1. Introduction
The intensification of the use of digital technologies in recent decades has fostered profound transformations in the modes of producing, organizing, and circulating information, especially in the scientific field. In this context, artificial intelligence plays a central role by mediating informational processes, influencing not only access to knowledge, but also the criteria of visibility and relevance attributed to content in digital environments. Such dynamics are embedded within a network society in which informational flows are continuously reorganized by technological systems based on data, algorithms, and behavioral patterns, redefining the forms of interaction between individuals, institutions, and information (CASTELLS, 1999).
Information mediation, traditionally understood as a human and institutional process, has progressively come to be shared with automated systems capable of filtering, classifying, and recommending content on a large scale. This shift reconfigures the modes of accessing knowledge while introducing new layers of opacity into the decision-making processes that determine what becomes visible or invisible in the digital environment (SANTAELLA, 2013). In this scenario, digital culture is consolidated as a space of convergence among technologies, social practices, and symbolic dynamics, expanding the possibilities for the circulation of scientific knowledge, yet also exacerbating tensions surrounding informational inequality and the concentration of power in digital environments (LÉVY, 2010).
The growing reliance on algorithmic systems for the organization and distribution of scientific information raises relevant concerns in the field of digital rights, particularly regarding transparency and equity of access. Digital platforms and recommendation mechanisms, by operating on often opaque criteria, can reinforce informational asymmetries and restrict the plurality of perspectives, directly impacting the way knowledge is produced, disseminated, and socially appropriated. In this sense, algorithmic mediation is not merely a technical process, but rather a phenomenon intersected by power struggles and institutional interests.
Against this backdrop, the following research problem emerges: in what ways do artificial intelligence systems influence the mediation, visibility, and circulation of scientific information, and what are the impacts of these processes on digital rights? Understanding these dynamics is essential to critically analyzing the effects of digital technologies on the contemporary configuration of access to knowledge, as well as identifying the challenges posed to the democratization of information.
The relevance of this study is justified by the need to deepen the debate on the impacts of artificial intelligence on informational dynamics, particularly in a scenario where access to scientific information plays a pivotal role in social, educational, and technological development. By investigating the mechanisms that regulate the visibility and circulation of knowledge, this study seeks to contribute to the construction of a critical reflection on digital mediation processes and their implications for safeguarding rights within the contemporary informational environment.
This study aims to analyze the role of artificial intelligence in mediating scientific information, investigating its effects on visibility and power relations in the circulation of knowledge, as well as its implications for digital rights in the contemporary era.
2. Development
The analysis of the impacts of artificial intelligence on the circulation of scientific information requires the articulation of different theoretical fields, particularly those linked to Information Science, digital culture, and studies on mediation and power in technological environments. In this context, understanding contemporary informational processes demands the recognition that information does not circulate neutrally, but is conditioned by technical and social structures that organize, filter, and hierarchize informational flows (CASTELLS, 1999). Thus, information mediation comes to be understood as a complex process permeated by technological apparatuses that redefine the relationships among subjects, knowledge, and society.
Artificial intelligence, by acting as a mediator of these processes, introduces new dynamics of organizing and accessing information, based on algorithmic systems capable of operating at scale. These systems not only expand the capacity to process and disseminate knowledge, but also establish visibility criteria that directly influence what becomes accessible in digital environments (SANTAELLA, 2013). In this sense, informational mediation ceases to be exclusively human and comes to incorporate automated logics that, while efficient, may reinforce patterns of informational selection and exclusion.
The centrality of algorithms in defining informational flows highlights the emergence of visibility regimes that operate according to often opaque criteria, driven by data, institutional interests, and user behavioral patterns. These regimes directly impact the circulation of scientific information, potentially expanding its reach while simultaneously restricting its diversity by privileging certain content over others (LÉVY, 2010). In this way, the visibility of information becomes the outcome of mediating processes involving symbolic struggles and power relations, shaping a scenario in which access to knowledge is conditioned by technological and economic infrastructures (MANOVICH, 2001).
In this context, the discussion of digital rights becomes central, since algorithmic mediation directly interferes with principles such as transparency, equity, and access to information. The growing dependence on digital platforms for circulating scientific knowledge underscores the need to critically analyze the mechanisms that regulate these processes, taking into account their social and political implications. Technological mediation, therefore, cannot be understood merely as a technical phenomenon, but as a structuring dimension of contemporary power relations and knowledge production (CASTELLS, 1999).
Given this scenario, the development of this study is organized into four main axes: first, it discusses the relationship between artificial intelligence and the mediation of scientific information, based on contributions from Information Science and digital culture; second, it analyzes the notion of digital rights and algorithmically mediated regimes of visibility; third, it presents the methodological procedures adopted; and finally, it conducts a critical analysis of algorithmic power and its effects on the circulation of scientific information.
2.1 Artificial intelligence and the mediation of scientific information
Understanding artificial intelligence as a structuring element in the mediation of scientific information requires its positioning within the theoretical field of Information Science, particularly regarding the processes of organizing, circulating, and appropriating knowledge. Traditionally, information mediation has been understood as an activity performed by subjects and institutions responsible for facilitating access to knowledge, involving practices of selecting, interpreting, and disseminating informational content (ALMEIDA JÚNIOR, 2009). However, with the advancement of digital technologies, these processes have progressively come to be shared with automated systems capable of operating on an expanded scale and driven by algorithmic logics.
In this context, artificial intelligence emerges as a contemporary form of informational mediation, operating through mechanisms of collecting, processing, and analyzing large volumes of data. These systems not only organize scientific information, but also influence its circulation by defining criteria for relevance, recommendation, and visibility. Such dynamics significantly alter the modes of interaction between individuals and knowledge, given that access to information becomes mediated by technological structures that often operate opaquely (SANTAELLA, 2013).
The insertion of artificial intelligence into informational processes is directly related to the transformations of digital culture, characterized by media convergence, the intensification of communicational flows, and the expansion of possibilities for producing and sharing content (LÉVY, 2010). In this environment, scientific information ceases to circulate exclusively in traditional institutional spaces, such as journals and libraries, and becomes part of broader digital ecosystems, in which platforms, networks, and automated systems play a central role in its dissemination. This reconfiguration broadens the reach of knowledge, but it also introduces new forms of informational control and filtering.
Furthermore, algorithmic mediation contributes to the constitution of new regimes of information organization, based on dynamic, data-driven structures. The logic of digital systems, marked by modularity, automation, and variability, redefines the modes of production and circulation of scientific knowledge, rendering them more fluid and interconnected (MANOVICH, 2001). In this sense, artificial intelligence not only optimizes informational processes, but also transforms the very nature of mediation, shifting it from a model centered on human intervention to a hybrid system in which humans and machines act in an integrated manner.
Finally, it is important to emphasize that this new configuration of information mediation is not limited to technical aspects, but involves social, cultural, and political implications. By influencing what is accessed, made visible, and shared, artificial intelligence actively participates in the construction of knowledge and the definition of informational agendas. Thus, understanding its role in the mediation of scientific information is essential for critically analyzing contemporary processes of knowledge circulation and their implications for the democratization of access to knowledge.
2.2 Digital rights and regimes of visibility
The emergence of digital rights in the contemporary context is directly associated with the growing centrality of digital technologies in organizing social, economic, and informational life. In this scenario, access to information, privacy, transparency, and freedom of expression come under strain from technological infrastructures that operate on the basis of data and algorithms. Such transformations demand the expansion of the human rights debate to the digital environment, acknowledging that informational dynamics mediated by automated systems directly impact the guarantee and enforcement of these rights (CASTELLS, 1999).
Algorithms, in this context, assume a central role in shaping so-called regimes of visibility, as they are responsible for determining which content will be prioritized, recommended, or hidden in digital environments. These systems operate on criteria that, although based on data and behavioral patterns, remain largely opaque to users. Such opacity compromises the transparency of informational processes and hinders the understanding of how dynamics of access to and circulation of knowledge are structured (PASQUALE, 2015).
The notion of a regime of visibility enables the understanding that information visibility is not a neutral attribute, but the outcome of mediating processes involving symbolic struggles, institutional interests, and power relations. In this sense, scientific information, when circulating in digital environments, is subject to selection and hierarchization mechanisms that may favor certain content to the detriment of others, impacting the plurality and diversity of available knowledge (SANTAELLA, 2013). Visibility thus becomes a strategic resource, associated with the capacity to influence perceptions, agendas, and decision-making processes.
Informational power, in turn, manifests in the ability to control information flows, define relevance criteria, and structure modes of access to knowledge. In digital environments, this power is frequently concentrated in major technology platforms, which operate as intermediaries between producers and consumers of information. By using algorithms to organize content, these platforms play an active role in informational mediation, influencing not only what is seen, but also what remains invisible (MANOVICH, 2001).
Informational invisibility, therefore, should not be understood as an absence of content, but as the result of exclusion and filtering processes that limit access to certain information. This phenomenon is particularly relevant in the scientific field, where the unequal circulation of knowledge can reinforce asymmetries among institutions, countries, and social groups. In this way, analyzing regimes of visibility mediated by algorithms proves fundamental to understanding the challenges posed to the democratization of information and the safeguarding of digital rights.
In light of this, it becomes evident that the relationship among algorithms, informational power, and visibility constitutes one of the main axes of tension in the contemporary digital environment. A critical understanding of these processes is essential for developing strategies that promote greater transparency, equity, and diversity in the circulation of information, contributing to the realization of digital rights in an increasingly technology-mediated society.
This study adopts an exploratory, qualitative approach guided by the critical analysis of algorithmic mediation processes in the circulation of scientific information within digital environments. The choice of this approach stems from the complexity of the investigated object, which encompasses not only technical dimensions, but also symbolic, social, and political aspects related to informational visibility and the safeguarding of rights in the context of digital culture (GIL, 2008).
From a methodological standpoint, the research is structured around a selective literature review guided by analytical axes, focusing on three main axes: (i) information mediation in Information Science; (ii) digital culture and the circulation of knowledge; and (iii) regimes of visibility and algorithmic power. To this end, theoretical contributions addressing the network society, cyberculture, informational mediation, and the dynamics of information organization in digital environments were mobilized, enabling the construction of a conceptual framework capable of sustaining the proposed analysis (CASTELLS, 1999; LÉVY, 2010; SANTAELLA, 2013; MANOVICH, 2001).
Unlike descriptive approaches, this study adopts critical theoretical analysis as its central strategy, understood as an interpretative process that seeks to identify structural relationships between technology, information, and power. In this sense, the analysis focuses on how artificial intelligence systems, acting as mediation devices, influence the visibility of scientific information through mechanisms of filtering, recommendation, and content hierarchization. Such a perspective makes it evident that the circulation of knowledge is not merely the result of its production, but also of the technical and institutional conditions that govern its exposure in digital environments.
As an analytical focus, the study considers the role of digital platforms and algorithmic systems as informational mediation infrastructures responsible for organizing scientific information flows on a large scale. Based on this focus, it seeks to understand how these systems produce effects of visibility and invisibility, impacting access to knowledge and shaping dynamics of informational power. This methodological choice allows the theoretical debate to be brought closer to the concrete practices of information circulation in the contemporary digital environment.
Finally, the integration of a targeted literature review and critical analysis enables the construction of a consistent interpretation regarding the effects of artificial intelligence on the mediation of scientific information, highlighting its implications for digital rights. By favoring this approach, the study contributes to an in-depth reading of contemporary informational transformations, underscoring both their potentialities and their limits concerning the democratization of access to knowledge.
The analysis of algorithmic power in the circulation of scientific information reveals that contemporary informational processes are profoundly conditioned by artificial intelligence systems that operate as agencies of mediation, selection, and hierarchization of knowledge. In this context, the circulation of information ceases to depend exclusively on traditional scientific or institutional criteria and comes to be influenced by algorithmic logics driven by data, engagement, and user behavior patterns (MANOVICH, 2001). This transformation entails a significant reconfiguration of the dynamics of visibility, insofar as access to scientific knowledge becomes mediated by technological infrastructures that define what is prioritized or marginalized in digital environments.
The centrality of algorithms in this process highlights the constitution of an informational power manifested in the capacity to organize knowledge flows on a large scale. This power is not limited to the technical dimension, but involves implicit decisions regarding the relevance, authority, and legitimacy of information, directly influencing how scientific knowledge is produced, disseminated, and socially appropriated (CASTELLS, 1999). Thus, algorithmic mediation acts as a structuring filter, capable of amplifying certain contents while silencing others, shaping regimes of visibility that impact informational plurality and diversity.
From the perspective of digital rights, this dynamic presents significant implications. The opacity of algorithmic systems compromises the transparency of mediation processes, hindering an understanding of the criteria that guide the circulation of information. Furthermore, the prioritization of content based on performance metrics, such as clicks and interactions, can foster the superficialization of knowledge and restrict access to less visible, yet equally relevant, scientific production (PASQUALE, 2015). In this sense, the circulation of scientific information becomes permeated by logics that are not always aligned with the principles of equity and the democratization of access to knowledge.
Another relevant aspect pertains to the concentration of power within digital platforms, which act as central intermediaries in the organization of information. By controlling recommendation and indexing mechanisms, these platforms play a decisive role in defining informational flows, influencing scientific agendas and visibility patterns. Such concentration reinforces existing asymmetries in the scientific field, especially across different regions, institutions, and research groups, widening inequalities in access to and the circulation of knowledge (SANTAELLA, 2013).
The nexus between artificial intelligence, informational mediation, and algorithmic power demonstrates that the circulation of scientific information cannot be understood merely as a technical process, but as a social and political phenomenon marked by disputes over visibility and control. In this scenario, it is essential to develop a critical perspective that considers both the potential and the limits of these systems, recognizing that, while they expand the reach of knowledge, they also introduce mechanisms of exclusion and hierarchization that directly impact digital rights.
In light of this, the analysis of algorithmic power allows us to understand that democratizing access to scientific information depends not only on expanding digital technologies, but on constructing mediation models that are more transparent, equitable, and oriented toward the public interest. Such a perspective reinforces the need to advance the debate on the regulation, ethics, and governance of digital technologies, so as to ensure that the circulation of knowledge takes place in a fairer and more inclusive manner in contemporary society.
In this sense, algorithmic power can be understood as a new form of structural mediation of information, in which visibility and invisibility cease to be side effects and become central elements in the organization of knowledge in digital society.
3. Final considerations
This study aimed to analyze the role of artificial intelligence in the mediation of scientific information, with an emphasis on its effects on visibility and power relations in the circulation of knowledge, as well as its implications for digital rights. Drawing on the frameworks of Information Science and digital culture, it was possible to understand that algorithmic systems act not merely as technical tools, but as structuring agents of contemporary informational flows.
The results show that algorithmic mediation redefines the criteria for access, selection, and hierarchization of scientific information, directly influencing what becomes visible or invisible in digital environments. In this process, the circulation of knowledge becomes conditioned by data-driven logics and performance metrics, which may favor certain contents over others. This dynamic contributes to the emergence of informational asymmetries, impacting the diversity and plurality of available knowledge.
Furthermore, it was observed that the opacity of artificial intelligence systems and the concentration of power in digital platforms pose significant challenges to the guarantee of digital rights. The difficulty of understanding the criteria that guide the visibility of information compromises principles such as transparency, equity, and democratic access to knowledge. In this sense, technological mediation, while expanding the possibilities for the circulation of scientific information, also imposes substantial limits on its democratization.
The implications of this scenario are significant for contemporary society, especially regarding the need to develop strategies that foster greater transparency in algorithmic systems and broaden equitable access to scientific knowledge. It is essential to advance the debate on the regulation, ethics, and governance of digital technologies, ensuring that the circulation of information takes place in a fairer, more inclusive manner aligned with the principles of digital rights.
Finally, it is worth emphasizing that a critical understanding of algorithmic mediation processes represents an essential step toward strengthening a more democratic informational culture, in which access to scientific knowledge is not constrained by invisible barriers, but guided by the public interest and the promotion of rights in the digital age.