Data You Should Never Feed into AI

Every prompt, document, or dataset you upload to a public AI model can potentially be stored, analyzed, and used to train future iterations of the software. Sharing the wrong information can lead to severe data breaches, legal penalties, and a loss of intellectual property.  To protect the PGST government's data and your personal identity safe, here is a breakdown of the critical data types that must never be shared with public AI models.

1. Regulated and Sensitive Personal Data

Regulatory frameworks like the GDPR, CCPA, and HIPAA carry strict penalties for the mishandling of sensitive information. Entering this data into an AI tool strips away your control over how it is stored and processed.

  • Personally Identifiable Information (PII): Social Security numbers, home addresses, passport details, driver’s licenses, and phone numbers.

  • Protected Health Information (PHI): Medical histories, diagnoses, biometric data, and health insurance information.

  • Demographic & Sensitive Classes: Data detailing racial or ethnic origin, political opinions, religious beliefs, or sexual orientation.

2. Proprietary Intellectual Property & Trade Secrets

If you feed your company's crown jewels into an AI to help refine them, you risk making that information part of the public domain or exposing it to competitors.

  • Source Code: Pasting proprietary code blocks to find bugs or optimize performance can inadvertently leak your software architecture or introduce security vulnerabilities.

  • Product Roadmaps & R&D: Unreleased product designs, patent drafts, formulas, and strategic future plans.

  • Marketing Strategies: Pre-launch campaign materials and confidential market research.

3. Financial and Legal Records

Financial data requires the highest level of confidentiality. Exposing these documents can impact market valuation, violate compliance standards, or invite insider trading risks.

  • Corporate Financials: Quarterly earnings before public release, internal audits, and detailed budget spreadsheets.

  • Legal Documentation: Active litigation strategies, non-disclosure agreements (NDAs), trade union memberships, and employee dispute records.

  • Banking Information: Corporate or personal bank account numbers, credit card details, and tax documentation.

4. Credentials and Authentication Details

AI prompts are often stored in history logs or reviewed by third-party human annotators. Treating an AI prompt like a notepad for active secrets is a massive security risk.

  • Passwords & Passphrases: Never use AI to generate variations of your active passwords.

  • API Keys & Tokens: Keep cryptographic keys, cloud access tokens, and configuration strings entirely away from AI dialog boxes.

The Golden Rule of AI Data Safety

If you wouldn't post the information on a public social media platform, do not paste it into a public AI prompt.

How to Stay Safe

  • Use Enterprise-Grade AI: If your work requires AI assistance, ensure your organization uses enterprise versions (like Microsoft Copilot with commercial data protection) where data logging and training are explicitly turned off.

  • Anonymize First: If you need help analyzing a dataset or draft, strip out all specific names, exact numbers, and identifying metrics before uploading.

  • Review AI Settings: Opt-out of data sharing and training history in the privacy settings of your personal AI accounts.

  • Human Review: Always review the information for confidentiality, integrity and accuracy (CIA)


Note:  This article was generated using AI