Newswise — LOS ANGELES (June 27, 2024) -- A team of investigators in Cedars-Sinai’s Department of Computational Biomedicine is spotlighting the importance of diversity in science, technology, engineering and math (STEM) education and artificial intelligence (AI) research.
A recent opinion column published in the Cell Press journal Patterns lays out what the investigators see as the challenges and opportunities for those who identify as lesbian, gay, bisexual, transgender and queer or questioning (LGBTQ+) to increase their representation in these fields. The column emphasizes the importance of addressing the biases and erasure of gender and sexual diversity in data and computational models.
“Our team works to improve patients’ lives by using computers, computing technologies and data resources; insights from a diverse community are invaluable in helping us do that,” said Jason Moore, PhD, professor and chair of the Department of Computational Biomedicine and an investigator who helped author the opinion article.
Moore said it’s not only a matter of tolerance and acceptance: “LGBTQ+ inclusion is necessary to enhance scientific problem-solving, generate more equitable knowledge and address the health disparities and needs of diverse communities. Not doing so can impact computer models and all patients, potentially leading to harmful conclusions.”
The column’s authors propose strategies and resources for LGBTQ+ inclusion, such as improving data collection and model evaluation, revising policies, creating gender- and sexual diversity-inclusive curricula, and fostering allyship and support networks. They provide examples of conferences, organizations and programs that promote LGBTQ+ participation and leadership in STEM and AI, and they acknowledge the contributions of LGBTQ+ scientists in the history and development of STEM and AI.
To learn more about the team’s perspectives, the Cedars-Sinai Newsroom recently talked with two of the paper’s authors—Pei-Chen Peng, PhD, an assistant professor in the Department of Computational Biomedicine, and Ryan Urbanowicz, PhD, a research assistant professor and director of Cedars-Sinai’s National AI Campus, a U.S.-wide AI and machine learning collaborative and project-based initiative.
Why was it important to bring this topic to the forefront?
Urbanowicz: Considering the ever-increasing use of AI in clinical care and research, it seemed timely to encourage open discussions about the unique challenges of the LGBTQ+ community and how they overlap with STEM and AI, both from the perspective of encouraging and supporting LGBTQ+ scientific trainees, and in how to tackle the challenges and considerations of LGBTQ+ in STEM and AI research.
Peng: When the Patterns journal invited us to submit an opinion article related to the experiences of queer scientists for its June issue, we saw this as a great opportunity to further highlight the experiences of the LGBTQ+ community and to advocate for queer scientists. As we wrote in the article, LGBTQ+ scientists are underrepresented in the biomedical AI and STEM community, which can cost the scientific community great minds and stifle innovation.
Why is it critical to have LGBTQ+ inclusion in STEM education?
Peng: The awareness of gender and sex diversity in STEM education inevitably influences clinical research methods. Inclusion of LGBTQ+ ensures that the STEM community is reflective of the broader society and reduces biases when we do biomedical and AI research.
Urbanowicz: I think that fostering a diverse community of STEM trainees ensures a more diverse set of perspectives and ideas, essential to our research community’s ability to do its best work as a whole.
Is there an area of opportunity that you are particularly passionate about?
Urbanowicz: Personally, I want to do my part as an LGBTQ+ scientist to be a visible and accessible example/role model to other LGBTQ+ trainees in STEM and AI research. Also, I want to bring awareness to the current limitations of AI, specifically with regard to potential disparity.
Peng: I’m excited about the potential for positive changes. We’ve highlighted the importance of inclusivity and representation, addressing how diverse perspectives can lead to more innovative and equitable scientific advancements, and we encourage all scientists to take initiative in advancing our understanding of LGBTQ+ health issues. I’m also proud that we were able to provide a catalog of existing educational and professional resources that the community can refer to as needed. For example, trainees and researchers will know which conferences are inclusive and promote diversity, and they can choose venues where they can present their research findings confidently.
What are some ways that AI models can ensure health equity for LGBTQ+ people?
Urbanowicz: When it comes to both medical and AI research, awareness of what makes the LGBTQ+ community unique and taking these considerations into account when it comes to data collection, study design and research resources should all improve overall health equity.
Based on the opportunities identified in your article, how can Cedars-Sinai be more inclusive?
Peng: Our National AI Campus is one area that comes to mind. It’s a training program that aims to make AI accessible to a diverse community with training experiences that focus on biomedical projects. Beyond promoting participants’ diversity, the program also could address LGBTQ+ issues by developing or inviting AI and/or machine learning projects that tackle LGBTQ+ health and analytical challenges.
Urbanowicz: I agree with Dr. Peng. National AI Campus is founded on principles of inclusion and accessibility for all students interested in learning about machine learning and artificial intelligence. In the future, in addition to introducing projects that tackle LGBTQ+ issues, we can encourage more LGBTQ+ participants to get involved and highlight the importance of these issues to trainees at large.
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