Vaibhav Mehrotra, Debra Farber, Gerard Stegmaier
By attending this session, you will understand the risks that companies face by leveraging large language models like ChatGPT including dark data misuse and discovery challenges, biased outputs, explainability and observability challenges, data protection rights and auto-inferences, and unclear data stewardship.
LLM prompts provide an easy mechanism to combine and query unstructured, semi-structured, and unstructured data capabilities to businesses. As LLMs have memorization and contextual linkage capabilities for multiple data categories, sensitive data can easily be queried and misused for various purposes. You will come away from this session understanding why privacy, security, and legal teams need a data discovery tool that can search and correlate sensitive data across multiple categories to mitigate risks. You’ll also learn why it’s important to leverage context-driven, self-learning AI to create a multi-dimensional metagraph for an individual’s data, focusing on contextual attributes like residency, the purpose of use, and security & privacy risks.
Vaibhav Mehrotra, CEO and Co-Founder, Secuvy
Gerard Stegmaier, Partner, Reed Smith