Security News > 2021 > July > How to strike the balance between privacy and personalization in healthcare and beyond

When it comes to technologies fueled by data, such as artificial intelligence, it's even harder to strike the balance between equitable access and inherent risk.

They've figured out how to do this without sharing their valuable data.

Domain experts, like doctors and other professionals, can leverage the pretrained models on their organization's data to localize them, reflecting their own patient populations, and they can do it without the need for a data scientist or compromising their most valuable asset: their data.

Beyond privacy, localizing AI and NLP models not only mitigates risks with storing and accessing data, but it also empowers providers to deliver better care.

How we responsibly handle this data has to be a big part of the conversation - and making sure it stays in the right hands is a good first step.

While strict regulations in healthcare are nothing new, as we hear about more high-profile data breaches and ransomware attacks, all industries are going to have to rethink their data privacy hygiene.

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