2023/02/01 by Kashyap Haresamudram, Stefan Larsson, Fredrik Heintz · 72 citations
Computer Science · Social Sciences · #Adversarial Robustness in Machine Learning #Artificial intelligence #Computer science #Computer security #Context (archaeology) #Data science #Ethics and Social Impacts of AI #Explainable Artificial Intelligence (XAI) #Fragmentation (computing) #Transparency (behavior)
paper · open access · doi:10.1109/mc.2022.3213181
published in Computer 56(2), 93-100 (IEEE Computer Society)
openalex publication_date 2023/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/25
The concept of transparency is fragmented in artificial intelligence (AI) research, often limited to transparency of the algorithm alone. We propose that AI transparency operates on three levels—algorithmic, interaction, and social—all of which need to be considered to build trust in AI. We expand upon these levels using current research directions, and identify research gaps resulting from the conceptual fragmentation of AI transparency highlighted within the context of the three levels.