AI Ethics and Intelligent Systems Investigation
AI can classify, predict, and recommend — but who trained it, on what data, and who wins or loses when it is wrong?
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Venture In
Wero
Observe
Kite
Infer
Whakaaro
Create
Auaha
Evaluate
Tohu
Evidence you will build
- AI bias investigation report
- Human vs AI comparison table
- Ethics evaluation rubric
- Speculative design proposal
Why this matters
Intelligent systems shape science, health, and whenua monitoring — communities need people who can critique AI fairly, not just use it.
What you will investigate and collect
You will investigate a real AI tool used in science, compare its outputs to human expertise, and argue for fairer or more careful use. Sources of bias, error, and limitation in an AI system applied to a science or environmental question. Bias investigation notes, human vs AI comparison tables, ethics rubric scores, and a speculative design sketch.
- Date
- Sample or case ID
- AI output
- Human reference
What you might make or share
- Arduino data logger scaffoldArduino
Prototype timed captures tied to reliability evidence
If jitter or sampling gaps blurred your inference, scripted intervals target that gap.
What you will investigate
You will investigate a real AI tool used in science, compare its outputs to human expertise, and argue for fairer or more careful use.
What you will collect
Date, Sample or case ID
What you might make or share
An ethics evaluation, a comparison table