Hybrid HCAI — A Thought Experiment on the Ultimate Symbiosis of Human and Artificial Intelligence
DOI:
https://doi.org/10.33423/4w4h6z97Keywords:
organizational psyhology, Human-Centered Artificial Intelligence, Hybrid Intelligence, Human-AI Collaboration, neuro-symbolic AI, human-in-the-loop, collective intelligence, self-organization, organizational agility, knowledge management, Artificial General IntelligenceAbstract
The rapid development of artificial intelligence (AI) contrasts with the stillpartial understanding of its economic, organizational, and societal impacts.
This paper develops a conceptual model of Hybrid Human-Centered Artificial Intelligence (Hybrid-HCAI), proposing that AI should complement rather than comprehensively replicate or replace human intelligence. The model presents a tri-hybrid architecture integrating subsymbolic AI, symbolic AI, and human intelligence according to their comparative strengths. Subsymbolic AI performs data-intensive tasks such as pattern recognition, forecasting, classification, and generation, while symbolic AI represents explicit knowledge, rules, causal relationships, norms, and governance structures.
Human intelligence contributes contextual understanding, experiential knowledge, creativity, intuition, values, social competence, and responsibility. The symbolic layer additionally serves as a mediating and regulating function, coordinating interactions between humans and machines as a “social operating system.”
The paper derives a theoretical impact model focusing on productivity, organizational agility, innovation, structural stability, and cultural integrity, with participation, fairness, reciprocity, trust, and recognition as key mediators. It proposes testable hypotheses and an interdisciplinary research agenda, positioning Hybrid-HCAI as a conceptual research program rather than a validated technology.
References
Acemoglu, D. (2024). The World Needs a Pro-Human AI Agenda. Project Syndicate.
Acemoglu, D. (2025). Will We Squander the AI Opportunity? Project Syndicate.
Acemoglu, D., & Johnson, S. (2023). Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity. PublicAffairs.
Dellermann, D., Calma, A., Lipusch, N., Weber, T., Weigel, S., & Ebel, P. (2019). The future of human-AI collaboration: A taxonomy of design knowledge for hybrid intelligence systems. Proceedings of the 52nd Hawaii International Conference on System Sciences.
Dellermann, D., Ebel, P., Söllner, M., & Leimeister, J. M. (2019). Hybrid Intelligence. Business & Information Systems Engineering, 61(5), 637–643.
Garibay, O.O., Winslow, B., Andolina, S., Antona, M., Bodenschatz, A., Coursaris, C., et al. (2023). Six Human-Centered Artificial Intelligence Grand Challenges. International Journal of Human–Computer Interaction, 39(3), 391–437.
Goertzel, B., & Pennachin, C. (Eds.). (2007). Artificial General Intelligence. Springer.
Marcus, G. (2018). Deep Learning: A Critical Appraisal. arXiv preprint arXiv:1801.00631.
Marcus, G. (2020). The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence. arXiv preprint arXiv:2002.06177.
Marcus, G. (2024). Taming Silicon Valley: How We Can Ensure That AI Works for Us. MIT Press.
Shneiderman, B. (2022). Human-Centered AI. Oxford University Press.
Solow, R.M. (1987). We’d Better Watch Out. The New York Times Book Review, 12 July.
Winslow, B., Garibay, O.O., Goyal, T., Koon, S., Margetis, G., Salvendy, G., … Vardoulakis, L. (2026). Revisiting the Six Human-Centered Artificial Intelligence Grand Challenges in the Age of Generative AI. International Journal of Human–Computer Interaction.
Schieck, F. (2023). Wo liegt der Fehler im System der Digitalen Transformation und welche Anforderungen ergeben sich damit für den Einsatz von künstlicher Intelligenz? BCM Consult.
Schieck, F. (2024). Wann wird KI zur Killerapplikation für Produktivitätswachstum und Bürokratieabbau in Unternehmen? BCM Consult.
