Analysis of the impacts of generative AI-driven human-machine communication interactions on user subjectivity in social media

Abstract

Generative artificial intelligence has arrived on social media with large language models like chatgpt making features for AI-assisted production and communication mainstream. People have transformed how they make stuff and work with machines. This research analyses the effect of these advancements on the subjectivity of users from the perspective of human-machine communication theory. The usage of AI-assisted production can minimise the difficulty of expression, but the anchoring effect may discreetly limit the autonomous judgement of users; Personalised recommendation reinforces the selective exposure to information, undermining the conditions that support critical reflection; The involvement of AI in self-presentation blurs the barrier between human and machine, and the identity identification needs to be repositioned. In an effort to seek a balance point between AI efficiency and human autonomy, the paper proposes many solutions in three fields to address these issues, including technical transparency, media literacy education and platform standards. The factual applications of AI given in this article are taken from public papers such as the Stanford "Artificial Intelligence Index Report". The major research approaches are literature analysis and deduction of theory.