Healthy Distrust in AI systems
원문 초록
Under the slogan of trustworthy AI, much of contemporary AI research is focused on designing AI systems and usage practices that inspire human trust and, thus, enhance adoption of AI systems. However, a person affected by an AI system may not be convinced by AI system design alone -- neither should they, if the AI system is embedded in a social context that gives good reason to believe that it is used in tension with a person's interest. In such cases, distrust in the system may be justified and necessary to build meaningful trust in the first place. We propose the term "healthy distrust" to describe such a justified, careful stance towards certain AI usage practices. We investigate prior notions of trust and distrust in computer science, sociology, history, psychology, and philosophy, outline a remaining gap that healthy distrust might fill and conceptualize healthy distrust as a crucial part for AI usage that respects human autonomy.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
AI-Reporter: A Path to a New Genre of Scientific Communication
Large Language Models for History, Philosophy, and Sociology of Science: Interpretive Uses, Methodological Challenges, and Critical Perspectives
Stereotype Detection in Natural Language Processing
The heteronomy of algorithms: Traditional knowledge and computational knowledge
Astro-HEP-BERT: A bidirectional language model for studying the meanings of concepts in astrophysics and high energy physics
Meaning at the Planck scale? Contextualized word embeddings for doing history, philosophy, and sociology of science
토론
이 논문과 연결된 포럼 글이 아직 없습니다.