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Web search engines influence perception of social reality by filtering andranking information. However, their outputs are often subjected to bias thatcan lead to skewed representation of subjects such as professional occupationsor gender. In our paper, we use a mixed-method approach to investigate presenceof race and gender bias in representation of artificial intelligence (AI) inimage search results coming from six different search engines. Our findingsshow that search engines prioritize anthropomorphic images of AI that portrayit as white, whereas non-white images of AI are present only in non-Westernsearch engines. By contrast, gender representation of AI is more diverse andless skewed towards a specific gender that can be attributed to higherawareness about gender bias in search outputs. Our observations indicate boththe the need and the possibility for addressing bias in representation ofsocietally relevant subjects, such as technological innovation, and emphasizethe importance of designing new approaches for detecting bias in informationretrieval systems.

Detecting race and gender bias in visual representation of AI on web search engines