Module 4 of 5 · Novice · 6 min read
Using AI safely and responsibly
Privacy, bias, intellectual property and when to keep a human in the loop.
- 1Know your tool's data policy before pasting anything confidential.
- 2Models can reflect biases in their training data; review outputs that affect people.
- 3You are responsible for what you publish or act on, whoever drafted it.
01Privacy and data
Consumer chat apps and enterprise plans handle data differently. Business and API plans usually do not train on your inputs; some free consumer tiers may unless you opt out. Your organisation may also have rules about approved tools.
A good default: do not paste passwords, customer personal data, health records or unreleased financials into a tool unless you know it is approved for that data.
02Bias and fairness
Models learn from human-written data, including its stereotypes and blind spots. Labs work hard to reduce this, but outputs can still be skewed, especially in hiring, lending, health and legal contexts.
When AI output affects real people, have a human review it, test it across different groups, and never let a model make high-stakes decisions on its own.
03Ownership and disclosure
Rules on AI-generated content are still evolving. Many publishers, schools and employers now ask you to disclose meaningful AI assistance. Check the policies that apply to you.
Treat AI output like a draft from a capable assistant: you review it, you edit it, and you own the result.
Finished reading?
Mark it complete to track your progress, then test yourself with the AI Safety & Responsibility quiz.