An Enactivist Approach to Human-Computer Interaction: Bridging the Gap Between Human Agency and Affordances
HCI International 2025 – Late Breaking Papers January 1, 2026 Peer reviewed DOI: 10.1007/978-3-032-12657-3_3 via Springer Nature
Summary
The paper proposes a new framework for understanding human agency in human-computer interaction, especially in extended reality (XR), brain-computer interfaces (BCI), and generative AI. Drawing on enactivist theories of cognition, it introduces 'feelings of agency' (FoA) as an alternative to the established 'sense of agency' (SoA). FoA includes affective engagement and volitional attention, measured through neurodynamic indicators and first-person reports. The framework aims to guide design that enhances human agency in interactive technologies.
Study at a glance
| Design | theoretical or philosophical paper |
|---|---|
| Key finding | The paper argues that 'feelings of agency', comprising affective engagement and volitional attention, offer richer insights for designing digital affordances that enhance human agency in XR, BCI, and generative AI environments. |
Abstract
Emerging paradigms in XR, AI, and BCI contexts necessitate novel theoretical frameworks for understanding human autonomy and agency in HCI. Drawing from enactivist theories of cognition, we conceptualize human agents as self-organizing, operationally closed systems that actively enact their cognitive domains through dynamic interaction with their environments. To develop measurable variables aligned with this framework, we introduce “feelings of agency” (FoA) as an alternative to the established construct of “sense of agency” (SoA), refining Synofzyk’s multifactorial weighting model and offering a novel conceptual pathway for overcoming gaps in the dominant comparator model. We define FoA as comprising two subconstructs: affective engagement and volitional attention , which we operationalize through integrated neurodynamic indicators (valence, arousal, cross frequency coupling within the dorsal attention system) and first-person phenomenological reports. We argue that these neurophenomenological indicators provide richer, more actionable insights for digital affordance design, particularly in XR, BCI, Human AI Interaction (HAX), and generative AI environments. Our framework aims to inform and inspire design parameters that significantly enhance human agency in rapidly evolving interactive domains.