Accounting for the Unaccounted in AI and Care: Bringing Young Carers into the AI Realm
Journal of Medical Internet Research ·
This position paper introduces young carers as a key stakeholder within AI. Research on AI for health care endeavors to assist and optimize current health care services; yet, young carers have been neglected thus far. Accordingly, this paper situates itself at the intersection of young people under the age of 18 years old providing care (referred to as young carers) and AI research. Through a socio-legal and public health lens, this paper (1) situates young carers to showcase (2) why they must be accounted for in AI systems, and (3) how AI researchers can do so. This lens highlights the difficulties young carers tend to face at present and how AI systems can alleviate those—rather than reproduce them. Accordingly, we rely on the norms-in-the-loop framework to demonstrate why the AI community must account for young carers in AI systems. We first synthesize research on both young carers and AI research on contextual, legal, and social norms to then propose practical ways to do so through design, datasets, and in situ personalization. Overall, this paper offers a critical foundation for AI researchers to include young carers in the development of AI systems at various levels: from institutions to care receivers, and to young carers themselves. Ultimately, this paper posits that young carers must be identified and supported, which demands their inclusion in AI research to understand how best to do so. Accounting for young carers will allow for their unique perspectives to be reflected in AI systems and help them thrive beyond their care responsibilities.
This position paper introduces young carers as a key stakeholder within AI. Research on AI for health care endeavors to assist and optimize current health care services; yet, young carers have been neglected thus far. Accordingly, this paper situates itself at the intersection of young people under the age of 18 years old providing care (referred to as young carers) and AI research. Through a socio-legal and public health lens, this paper (1) situates young carers to showcase (2) why they must be accounted for in AI systems, and (3) how AI researchers can do so. This lens highlights the difficulties young carers tend to face at present and how AI systems can alleviate those—rather than reproduce them. Accordingly, we rely on the norms-in-the-loop framework to demonstrate why the AI community must account for young carers in AI systems. We first synthesize research on both young carers and AI research on contextual, legal, and social norms to then propose practical ways to do so through design, datasets, and in situ personalization. Overall, this paper offers a critical foundation for AI researchers to include young carers in the development of AI systems at various levels: from institutions to care receivers, and to young carers themselves. Ultimately, this paper posits that young carers must be identified and supported, which demands their inclusion in AI research to understand how best to do so. Accounting for young carers will allow for their unique perspectives to be reflected in AI systems and help them thrive beyond their care responsibilities.