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Paper short abstract

As AI enters medical contexts, media discussions are polarized between risks and opportunities. However, real-life implementations of AI shape which potentials are realized. This study focuses on AI bias, examining how it is encountered, discussed, and addressed in the Swedish healthcare context.

Paper long abstract

Public discussions frequently frame medical AI applications as outperforming human expertise (Bunz & Braghieri, 2022). At the same time, critical scholars question the narrative of ‘AI for social good’ (Radhakrishnan, 2021) and warn about AI exacerbating existing problems of unjust healthcare access and outcomes. Both dystopian and utopian academic and media narratives stand in contrast to ‘epistemic modesty’ displayed by those who encounter the technology’s potential and limitations in their own practice (Samuel et al., 2021).

In this paper, I focus on AI bias in the medical context as a polarizing topic: some argue AI could revolutionize medicine and address existing inequalities, while others warn it could disastrously exacerbate existing biases. In the Nordic countries, proponents of rapid AI adoption suggest that Nordic welfare states with advanced digitalization and a strong focus on equality could take a leading role in developing AI systems that balance economic incentives and social justice.

Focusing on Swedish AI projects that have been implemented in medical practice, I examine how critical discussions of AI risk and AI bias are taken up, and whether theoretical discussions about marginalized bodies and promises of equality as a Nordic strength travel into practice. Interviewing medical and technical staff involved with implementing AI projects, I investigate to what extent and what types of biases are encountered, discussed, and addressed in their work, and how practitioners make sense of marginalized bodies and discrimination in medicine in relation to the implementation of AI tools.