Neuroforster

Jeff Hutchings, Acclaimed Dalhousie University biologist

"Not only has the Canadian public lost critical environmental and cultural baseline data more than 100 years old, but scientists have lost the symbolic heart of their research operations....

One scientist after another struggled to make sense of the shuttering of libraries devoted to water and fish in a nation that guards the world's largest coastline and roughly 18 per cent of the world's surface freshwater. Most saw in the actions a political agenda by the Harper government to reduce the role of government in Canadian society, as well as the use of scientific evidence in making policy....

The Freshwater Institute library held collections dating back 100 years, on the quality and state of freshwater systems in central Canada, the Great Lakes and the Arctic."

A huge number of our reasoning mistakes stem from confirmation bias: looking for or interpreting evidence to confirm a belief rather than disprove it. We're great at reasoning forwards: if A causes B, and we see A, we conclude that B will happen. We're terrible at reasoning backwards; if we want to test the A-B relationship, we'll look at all the Bs to see if they were caused by A, when we should really be checking what happened before all the Cs. Here's a great example of this kind of mistake in causal reasoning:

"The military looked at the bombers that had returned from enemy territory. They recorded where those planes had taken the most damage. Over and over again, they saw the bullet holes tended to accumulate along the wings, around the tail gunner, and down the center of the body. Wings. Body. Tail gunner. Considering this information, where would you put the extra armor? Naturally, the commanders wanted to put the thicker protection where they could clearly see the most damage, where the holes clustered. But Wald said no, that would be precisely the wrong decision. Putting the armor there wouldn’t improve their chances at all."

Dear BIC:

I thought that this would be great for annotating the data acquired in my neuroscience research, but then I realized that the ink didn't have sparkles in it. The lack of sparkles is making the data very hard to extrapolate. I will not be using this product again. Plus, every time I use it at the lab, some guy in a pen costume shows up and tries to make us kiss him. He is scaring the undergrads.