Incorporating gender and intersectionality in Artificial Intelligence (AI) models and algorithms

Incorporating gender and intersectionality in Artificial Intelligence (AI) models and algorithms Incorporating gender and intersectionality in Artificial Intelligence (AI) models and algorithms Risks of harm from the multiple and overlapping crises related to COVID-19 vary based upon one’s gender, age (children, adolescents and elderly), level of education, occupation, geographical location (urban. [...] Intersectionality Intersectionality is a strategy to ensure The Checklist is not an exhaustive list of transformative change through understanding and considerations but is meant to be a starting point highlighting the realities and diversity in the lives of to ensure gender and intersectionality are girls, boys, women and men under different social embedded in the research process. [...] The aim is, among others, to capture difference within and among them due to such differing needs and experiences of target groups, social markers as age, race, class, religion, avoid assumptions such as the homogeneity of a geographical location, sexual orientation and the certain group of people such as women in given like. [...] This Checklist is a guide to ensure stakeholders, including experts, developers and analysts, ethics review board, get adequate information to incorporate gender and intersectionality across the How to use the checklist data life cycle, including research design, data Answer questions in detail as much as collection, processing, analysis, dissemination, and possible. [...] What additional data sources/types will help us capture differing experiences of people under different circumstances? What assumptions are we making with regards to the data sources? Do these data sources and data collection method/s help us access adequate information on gender and other social determinants of gender? (collect relevant social determinants of health data by male and female (e.g.