“Chatty Women”, iterative data, and the tribulations of fitness gadgets (Andy’s Digest, vol 1)

A great pleasure in life, is conuming amazing content across the web. Here’s 3 great things I’ve read in the last two weeks which help me connect data with things happening in the wider world. I hope you like them!

(from The Economist)
  • 5min read: Chatty women and strong, silent men (The Economist)
    • Why should you read this? First because it’s data-driven diversity and second because it teaches us how to have better conversations with others.
    • tl/dr: An Uber exec resigned over a sexist comment (Paraphrased: “More women on the board? They’ll never stop talking”). The Economist looks to see if any data supports that: it doesn’t. However, the data does reveal fascinating differences between gender’s conversational styles and goals. This is great information for all of us to empathise with others.
(from Periscopic)
  • 5min read: Visualizing Spanish Migration (Periscopic)
    • Why should you read this? This is about iteration with data: the only way to insight
    • tl/dr: It is simply not possible to get the best articulation of your data without exploring it and teasing out the best view through iteration. This article excellently describes the iteration process and how it helped develop the best possible end result.
(from Fitbit)
  • 27min podcast: Human vs Machine: Fitness Gadgets (Bloomberg)
    • Why should you listen? Because AI and machine learning aren’t good enough to threaten humans yet.
    • tl/dr: Fitness gadgets suffer from Dead-End Dashboard problems but they’re getting better. This podcast pits them against a real fitness trainer. The conclusion? Like most AI applications, they’re far from fully functional and for the foreseeable future. The point is that for now, augmenting human ingenuity is the right path forward for AI and ML.

Let me know your thoughts – do you have any comments? Do you want to see more posts like this?