In what seems like the blink of an eye, mentions of artificial intelligence have become ubiquitous in the healthcare industry.
From deep learning algorithms that can read CT scans faster than humans to natural language processing (NLP) that can comb through unstructured data in electronic health records (EHRs), the applications for AI in healthcare seem endless.
But like any technology at the peak of its hype curve, artificial intelligence faces criticism from its skeptics alongside enthusiasm from die-hard evangelists.
Despite its potential to unlock new insights and streamline the way providers and patients interact with healthcare data, AI may bring not inconsiderable threats of privacy problems, ethics concerns, and medical errors.
Balancing the risks and rewards of AI in healthcare will require collaborative effort from technology developers, regulators, end-users, consumers – and maybe even philosophy majors.
The first step will be addressing the highly divisive discussion points commonly raised when considering the adoption of some of the most complex technologies the healthcare world has to offer.
Image Credit: Alias Studio Sydney
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