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Chris Allison @ToferC
, 11 tweets, 9 min read Read on Twitter
Thread: Building an ethical foundation for the AI-driven future @PeriscopeData
First question: What value do you bring to your org. as a data professional? #techskills #businessoutcomes -- likely responses. Then Facebook & #unintendedoutcomes #ODSCWest
Industry starting to confront #ethics in terms of daily applications of #AI algorithms. #Bias based on data - in the case of courts, potentially hundreds of years of biased decisions as part of the training set.
"I'm just an engineer" not an appropriate response. People using #AI products might not understand what or how decisions and predictions are being made, but will be making real world decisions based on them. YOU and your team might be the only ones who do.
#Inclusive & #diversity in team composition can help you make better decisions in the design and delivery of your projects. You can (and need to be) the #conscience & #ethics of your team.
Who does this well? @CrisisTextLine (AI support to trained human operators) - thoughtful human conversations about results and trade-offs in algorithms.
Optimizing system goes so far - often incorporating new and more #diverse #data sets will get you a lot further. #ODSCWest
How to incorporate #data ethically?
1. Holistic metrics (more to life than click-throughs)
2. Build diverse, inclusive & representative #AI #Machinelearning teams (they will also perform better)
3. Check your sources of data and think about #bias. Get multiple sources.
For leaders: Centralized #data teams are more likely to think about (and address) bias. (Don't have your data team reporting to sales).
Chief Data Officer == a good thing & also Chief Conscience Officer around data use. #ODSCWest
Thanks to @harryglaser from @PeriscopeData for a great discussion at #ODSCWest
Leaders: set this by example. Talk about #inclusivity and #diversity around data - a lot. Build a representative #datascience team. Support them and make them #accountable
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