Barriers to Adoption of AI

Here are few of the barriers to adoptions of Artificial Intelligence

1. Government Regulations

The Current FDA regulations designed to protect humans from harm by machines rate AI as a class 3 risk to humans. This will make it difficult to change laws to allow AI increased direct Interaction with patients.

2. Accountability 

There are laws in place to protect humans working in the medical field in the case they make a mistake, but what happens when AI makes a mistake?  These mistakes could be due to a missed update or incorrect data.  In these cases, it is currently unclear who would be at fault: The developer of the machine or the hospital using the machine? 



3. Data Integrity 

Data integrity is the accuracy and completeness of the collected data, and data is what drives AI’s capacity for Machine Learning. The data that influences ML must have a wide variety of different classes, sources, and types. To be useful it must also be representative of relevant populations, as there are different variables that would be overlooked if the samples are not inclusive. 


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