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The ethic of education is a set of professional rules and regulations agreed upon by the scientific community that obliges actors to comply with codes of conduct in the science education process. This article is asking about levels and types of academic dishonesty and recognizing factors affecting it in Iran’s social sciences education. The data were collected using semi-structured interviews with Ph.D. students of public Universities in Tehran were analyzed with qualitative content analysis. Research findings show that academic dishonesty and factors affecting it are evident in the education of social science at two levels of micro and macro. At the micro or actor’s level, individual characteristics and personality traits of students and professors impact on the occurrence of academic dishonesty. Moreover, at the macro or structural level, the way of distribution of resources and rules in the education paves the way for and facilitates the occurrence of academic dishonesty. Consequently, dishonesty in the education of Iran’s social sciences and factors affecting it can be explained in the light of a structuration approach.

This study seeks to explore the implications of Bruno Latour’s Actor-Network Theory (ANT) regarding the integration of artificial intelligence into educational processes. The research employs a qualitative “theoretical essay” methodology, utilizing “document analysis” as the primary tool for data collection. the research data were mainly gathered through primary texts of Actor–Network Theory and secondary texts. Theoretical foundations and relevant literature on Actor-Network Theory were analyzed through a reflective and interpretive approach from an ANT perspective. Findings reveal that agency is no longer exclusive to humans but is distributed across unstable, multi-centered networks; meaning is not transmitted by teachers but is continuously co-constructed through interactions among human and non-human actors; and ethical responsibility no longer rests on any single individual, but is embedded within and interrogated by the opaque structures of algorithmic black boxes. In this context, humanity in education can no longer be defined in opposition to machines, but rather emerges through capacities of negotiation, interpretation, and regulation within technologically mediated networks. In conclusion, this article argues that the future of education lies not in resisting technology, but in consciously redefining the human role not as the sole possessor of agency, but as the network’s regulator, interpreter of meaning, and architect of humanistic values amidst interactions with non-human elements. This perspective necessitates the design of interpretable AI systems, the cultivation of critical algorithmic literacy, and the establishment of multi-stakeholder ethical oversight mechanisms.