How to set realistic expectations for AI

#AI isn't always ready for prime time–and companies shouldn't expect it to be. Here are five key points targeting what's currently feasible and what isn't. [Read More]

Summary… * Machine-Made


The most important lesson to be learned from Watson or any other #AI technology that is being trialed in business right now is that #AI isn't perfect.
Analytics and algorithms were continuously re-run and refined until the #AI diagnoses came within 99.9% accuracy of what a highly skilled medical doctor would diagnose.
If you're carrying forward these assumptions into an #AI system, your system will also be biased.
This is an area of anomaly where #AI logic often falls short—and a reason why you still need human practitioners working alongside #AI tools.
SubscribeYour takeHave you been tasked with running an #AI project?

Opinion… * Man-Made


Let’s get rid of the overhyped “Artificial Intelligence” term; especially with a history of overpromising and underdelivering. Shouldn’t the current implementations be better labeled with the word “Automation”? #AI #Trend

Source: Techrepublic