×
Unstructured Data Poses Important Considerations for Privacy, Governance and Ownership in the AI Era
Written by
Published on
Join our daily newsletter for breaking news, product launches and deals, research breakdowns, and other industry-leading AI coverage
Join Now

The rapid advancements in AI’s ability to analyze unstructured data are raising important questions about data privacy and ownership.

Key Takeaways: As AI systems become increasingly capable of extracting insights from vast amounts of unstructured data, it’s crucial to consider the privacy implications:

  • While unstructured data may seem less sensitive than structured databases containing personal identifiers, AI can still pull together inferences, timelines, and narratives that could be highly intrusive.
  • The era of AI moving from structured data sets to a more general technology approaching “universal knowledge” is both thrilling and potentially terrifying from a privacy perspective.

Advancements in AI Hardware: New hardware developments are enabling AI systems to process unstructured data more effectively:

  • Michelle Fang highlighted a chip with 900,000 cores and 4 billion transistors that allows for easier scaling and eliminates the need for complex parallel programming.
  • These advancements allow developers to focus on AI rather than parallel programming, enabling them to start and scale their work more quickly.

Data Governance and Ownership: As AI’s capabilities with unstructured data expand, data governance becomes increasingly important:

  • Identifying where data resides, such as in AWS object storage, and analyzing the metadata can help assess whether AI could build sensitive information models from the bits and pieces gleaned through unstructured data.
  • The question of who owns the data being analyzed by AI is a critical one that must be addressed.

Broader Implications: The privacy threats posed by AI’s ability to process unstructured data may become more apparent as the technology advances:

  • As we move forward, it will be important to proactively identify potential privacy issues rather than waiting for them to surface through anecdotal user experiences.
  • While the hardware advancements are impressive, it’s crucial to consider what it means when AI can reduce, refine, and figure out personal information from unstructured data.
Is Unstructured Data Less Private?

Recent News

Baidu reports steepest revenue drop in 2 years amid slowdown

China's tech giant Baidu saw revenue drop 3% despite major AI investments, signaling broader challenges for the nation's technology sector amid economic headwinds.

How to manage risk in the age of AI

A conversation with Palo Alto Networks CEO about his approach to innovation as new technologies and risks emerge.

How to balance bold, responsible and successful AI deployment

Major companies are establishing AI governance structures and training programs while racing to deploy generative AI for competitive advantage.