Wild Houses by Colin Barrett

I had a three 2024 Booker Prize long list nominee vacation over Labor Day and this was one of them. It did not make it to the shortlist, but as is so often the case for me, I am glad that I read it, I would not have been likely to find this one on my own, and I often like some of the long list more than those that make the cut to the short list. This is a short and ruthless story--apparently the author's first full length novel, and maybe it's sparseness is a result of a story teller who does so succinctly. What happens is that Donal's brother Cillian falls in with some drug smugglers to make a bit of cash on the side, and gets into trouble when his stash is below the water line and it literally dissolves away. To pressure him into paying them back, Gabe and Sketch Ferdia, kidnap Donal and stash him in a gigantic loner's house. The Feria's are thuggish, unpredictable, prone to sudden bursts of rage and violence, and yet capable of tenderness and camaraderie between themselves. The story alternates between what is happening to Donal with the slow realization of his family as to what has become of him, leading up to a dramatic finale.

His Three Daughters (2023)

This is a bit of a departure from my usual solo travel work movie watching fare--it is a serious movie about a serious--and universal00life experience of having a parent die. True, some dodge it, but that is usually a tragedy of a different sort. The movie opens in a New York City apartment where we meet we meet Katie (Carrie Coon), Christina (Elizabeth Olsen) and Rachel (Natasha Lyonne). The scene is painful to watch and yet as the movie rolls out over the next hour and a half, it also is a scene that doesn’t really capture who they are. Yes, they are sisters and daughters (and two are mothers). But in the days leading up to their father’s death, they’re reminded of the complexity of human emotion, behavior, and understanding. There is a lot that the daughters do not agree upon, and are left to grapple with as their father dwindles away, and it is a microcosm of the things that happen all too often for families that leave a lot unsaid and for whom there are misunderstandings, resentments, tensions, piled on top of the challenges of everyday life. When you don't communicate, you don't communicate and grappling with death does not make it any better. The script is pitch perfect, and while it was painful to watch, it felt very real. Grief tears down what we think of ourselves. It’s cruel. It’s harsh. It’s inevitable. It shatters the walls we put up around our personalities that so often reduce us to easy descriptions like sister, daughter, and mother, and none of that helps to get through to the place you need to get to move on.

Noise by Daniel Kahneman, Olivier Sibony, and Cass Sunstein

This is a book that takes a deep dive into unconscious bias, and tries on a number of different levels to point it out, and to help the reader to see that no one escapes this one, we all succumb to it to a greater or lesser extent, and the trick is to constantly be on the look out for it and to try to counterbalance it. This scattergun variability in judgments of all kinds, from court sentencing to insurance underwriting to medical diagnosis, is what the authors call, well, noise. Like its more famous cousin, bias, noise is an error in judgment. The authors distinguish between the two using a shooting-range metaphor. If all the shots land systematically off-target in the same direction, that’s bias; by contrast, noise is all over the place. Some of the shots might even be on target, because the issue here is not missing the target but a lack of consistency. Given the same facts, one criminal gets life and another who is equally guilty gets off. Which brings us to the other significant distinction between bias and noise: to detect bias, you have to know what the right answer is, or to use the book’s metaphor, you have to be standing at the front of the target, so you can see the bullseye. Noise requires no such particulars. It is detectable no matter which side of the target you’re standing on, since all you need to know is whether or not there is variability. One insurance company executive estimated the annual cost of noise in underwriting in the hundreds of millions of dollars. And you should want to detect noise, the authors argue, because it is not only unfair, it can be hugely costly--in money, in opportunity, and in human capital.