Preserving Privacy While Using Personal Data for AI Training  

One of the biggest challenges facing businesses wanting to use the full opportunities presented by AI tools is the availability of data which is a view a view shared by Gartner; “While AI projects may look feasible on paper, they often falter at the very first step when access to data — especially personal and sensitive data — is prohibited or discouraged because of risk.”

And there is cause for optimism, with Gartner predicting that:

By 2024, the use of privacy-preserving techniques for AI model training will unlock up to 50% more personal data for model training & the use of data protection techniques will increase industry collaborations on AI projects by 70%.

At Diveplane we are passionate about the ethical use of AI, with data privacy preservation at the heart of everything we do.  Our GEMINAI software can help unlock the full value of your data without risking privacy leakage.  Our unique, leading edge technology goes far beyond many solutions on the market today that use simple masking or privacy techniques but are still susceptible to data re-engineering or attack.

Gartner state that “Data privacy and security is viewed as the primary barrier to AI implementations”.

With GEMINAI by Diveplane organizations can break down these barriers safely and take full advantage of the opportunity artificial intelligence presents.

Gartner, Preserving Privacy While Using Personal Data for AI Training, 10 November 2020, Anthony Mullen, Avivah Litan, Pieter den Hamer, Erick Brethenoux, David Mahdi.

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