Template: Request for Access to Personal Data Under [GDPR/CCPA]
Subject: Request for Access to Personal Data Under [GDPR/CCPA]
Dear [Company Name] Data Protection Officer,
I am formally requesting access to all personal data your company has collected, processed, or stored about me under the [General Data Protection Regulation (GDPR) Article 15 / California Consumer Privacy Act (CCPA)]
Full Name: [Your Name]
Email Address(es): [Your Email(s)]
Phone Number: [Your Contact Number]
Date of Birth (if applicable): [Your DOB]
LinkedIn/Profile Links (if applicable): [Your Profile Links]
I request that you provide the following information:
A full copy of my personal data held in your system, including:
· Résumé, employment history, salary estimates
· Social media insights, behavioral analysis, recruitment scores
· Any predictive hiring or AI-based assessments about me
· How and when you obtained my data, including:
o Third-party data sources (data brokers, public records)
o AI-generated insights used in my candidate profile
o A list of any third parties that have received or purchased my data.
o Options to correct, delete, or opt out of further data collection.
Under GDPR Article 12 and CCPA regulations, you are required to respond within 30 days and provide this information free of charge.
If you fail to comply, I will escalate this matter to the [Data Protection Authority / Federal Trade Commission].
Thank you for your cooperation. I look forward to your response.
Best regards,
[Your Name]
[Your Email]
Every time you browse the web, you're being tracked. Most websites contain invisible tracking code that allows companies to collect and monetize data about your online activity. Many of those companies are data brokers, who sell your sensitive information to anyone willing to pay. That’s why EFF created Privacy Badger, a free, open-source browser extension used by millions to fight corporate surveillance and take back control of their data.
We now know that this data is also sold to Talent Acquisition software companies to build shadow profiles.
Once scraped or uploaded, your data is run through an LLM/NLP engine that performs the following steps:
Entity Extraction – Pulling your name, employers, job titles, school, location, and dates.
Sentiment Analysis – Detecting tone in your blog posts, cover letters, or even Slack messages.
Psychometric Inference – Mapping text to traits like agreeableness, openness, or conscientiousness using frameworks like OCEAN.
Trajectory Forecasting – Predicting your future performance based on your writing style, gaps, job hops, and metadata.
Cultural Fit Score – Comparing your profile to internal “top performers” and organizational values.
Each layer adds another layer of fiction to your shadow résumé—except this one carries real-world consequences.
