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Towards more ‘fair’ AI: algorithmic intent in a disparate society — part 7
Can ‘fair’ algorithms help address unfair policies offline? Part 7 of 9 (because this must end…)
Quick review of previous posts.
Post 1: It’s a WEIRD world online and a weird one offline.
Post 2: More fun with words so we think we understand each other:
- Algorithms are apathetic math manipulated for and by humans.
- Each human holds one or more ‘ground truths,’ which is what that human understands to be measurably accurate for defined conditions.
- Algorithms rely on ‘ground truths’ to perform complicated calculations geared towards ‘predicted outcomes.’
- ‘Predicted outcomes’ never happen but we continue to try.
Post 3: Everything is made up of deceptive data that we tend to perceive differently depending on who/where/when we are.
Post 4: Context is critical and we should try our best to be critical of our context at all times (but this is resource-intensive so we usually aren’t.)
Post 5: Any laws and regulations that we humans create are created by and for humans and then implemented (online and off) in varied and ever-changing circumstances.
Post 6: Algorithms offer various solutions for implicit and explicit problems that we humans define.
