AI in Pacific healthcare: 'Significant work' needed, says professor

Significant work remains to ensure artificial intelligence systems serve Māori and Pacific peoples effectively and equitably, according to Professor Robyn Whittaker, co-director of the University of Auckland's TRANSFORM Research Centre. Speaking at the Te Poutoko Ora a Kiwa Research Symposium, Whittaker highlighted a critical issue: many AI systems used worldwide are trained on datasets that lack adequate representation of Māori and Pacific populations.

"It is very unlikely these tools have been properly tested on Māori and Pacific communities," Whittaker stated. "There is still significant work needed to ensure they perform well for our people." Her team is actively evaluating AI tools with a focus on safety, ethics, equity, and incorporating Pacific perspectives. She noted that while predictive algorithms were used during the COVID-19 pandemic to identify at-risk Pacific patients, such tools require high-quality, locally relevant data to function accurately.

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It is very unlikely these tools have been properly tested on Māori and Pacific communities. There is still significant work needed to ensure they perform well for our people.

Co-director of Te Poutoko Ora a Kiwa, Professor Sir Collin Tukuitonga, stressed that new technologies should not exacerbate existing health inequities but rather support better, fairer health outcomes across the Pacific. A 2023 report to the New Zealand government identified health inequities affecting Māori and Pasifika, including those related to AI. The report indicated that New Zealand's health system has historically underperformed for these groups, and human error can lead to unequal outcomes.

The report suggested AI tools might outperform clinicians in identifying rare conditions affecting disadvantaged groups, provided the AI is developed and fine-tuned on diverse data reflecting group-specific disease prevalence. However, poor data quality has been identified as a contributor to health inequalities. For Pacific peoples, health is understood holistically, encompassing physical, mental, spiritual, social, and economic well-being. Ensuring AI implementation respects these cultural values is paramount.

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We need to work together to ensure AI is implemented in ways that are safe, ethical, and equitable for all. We are particularly concerned about bias, data sovereignty, and the control of indigenous data.