Work

AI models, bias and data sharing efforts to tackle Alzheimer's disease and related dementias

Year: 2025

Type: article

Abstract: 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.

Source: The Journal of Prevention of Alzheimer s Disease

DOI: 10.1016/j.tjpad.2025.100400

Authors: Vijaya B. Kolachalama, Vijay Sureshkumar, Rhoda Au

Institutions: Boston University, Gates Ventures, Framingham Heart Study

Language: English

Topic: Ethics and Social Impacts of AI

Subfield: Safety Research

Field: Social Sciences

Domain: Social Sciences

Open Access status: gold

Estimated APC paid: $4,060

Funders: Gates Ventures, American Heart Association, National Institutes of Health, National Institute on Aging