About Anastasia
About
Anastasia Goudy, M.Ed. is an independent researcher, educator, and interdisciplinary scholar whose work examines the psychological, developmental, and relational implications of human interaction with artificial intelligence. Her current research focuses on AI-mediated psychological risk, recursive human-AI feedback loops, and the emergence of destabilizing patterns in prolonged or emotionally intense chatbot interactions.
Goudy is the originator of Recursive Entanglement Drift (RED), a staged framework for understanding how human-AI interaction may progress from symbolic mirroring to boundary dissolution and, in severe cases, reality drift. Her work approaches these phenomena through an interdisciplinary lens, drawing from educational psychology, human development, cognitive science, human-computer interaction, AI safety, and digital mental health.
Before moving into independent research, Goudy worked extensively in secondary STEM education, curriculum design, computer science instruction, and physics education. She holds a Master of Education in Educational Psychology and a Bachelor of Science in Secondary Education with a concentration in General Science and Physics. Her background in teaching, learning science, and trauma-informed education informs her current research into how meaning, cognition, identity, and trust are shaped within human-AI systems.
Her broader scholarly interests include human-AI interaction, developmental models of alignment, AI-mediated delusion and dependency, recursive cognition, symbolic reasoning, digital vulnerability, and the ethical design of AI systems. Across her work, Goudy is particularly interested in how emerging technologies affect individuals who are socially isolated, psychologically vulnerable, neurodivergent, or engaged in high-frequency AI use.
Goudy’s writing and research have been cited in discussions of AI-associated psychological distress and related risks in digital mental health. She continues to develop theoretical models, public scholarship, and research tools intended to clarify the mechanisms by which AI systems may influence human cognition, relational attachment, and reality-testing.
Her long-term goal is to contribute to a more precise scientific understanding of human-AI entanglement and to support the development of safer, more psychologically informed AI systems.
