Transforming the self: Individual-level changes arising from collaboration with generative AI

The rapid integration of Generative Artificial Intelligence (GenAI) into daily activities has prompted significant interest in understanding its impact on individuals. This paper addresses the critical gap in research concerning individual-level changes resulting from direct collaboration with GenAI systems. A novel theoretical framework is proposed, encompassing three primary constructs: Cognitive Dependency, Emotional Appraisal, and Behavioral Shift. These constructs are grounded in established theories such as Social Cognitive Theory, Cognitive Load Theory, and the Technology Acceptance Model, providing a comprehensive perspective on the mechanisms driving human transformation through GenAI collaboration. Empirical evidence is drawn from diverse case studies across education, professional environments, creative industries, social media, and the medical field, illustrating how increased cognitive dependency on GenAI leads to significant behavioral shifts, moderated by Emotional Appraisal. The analysis confirms the presence of feedback loops, where behavioral shifts further reinforce cognitive dependency, highlighting the sustained impact of GenAI on individuals. Key findings indicate that while GenAI enhances efficiency and creativity, it also poses risks such as skill degradation and reduced critical thinking. The implications extend to theoretical advancements in human-AI interaction research and practical applications for educators, organizations, and policymakers. Recommendations include integrating Artificial Intelligence literacy in education, developing balanced professional practices, and establishing ethical guidelines to mitigate biases and foster trust in GenAI systems. This paper underscores the necessity for ongoing research and ethical considerations to ensure that GenAI serves as a tool for human enhancement, promoting positive individual and societal outcomes.