Why Should You Care About the Definition of ‘AI'?

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.