Editorial Cognitive AI Literacy for Future Media Professionals in Higher Education

Abstract

Artificial intelligence is transforming journalism, advertising, public relations, and strategic communication, creating a need to reconsider the competencies developed within higher media education. Although numerous AI literacy frameworks have been proposed, most conceptualise AI literacy as a set of general technological competencies and provide limited guidance for profession specific editorial practice. This study develops a conceptual framework that explains how AI literacy can be integrated into media education while preserving human responsibility for interpretation, ethical reasoning, and editorial decision making.

The study employs qualitative document analysis and conceptual synthesis of international AI policy documents, educational competency frameworks, and research in journalism, communication studies, cognitive psychology, and AI ethics. Based on this analysis, it proposes the Editorial Cognitive AI Literacy Model (ECAIL), which reconceptualises AI literacy as a recursive editorial cognitive process comprising six interrelated competency domains coordinated through Editorial Judgement. Editorial Judgement is introduced as the central cognitive mechanism integrating technological competence, critical evaluation, ethical reasoning, and professional responsibility throughout AI supported communication.

The proposed model extends AI literacy theory by offering a profession specific framework for higher media education and provides a theoretical foundation for curriculum design, competency development, and responsible human AI collaboration while reinforcing editorial autonomy and public trust.