This study addresses gender inequity in technological development envi- ronments, relying on the pillars of technology, artificial intelligence, and design. Based on concepts to characterize biases and their actual effects, such as the creation of digital gaps or voids for certain profiles in the digital parallel, the occurrence of gender algorithm biases, created from the data produced, is ob- served. The discussion is centered on the hypothesis that a lack of diversity could limit the understanding and consideration of different needs and perspec- tives, potentially enhancing the creation of unconscious biases in algorithms and exacerbating digital disparities. It is proposed that it may be possible to materialize ethical-social markers that artificial intelligence experts consider when developing algorithms, categorized by themes of technical structuring, UX aspects, AI principles, and personal experiences. The research focuses on the decision-maker, part of the project, their justifications, and mental models. Initially individually and later collectively, but maintaining a group identity by gender, in this case, female and male. Twenty interviews were conducted using the contextual inquiry method in which experts simulate constructing an algorithm for the dissemination of a job advertisement in technology. To deepen the discussion, two focus groups were held to evaluate whether the use of drivers based on Design concepts focused on inclusion could lead to increased engagement and depth of their analyses, promoting more conscious decision- making. In projects of significant social impact, this approach can contribute to more sensitive and inclusive development and help mitigate gender biases.