Search engines like Google have become major information gatekeepers that use artificial intelligence (AI) to determine who and what voters find when searching for political information. This article proposes and tests a framework of algorithmic representation of minoritized groups in a series of four studies. First, two algorithm audits of political image searches delineate how search engines reflect and uphold structural inequalities by under- and misrepresenting women and non-white politicians. Second, two online experiments show that these biases in algorithmic representation in turn distort perceptions of the political reality and actively reinforce a white and masculinized view of politics. Together, the results have substantive implications for the scientific understanding of how AI technology amplifies biases in political perceptions and decision-making. The article contributes to ongoing public debates and cross-disciplinary research on algorithmic fairness and injustice.

翻译：像谷歌这样的搜索引擎已成为主要的信息守门人，它们利用人工智能（AI）决定选民在搜索政治信息时能找到谁以及什么信息。本文通过四项研究提出并测试了少数群体算法表征的框架。首先，两项对政治图像搜索的算法审计揭示了搜索引擎如何通过低估和歪曲女性和非白人政治家的形象来反映并维持结构性不平等。其次，两项在线实验表明，算法表征中的这些偏见进而扭曲了人们对政治现实的认知，并积极强化了政治的白人化和男性化视角。这些结果共同对科学理解人工智能技术如何放大政治认知与决策中的偏见具有实质性意义。本文为关于算法公平与不公的持续公共辩论和跨学科研究做出了贡献。