Designing New Possibilities: Trauma-Informed Life Design with Culturally Responsive AI-Generated Scenarios for Higher Education
Year: 2025
Type: article
Abstract: This paper presents a conceptual model for integrating life design principles with AI-generated, culturally adaptive scenarios to reframe limiting beliefs in higher education contexts.Drawing on a workshop with university staff, faculty, and students, we demonstrate how artificial intelligencespecifically large language models-can identify perceptual, emotional, and cultural blocks that impede growth, while supporting reflective and creative problem-solving at scale.The workshop adopted a trauma-informed framework to foster psychological safety, enabling participants to explore personal and systemic constraints through grounding exercises, collaborative reframing, and AI-driven simulations.Rather than relying on generic prompts, culturally inclusive metaphors and scenarios were used to honor diverse lived experiences and avoid reinforcing dominant cultural assumptions.Core activities included identifying persistent frustrations and aspirations, reframing complex challenges into actionable steps, and co-creating adaptive AI scenarios.While this paper does not present empirical outcomes, it offers a scalable, ethically sensitive approach for educators, technologists, and organizational leaders seeking to democratize access to reflective tools and foster inclusive development.By integrating design thinking, digital innovation, and psychological insight, this model contributes to ongoing conversations about digital well-being, ethical AI, and the cultivation of agency and adaptability in digitally mediated environments.Ultimately, reframing limiting beliefs is both a personal and collective journey-one that can be meaningfully supported by evolving AI tools attuned to the people and cultures they serve.
Authors: Kelly Cooney, Christina Harnett, Patrick Brugh
Institution: Johns Hopkins University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7081956175
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