Fortanix® Inc., a data-first multicloud security company, today introduced Confidential AI, a new software and infrastructure subscription service promising users the secure use of private data without compromising privacy and compliance.
AI modeling relies on accurate complete data sets. Because of privacy laws, data teams instead often use educated assumptions to make AI models as strong as possible. The development of AI applications can be hindered by the inability to use highly sensitive, private data for AI modeling. Fortanix utilizes Intel SGX secure enclaves on Microsoft Azure confidential computing infrastructure to provide trusted execution environments, making AI models more accurate.
Ambuj Kumar, CEO and cofounder of Fortanix said, “For today’s AI teams, one thing that gets in the way of quality models is the fact that data teams aren’t able to fully utilize private data.” Kumar added, “Confidential AI ensures that highly sensitive data can’t be compromised even while in use, giving organizations the peace of mind that comes with assured privacy and compliance.”
Impact of privacy regulations on AI in healthcare
Fortanix’s confidential computing technology has demonstrated proven use cases, such as powering UC San Francisco’s privacy-preserving analytics platform, BeeKeeperAI, which secures healthcare AI with confidential computing by facilitating a zero-trust interaction between algorithm developers and data stewards. In this environment, the validity of these algorithms can be assessed in the context of real-world data, all without algorithm developers having to expose their algorithm or data stewards having to release data.
The practical applications of AI modeling in healthcare are only beginning to be realized, and some clinical implications sound like the stuff of science fiction. AI has the potential to enable better healthcare outcomes, but in regulated, privacy-sensitive industries such as healthcare, utilizing private data will demand ever-shifting controls in order to keep the core data safe.
Algorithms that are used in the context of delivering health care must be capable of consistently performing across diverse patient populations, socioeconomic groups, and geographic locations, and also be equipment agnostic. Gaining regulatory approval for clinical artificial intelligence (AI) algorithms requires highly diverse and detailed clinical data to develop, optimize, and validate unbiased algorithm models.
Fortanix offers customers key management, database encryption, and now confidential computing as required per the Health Insurance Portability and Accountability Act (HIPAA), which sets the privacy standards for protecting sensitive patient data. Healthcare organizations and companies that handle sensitive protected health information (PHI) must have certain processes and security measures in place to provide the necessary framework that controls who has access to data and restrictions on sharing of this sensitive data.
The Fortanix Confidential AI service is available now as a private preview, with full general availability expected in January 2022.
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