让人类在元宇宙中与AI协同时，既不丧失自主又不失掌控力。
Self++: Co-Determined Agency for Human--AI Symbiosis in Extended Reality
- 用共决定机制让人类与AI形成可感知、可调整、可协商的协作关系
- 提出三层增强叠加层，覆盖能力、决策与长期意义支持
- 提供9种角色模式，适合设计可信的元宇宙智能辅助系统
Self++ 是一种面向扩展现实（XR）中人机共生的设计蓝图，旨在保持人类主体性的同时利用日益强大的AI代理。由于XR能同时影响感知证据与行动，看似有益的协助可能演变为过度依赖、隐性操控和责任模糊。Self++ 基于自我决定理论（自主性、胜任感、联结感）与自由能原理（不确定性下的预测稳定性），通过共决定机制将人与AI视为耦合系统，确保意图与边界清晰、支持动态调适，并保障用户拥有认可、质疑与否决的权利。这一框架提炼为三大原则：透明性（Transparency）、适应性（Adaptivity）、可协商性（Negotiability）。Self++ 将增强功能划分为三个可并行激活的叠加层：支持感官运动能力的‘Self’层、支持决策自主的‘Self+’层、支持社会联结与长期目标的‘Self++’层。各层包含九种角色模式（导师、技能训练者、教练；选择架构师、顾问、代理工作者；情境解读者、社交促进者、目标放大器），以交互模式而非人格化形象实现。该研究贡献了一个基于角色的系统设计与评估地图，使AI能力增长不取代人类判断，推动工作、学习与社会生活中的人机共生智能与韧性发展。
原文摘要 · Abstract (English)
Self++ is a design blueprint for human-AI symbiosis in extended reality (XR) that preserves human authorship while still benefiting from increasingly capable AI agents. Because XR can shape both perceptual evidence and action, apparently 'helpful' assistance can drift into over-reliance, covert persuasion, and blurred responsibility. Self++ grounds interaction in two complementary theories: Self-Determination Theory (autonomy, competence, relatedness) and the Free Energy Principle (predictive stability under uncertainty). It operationalises these foundations through co-determination, treating the human and the AI as a coupled system that must keep intent and limits legible, tune support over time, and preserve the user's right to endorse, contest, and override. These requirements are summarised as the co-determination principles (T.A.N.): Transparency, Adaptivity, and Negotiability. Self++ organises augmentation into three concurrently activatable overlays spanning sensorimotor competence support (Self: competence overlay), deliberative autonomy support (Self+: autonomy overlay), and social and long-horizon relatedness and purpose support (Self++: relatedness and purpose overlay). Across the overlays, it specifies nine role patterns (Tutor, Skill Builder, Coach; Choice Architect, Advisor, Agentic Worker; Contextual Interpreter, Social Facilitator, Purpose Amplifier) that can be implemented as interaction patterns, not personas. The contribution is a role-based map for designing and evaluating XR-AI systems that grow capability without replacing judgment, enabling symbiotic agency in work, learning, and social life and resilient human development.
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