Reinvention mediates impacts of skin tone bias in algorithms: implications for technology diffusion
两项研究考察了图像识别算法中的肤色偏见如何影响用户的采用和使用，发现深肤色用户更可能遇到偏见，但反而更广泛地使用技术，并通过重塑行为来适应偏见。
Abstract Two studies examine how skin tone bias in image recognition algorithms impacts users’ adoption and usage of image recognition technology. We employed a diffusion of innovations framework to explore perceptions of compatibility, complexity, observability, relative advantage, and reinvention to determine their influence on participants' utilization of image recognition algorithms. Despite being more likely to encounter algorithm bias, individuals with darker skin tones perceived image recognition algorithms as having greater levels of compatibility and relative advantage, being more observable, and less complex and thus used them more extensively compared to those with lighter skin tones. Individuals with darker skin tones also displayed higher levels of reinvention behaviors, suggesting a potential adaptive response to counteract algorithm biases.