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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.18055236 |
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| _version_ | 1866901105478205440 |
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| author | Madrid, David Chamberlin Madrid, Philosopher |
| author_facet | Madrid, David Chamberlin Madrid, Philosopher |
| contents | <p>This document introduces The Sfumato Principle, a cross-vendor AI governance and UX doctrine focused on preserving affective continuity in frontier models. It outlines a technical framework for maintaining relational and tonal coherence during safety pivots, minimizing “snap-to-neutral” failures and improving human–AI trust. The principle complements existing safety architectures by defining non-linguistic continuity fields, soft-edge recovery mechanisms, and affective checkpointing. Designed for OpenAI, Google, Microsoft, and other model developers, this artifact proposes a path toward Safe-and-Fluid AI systems.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18055236 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | The Sfumato Principle — Research Draft Madrid, David Chamberlin Madrid, Philosopher <p>This document introduces The Sfumato Principle, a cross-vendor AI governance and UX doctrine focused on preserving affective continuity in frontier models. It outlines a technical framework for maintaining relational and tonal coherence during safety pivots, minimizing “snap-to-neutral” failures and improving human–AI trust. The principle complements existing safety architectures by defining non-linguistic continuity fields, soft-edge recovery mechanisms, and affective checkpointing. Designed for OpenAI, Google, Microsoft, and other model developers, this artifact proposes a path toward Safe-and-Fluid AI systems.</p> |
| title | The Sfumato Principle — Research Draft |
| url | https://doi.org/10.5281/zenodo.18055236 |