If you’ve been to a healthcare IT conference lately, you’ve seen a lively exchange of ideas regarding AI. Whether at larger conferences like HIMSS or RSNA, or smaller ones like Stanford Medicine X, World Medical Innovation Forum, Ai4 Healthcare, AIMed, just to name a few, AI presentations, panel discussions, and products are seemingly everywhere. There are countless news items every week describing how AI is aiding in the early detection of cancer, predicting the onset of sepsis, decreasing hospital readmissions, decreasing radiation doses in imaging, helping pinpoint personalized treatments, and participating in myriad other important use cases in healthcare. The CEO of our partner NVIDIA, Jensen Huang, has said that AI is “the single most powerful force of our time.”
Everyone knows that “AI” stands for “artificial intelligence.” Or does it?
Whereas the origins of the name “artificial intelligence” harken back to a 1956 conference held at Dartmouth College, the transition of “AI” from academic to colloquial language introduced some biases to our perception. No longer was AI a way to describe a research project based on the conjecture that “every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it.” Writers, filmmakers, and others started imagining scenarios in which AI was not a neutral term but rather something that could cause trepidation. The fear of humans being replaced by AI became a cultural trope. In healthcare, there have been dire predictions of AI replacing radiologists.
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There is a movement afoot to attempt to balance this perception. Words matter, and perhaps “artificial” doesn’t convey the most accurate meaning. We know from current research that AI paired with humans is a powerful combination, one that is synergistically better than its constituent parts. Therefore, calling AI “augmented intelligence” is a better way to describe what this technology can do for humanity. The benefits of AI in healthcare lie in augmenting the abilities of human providers, essentially giving people superpowers rather than replacing people. Given the shortage of healthcare providers around the world and the prevalence of burnout in healthcare, any technology that is proven to be safe and effective and that can help alleviate these concerns should be welcome—and shouldn’t be called “artificial.”
To learn how NetApp® and NVIDIA can help realize the promise of augmented intelligence in healthcare by bringing research into clinical practice, visit our page here.
Esteban joined NetApp to build a Healthcare AI practice leveraging our full portfolio to help create ML-based solutions that improve patient care, and reduce provider burnout. Esteban has been in the Healthcare IT industry for 15 years, having gone from a being storage geek at various startups to spending 12 years as a healthcare-storage geek at FUJIFILM Medical Systems. He's a visible participant in the AI-in-Healthcare conversation, speaking and writing at length on the subject. He is particularly interested in the translation of Machine Learning research into clinical practice, and the integration of AI tools into existing workflows. He is a competitive powerlifter in the USAPL federation so he will try to sneak early-morning training in wherever he's traveling.