Simulating Life Paths with Digital Twins: AI-Generated Future Selves Influence Decision-Making and Expand Human Choice
Rachel Poonsiriwong, Chayapatr Archiwaranguprok, Constanze Albrecht, Peggy Yin, Nattavudh Powdthavee, Hal Hershfield, Monchai Lertsutthiwong, Kavin Winson, Pat Pataranutaporn

TL;DR
This study introduces AI-generated digital twins that simulate future life scenarios to enhance decision-making, showing they can expand human choice and influence preferences through vivid, personalized avatars.
Contribution
The paper presents a novel approach using AI to create personalized digital twins that simulate future selves, aiding deliberation without prescribing optimal outcomes.
Findings
AI avatars increased decision shifts toward presented options.
Introducing a third, system-generated option expanded choice.
Participants valued reasoning and meaning over vividness.
Abstract
Major life transitions demand high-stakes decisions, yet people often struggle to imagine how their future selves will live with the consequences. To support this limited capacity for mental time travel, we introduce AI-enabled digital twins that have ``lived through'' simulated life scenarios. Rather than predicting optimal outcomes, these simulations extend prospective cognition by making alternative futures vivid enough to support deliberation without assuming which path is best. We evaluate this idea in a randomized controlled study (N=192) using multimodal synthesis - facial age progression, voice cloning, and large language model dialogue - to create personalized avatars representing participants 30 years forward. Young adults 18 to 28 years old described pending binary decisions and were assigned to guided imagination or one of four avatar conditions: single-option, balanced…
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Taxonomy
TopicsVirtual Reality Applications and Impacts · Aging and Gerontology Research · Social Robot Interaction and HRI
