Posted in  AI, machine learning, Privacy Red Team, Uncategorised   on  February 2, 2024 by  Rebecca0 comments

Process and procedures are crucial for effective and safe AI red teams Unleashing a red team on an AI system is one way to detect and find risks and vulnerabilities. However, there can be unintended consequences if not executed carefully. This is where process reigns supreme. By establishing clear procedures, the AI red team transforms

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Posted in  AI, Privacy Engineering, Uncategorised   on  January 19, 2024 by  Rebecca0 comments

AI governance is increasingly handled by privacy teams.   Privacy professionals at medium-sized and large companies are a busy bunch. Their roles encompass a wide range of tasks, from staying abreast of evolving international privacy regulations to addressing data subject access requests (DSARs), conducting regular audits of data usage, and educating colleagues about the importance of

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Genetic information is pretty sensitive.  It can reveal a lot about you, and it can be used to target you racially or ethnically.  It can reveal health information.  And you can’t change it if it gets into the hands of bad actors.   That’s why 23AndMe’s recent breach was scary and shocking to many of the

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Posted in  AI, machine learning, Privacy Engineering   on  December 20, 2023 by  Rebecca0 comments

The Perplexing Paradox of Anonymity: A Legal versus Privacy Perspective

In the ever-evolving landscape of data privacy, anonymization has emerged as a cornerstone of protecting sensitive information. However, a striking paradox exists between legal and privacy definitions of anonymity. While legal definitions often focus on removing identifying information like PII, privacy engineers strive for more robust protections, such as differential privacy.

This blog post delves into this conundrum.

Key Takeaways:

• Anonymity is a multifaceted concept with varying interpretations and levels of protection.

• Legal definitions of anonymity may lag behind privacy engineering best practices.

• Companies must carefully consider the anonymization methods they employ to safeguard sensitive data.

• Harmonizing legal and privacy perspectives on anonymity is essential for effective data protection.

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