发表机构
University of Exeter; University of Salford（埃克塞特大学; 索尔福德大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文构建社会技术过程理论，区分AI相关事件、危机与丑闻，提出可问责透明度应对配置，调和算法参与对品牌反应的双向影响，明确相关推断的适用范围。
AI 中文摘要
人工智能系统正日益通过聊天机器人、推荐系统、自动化决策及生成式界面等载体，兑现面向市场的承诺。其故障、误用与不实陈述引发了一个传统品牌危机模型未充分明确的问题：当技术因果、面向客户的控制权及治理职责分布于AI系统、开发者、部署者、供应商与用户之间时，利益相关者如何分配责任？本文为概念性论文，通过对经核实的学术及原始资料进行结构化、联合范围综合，构建了一种社会技术过程理论。该理论将AI/算法事件与AI相关组织危机、进而与AI相关组织丑闻相区分，提出事件构成会塑造特定行动者的归因；归因会影响对能力、完整性、公平性及关系的评估；而公众道德化可能（但非必然）将事件升级为丑闻。该理论调和了相关研究发现：在部分场景中，算法参与可缓冲负面品牌反应，而在另一些场景中，机器人与聊天机器人故障则会将责任转向关联企业。它提出了可问责透明度这一应对配置，其结合了及时通知、可理解的说明、角色责任承认、补救措施、纠正证据及追索途径。证据支持关于责备、信任、满意度、企业评价及沟通可信度的有条件、近端推断，其强度高于关于持久声誉、品牌资产或市场表现的主张。
英文摘要
Artificial intelligence systems increasingly enact market-facing promises through chatbots, recommendation systems, automated decisions, and generative interfaces. Their failures, misuse, and misrepresentation raise a question that conventional brand-crisis models do not fully specify: how do stakeholders assign responsibility when technical causation, customer-facing control, and governance duties are distributed across an AI system, developer, deployer, vendor, and user? This conceptual paper develops a sociotechnical process theory from a structured, federated scoping synthesis of verified academic and primary sources. It distinguishes an AI/algorithmic incident from an AI-related organisational crisis and, in turn, from an AI-related organisational scandal. The framework proposes that incident configuration shapes actor-specific attribution; attribution informs capability, integrity, fairness, and relationship appraisals; and public moralisation may, but need not, escalate an incident into scandal. The theory offers a reconciliation of findings that algorithm involvement can buffer negative brand reactions in some settings while robot and chatbot failures can redirect responsibility to an associated firm in others. It introduces accountable transparency as a proposed response configuration that combines timely notice, an intelligible account, role-responsibility acknowledgement, remedy, evidence of correction, and recourse. The evidence supports conditional, proximal inferences about blame, trust, satisfaction, firm evaluation, and communication credibility more strongly than claims about durable reputation, brand equity, or market performance.
