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AI in health raises privacy concerns
AI in health raises privacy concerns
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Health providers and consumers need to consider questions of privacy and confidentiality before using artificial intelligence to assist in healthcare, an Otago law expert says.
Associate professor of law Colin Gavaghan is part of a three-year multi-disciplinary project funded by the Law Foundation looking at applications of AI in New Zealand that raise legal, ethical and social questions.
AI has big implications for medicine, as tasks that are currently done by a human doctor or nurse could be done by a machine.
For example, Babylon Health recently unveiled AI technology that it claims can get medical examination scores equivalent to those of human doctors and make accurate diagnoses.
Health services such as this can be delivered by companies outside New Zealand, which means health data would be sent offshore.
Gavaghan says foreign health providers are not subject to New Zealand law, and confidentiality and privacy issues arise when there is a lack of guarantee about what will happen to information when it leaves the country.
Health providers also need to think through what is lost when jobs are taken over by machines. Patients may go to their GP about a certain complaint, but in fact want to talk about something else in person that may never be revealed to an AI robot.
“These things will only come out in context when trust builds up, and I’m interested in to what extent that will be lost as we rely more and more on automative services,” he says.
Gavaghan says there is a lack of understanding about who is doing what in the AI space and there is a need to take stock and potentially create a standards organisation.
A central body with oversight of technological developments in the AI space could be useful as a way of vetting overseas companies or products for accuracy, transparency, privacy and confidentiality concerns, he says.
Otago university associate professor department of primary health care and general practice Angela Ballantyne says health is a highly regulated sector and this may present a barrier to the introduction of AI.
“The risk of underutilising AI is that we continue to rely on less effective processes for diagnosing disease and allocating resources, and we therefore have avoidable levels of error in the system. This translates to greater patient suffering,” she says.
“While there is lots of hype about AI being transformational in healthcare, the reality at the moment is that diagnostics is where we are seeing the most practical applications of AI.”
Challenges yet to be overcome include the risk of AI perpetuating existing inequalities, as the datasets used to train AI track human behaviour and so reflect the biases and inequalities already in the health system.
Also, AI relies on access to huge datasets, which raises questions around patient consent and trust in the companies developing AI as well as the agencies controlling access to the health data, Ballantyne says.