The content discusses the cultural bias in Explainable AI (XAI) research, highlighting the lack of consideration for cultural variations in human explanatory needs. It emphasizes the prevalence of Western-centric assumptions in XAI designs and user studies. The analysis reveals significant shortcomings in addressing diverse cultural perspectives and calls for increased awareness and inclusivity in XAI research.
The study explores the impact of internalist explanations on different cultures, pointing out how individualist and collectivist societies may prefer distinct types of explanations. It highlights the need for more externalist explanations to cater to diverse cultural preferences. Additionally, it discusses the limitations of WEIRD sampling practices and suggests strategies to enhance cultural diversity in XAI user studies.
Furthermore, the analysis uncovers hasty generalizations made in XAI user studies, where findings are extrapolated beyond their sample populations without sufficient evidence or justification. The content stresses the importance of acknowledging and addressing these biases to ensure more inclusive and culturally sensitive XAI developments.
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arxiv.org
Key Insights Distilled From
by Uwe Peters,M... at arxiv.org 03-12-2024
https://arxiv.org/pdf/2403.05579.pdfDeeper Inquiries