RESUMEN
When integrating AI tools in healthcare settings, complex interactions between technologies and primary users are not always fully understood or visible. This deficient and ambiguous understanding hampers attempts by healthcare organizations to adopt AI/ML, and it also creates new challenges for researchers to identify opportunities for simplifying adoption and developing best practices for the use of AI-based solutions. Our study fills this gap by documenting the process of designing, building, and maintaining an AI solution called SepsisWatch at Duke University Health System. We conducted 20 interviews with the team of engineers and scientists that led the multi-year effort to build the tool, integrate it into practice, and maintain the solution. This "Algorithm Journey Map" enumerates all social and technical activities throughout the AI solution's procurement, development, integration, and full lifecycle management. In addition to mapping the "who?" and "what?" of the adoption of the AI tool, we also show several 'lessons learned' throughout the algorithm journey maps including modeling assumptions, stakeholder inclusion, and organizational structure. In doing so, we identify generalizable insights about how to recognize and navigate barriers to AI/ML adoption in healthcare settings. We expect that this effort will further the development of best practices for operationalizing and sustaining ethical principles-in algorithmic systems.
RESUMEN
The COVID-19 pandemic and crisis around racial injustice have generated compounded macro-level stressors for American society that negatively impact mental health and wellbeing. We contribute to understanding the impact of these crises by examining the process of developing social resilience, which we conceptualize as a temporally-embedded process of sense-making through which actors activate a sense of dignity, agency, and hope in the face of challenges to sustain wellbeing based on available resources. We interviewed 80 college students (aged 18-23) living in the American Northeast and Midwest before (September 2019-February 2020) and during (June-July 2020) the pandemic to analyze how they make sense of crises, respond to challenges, and project themselves into the future. We compare "privileged" upper-middle class youth who have families with more resources to buffer themselves against growing uncertainty, with "less privileged" youth from lower-middle and working class families. Efforts to achieve a sense of dignity, agency, and hope amidst widespread uncertainty illuminate opportunities and constraints in the process of building social resilience, which take different temporal forms across the two class groups given their experiences and resources.