Abstract
The news correspondents obtained a quote from the research from the Grenoble Sch ool of Management, "The lack of transparency related to AI algorithms and their categorization methods make practical insights into effective management of the risks associated to their utilization of crucial importance. We address these is sues through two field tests aimed at mitigating biases in online science, techn ology, engineering, and mathematics (STEM) education-related ads targeting teena gers. We conducted online ad campaigns involving gender-unspecific, women-specif ic, and gender-neutral ads targeted at young social network users. Our findings show that inclusion in the ad of a gender-oriented message tends to alleviate al gorithmic gender bias but also reduced overall ad visibility." According to the news reporters, the research concluded: "Our research shows als o that text length has a significant impact on ad visibility, and that gender-or iented messages influence the display of the ad based on gender." This research has been peer-reviewed.
NETL
NSTL