Algorithms are only as good as the data that feeds them. Data scientists are deeply familiar with the impact of GIGO (garbage in, garbage out), where messy inaccuracies, fragmented data, and the like result in poor analysis. But fairness, inclusion, and bias in the...
This is Part 5 in a series about Collective Data Empowerment. If you want to get the whole series and accompanying tools in an ebook, go here. So, you’re a data executive. You’re on a mission to build a data-driven culture. You spend your days leading organizational...
This is Part 4 in a series about Collective Data Empowerment. If you want to get the whole series and accompanying tools in an ebook, go here. Imagine… You are in a dark forest. Above, the dense canopy of branches and leaves hides the sun’s position. Your phone...
“But now we’ve realized that, well hang on, if you’re gonna build a driverless car, how does the car interact with the humans on the road? And that is not an engineering challenge, that is a liberal arts challenge because you’re looking at the world of philosophy,...
Ann Jackson popped onto my radar when several colleagues shared her blog post “Aiming for data-driven? Don’t forget the people.” It was one of those tabs you keep open after reading because you know you have to do something with it, but you’re not sure what. Here’s...
This is Part 3 in a series about Collective Data Empowerment. If you want to get the whole series and accompanying tools in an ebook, go here. Think about a challenge your company faces. Consider: who among your colleagues knows the most about it? Who has the most...
