مخاطب و الگوریتم: تحلیل لایه ای علی از آینده‌ی «خودمختاری»

This study examines the future of the concept of autonomy in audience–algorithm interaction; a relationship that has become one of the most important social and cultural challenges in the digital age. Its main question is: how can algorithmic logic and digital governance structures lead to the weakening or strengthening of users’ autonomy? The study was conducted with a critical futures studies approach and using the Causal Layered Analysis (CLA) framework. Data were collected through a systematic review of scholarly sources from 2015 to 2025. Searches were conducted in Scopus, Google Scholar, as well as Noormags and Magiran. A total of 942 records were identified, and after removing duplicates and screening, 86 sources were included in the final analysis. The review stages were documented according to the PRISMA guidelines, and the data were categorized using thematic coding across the four CLA layers (litany, systemic causes, worldview, and myth/metaphor). The results showed that the erosion of autonomy is the product of the interaction among economic forces (surveillance capitalism), technical designs (personalization, prediction-centrism), cultural paradigms (dataism, technocentrism), and social myths (the omniscient algorithm). Accordingly, and by identifying two driving forces—optimization and control, and agency and self-determination—four scenarios were drawn: continuation of algorithmic domination, resistance and critical awareness, coexistence and strengthened autonomy, and the passive and diminished audience. The future of autonomy is not a technological destiny but a socio-political project whose realization depends on data-driven policymaking, value-sensitive design, and the promotion of algorithmic literacy.
Extended Abstract:
Introduction
The rapid expansion of algorithmic systems across digital platforms has fundamentally reconfigured the architecture of everyday life. From content recommendation and automated moderation to predictive analytics in finance, employment, and governance, algorithmic infrastructures increasingly mediate how individuals access information and make decisions. While these systems enhance convenience and reduce cognitive load, they simultaneously influence users’ perceptual horizons, behavioral patterns, and decision-making processes.
Autonomy, traditionally defined in philosophical discourse as self-governance grounded in rational choice, faces new challenges in algorithmically structured environments. Classical Kantian autonomy emphasizes individual rational agency; however, contemporary critiques have shifted toward relational autonomy, recognizing that agency is socially and technologically embedded. In digital contexts, autonomy must therefore be understood as emerging within dynamic interactions among users, platform architectures, economic incentives, and regulatory regimes.
Algorithmic governance introduces new infrastructures of power. Decision-making processes become automated, opaque, and data-driven, producing asymmetries between platform operators and users. Practices such as hyper-personalization, predictive modeling, and behavioral targeting blur the line between assistance and manipulation. Phenomena such as filter bubbles and echo chambers restrict exposure to diverse perspectives, thereby constraining cognitive autonomy. Meanwhile, surveillance-based business models transform users into data resources, embedding autonomy within market-driven optimization logics.
Despite growing scholarship on digital governance and artificial intelligence, conceptual fragmentation persists. Many studies focus either on technical risks, legal regulation, or cultural critique, without integrating these layers into a coherent analytical framework. This study addresses that gap by employing Causal Layered Analysis to examine autonomy across four interconnected dimensions: surface manifestations (litany), structural causes, dominant worldviews, and deep cultural myths. By doing so, it reframes autonomy as a multi-layered, contested construct situated within broader socio-technical transformations.
Methodology
This research adopts a qualitative, critical future methodology grounded in Causal Layered Analysis (CLA). A systematic literature review was conducted to construct the empirical foundation for analysis. Academic databases including Scopus and Google Scholar, as well as Persian databases (Magiran and Noormags), were searched for publications between 2015 and 2025.Search strings combined key terms such as “algorithmic governance,” “autonomy,” “agency,” “causal layered analysis,” “digital sovereignty,” and related Persian equivalents. The initial search identified 942 records. After removing duplicates (reducing the corpus to 765 documents), title and abstract screening yielded 212 relevant sources. Full-text assessment based on inclusion criteria (peer-reviewed status, methodological clarity, and substantive relevance) resulted in a final dataset of 86 scholarly works. The review process followed PRISMA documentation standards. A thematic coding process was applied. Forty-eight detailed categories, thirteen intermediate themes, and four overarching themes were identified and mapped onto the four CLA layers:
Litany: observable symptoms such as filter bubbles, privacy erosion, misinformation, and perceived loss of control.
Systemic causes: economic structures (surveillance capitalism), design logics (infinite scroll, behavioral nudges), regulatory gaps, and centralized platform power
Worldviews: dataism, technological solutionism, neoliberal individualism, and efficiency-driven rationality
Myths/metaphors: the algorithm as neutral oracle, the inevitability of technological progress, and the user as product
This layered mapping enabled the identification of deeper drivers shaping autonomy outcomes and informed scenario construction
Results and Discussion
The findings demonstrate that autonomy erosion operates simultaneously across experiential, structural, ideological, and symbolic dimensions. At the surface level, users encounter constrained informational diversity, opaque decision-making processes, and subtle behavioral steering. At the systemic level, surveillance-based economic models and predictive design architectures prioritize optimization over self-determination. Dominant worldviews normalize technological inevitability and position efficiency as a superior value, marginalizing critical reflection. At the mythic level, cultural narratives portray algorithms as objective, omniscient, and superior to human judgment. Two fundamental driving forces emerged from cross-layer synthesis: 1. Optimization and Control: rooted in predictive analytics, behavioral data extraction, and efficiency maximization, and 2. Agency and Self-Determination: expressed through algorithmic literacy, regulatory interventions, civic activism, and value-sensitive design. The interaction between these forces generates four plausible futures:
Algorithmic Dominance: control logics prevail; autonomy becomes largely symbolic.
Critical Resistance: users and civil society challenge opacity and demand accountability.
Augmented Coexistence: balanced integration where algorithms function as supportive collaborators under transparent governance.
Diminished Agency: widespread passivity and intensified behavioral extraction reduce users to data subjects.
These scenarios do not represent predictions but structured possibilities that clarify the stakes of present choices. The study underscores that autonomy is neither fully eroded nor automatically preserved; it is shaped by regulatory frameworks, platform governance, and collective agency.
Conclusion
This study has demonstrated that audience autonomy in algorithmically mediated environments cannot be reduced to a question of individual choice or technological design alone. Through the integration of Causal Layered Analysis, relational autonomy theory, and the concept of algorithmic governance, the research reveals that autonomy is structured across multiple, interdependent layers: everyday user experience, economic and institutional arrangements, legitimizing worldviews, and deep cultural narratives.
The erosion of autonomy is not simply the byproduct of technical inefficiencies or isolated platform practices; rather, it is embedded within surveillance-based business models, optimization-driven design architectures, and dominant ideologies that frame technological systems as neutral, inevitable, and inherently beneficial. At the same time, the findings indicate that autonomy remains a contested and dynamic capacity. Its trajectory depends on how societies negotiate the tension between control-oriented optimization and agency-centered self-determination.
The four scenarios developed in this study highlight that the future of autonomy is not technologically predetermined. Instead, it is shaped by collective decisions in policy-making, institutional design, and civic engagement. Strengthening autonomy requires multi-level interventions: transparent and accountable algorithmic governance frameworks; data sovereignty mechanisms that restore meaningful user control; value-sensitive design principles embedded in platform architecture; and the institutionalization of algorithmic literacy as a public good.
Ultimately, autonomy in the digital age should be reconceptualized as relational and ecological; emerging from the interaction among users, organizations, and socio-political contexts. The preservation and enhancement of autonomy therefore constitute a socio-political project rather than a technical adjustment. Whether algorithmic systems become infrastructures of subtle domination or instruments of human augmentation depends on how power, knowledge, and design are redistributed in the evolving digital ecosystem.