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Advances in computer science and data-analytic methods are driving a new era in mental health research and application. Artificial intelligence (AI) technologies hold the potential to enhance the assessment, diagnosis, and treatment of people experiencing mental health problems and to increase the reach and impact of mental health care. However, AI applications will not mitigate mental health disparities if they are built from historical data that reflect underlying social biases and inequities. AI models biased against sensitive classes could reinforce and even perpetuate existing inequities if these models create legacies that differentially impact who is diagnosed and treated, and how effectively. The current article reviews the health-equity implications of applying AI to mental health problems, outlines state-of-the-art methods for assessing and mitigating algorithmic bias, and presents a call to action to guide the development of fair-aware AI in psychological science. 

Background The COVID-19 health crisis has disproportionately impacted populations who have been historically marginalized in health care and public health, including low-income and racial and ethnic minority groups. Members of marginalized communities experience undue barriers to accessing health care through virtual care technologies, which have become the primary mode of ambulatory health care delivery during the COVID-19 pandemic. Insights generated during the COVID-19 pandemic can inform strategies to promote health equity in virtual care now and in the future. Objective The aim of this study is to generate insights arising from literature that was published in direct response to the widespread use of virtual care during the COVID-19 pandemic, and had a primary focus on providing recommendations for promoting health equity in the delivery of virtual care. Methods We conducted a narrative review of literature on health equity and virtual care during the COVID-19 pandemic published in 2020, describing strategies that have been proposed in the literature at three levels: (1) policy and government, (2) organizations and health systems, and (3) communities and patients. Results We highlight three strategies for promoting health equity through virtual care that have been underaddressed in this literature: (1) simplifying complex interfaces and workflows, (2) using supportive intermediaries, and (3) creating mechanisms through which marginalized community members can provide immediate input into the planning and delivery of virtual care. Conclusions We conclude by outlining three areas of work that are required to ensure that virtual care is employed in ways that are equity enhancing in a post–COVID-19 reality.