Archives: KSB

Convert data to support an AI or automation solution.

Explain how algorithmic bias can arise from dataset selection or methodologies used in AI systems.

Describe how errors or algorithmic bias can affect users or organisations when AI or automation is used.

Outline a post-deployment mitigation strategy to combat overreliance.

Explain common sources of error in AI or automation systems and mitigation approaches or fairness metrics.

Prepare data to support an AI or automation solution.

Analyse data to support an AI or automation solution.

Explain the purpose of human in the loop safeguards within feedback and evaluation loops.

Describe how feedback and evaluation loops are used to improve systems, processes, productivity, or performance.

Make changes to an AI or automation solution based on testing and feedback to ensure accessibility in alignment with organisational needs.