6/ Here's what I came up with:
- accuracy isn't always the right performance measure
- mathematical models encode and replicate the biases found in their training data
- there can be competing and contradictory ideas of what makes something fair
- under certain conditions people are likely to over-rely on machine outputs (automation bias)
- the choices we make about how to use tools embody and reveal what we value