A Look at AI

From the Gartner Blog:

When AI is Really AGF (Artificial Gut Feel)     By Anthony J. Bradley | September 20, 2022

Human Interviewer: “Do you prefer dogs or cats?”

Randy the Robot, “Yes, I’m very familiar with their pixel patterns.”

In the words of former U.S. Secretary of Defense, Donald Rumsfeld, “There are known knowns, known unknowns and unknown unknowns.” He positioned unknown-unknowns as the most challenging situation. For AI, it is an impossible situation. AI operates best in the known-known situation. In other words, it is best to know exactly what you are looking to find. 

Known-Knowns is Where AI Accuracy is Most Accurate

AI is taking the field of radiology by storm. In 2018, Stanford created the AI CheXNeXt algorithm trained with over 100,000 chest X-rays to identify 14 pathologies. For 10 of the diseases CheXNeXt performed on par with radiologists. On one it outperformed radiologists. With three maladies the radiologists outperformed CheXNeXt. This success is only possible because we know what normal and abnormal chest X-rays look like for these pathologies. Actually, the known-known scenario applies to a large number of AI computer vision detection scenarios from recognizing defects on a manufacturing line to identifying products in a shoppers grocery cart and even diagnosing illnesses by analyzing facial features. Computer vision is one of the fastest growing sectors of AI because we know what we are looking for and deep learning is getting better and better at image recognition.   ... (more at link)