Stateful Intelligence: Engineering Trust, Continuity, and Dignity in Human-AI Experiences
Description
Research Context: This work is a core component of the Presence Engine™ Living Thesis (DOI: 10.5281/zenodo.17280692).
This preprint introduces the Presence Engine™, a foundational framework for privacy-first, personality-adaptive AI systems designed to maintain behavioral continuity and support human cognitive development. Current AI architectures operate stateless, each interaction begins from zero context, undermining trust formation and preventing meaningful long-term collaboration.
The Presence Engine™ proposes an alternative: stateful AI infrastructure grounded in social learning theory and critical thinking dispositions research. The system maintains emotional and behavioral continuity through local-first processing, models productive thinking patterns (reflection, perseverance, truth-seeking) through a curated Character Brain of 47,000–50,000 staged reflections per personality vertical, and guarantees user privacy through encrypted, user-controlled data architecture that eliminates data extraction incentives.
Key contributions:
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Theoretical framework integrating Bandura's social learning theory with dispositional psychology and OCEAN/HEXACO personality adaptation for human-AI interaction
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Four core principles: thinking patterns over skills, privacy-first as requirement, continuity enabling specialization, dignity by default
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Technical architecture specifications for local-first processing, personality-adaptive interfaces, and ethical safeguards (manipulation detection, honesty requirements, anti-coercion mechanisms)
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12-month validation methodology (Phase 1: 50–100 users; Phase 2: 500+ users; Phase 3: longitudinal + control group)
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Failure mode analysis and mitigation strategies for personality misclassification, disposition modeling backfire, and system abuse
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Competitive positioning analysis differentiating stateful continuity architecture from existing memory features and personality platforms
Keywords: Human-Centric AIX, Presence Engine, Stateful AI, Privacy-First Architecture, Personality Adaptation, Social Learning Theory, Critical Thinking Dispositions, AI Alignment, Human Development, Affective Computing
Living Thesis | DOI: https://zenodo.org/records/17280692
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StatefulIntelligence_Human-AIExperiences_PresenceEngine.pdf
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- Is part of
- Thesis: https://zenodo.org/records/17280692 (URL)
Dates
- Copyrighted
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2025-10-24Date of copyright
References
- Smith, T. (2025). Presence Engine™: A framework for human-centric AIX™ (AI Experience). Version 3.0. Antiparty Press https://zenodo.org/records/17280692
- Bandura, A. (1977). Social Learning Theory. Englewood Cliffs, NJ: Prentice Hall. https://www.asecib.ase.ro/mps/Bandura_SocialLearningTheory.pdf
- Bandura, A. (1986). Social Foundations of Thought and Action: A Social Cognitive Theory. Englewood Cliffs, NJ: Prentice Hall. https://psycnet.apa.org/record/1985-98423-000
- Costa, P. T., & McCrae, R. R. (1992). Revised NEO Personality Inventory (NEO-PI-R) and NEO Five-Factor Inventory (NEO-FFI) professional manual. Odessa, FL: Psychological Assessment Resources. https://psycnet.apa.org/record/2008-14475-009
- Facione, P. A. (1990). Critical thinking: A statement of expert consensus for purposes of educational assessment and instruction. Millbrae, CA: The California Academic Press. https://www.researchgate.net/publication/242279575_Critical_Thinking_A_Statement_of_Expert_Consensus_for_Purposes_of_Educational_Assessment_and_Instruction
- Giancarlo, C. A., Blohm, S. W., & Facione, P. A. (2004). The disposition toward critical thinking: Its character, measurement, and relationship to critical thinking skill. Informal Logic, 20(1), 61-84. https://www.researchgate.net/publication/252896581_The_Disposition_Toward_Critical_Thinking_Its_Character_Measurement_and_Relationship_to_Critical_Thinking_Skill
- John, O. P., Naumann, L. P., & Soto, C. J. (2008). Paradigm shift to the integrative Big Five trait taxonomy. In O. P. John, R. W. Robins, & L. A. Pervin (Eds.), Handbook of personality: Theory and research (3rd ed., pp. 114-158). New York: Guilford Press. https://books.google.com/books/about/Handbook_of_Personality.html?id=olgW-du4RBcC
- McCrae, R. R., & Costa, P. T. (1997). Personality trait structure as a human universal. American Psychologist, 52(5), 509-516. https://psycnet.apa.org/record/1997-04451-001
- Schlicher, M., Li, Y., Murthy, S. M. K., Sun, Q., & Schuller, B. W. (2025). Emotionally adaptive support: A narrative review of affective computing for mental health. Frontiers in Digital Health, 7, 1657031. https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2025.1657031/full
- Pathak, V., Jain, S., & Malik, A. (2025). PADO: Personality-induced multi-agents for detecting OCEAN in human-generated texts. In Proceedings of the 31st International Conference on Computational Linguistics (pp. 5719–5736). https://aclanthology.org/2025.coling-main.382/
- Yeo, H., Noh, T., & Seungwan. (2025). Affective computing: Recent advances, challenges, and future directions. IEEE Transactions on Affective Computing. https://www.researchgate.net/publication/376638215_Affective_Computing_Recent_Advances_Challenges_and_Future_Trends
- Ajithkumar, P. (2025). AI-native memory and the rise of context-aware AI agents: Second me. Retrieved from https://ajithp.com/2025/06/30/ai-native-memory-persistent-agents-second-me/
- Tribe AI. (2025). Beyond the bubble: How context-aware memory systems are changing the game in 2025. Retrieved from https://www.tribe.ai/applied-ai/beyond-the-bubble-how-context-aware-memory-systems-are-changing-the-game-in-2025/
- Brown, M., & Johnson, K. (2022). How personal values and critical dispositions support digital citizenship. Journal of Digital Literacy, 18(4), 445-462. https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.990518/full
- Bachtiar. (2024). Strategies and challenges in encouraging students' critical thinking skills in online learning: A literature review. International Journal of Research Publication and Reviews, 6(2), 1-15. https://www.ijfmr.com/papers/2024/2/14527.pdf
- United Nations Development Programme. (2025). Human development report 2025: A matter of choice: People and possibilities in the age of AI. New York: UNDP. https://hdr.undp.org/system/files/documents/global-report-document/hdr2025reporten.pdf
- Conceição, P., & UNDP Human Development Report Office. (2025). Navigating AI with a human development compass. Journal of Human Development and Capabilities, 26(3), 415-432. https://ideas.repec.org/a/taf/jhudca/v26y2025i3p439-448.html
- Bender, E. M., Gebru, T., & Mitchell, M. (2023). AI alignment: A comprehensive survey. arXiv preprint, 2310.19852. https://arxiv.org/abs/2310.19852