Harmonizace lidské povahy s umělou inteligencí: Vývoj rámce sebeurčení pro společnou tvorbu kódu

In 1967, Marvin Minsky envisioned minds—biological and artificial—collaborating beyond their individual limitations. That same year, Brian Randell captured software engineering’s irreducibly social nature as the “multi-person construction of multi-version programs.” Today, the prophecy becomes reality. Artificial intelligence, that ‘man-made yet alien’ presence, transforms the very nature of collaborative programming itself. This dissertation optimizes human-AI programming roles through self-determination theory and personality psychology. As developers encounter AI collaboration—experiencing a technological thrownness into unprecedented relational dynamics—frameworks must emerge that harmonize human agency with algorithmic augmentation. The research employs Design Science Research across five systematic cycles: Cycle 1 explores personality-role causal relationships through behavioral science methods. Cycles 2 & 3 adopt pragmatist axiology to design and extend the Role Optimization Motivation Alignment (ROMA) framework with AI integration. Cycle 4 develops an ISO/IEC 29110 Software Basic Profile & Agile Guidelines extension for Very Small Entities, while Cycle 5 validates through in-situ test artifacts and empirical triangulation, engaging 200 experimental participants and 46 interview respondents. Results demonstrate that ROMA significantly enhances self-determination and team dynamics through personality-driven role optimization in both human-human and human-AI (“Human ⧉ AI”) collaborative contexts. Five distinct personality archetypes emerge: The Explorer (high Openness), The Orchestrator (high Extraversion/Agreeableness), The Craftsperson (high Neuroticism/low Extraversion), The Architect (high Conscientiousness), and The Adapter (balanced profile). Personality-aligned role assignments increase intrinsic motivation by an average of 23% among professionals and up to 65% among undergraduates, with AI mode selection (Co-Pilot, Co-Navigator, Agent) proving crucial for self-determination need satisfaction. The dissertation contributes: (1) an empirically-validated framework linking personality traits to programming role preferences and self-determination outcomes; (2) a taxonomy of AI modalities mapped to personality profiles while preserving human agency; and (3) an ISO/IEC 29110 extension enabling VSEs to implement personality-driven role optimization within established standards.