How do you ensure your technically interesting project is truly a force for good, not merely further entrenching existing biases, stereotypes, and social problems? This great set of rules, based on experiences working on AI solutions in low-income countries, can help, regardless of where you're working:
1. Ask who's not at the table - are you truly inclusive?
2. Let others check your work - fairness is subjective
3. Doubt your data - does your data suffer from collection bias?
4. Respect context - a model developed in one context may fail in others
5. Automate with care - take baby steps, don't take people out of the loop too soon
https://techcrunch.com/2018/05/24/navigating-the-risks-of-artificial-intelligence-and-machine-learning-in-low-income-countries/On a recent work trip, I found myself in a swanky-but-still-hip office of a private tech firm. I was drinking a freshly frothed cappuccino, eyeing a mini-fridge stocked with local beer and standing…
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