What lies in the shadows and why weather apps are always wrong.

We live in the age of data overload; we arguably have more data than our brains can effectively comprehend. So, how do we start making sense of all of the information? To start, we can take a lesson from past artists and weather forecasting. Plus: is it time to retire Peer Review?

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Welcome to the April 23 edition of The Digest.

Mystery and misrepresentation, distortion and disorder - what comes to your mind when considering shadows?

They seem to defy physics, don't they? In paintings, at least, they often do. Ever since art has been around - and that's been a long time - artists have had difficulty depicting shadows. While some decided to discard them entirely, others began to experiment to address this representational problem. The real problem is that our visual brain trying to make sense of what it sees and interpreting it onto the canvas. It seems our mind's eye has a tolerance for impossibility, meaning that even though what is painted defies logic and physics, we still understand the key message. Essentially the artist becomes the neuroscientist, experimenting with the liberties of realistic shadow and using the laws of physics as more of a guideline than the rule. The author writes: “Because we do not notice them, transgressions of physics reveal that our visual brain uses a simpler, reduced physics to understand the world.”Take a closer look at how past artists have addressed the difficulty in solving a representational problem. You won’t look at shadows in paintings the same way again. Link.

Results are in on the largest experiment ever conducted - and, according to the author, the conclusion is grim.

The experiment: Peer Review. The importance of peer review is covered in every basic scientific method lesson: it prevents bad science and helps advance new innovations. But does it actually *do* what it’s supposed to? Not so much, according to the article. Instead, several studies have found that reviewers only catch 25%-30% of errors ranging from minor spelling mistakes to critical issues. Not to mention fraudulent papers are published too often for our liking and often reviews are just sent to the shredder. Still, we are left with questions: how do we go forward from a faulty system and create a process flow that does what it’s intended to do, reliably? Not so much, according to this article. According to the author, peer review is its own failed experiment, and it’s time to move on. Link.

If I asked you to look up the weather today, would you go to the local news outlet? Your Apple Weather app? Carrot or Clime?

What draws you to this choice - forecast accuracy or how the app makes you feel?Weather forecasts - whether it’s from the local meteorologist or your Apple Weather app - are always a game of prediction and probabilities, but weather apps seem to fail more often than not. This is because 1.) despite major advances in forecasting technology, not all weather apps are the same and 2.) there is something to say about human interpretation and nuance.This second reason is really important. We can have all the data we want, but understanding and interpreting that data is key. Despite all the improvements to forecasting, our desire to know everything and know it now may be just the thing causing our dissatisfaction with weather apps. Link.