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.

翻译：Self++是面向扩展现实（XR）中人机共生关系的设计蓝图，旨在保留人类自主创作权的同时，充分利用日益强大的智能体能力。由于XR既能塑造感知证据又能塑造行动，看似"有益"的辅助可能演变为过度依赖、隐性说服和责任模糊。Self++将交互建立在两种互补理论之上：自我决定理论（自主性、能力感、归属感）和自由能原理（不确定性下的预测稳定性）。它通过共同决定机制将这两大基础操作化，将人类与AI视为耦合系统，必须确保意图与界限清晰可辨、随时间动态调整支持力度，并保障用户拥有认可、质疑和否决的权利。这些需求被归纳为共同决定三原则（T.A.N.）：透明性（Transparency）、适应性（Adaptivity）与可协商性（Negotiability）。Self++将增强过程组织为三个可并行激活的覆盖层：感觉运动能力支持层（Self：能力覆盖层）、深思熟虑自主性支持层（Self+：自主覆盖层），以及社会性、长期归属感与目标支持层（Self++：归属感与目标覆盖层）。在各覆盖层中，它具体规定了九种角色模式（导师、技能构建者、教练；选择架构师、顾问、能动工作者；情境诠释者、社交促进者、目标放大器），这些模式可作为交互范式而非人格拟态来实现。本研究的贡献在于提供了一份基于角色的设计蓝图，用于构建和评估既能提升能力又不取代判断的XR-AI系统，从而在劳动、学习与社交生活中实现共生主体性，促进人类韧性发展。