The Energy of Gratitude: AI, Introspection, and Sustainable Self-Actualization

This paper proposes a novel synthesis of humanistic psychology, AI ethics, and energy sustainability by examining how brief, gratitude-oriented interactions with large language models (LLMs) may support psychological self-actualization while consuming minimal energy. Drawing on Abraham Maslow’s late-stage theory of Being-cognition, the study reframes AI-mediated dialogue as a low-energy, high-value cultural practice that fosters introspection, intrinsic motivation, and emotional integration. Through theoretical analysis, cross-cultural contextualization, and behavioral modeling, the paper argues that the marginal energy cost of such interactions can be ethically justified when embedded within a broader ecology of intentional digital reduction—such as a daily ten-minute period of offline introspection. This interdisciplinary framework contributes to emerging discourses on Green AI, sustainable well-being, and the symbolic design of human–AI interaction, offering a rare integration of psychological depth, cultural continuity, and environmental responsibility.