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Applying your skills

Instruction and application
In Progress

Module 3 key takeaways​

  • Ethical AI/ML requires understanding frameworks, privacy laws (GDPR, CCPA), responsible data use and bias minimisation.
  • Strong data governance ensures ethical ML through lineage mapping, metadata management and robust security for integrity and compliance.
  • AI/ML sustainability focuses on reducing environmental impact, optimising resources and tracking sustainability metrics.

Action item: Share how you will apply your new skills to your role​

Directions: Create a discussion post that answers the questions provided below. Take time this week to read what others share — you never know what will spark a new idea!

In your discussion post, reflect on the following questions:

  • How can you ensure that AI/ML models used in your role or organisation are developed and deployed ethically? What steps can you take to identify and mitigate bias in data and algorithms?
  • What data governance challenges exist in your organisation, and how might stronger policies around data security, transparency and accountability improve the effectiveness of AI/ML initiatives?
  • How can you incorporate sustainability into AI/ML projects in your organisation? What practices could help reduce energy consumption, optimise resources or align AI development with long-term environmental and business goals?