Reconfiguring Reflexivity in the era of AI: A critically oriented exploration through Constructivist and Posthumanist lenses

Introduction

Reflexivity within the qualitative research context involves the practice of critically examining how the researcher’s own assumptions, views, and choices, influence the research process and outcomes. As artificial intelligence (AI) becomes increasingly integrated into qualitative research and influencing all research stages, the foundational concept of reflexivity demands renewed examination.

Goals and Methods

This study adopts a critically oriented approach grounded in constructivist and posthumanist thinking to explore how AI shapes reflexivity. This orientation is supported by a post-qualitative positioning which resists fixed methodological frameworks and instead views method as emergent, situated, and entangled with theory and context. Such an approach is particularly suited to this study’s focus, as the relationship between AI and reflexivity is a complex, evolving, and definitely under-examined phenomenon.

Results (Obtained or Expected)

The critically oriented approach moves beyond revealing the significance of reflexivity in research and the different types of reflexivity in contemporary qualitative research, such as positional and epistemological reflexivity. It exposes how AI may undermine these types of reflexivity within the research context, challenging the constructivist paradigm of the human researcher being the sole and central agent in reflexive practice. Rather unexpectedly and paradoxically, it also divulges how AI can amplify reflexivity through distributed reflexivity—that is, reflexivity extending beyond the individual researcher, as informed by AI crescendos.

Conclusions

This study contributes to current scholar discussions of the impacts of AI in qualitative research, by reasserting reflexivity as a dynamic and evolving practice in the age of AI. The critical stance taken toward the relationship between reflexivity and AI reflects critiques of constructivism by challenging human-driven reflection and knowledge construction, while also highlighting the risks within posthumanism of embracing AI uncritically and without reflection.