👋 Hello and Welcome!
I’m sharing resources and ideas about ethical AI.
My perspective is that of a technical consultant who works as a software engineer, data engineer, and cloud architect on analytics and development teams.
Usually, the teams exist within siloehed enterprises and build amazing products and platforms. But there is an element of mystery to their creations. Mystery about HOW the machine learning models actually work.
That is why explainability, fairness, and safety are such important topics. And yet it is hard for teams to get started.
Adding extra steps to their development process feels like exercising daily, eating 3-5 servings of fruits and veggies, or flossing. We all know these are good time investments but still we don’t do them daily.
Convincing your team leader, your team, and/or your manager to spend more time (and MONEY) on explainability, fairness, and safety is challenging also. Especially when no one is really complaining.
So with all this in mind, I’m here sharing what I’m learning about explainability, fairness, and safety related to Artifical Intelligence.