Algorithmically informed decision-making was an early focus in domains such as human factors, e.g., air traffic control and clinical contexts. As data collection has become more automated and computing capabilities have expanded, AI has become both a household term and a household item. Today, algorithmic decision-making tools are now used in every field; they are used to evaluate prisoners for parole, triage patients in emergency rooms, and predict where and when services might be needed.In the originating contexts of algorithmic decision-making, end-users would have been someone such as a doctor or an air traffic controller. In these contexts, the decision-maker (e.g., air traffic controller) and stakeholders of the decision (e.g., passengers) likely have high levels of consensus -safely flying from origin to destination -making decision-making more straightforward. Introduction 1.1 Problem Space 1.2 Design Methodology 1.3 Design Intervention Literature Review 2.1 Conceptual Framing Design designs back: reframing technical to sociotechnical No right to be wrong Trapped in the abstract -Limitations of mathematical fairness 2.