We live in an age in which data and information are a constant presence in our lives. Corporations have historically extracted information from data to make operational and commercial decisions, such as getting to know customers and understanding their interests and needs so as to anticipate their behavior and influence their purchasing decisions. This is now common practice.
As computing power has increased and algorithms have developed, these strategies have become increasingly complex. They allow data to be used in increasingly automated, efficient, customized ways to enable organizations, states, and individuals to make decisions at different levels and on different scales. In other words, it is becoming increasingly clear that having access to data and being able to derive information from it is a source of power.
At Fundar, we are convinced that data and information also have an essential part to play in improving people’s lives, provided that the information itself and the way it is processed are used to design, implement, manage, evaluate, and improve public policies; the data used is reliable; and that these processes bring about the intended impacts and therefore benefit citizens. Producing quality data, viewing it as an asset, and using it correctly to obtain information are fundamental steps toward sustainable development, including in Argentina. In other words, in the age of artificial intelligence and data, information is more than just an asset that can be leveraged by corporations: it needs to become part of the population’s heritage.
To achieve this goal, data and algorithms need to be made widely available. The first step toward this is recognizing the existence and value of the data sets that are held by various organizations. A key aspect of this process is managing these sets with a technical, pluralistic, reflective vision to guarantee their quality, make them more user-friendly, and facilitate exchange. There is also a need to encourage stakeholders in the different stages of the data life cycle to get involved and build partnerships.
This implies a major cultural shift in the way in which decisions are made and policies are analyzed. In particular, studies based on data that is generated specifically for public policy purposes need to be complemented by studies using data generated for other purposes, which therefore has broader coverage of the population. In other words, it is a matter of moving from a purely qualitative view of policy design to a mixed view that also involves quantitative analysis.
It is important to note that the use of data and algorithms for development implies adopting an ethical, human rights perspective, as the use of these impacts the lives of citizens and increasingly challenges respect for rights such as privacy and data protection. We need to call current laws, regulations, and standards into question and reflect upon their implications.
Incorporating data- and algorithm-based management, decision-making, and policy design processes is a complex challenge in Argentina. The complexity of the situation owes largely to the quality and availability of data. In some cases, the data is not stored, is insufficient, or is not shared. In others, it is generated as part of administrative processes that pay little attention to how it will then be used, which affects its quality and usability. There are also risks associated with how this data is used, which can lead to biased decisions due to the misinterpretation of results, the use of incorrect data or algorithms, and a lack of awareness of the limits, possibilities, and potential benefits of these tools, which means that they end up not being used for decision making. Identifying use cases and their potential impacts is a first step toward overcoming these difficulties.
Carrying out more studies that use data will help us act appropriately in contexts in which artificial intelligence may be implemented, as will determining the scope and limitations of these studies, their value, and how they might affect rights. This entails more than just incorporating technology or making mere methodological changes: implementing decision-making based on data and analytical algorithms implies a profound cultural paradigm shift, building on the premise that using information appropriately can save lives, as became evident during the COVID-19 pandemic.