Product, business & communication

Apply responsible-AI and data-protection basics

Bias, transparency, consent, DPDP Act/GDPR basics, model documentation.

~6 focused hours·beginner

Tools: Model/data documentation templates, bias-testing checklists, DPDP Act / GDPR reference guides

What employers mean

You should be able to…

  1. Apply DPDP Act (India) basics — consent, purpose limitation, data minimization — to an AI feature
  2. Check a model or dataset for obvious demographic bias before launch
  3. Write clear consent/disclosure language when a user is interacting with an AI system
  4. Document a model's known limitations for internal and external audiences
  5. Identify when a use case needs a human-in-the-loop for legal or ethical reasons
  6. Explain the difference between DPDP Act and GDPR obligations for an Indian company serving global users

Needs first: Explain how LLMs work and where they fail

Learn — free, link-checked

The few resources that matter

Practice

Responsible-AI checklist + model card for a resume-screening assistant

Take a hypothetical AI feature that screens resumes for a recruiting team and write (1) a DPDP Act-aligned consent and data-handling note for candidates, (2) a bias-check plan naming specific demographic attributes to test and how, and (3) a one-page model documentation card stating known limitations and required human oversight points.

Done when
  • Consent note cites specific DPDP Act obligations (purpose limitation, consent, data minimization)
  • Bias-check plan names at least 3 attributes to test and a method for each
  • Model card states at least 2 known limitations and where a human must review before a decision
  • All three documents are consistent with each other (no contradictions on data handling)
Prove it

Evidence a recruiter can check

  • Public consent/data-handling note
  • Bias-check plan document
  • Model documentation card
Interview

Questions you'll get asked

  1. What does the DPDP Act require when an AI feature processes personal data?
  2. How would you check whether a hiring-screening model is biased before launch?
  3. What disclosure would you require when a user is chatting with a bot instead of a human?
  4. Tell me about a use case that needed a human-in-the-loop for compliance reasons, not just accuracy.
  5. How do DPDP Act and GDPR obligations differ for an Indian company with EU customers?
  6. What would you put in a model documentation card for a customer-facing LLM feature?
See where you stand for AI Product Manager