journal articles
AI MODELS, BIAS AND DATA SHARING EFFORTS TO TACKLE ALZHEIMER\'S DISEASE AND RELATED DEMENTIAS
Vijaya B. Kolachalama, Vijay Sureshkumar, Rhoda Au
J Prev Alz Dis 2026;1(13)
Artificial intelligence (AI), often seen as a harbinger of future innovation, also presents a dilemma: it can perpetuate existing human biases. However, this issue is not novel or unique to AI. Humans have long been the progenitors of biases, and AI, as a product of human creation, often mirrors these inherent tendencies. Here, we present a perspective on the development and use of AI, recognizing it as a tool influenced by human input and societal norms, rather than an autonomous entity. Modern efforts to technologically enabled data collection approaches and model development, particularly in the context of Alzheimer’s disease and related dementias, can potentially reduce bias in AI. We also highlight the importance of data sharing from existing legacy cohorts to help accelerate ongoing AI model development efforts for greater scientific good and clinical care.
CITATION:
Vijaya B. Kolachalama ; Vijay Sureshkumar ; Rhoda Au (2025): AI models, bias and data sharing efforts to tackle Alzheimer's disease and related dementias. The Journal of Prevention of Alzheimer’s Disease (JPAD). https://doi.org/10.1016/j.tjpad.2025.100400