May 11, 2023

3 Key AI/ML Takeaways from the PETs Summit North America

Insights sourced from a panel discussion focused on the value Privacy Enhancing Technologies can deliver for AI/ML use cases

Enveil CEO Ellison Anne Williams was fortunate to facilitate a panel discussion today on a topic that is quickly gaining visibility across a broad range of industries: privacy concerns relating to the use of AI/ML. Specifically, the panelists explored the intersection points between Privacy Enhancing Technologies (PETs) and machine learning — and how these technologies can deliver value for ML use cases. 

Here are our three quick takeaways from the conversation: 

  1. Lead with the business value — When adopting AI/ML, start with the defining business value, not by chasing the technology
  2. Privacy-Preserving Machine Learning (PETs + ML) is powerful, but it isn't an AI silver bullet — PPML addresses many challenges in the AI arena, including security and privacy relating to sensitive models and underlying training data, but these solutions and approaches must be used in the context of a broader modelOps, risk, and governance framework.
  3. Regulation and policy for AI, PETs, and PPML should be suggestive and not prescriptive — Regulation and policy should guide toward broad technology 'satisfaction' but allow for technology evolution.

Thanks to all the panelists (Katherine Fick, Paul Lekas, Vaikkunth Mugunthan, and Eugenio Zuccarelli) for their insights, and to the Privacy-Enhancing Technology Summit North America for serving as the venue for this important discussion. 

PETs Summit 2023 PPML Panel

Looking for more on PPML? Check out these resources: 

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Enveil is a pioneering Privacy Enhancing Technology company protecting Data in Use. Enveil’s business-enabling and privacy-preserving capabilities change the paradigm of how and where organizations can leverage data to unlock value. Defining the transformative category of Privacy Enhancing Technologies (PETs), Enveil’s award-winning ZeroReveal® solutions for secure data usage, sharing, collaboration, and monetization protect data while it's being used or processed. Customers can extract insights, cross-match, search, and analyze data assets at scale without ever revealing the content of the search itself, compromising the security or ownership of the underlying data, or exposing their interests and intent.
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