Possible You: AI-Generated Digital Twins as Creative Mirrors for Future Self Modeling

Pat Pataranutaporn, Kavin Winson, Peggy Yin, Auttasak Lapapirojn, Thanawit Prasongpongchai, Monchai Lertsutthiwong, Patricia Maes, Hal Hershfield

Track: Paper

Keywords: Generative AI, Digital Twins, Virtual Self Modeling, Future Self, Human-AI Interaction

TL;DR: We demonstrate that AI-generated digital twins serving as 'creative mirrors' for future self modeling significantly enhance career exploration, suggesting new paradigms for human-AI collaboration in identity formation.

Abstract: The human capacity to envision possible futures fundamentally shapes who we become. Yet for many, especially those without access to mentorship or resources, imagining vivid career futures remains abstract and distant. We present ``Possible You,'' a creative AI system that transforms career exploration into an intimate dialogue with one's future selves. Through personalized narratives and AI-generated portraits, the system makes abstract futures tangible and emotionally resonant. In our mixed-methods study (N=209), we discovered that the perceived authenticity of these AI-created futures influenced participants' sense of connection to their future selves. While viewing multiple possible selves expanded participants' sense of possibility, exploring a single future self fostered deeper commitment. This tension reveals a fundamental aspect of human future-making: we need both breadth to discover and depth to commit. Our work demonstrates how creative AI can serve not as predictor or prescriber of futures, but as a mirror that helps humans see and shape their own becoming—contributing to a more equitable landscape where all people can vividly imagine and pursue meaningful futures.

Submission Number: 195