Community Q&A on AI Security | Episode 34

In this episode of BHIS Presents: AI Security Ops, our panel tackles real questions from the community about AI, hallucinations, privacy, and practical use cases. From limiting model hallucinations to understanding memory features and explaining AI to non-technical audiences, we dive into the nuances of large language models and their role in cybersecurity.

We break down:

• Why LLMs sometimes “make stuff up” and how to reduce hallucinations
• The role of prompts, temperature, and RAG databases in accuracy
• Prompting best practices and reasoning modes for better results
• Legal liability: Can you sue ChatGPT for bad advice?
• Memory features, data retention, and privacy trade-offs
• Security paranoia: AI apps, trust, and enterprise vs free accounts
• Practical examples like customizing AI for writing style
• How to explain AI to your mom (or any non-technical audience)
• Why AI isn’t magic—just math and advanced auto-complete

Whether you’re deploying AI tools or just curious about the hype, this episode will help you understand the realities of AI in security and how to use it responsibly.

Chapters

• (00:00) - Welcome & Sponsor Shoutouts
• (00:50) - Episode Overview: Community Q&A
• (01:19) - Q1: Will ChatGPT Make Stuff Up?
• (07:50) - Q2: Can Lawyers Sue ChatGPT for False Cases?
• (11:15) - Q3: How Can AI Improve Without Ingesting Everything?
• (22:04) - Q4: How Do You Explain AI to Non-Technical People?
• (28:00) - Closing Remarks & Training Plug

Antisyphon Training
https://www.antisyphontraining.com/

Active Countermeasures
https://www.activecountermeasures.com

Wild West Hackin Fest
https://wildwesthackinfest.com

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Joff Thyer - https://blackhillsinfosec.com/team/joff-thyer/
Derek Banks - https://www.blackhillsinfosec.com/team/derek-banks/
Brian Fehrman - https://www.blackhillsinfosec.com/team/brian-fehrman/
Bronwen Aker - http://blackhillsinfosec.com/team/bronwen-aker/
Ben Bowman - https://www.blackhillsinfosec.com/team/ben-bowman/