Despite no systemic age gap in the workforce, online databases and AI platforms depict women as younger than men across professions, according to a study conducted at UC Berkeley and published in Nature last week. This bias is clearer in jobs with higher statuses and salaries. Gender and age bias in training datasets for large language models, or LLMs, such as ChatGPT 4.5 could disadvantage older female candidates in AI-screened hiring processes, according to the study. Assistant Professor Solène Delecourt from UC Berkeley’s Haas School of Business co-authored the paper with Douglas Guilbeault from Stanford’s Graduate School of Business and Bhargav Srinivasa Desikan from the Oxford Internet Institute. Read more through the link in bio. ✍️: Syontoni Hattori-Chatterjee 📸: Courtesy of Haas photographer . . . #ucberkeley #dailycal #berkeley #chatgpt #haasschoolofbusiness #googleimages