University of Houston joins national consortium to advance health equity and researcher diversity

The University of Houston has joined a national initiative to increase the diversity of artificial intelligence researchers to make sure the technology of machine learning benefits everyone. With a new $50 million grant from the National Institutes of Health, the University of North Texas Health Science Center will lead the coordinating center of the AIM-AHEAD program (Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity). It will bring together experts in community engagement, artificial intelligence/machine learning (AI/ML), health equity research, data science training and data infrastructure.  

“Beyond health care, AI has been used in areas from facial recognition to self-driving cars and beyond, but there is an extreme lack of diversity among the developers of AI/ML tools. Many studies have shown that flawed AI systems and algorithms perpetuate gender and racial biases and have resulted in untoward outcomes,” said Bettina Beech, chief population health officer at the University of Houston and newly named AIM-AHEAD coordinating center team member. Other universities comprising the consortium’s leadership core include University of Colorado-Anschutz Medical Center in Aurora; University of California, Los Angeles; Meharry Medical College in Nashville; Morehouse School of Medicine in Atlanta; Johns Hopkins University and Vanderbilt University Medical Center.  

“This network will be foundational to achieving the goals of the AIM-AHEAD program, which include providing more inclusive data for health disparities research, and enhancing the diversity of AI/ML leadership,” said NIH Associate Director for Data Science Susan Gregurick.   

According to the NIH, “AIM-AHEAD was created to close the gaps in the AI/ML field, which currently lacks diversity in its researchers and in data, including electronic health records (EHRs). These gaps pose a risk of creating and continuing harmful biases in how AI/ML is used, how algorithms are developed and trained, and how findings are interpreted. Critically, these gaps can lead to continued health disparities and inequities for underrepresented communities.” 

While undisputedly groundbreaking technology, AI, which mimics human decision making through its choice of algorithms, has brought with it human bias baked into the system. After all, humans program the system.  

So, while on a daily basis these algorithms decide what you will see next in your online newsfeed, they also make more consequential decisions like whether you qualify for a loan or if you will get the interview for that new job you applied for. Those decisions can be rife with bias. 

“AI solutions need to be implemented in a responsible manner and are now guided by AI ethical FAIR (findable, accessible, interoperable, reusable) principles,” said Beech, who believes the NIH grant underscores the need for deliberate steps to avoid unintended bias.  

Beech oversees the integration of population health education and research across the University of Houston. She understands the relevance of AI equity for population health, too.  

“The AIM-AHEAD project directly connects with the University of Houston’s plan to train and diversify the future workforce in population health, increase the use of digital tools for chronic disease self-management, and to advance population health research,” said Beech.  

The University of Houston, including its Computational Biomedicine Lab and College of Medicine, recently obtained another NIH grant to develop an online training program of AI/ML FAIR principles for early career faculty from diverse groups underrepresented in biomedical science.