We all know that racist algorithms can harm people across many sectors, and healthcare is no exception. In a powerful commentary published in CellPress, Ferryman et al. argue that racism must be treated as a core ethical issue in healthcare AI, not merely a flaw to be patched after deployment.
To address this, anti-racist practices must be integrated throughout the entire AI lifecycle. Developers, ethicists, and institutions all have a role to play in recognising and dismantling the systemic and individual racism that shapes biased data and algorithms. If you are a long-time reader of this site, you know the consequences of these biases are not abstract; they directly influence diagnoses, treatment decisions, and health outcomes for racially marginalised communities.
Ferryman et al. propose solutions such as centring the voices of impacted communities, critically examining the assumptions that shape AI design, and rejecting the illusion of “colourblind” or objective technology. You could argue that the field of ethical AI has been “whitewashed”, often only focusing on issues such as environmental impact or gender inequality while not fully acknowledging racism. We must adopt an intersectional approach to build AI that genuinely serves everyone, recognising racism as a foundational issue, not a miscellaneous add-on.
Or, as Ferryman et al. state it best:
Considerations of racism should be central to health AI ethics because racism is an injustice, and justice is a central issue in moral philosophy overall and in bioethics specifically.
See: Racism is an ethical issue for healthcare artificial intelligence at Cell Reports Medicine.
Image: Elise Racine / No Abnormalities / Licenced by CC-BY 4.0