Rethinking Trust in AI Assistants for Software Development (Supplementary Material)

Context: Trust is a fundamental concept in human decision-making and collaboration that has long been studied in philosophy and psychology. However, software engineering (SE) articles often use the term 'trust' informally—providing an explicit definition or embedding results in established trust models is rare. In SE research on AI assistants, this practice culminates in equating trust with the likelihood of accepting generated content, which does not capture the full complexity of the trust concept. Without a common definition, true secondary research on trust is impossible.

Objective: The objectives of our research were: (1) to present the psychological and philosophical foundations of human trust, (2) to systematically study how trust is conceptualized in SE and the related disciplines human-computer interaction and information systems, and (3) to discuss limitations of equating trust with content acceptance, outlining how SE research can adopt existing trust models to overcome the widespread informal use of the term 'trust'.

Method: We conducted a literature review across disciplines (n=84 articles) and a critical review of recent SE articles (n=58) on trust.

Results: We found that trust is rarely defined and conceptualized in SE articles. Related disciplines commonly embed their methodology and results in established trust models, clearly distinguishing, for example, between initial trust and trust formation and discussing whether and when trust can be applied to AI assistants.

Conclusions: Our study reveals a significant maturity gap of trust research in SE compared to related disciplines. We provide concrete recommendations on how SE researchers can adopt established trust models and instruments to study trust in AI assistants beyond the acceptance of generated software artifacts.

研究背景：信任是人类决策与协作的核心概念，长期以来在哲学与心理学领域得到广泛研究。然而，软件工程（SE）领域的学术文章往往对“信任”一词采用非正式用法，极少给出明确定义，也鲜有将研究成果嵌入已确立的成熟信任模型中。在针对AI助手（AI Assistants）的软件工程研究中，这种做法最终将信任等同于接受生成内容的概率，未能涵盖信任概念的全部复杂性。若缺乏统一的定义，便无法开展真正意义上的信任相关二次研究。
研究目标：本研究的目标如下：（1）梳理人类信任的心理学及哲学基础；（2）系统探究软件工程及相关学科（人机交互、信息系统）中信任的概念化方式；（3）探讨将信任等同于内容接受度的研究局限，并阐明软件工程领域可如何借鉴现有信任模型，以扭转“信任”一词被随意使用的普遍现状。
研究方法：本研究开展了跨学科文献综述（共纳入84篇文献），并针对近期发表的软件工程领域信任相关文章进行了批判性综述（共纳入58篇文献）。
研究结果：本研究发现，软件工程领域的文章极少对信任进行明确定义与概念化。相关学科则普遍将研究方法与成果嵌入成熟的信任模型中，例如明确区分初始信任与信任形成过程，并探讨信任可在何种条件下应用于AI助手。
研究结论：相较于相关学科，本研究揭示出软件工程领域的信任研究存在显著的成熟度差距。针对软件工程研究者如何借鉴现有信任模型与工具，以在超越生成软件工件接受度的维度下开展AI助手相关信任研究，本研究给出了具体建议。