Browsing by Author "Stinson, Katie"
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Item Community perspectives on AI/ML and health equity: AIM-AHEAD nationwide stakeholder listening sessions(PLOS, 2023-06-30) Vishwanatha, Jamboor K.; Christian, Allison; Sambamoorthi, Usha; Thompson, Erika L.; Stinson, Katie; Syed, Toufeeq A.Artificial intelligence and machine learning (AI/ML) tools have the potential to improve health equity. However, many historically underrepresented communities have not been engaged in AI/ML training, research, and infrastructure development. Therefore, AIM-AHEAD (Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity) seeks to increase participation and engagement of researchers and communities through mutually beneficial partnerships. The purpose of this paper is to summarize feedback from listening sessions conducted by the AIM-AHEAD Coordinating Center in February 2022, titled the "AIM-AHEAD Community Building Convention (ACBC)." A total of six listening sessions were held over three days. A total of 977 people registered with AIM-AHEAD to attend ACBC and 557 individuals attended the listening sessions across stakeholder groups. Facilitators led the conversation based on a series of guiding questions, and responses were captured through voice and chat via the Slido platform. A professional third-party provider transcribed the audio. Qualitative analysis included data from transcripts and chat logs. Thematic analysis was then used to identify common and unique themes across all transcripts. Six main themes arose from the sessions. Attendees felt that storytelling would be a powerful tool in communicating the impact of AI/ML in promoting health equity, trust building is vital and can be fostered through existing trusted relationships, and diverse communities should be involved every step of the way. Attendees shared a wealth of information that will guide AIM-AHEAD's future activities. The sessions highlighted the need for researchers to translate AI/ML concepts into vignettes that are digestible to the larger public, the importance of diversity, and how open-science platforms can be used to encourage multi-disciplinary collaboration. While the sessions confirmed some of the existing barriers in applying AI/ML for health equity, they also offered new insights that were captured in the six themes.Item Implementation of an unconscious bias course for the National Research Mentoring Network(BioMed Central Ltd., 2022-05-21) Javier, Damaris; Solis, Linda Grace; Paul, Mirabelle Fernandes; Thompson, Erika L.; Maynard, Grace; Latif, Zainab; Stinson, Katie; Ahmed, Toufeeq; Vishwanatha, Jamboor K.Purpose: Increased awareness and mitigation of one's unconscious bias is a critical strategy in diversifying the Science, Technology, Engineering, Mathematics, and Medicine (STEMM) disciplines and workforce. Greater management of unconscious bias can enhance diverse recruitment, persistence, retention, and engagement of trainees. The purpose of this study was to describe the implementation of an asynchronous course on unconscious bias for people in STEMM. Specifically, we explored who engaged with the course and reflections from participation. Method: A five-part, asynchronous Unconscious Bias Course was developed and was hosted on a national mentoring platform starting in July 2020. To examine course engagement, we assessed the demographics of course participants and completion. Participant responses to reflection questions after each module were also synthesized using qualitative methods. Results: Overall, 977 people registered for the course and 42% completed all modules. In the reflection responses, participants reflected on their unconscious biases in their lived experiences and how it relates to actions, judgements, external factors, stereotypes, and un-intentionality. Participants also reflected on microaggressions, their impact on the recipients and others, and the relationship between microaggressions and unconscious bias. Participants reported four key strategies used by allies against unconscious bias: immediately acting (83%), reflection (46%), improving the organizational culture (30%), and individual-level ally-ship (44%). Strategies for self-awareness included: reflection, pausing/breathing, and self-observation. Conclusion: The assessment of the Unconscious Bias Course implementation revealed the course reached a wide cross-section of people in STEMM and demonstrated that participants were able to reflect on the underpinnings of the course. This course, and its suite of offerings, support a nationwide effort to mitigate bias and prepare individuals to be culturally competent in a diverse society in order to foster a STEMM environment that caters to individuals' success and diversification of these fields.