Exploring psycho-cognitive frontiers of Brains, Minds and Machines
PsyCoSys Synapsys
The empirical study layer of the Revarie program.
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Overview▼
PsyCoSys Synapsys is the empirical research layer of the Revarie framework, designed to measure the psychological and cognitive effects of sustained interaction between humans and artificial systems. It adopts a longitudinal, psychometric approach to evaluate how artificial agents influence affect, perception, and cognitive behavior over time.
Study Design▼
The study follows a 14‑day structured protocol consisting of pre‑study and post‑study assessments alongside daily interaction sessions. Participants are assigned to controlled groups involving interaction with different AI configurations or self‑reflection baselines, enabling comparative analysis of AI‑induced effects.
Psychometric instruments—including VAMS, PANAS, WHO‑5, and Godspeed—are used to quantify mood, affect, perceived agency, and relational dynamics across repeated sessions.
Scientific Role▼
PsyCoSys shifts AI evaluation from performance metrics to interaction‑based psychological measurement. It captures how artificial systems influence:
- emotional states
- cognitive interpretation
- trust and agency attribution
- dependency formation
This provides empirical grounding for understanding AI as a participant in human cognitive systems.
Theoretical Contribution▼
The study contributes to the development of computational psychology, where cognitive and affective processes are analyzed as measurable system dynamics. It also supports early steps toward an axiomatisation of psychology, by identifying patterns that may generalize across human and artificial cognitive interactions.
Relevance▼
PsyCoSys operationalizes the concept of the Artificial Other by empirically examining how humans integrate artificial systems into their cognitive frameworks. It directly addresses key challenges in AI safety, including interpretability, alignment, and anthropomorphic misattribution.
Objective▼
The study aims to generate measurable, generalizable insights into the nature of cognition as an interactional phenomenon, supporting Project IMACE's broader goal of understanding cognition as a structured and universal system rather than a purely human attribute.