The recent advancement of artificial intelligence must be understood as part of a broader transformation wherein digital infrastructures have moved from merely transmitting information to organizing meaning and adjudicating truth. In daily experience, search engines and social media once served as primary gateways to the world of information; now, large language models and generative systems have become interlocutors, interpreters, summarizers, and recommender, fundamentally reshaping the public sphere. For Iran, the stakes are high because the issue is not only what content AI produces but also which data it deems credible, which linguistic styles and historical narratives it reproduces, and which worldview it effectively imposes on users. Domestic policymaking in this domain often falls into a simplistic “opportunity/threat” binary or remains confined to general digital economy plans. Internationally, national strategies typically combine ethical principles, institutional flexibility, and a degree of functional ambiguity to balance innovation and regulatory intervention. For Iran, reliance on vague ethical declarations without enforceable mechanisms risks widening the gap between discourse and technical reality; conversely, rigid regulation without social participation, data infrastructure, and indigenous evaluation can stifle innovation and encourage circumvention. A framework that treats identity as a public policy issue and is technically and institutionally implementable is therefore an urgent necessity.

How can Iran, in the age of artificial intelligence, align technological development with the active preservation and creative renewal of its national identity (in its Iranian‑Islamic‑revolutionary configuration), without falling into cultural closure or harmful self-contained insularity?
This study advances a central policy proposition: by operationalizing a “cultural justice in AI” framework, supported by six interconnected policy pillars (spanning data sovereignty, indigenous evaluation benchmarks, participatory governance, and conditional international engagement) Iran can simultaneously foster responsible AI development and actively safeguard its national identity, thereby transforming potential algorithmic risks into opportunities for cultural resilience and creative renewal.
This study adopts an analytical and policy‑oriented methodology. It does not test a narrow empirical hypothesis but designs a decision‑ready framework suitable for translation into programs, standards, and institutional mechanisms within regulatory bodies. The analysis proceeds along three synergistic paths: a critical review of AI governance literature, with emphasis on the state’s dual role as facilitator of development and guarantor of risk mitigation; a focus on the specific characteristics of generative AI, which amplify risks such as hallucination, opacity, and unintended cultural homogenization; and the grounding of these discussions in Iran’s indigenous configuration of national identity, translating abstract governance concepts (data, benchmarks, auditing, accountability) into the language of identity‑laden domains (Persian language, historical memory, religious authority, revolutionary narrative, social cohesion).
The theoretical framework conceptualizes AI not as a neutral tool but as an “infrastructure of meaning” and a site of potential “data colonialism,” where cultural resources are extracted as raw material and returned as dominant stereotypes. Drawing on this critical lens, the study introduces the concept of “cultural justice in AI,” defined as the guarantee that Persian language, diverse dialects and expressive styles, and central narratives of history, religion, and revolution are not mere consumers of technological products but are actively present in the data layer, evaluation metrics, and decision‑making institutions. This perspective bridges infrastructure studies, critical data studies, and identity politics, emphasizing that cultural injustices often occur not in visible outputs but in the “invisibilities” of data collection, labeling, and weighting.
The analysis yields a multidimensional policy framework that moves beyond symbolic protection toward operational transparency and accountability. First, the study maps identity‑sensitive domains (such as religious authority and automated fatwa systems, Persian language and literature education, historical narrative generation, and content recommendation in mass media) and classifies them according to risk levels (very high, high, medium/low). This risk‑based approach guides the intensity of regulatory intervention: very high‑risk applications require licensing, mandatory human‑in‑the‑loop, pre‑ and post‑audit, and grievance mechanisms, while lower‑risk domains can operate under lighter, supervised self‑regulation.
Second, the article identifies three layers for translating the abstract notion of “identity risk” into actionable requirements: the data layer, where the creation and maintenance of high‑quality, diverse, and transparently documented Persian corpora are treated as public goods; the evaluation layer, where indigenous benchmarks are designed to assess not only technical fluency but also cultural‑identity dimensions such as distortion of religious concepts, ethnic stereotyping, and one‑sided historical narratives; and the institutional layer, where a participatory governance architecture is proposed. This includes a “Cultural Representation Council for AI,” a multi‑stakeholder body composed of linguists, historians, theologians, sociologists, and industry representatives, tasked with producing concrete audit protocols and data guidelines rather than general recommendations.
Third, six complementary policy pillars are detailed: (1) defining and institutionalizing sensitive identity domains and risk tiers; (2) building and reinforcing reliable Persian corpora and data assets as commons; (3) designing indigenous cultural‑identity evaluation benchmarks and regular auditing mechanisms; (4) embedding participatory governance and cultural representation within the regulatory structure; (5) enhancing interdisciplinary AI literacy across educational, media, and religious institutions; and (6) pursuing targeted, conditional international data diplomacy to influence global standards and avoid passive marginalization.
The discussion emphasizes that effective governance cannot rely solely on top‑down prohibition; it must be adaptive, learning‑oriented, and rooted in a political‑economic understanding of platform power. The framework advocates starting with policy pilots in selected domains, systematically gathering evidence, and iteratively revising rules, thereby maintaining innovation while ensuring accountability. It also warns that without deliberate investment in Persian data infrastructure and local evaluation tools, Iran risks becoming dependent on opaque foreign models that structurally embed alien cultural norms.
The intersection of artificial intelligence and national identity in Iran is a governance‑level challenge. As generative models become the primary mediators of meaning (affecting education, collective memory, religious practice, and entertainment) policy inaction effectively cedes authority to external standards and datasets. The study concludes that aligning AI development with the Iranian‑Islamic‑revolutionary identity requires simultaneous intervention in three layers: semantic infrastructure (data, models), assessment (evaluation, auditing), and institutions (participation, accountability). The proposed package (centered on cultural justice, data sovereignty, indigenous benchmarks, participatory governance, literacy, and data diplomacy) offers a path to transform AI from a threat of cultural homogenization into an instrument of dynamic identity preservation. Responsiveness, in the sense of clear data provenance, documented model assumptions, transparent evaluation procedures, and defined liability for high‑risk errors, serves as the unifying thread of this architecture. Ultimately, a learning‑based governance model that balances innovation with rigorous accountability can enable Iran to strengthen its digital sovereignty while actively and creatively renewing its national identity.