Towards an ethics in intelligent algorithms for female entrepreneurship: a systematic review of the propagation of social biases to digital media

How do cognitive biases and social influence shape our decisions and perceptions, and how do they propagate through societal norms and digital ecosystems? How do these factors affect the perception and recognition of women in entrepreneurship and leadership? The novelty of this research lies in its valuable guidance for evaluating the literature and advancing the knowledge base on the conceptual and social structures, as well as the propagation mechanisms of biases, to later understand how these dynamics specifically manifest themselves in female entrepreneurship and business leadership. This study aims to conduct a systematic review of the literature to establish a research framework and identify future research directions regarding the existence and dissemination of biases in female leadership and entrepreneurship, both in society and in different internet media. Through the selection and analysis of 462 articles published between 2006 and 2024 in the Scopus and Web of Science databases, using a systematic review approach, the study focuses on research related to cognitive biases. Articles were selected based on their relevance to the existence, influence, impact, and persistence of these biases, particularly in decision-making and their transmission to society and digital ecosystems. A strategic classification framework was then built using machine learning tools and TCM approach to highlight the influence of biases in various societal contexts, including how they propagate into intelligent algorithms. The presented framework not only provides an initial understanding of entrenched biases in society and their spread to digital media but also identifies gaps in existing research, highlighting opportunities and directions for future research. In addition, the study presents key insights for the development of algorithmic ethics, aimed at mitigating biases and promoting more equitable decisions in automated systems, considering that contemporary society bases its decisions on information provided by these intelligent algorithms available on the internet.