“Because human beings have a hand in all stages of the construction of AI systems, fairness-aware design must take precautions across the AI project workflow to prevent bias from having a discriminatory influence. This requires cross-stakeholder to understand the desired outcomes and appropraite measures, alongside consideration of any biases throughout this problem formulation that may lead to discriminatory or otherwise undesirable outcomes. These considerations should carry through into data collection, processing (and contextualisation), feature engineering, model building, and potential uses of models.