Week 1 self-check | AI GRCA Practice Lab

WEEK 1 · Foundations, harm & law · AI Foundations for Governance

Why does AI governance exist at all?

To slow down technology adoption for its own sakeTo manage the risks and responsibilities AI systems create for people and organisationsBecause all AI is illegal without itOnly to satisfy IT departments

WEEK 1 · Foundations, harm & law · AI Foundations for Governance

Who is the 'provider' in the AI actor model?

The organisation that develops or places the system on the market under its nameOnly the end userOnly a data supplierThe person affected by the system's output

WEEK 1 · Foundations, harm & law · AI Foundations for Governance

Which is a foreseeable example of 'basic AI risk thinking' applied to a fruit-recognition app misclassifying a fruit's ripeness?

Only high-stakes systems need risk thinkingRisk thinking only applies to generative AIThis scenario carries zero risk since it's a simple appEven a low-stakes system can still cause a bad outcome (e.g. wasted produce) if the consequence and likelihood of misclassification aren't considered

WEEK 1 · Foundations, harm & law · AI Foundations for Governance

Which best distinguishes a hosted open-source model from a paid vendor API model?

Vendor APIs are always cheaperOpen-source models cannot be evaluated for biasOpen-source hosting gives more control and data residency but more operational responsibility; vendor APIs offload infrastructure but reduce controlThey are functionally identical in every respect

WEEK 1 · Foundations, harm & law · AI Foundations for Governance

A 'small model' versus a 'large model' distinction primarily refers to:

The price of the laptop it runs onThe scale of the model's parameters and, generally, its training dataWhether it can be used for textWhether it is open-source

WEEK 1 · Foundations, harm & law · AI Foundations for Governance

What is a 'foundation model'?

A synonym for a spam filterAny model under 1GB in sizeA large model trained on broad data that can be adapted as a base for many downstream applicationsA model that only works offline

WEEK 1 · Foundations, harm & law · AI Foundations for Governance

Which best orders these from broadest to narrowest?

AI > machine learning > deep learning > generative AIGenerative AI > AI > machine learningDeep learning > AI > generative AIMachine learning > AI > deep learning

WEEK 1 · Foundations, harm & law · AI Foundations for Governance

Compared to fine-tuning, a key advantage of RAG is:

RAG always produces more creative writingRAG eliminates the need for any governanceRAG requires no data at allSource documents can be updated and cited without retraining the model