<b>Coupling Thresholds in Multi-Component Systems: A </b><b>Potential Critical Gap in AI Safety</b>
<p dir="ltr">Elias De Jesús, BS, MS</p><p dir="ltr">Independent Researcher (Bioscience Background)</p><p dir="ltr">This exploratory work examines coupling thresholds in multi-component systems as potential phase-transition points where coherence and instability coexist. Using synthetic simulations, the study identifies measurable lag signatures and correlation shifts that emerge near critical coupling levels, suggesting parallels to physical phase transitions in nature.</p><p dir="ltr">These findings propose that distributed AI systems may also exhibit similar critical thresholds, underscoring the need for a new interdisciplinary field at the intersection of physics and engineering to study coupling dynamics and systemic safety.</p><p><br></p><p dir="ltr">The work extends earlier reflections on complex systems and proposes that every system may have its own critical boundary of coherence — a “living threshold” where structure and adaptation meet.</p><p dir="ltr"><b>Archival Note:</b></p><p dir="ltr">This item is also archived on Zenodo for long-term preservation and cross-referencing: <a href="https://doi.org/10.5281/zenodo.17420768" target="_blank">https://doi.org/10.5281/zenodo.17420768</a></p><h3><b>Acknowledgment</b></h3><p dir="ltr"><br></p><p dir="ltr">Analytical and editorial assistance was provided through ChatGPT (GPT-5) for data interpretation, visualization design, and manuscript structure.</p><p dir="ltr">All conceptual insights, theoretical interpretations, and experimental ideas originate from the independent research of <b>Elias De Jesús</b>, BS, MS (Bioscience Background).</p>
