the National Development Office – the Colombian entity in charge of SISBEN – changed the calculation used to determine the profile of the poorest. It introduced a new and secret algorithm which would create a profile based on predicted income generation capacity. Experts collecting data for SISBEN through interviews had previously looked at the realities of people’s conditions: if a person had access to basic services such as water, sanitation, education, health and/or employment, the person was not deemed poor. But the new system sought instead to create detailed profiles about what a person could earn, rather than what a person has. This approach sought, through modelling, to predict households’ situation, rather than to document beneficiaries’ realities.
During the pandemic, the government launched a new system of payments called the Ingreso Solidario (meaning “solidarity income”). This system would provide monthly payments to people who were not covered by any other existing social program that relied on SISBEN; the ultimate goal of Ingreso Solidario was to send money to 2.9 million people who needed assistance due to the crisis caused by COVID-19. The Ingreso Solidario was, in some ways, very effective. People did not have to apply for this program: if they were selected as eligible, they would automatically receive a payment. Many people received the money immediately into their bank accounts, and payments were made very rapidly, within just a few weeks. Moreover, the Ingreso Solidario was an unconditional transfer and did not condition the receipt of the money to the fulfilment of certain requirements.
But the Ingreso Solidario was based on a new approach to social policy, driven by technology and data sharing. The Government entered agreements with private companies, including Experian and Transunion, to access their databases. Agreements were also made between different government agencies and departments. Through data-sharing arrangements across 34 public and private databases, the government cross checked the information provided in the interviews with information in dozens of databases to find inconsistencies and exclude anyone deemed not to require social assistance. In relying on cross-checking databases to “find” people who are in need, this approach depends heavily on enormous data collection, and it increases government’s reliance on the private sector.
This new approach to social policy, as implemented through the Ingreso Solidario, has fundamental implications. First, this system is difficult to challenge. The algorithm used to profile vulnerability, to predict income generating capacity, and to assign a score to people living in poverty, is confidential. The Government consistently argued that disclosing information about the algorithm would lead to macroeconomic crisis because if people knew how the system worked, they would try to cheat the system. Additionally, SISBEN has been normalized. Though there are many other ways that eligibility for social programs could be assessed, the public accepts it as natural and inevitable that the government has taken this arbitrary approach reliant on numerical scoring and predictions. Due to this normalization, combined with the lack of transparency, this new approach to determining eligibility for social programs has therefore not been contested.
Second, in adopting an approach which relies on cross-checking and analyzing data, the Ingreso Solidario is designed to avoid any contestation in the design and implementation of the algorithm. This is a thoroughly technocratic endeavor. The idea is to use databases and avoid going to, and working with, the communities. The government was, in Joan’s words, “trying to control everything from a distance” to “avoid having political discussions about who should be eligible.” There were no discussions and negotiations between the citizens and the Government to jointly address the challenges of using this technology to target poor people. Decisions about who the extra 2.9 million beneficiaries should be were taken unilaterally from above. As Joan argued, this was intentional: “The mindset of avoiding political discussion is clearly part of the idea of Ingreso Solidario.”
Third, because people were unaware that they were going to receive money, those who received a payment felt like they had won the lottery. Thus, as Joan argued, people saw this money not “as an entitlement, but just as a gift that this person was lucky to get.” This therefore represents a shift away from a conception of assistance as something we are entitled to by right. But in re-centering the notion of rights, we are reminded of the importance of taking human rights seriously when analyzing and redesigning these kinds of systems. Joan noted that we need to move away from an approach of deciding what poverty is from above, and instead move towards working with communities. We must use fundamental rights as guidance in designing a system that will provide support to those in poverty in an open, transparent, and participatory manner which does not seek to bypass political discussion.
María Beatriz Jiménez is an LLM student at NYU Law whose research focuses on digital rights. She previously worked for the Colombian government in the Ministry of Information and Communication Technologies and the Ministry of Trade.
Watch the event recording below:
Read the transcription here.
0:00 – Introduction
4:45 – Could you give us a bit of background about the historical context to this system of payments? What do you perceive to be the main policy priorities and driving forces surrounding social assistance programs in Colombia? And what systems were already in place before the Ingreso Solidario pandemic payments were introduced?
10:25 – What kind of information are experts looking for in their interviews for SISBEN?
12:20 – In what ways might the Ingreso Solidario represent a promising development in social policy? From a human rights perspective in particular, how might we praise the ways technologies and big data were used within this specific scheme?
15:10 – What technology-driven changes had already taken place before the pandemic hit, which facilitated the speed at which these payments were delivered? In what ways was Ingreso Solidario building upon earlier programs?
20:25 – The newer approach to SISBEN represented a shift, but does this not also represent a continuation of previous policy approaches? Would you say that this is mainly about getting more efficient at targeting, so that this is not so much a policy shift but rather a continuation by different means?
24:00 – What are the implications of shifting from an approach which focuses on expert surveys to ascertain realities, to an approach which focuses more on what could have been, or what could be the case in the future?
27:00 – If this is about taking a top-down approach which moves away from contestation, do you think this is intentional? Or do you think that this was just a happy side effect?
28:50 – The speed at which this has been implemented may not just be a function of the technological affordances of these systems, but also of politics, where the pandemic presented wider political opportunities?
30:40 – What kinds of methods did you adopt when you were researching the Ingreso Solidario, and what kinds of challenges did you face in doing this work?
36:00 – Did the Ingreso Solidario system work on its own terms, did it achieve its aims? What were the impacts of this program?
40:45 – This system led to arbitrary situations, in which recipients felt like they had won the lottery or received a gift because they were lucky to get a payment, rather than feeling entitled to basic social protection from the state. What does this shift from a notion of entitlement and rights to a more seemingly luck-based system mean, and why is that significant? What is the role of rights here?
46:25 – Audience Q&A
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