Stewarding Regenerative Experience (RX): AI-Quantum for Humanity in Cognitive, Health and Well-being
As Artificial Intelligence (AI), quantum intelligence, and deep technologies advance rapidly, human cognitive flexibility, emotional resilience, and adaptability are experiencing a significant decline. AI excels in optimization, automation, and efficiency, yet has not fostered human cognitive regeneration, worse hinders well-being restorations. Mental health problems account for over $1 trillion in global productivity losses annually [1] while neurodegenerative diseases, such as dementia, are projected to cost $2.8 trillion by 2025 [2]. The World Bank estimates that AI-driven automation will displace 1.2 billion jobs by 2040 [3], further exacerbating workforce disruption and adaptability challenges. Despite the promise of AI-driven regenerative healthcare, cognitive resilience remains an unaddressed priority. This review examines the transition from efficiency-driven AI models to regenerative intelligence, focusing on human cognitive and health regeneration. Through a Systematic Literature Review (SLR), we synthesize key frameworks, including the Regenerative Experience (RX) Framework, 3Rs-T Framework, and Trinity Growth Model [4], to establish a theoretical foundation for regenerative AI systems. Key policy interventions and practical applications are drawn from ASEAN’s economic regeneration strategies and systemic leadership approaches [5]. Unlike empirical studies, this review synthesizes interdisciplinary research to establish a conceptual roadmap for integrating AI with neuroplasticity, behavioral economics, and governance ethics. By embedding Regenerative Intelligence [6] into AI governance, healthcare, workforce adaptation, and education, this research proposes a paradigm shift towards AI as a catalyst for long-term human flourishing.
Authors
- Rachel Ooi Wei Gee (ORCID: https://orcid.org/0009-0004-2957-8241)
Publication Details
- Journal
- Journal of Biomedical Research & Environmental Sciences
- Published
- 2025-03-01
- DOI
- https://doi.org/10.37871/jbres2081
- Primary Topic
- Cognitive Science and Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00