Artificial Intelligence in Mental Health Research: Prospects and Pitfalls

Abstract

The world of artificial intelligence (AI) is producing many\npositive outcomes in health settings, including robots to\nsupport older people in aged care facilities (Corby &\nJennings, 2022; Padhan et al., 2023), precision diagnosis\nand treatment recommendations, and rule-based expert\nsystems to process or manage complex data sets (Davenport\n& Kalakota, 2019). For health-related researchers, AI can\nalso positively support the speed and accuracy of collecting\nand effectively analyzing large volumes of information to\nachieve improved healthcare outcomes and more targeted\ninterventions (Al Kuwaiti et al., 2023; Bohr &\nMemarzadeh, 2020).\nDespite its many benefits, some researchers, including\nmental health researchers, have expressed concerns about\nwhether AI should be encouraged or even permitted to support\nor drive research. These concerns include issues around\nsecurity, privacy, and ethical risks, leading to recommendations\nfor careful navigation and a cautious approach by the\nresearch community (Abulibdeh et al., 2024; Bouhouita-\nGuermech et al., 2023). This column considers how AI can\nbe used in health research, including the risks and how\nthese risks can be addressed.<p></p>

Ähnliche Arbeiten