用大模型设计可自适应的伦理合规行为引导系统
Designing Adaptive Digital Nudging Systems with LLM-Driven Reasoning
- 基于行为科学构建分层架构，将伦理与公平作为结构约束
- 通过15名用户测试验证，干预效果显著且情绪正向影响明显
- 适合需要合规引导的智能系统开发者参考
数字行为引导系统缺乏将行为科学转化为软件设计的架构指导。现有架构未能将多维用户建模与伦理合规作为核心设计考量。本文提出一种架构，通过明确的架构决策整合行为理论，将伦理与公平作为结构性防护机制而非实现细节。文献综述提炼出68种引导策略、11项质量属性和3个用户画像维度，形成架构需求。系统采用分层处理流程，配备跨切面评估模块以确保合规性。13位软件架构师验证了需求满足度与领域迁移能力。一个基于大模型的住宅能源可持续性原型在15名用户中测试，表现出高感知干预质量及可测量的积极情绪影响。该研究通过可复用模式，连接行为科学与软件架构，为兼顾有效性与伦理约束的自适应系统提供支持。
原文摘要 · Abstract (English)
Digital nudging systems lack architectural guidance for translating behavioral science into software design. While research identifies nudge strategies and quality attributes, existing architectures fail to integrate multi-dimensional user modeling with ethical compliance as architectural concerns. We present an architecture that uses behavioral theory through explicit architectural decisions, treating ethics and fairness as structural guardrails rather than implementation details. A literature review synthesized 68 nudging strategies, 11 quality attributes, and 3 user profiling dimensions into architectural requirements. The architecture implements sequential processing layers with cross-cutting evaluation modules enforcing regulatory compliance. Validation with 13 software architects confirmed requirements satisfaction and domain transferability. An LLM-powered proof-of-concept in residential energy sustainability demonstrated feasibility through evaluation with 15 users, achieving high perceived intervention quality and measurable positive emotional impact. This work bridges behavioral science and software architecture by providing reusable patterns for adaptive systems that balance effectiveness with ethical constraints.
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