Becoming the “post-reality”: AIGC, memory generation, and an experimental foray into AI anthropology

This article investigates how Artificial Intelligence Generated Content (AIGC) intervenes in memory and what this intervention means for qualitative knowledge production in an emergent “post-reality” condition. Drawing on new materialism theory, this article treats AI as an agential actor and examines how it co-constitutes reality through “intra-action” with human memory. The study employs an innovative experimental design, conducting in-depth interviews with 16 human participants and four AI participants role-played by large language models, based on their responses to AI-generated images. Empirically, the data show that AIGC can cue plausible recollections by matching culturally available memory templates, while disclosure of artificial provenance prompts renewed negotiation of authenticity. Comparison of the two deliberately non-equivalent material sets further reveals a limit to simulation: AI produces standardized recollections and statistical archetypes, whereas human accounts retain embodied, contingent details that we call an “authenticity core.” Our research indicates that the boundary between authentic and synthesized experience has become unstable and must be situated and negotiated. We define post-reality as this generative and contested condition and propose AI Anthropology as a reflexive agenda for qualitative research into experiential worlds co-constituted by humans and machines.