User:Alinapuri/Data Justice

Data Justice
The concept of ‘data justice’ aims to advance a research agenda that investigates the various connections between datafication and social justice and places an emphasis on the politics and effects of big data and data-driven processes which study the complex link between datafication and social justice. As Lina states, “Justice as a value is conditional on a range of principles that go beyond bias and that cannot be limited to technical components of a system” (Dencik, 2022).

Defining Data Justice
Data justice is closely aligned with the kinds of concerns that underpin critical data studies and related fields, because it seeks to examine data issues in the context of existing power dynamics, ideology, and social practices rather than as technical developments in the interactions between information systems and users (Van Dijck, 2014). According to Dencik, Hintz, & Cable (2016), the premise is that data developments must be integrated with social justice concerns and agendas rather than considered separately. Because of this, it is crucial to note that the connection between data and justice extends beyond technological issues. Data justice has mostly emerged in the dual context of the perceived limitations in how these developments have been framed and approached as well as the growing emphasis on the so-called big data and more recent versions of machine learning and artificial intelligence. A number of long-standing traditions are the foundation of data justice. These traditions are concerned with the social justice implications of the nature of information and communication systems .These traditions include discussions of ethics and human rights, activism, and a focus on social movements. Moreover, Densick further explains how because of the translation of social justice and fairness as defined in computational terms, other guiding principles may now be employed to lead the creation of data-driven technology.

Theoretical frameworks
People using digital tools and services have caused a change in how policies are established across the world, moving from being informed by data to being led by data (Kitchin, 2016). Researchers may deduce the movement, activities, and behavior of individuals using these fine-grained data sources, which has ramifications for how individuals are seen and dealt with by the government and the business sector on an ethical, political, and practical level. This increased exposure has profound social and political ramifications, especially in low-income areas where it has historically been difficult for the government to collect reliable information.The data revolution has so far been mainly technological since the capacity of data to sort, categorize, and intervene has not yet been properly tied to a social justice purpose. A notion of data justice is required to construct ethical pathways in a data-fying society, just as an idea of justice is required to establish the rule of law. Data justice is being framed in a variety of ways that might complement one another in many domains. By identifying shared values, we may unite them into a unified framework for more study and discussion.Most current frameworks for controlling data are challenged by how data justice is conceptualized. It does so because it starts from the premise that no framing can succeed in the field of public thinking if it excludes both the positive and bad features of data technology. The frameworks we now employ either place a strong emphasis on risk and damage or make the case for ensuring that data and the ability to evaluate them are as widely available as feasible. The political and theoretical challenge of bringing different ideas into harmony is enormous. The different ways that data justice has been framed since the development of big data suggest that academics and decision-makers are working to bridge the gap between the ideals of social justice and the realities of datafication.