GDPR
The European Union's General Data Protection Regulation governing how personal data is collected, stored, and processed. Important when choosing AI tools that handle your data.
Why it matters
If you handle any personal data from people in the EU, GDPR sets the rules, and the fines for ignoring it are serious. It matters when choosing AI tools because those tools often process names, emails, or customer details. Picking a service that respects GDPR keeps you compliant and builds trust with users. Even outside Europe, many businesses follow it as a baseline for responsible data handling.
In practice
You run a newsletter and want to use an AI tool to personalize emails. Before signing up, you check whether the tool is GDPR-compliant: does it let users request deletion, store data securely, and avoid using your subscribers' info to train its models without consent? A vendor that answers yes to these is a safer choice, protecting both your readers and your business from legal headaches.
Related terms
AI Alignment
The research challenge of ensuring AI systems pursue goals that are beneficial to humans. Misaligned AI could technically achieve its objective while causing unintended harm. Alignment research aims to make AI reliably helpful, harmless, and honest.
Bias (in AI)
Systematic errors in AI outputs reflecting prejudices in training data. Can manifest as gender stereotyping, racial assumptions, or cultural insensitivity in generated content.
Constitutional AI
A training approach where AI models are given a set of principles (a 'constitution') and learn to self-critique and revise their outputs to comply with those principles. Reduces reliance on human feedback for safety alignment.
Data Poisoning
A security attack where malicious data is deliberately introduced into AI training sets to manipulate model behavior. Can cause models to produce biased outputs, bypass safety filters, or leak sensitive information.
Guardrails
Safety mechanisms built into AI systems to prevent harmful, biased, or off-topic outputs. Includes content filters, topic restrictions, output validation, and behavioral boundaries that keep AI responses within acceptable limits.
Hallucination
When an AI model generates information that sounds plausible but is factually incorrect or entirely fabricated. Common with statistics, citations, and historical claims.