Edu GPT: A prelude to its responsible embrace in higher education

The domains of artificial intelligence (AI) and the field of education have an extending history of complementary advances and a co-evolutionary trajectory. Following this trajectory, the contemporaneity of the cited co-evolution has been tracked down in the most recent introduction of Edu GPT for campuses. In this commentary, we offer some procedural considerations and sort out some prerequisites that would serve as the prelude to Edu GPT’s embrace in higher education. As opposed to the wholesale adoption of this updated GPT in higher education, we advocate for a glocalized approach that relies on epistemic guidance to make historically informed decisions about welcoming or rejecting this GPT tool. The potentially catastrophic effects of blindly embracing of Edu GPT can be avoided by pragmatized alternative mechanisms for balanced and responsible uses of the tool. Besides, contextual diversities have to be especially considered while the approach further calls for a structural episodic implementation stages: (a) design, (b) development, (c) adoption, (d) monitoring, and (e) normalization. We further characterize the adoption method by criticality and decolonization as a reaction to Edu GPT’s western-data-centric epistemic colonization. Furthermore, before implementing Edu GPT in higher education, it is imperative to establish an evidence-based AI proficiency framework and detection infrastructure. In the same vein, teachers’ modeling is needed for students to follow when it comes to employing Edu GPT in academic activities as a norm.