Data privacy has been a growing requirement ever since the internet age began. So much personal information is flying around through computer networks. Protecting it has become a mandate.
By the end of 2024, 75% of the world’s population will have their personal data protected. It will fall under one or more privacy regulations. Privacy requirements hit all sized companies.
AI is running many of the algorithms responsible for keeping data protected. But what happens when there is a problem with the AI? This is the question that AI governance is working to address.
Consumer Privacy UX
A trend that we’ve seen over the last several months is putting more privacy power into the consumer’s hands. Consumer privacy portals tell people what data is being collected, how it is collected, and what is done with it.
Increased Scrutiny of Remote
Monitoring remote employees opens a can of worms when it comes to data
Organizations need to ensure that they aren’t encroaching on the rights
of their staff.
Increasingly, organizations look at where their cloud data is being stored
because the location governs the privacy rules and regulations that it may fall under.
Privacy-Enhancing Computation (PEC)
Data privacy by design is a fairly new term. Using privacy-enhancing
computation is a way that AI is helping cybersecurity.
By using PEC as a built-in component of software and apps, developers provide value to clients. They address privacy concerns by making data protection more automated.