I heard Dr. Cassie Holmes talk about her book Happier Hour: How to Beat Distraction, Expand Your Time, and Focus on What Matters Most and her approach to time management, making sure we get the most out of the limited free time most of us have, on the Hidden Brain podcast a month or so ago. She was an excellent guest, telling some great anecdotes and offering a superficial look at her recommendations for people to reorganize their time around the activities that give them the most joy or pleasure. The book, however, goes no deeper than that, and really could have been a pamphlet for all the insight it offers.
Happier Hour’s main advice is simple to understand and plan, albeit perhaps not to implement. Holmes asks readers to spend about two weeks tracking their time in small increments, writing down what they’re doing and how they felt while doing it. The goal is to identify the activities that give you the most happiness, however you may define that. That’s often social activities with family, friends, etc., but it will vary by person – you might enjoy solving a puzzle by yourself more than playing a game with friends, and if so, then you should enter that in your little journal.
Once you’ve gathered that information, you should then create a schedule of your week, filling in the activities that you must do before you get to anything else. Holmes distinguishes between types of required activities, however; for many people, there will be aspects of work that you enjoy, and aspects that you don’t enjoy but have to do anyway. (One recurring problem with Happier Hour, though, is that this is very much a book for privileged people. Here, you have to have a job that gives you some flexibility in when you perform required tasks, at the very least.) Her advice is to isolate the best parts of work – the ones that give you some positive feeling, however you wish to define that – and dedicate time to them at the time(s) of day when you feel best. She’s a morning person, and she likes the deep work parts of her job, so she sets aside a few hours each morning for it, delaying the lesser parts of the job, like answering emails, to the afternoon when she’s not at her best anyway.
She counsels the same approach to your leisure hours – some of which will, again, involve required tasks, like making dinner, chauffeuring children or other family members, or performing certain chores. As I write this, I just emptied the garbage and recycling bins in the kitchen, dealt with the cats’ litter, and took the trash bins to the curb, a required task I perform every Wednesday. That would be on my calendar, each Wednesday night, taking up maybe 15 minutes at most. Once those fixed tasks are in place, I would then fill I the remaining time with activities that give me the most joy and with required tasks that can be performed at any time, again prioritizing the good stuff for times when I feel my best. (This also would require that I know when I feel my best. It depends on the day.)
That’s all there is to the Happier Hour system, aside from some minor details. Beyond that, the book is fluff – a little research here and there on how social activities tend to make us happiest, how experiences beat acquisitions (no kidding), or how social media sucks, plus some mostly cute stories from Holmes’ own life (along with one pretty lousy one). I don’t mind hearing about the author’s experiences when they relate to the book; her decision to leave a prestigious but intense job that was cutting into her time with her young children is understandable, and there’s a straight line from that to the research she does now at UCLA. However, they also underscore how this book is only for a small sliver of the population: It is way, way easier to execute the program in Happier Hour if you’re either rich, or in a flexible job (like mine, come to think of it), or both. So many of her stories just scream wealth and privilege: oh, you have a weekly coffee-and-hot-cocoa date on Thursday mornings with your preschool-aged daughter? How nice for you, but most of your readers with kids that young will take them to day care or similar arrangements so they can go to their not flexible jobs.
I say this with full awareness that my job is flexible – I’m a writer, and as long as I hit my deadlines, I could write at any time of the day I wanted. I could do it from 2 to 4 in the morning if I wanted to. (I do not.) And I could write from anywhere; in the offseason, I don’t even need to be in this hemisphere, as long as I have a phone and an internet connection. I am in the target audience for this book. I just didn’t feel very moved by it, and by the time I was about 2/3 of the way through, I was just annoyed by how much extra verbiage there was around something that could be described in under ten pages. This book could have been a podcast, and in fact, it was.
Next up: Still reading Adam Hochschild’s To End All Wars.
Filterworld.
In his new book Filterworld: How Algorithms Flattened Culture, journalist Kyle Chayka details the myriad ways in which we are thrust towards homogeneity in music, television, movies, books, and even architecture and travel because, in his view, of the tyranny of the algorithm. The book is more of a polemic than a work of research, filled with personal anecdotes and quotes from philosophers as well as observers of culture, and while Chayka is somewhat correct in that a small number of companies are now determining what people watch, listen to, and read, that’s always been true – it’s just happening now by algorithm when technology was supposed to democratize access to culture.
Chayka’s premise is sound on its surface: Major tech companies now depend on maintaining your attention to hold or increase revenues, and they do that via algorithm. Netflix’s algorithm keeps recommending movies and shows it believes you’ll watch – not that you will like, but that you will watch, or at least not turn off – thus keeping you as a customer. Spotify’s auto-generated playlists largely serve you artists and songs that are similar to ones you’ve already liked, or at least have already listened to, as I’ve learned recently because I listened to one song by the rapper Werdperfect that a friend sent me and now Spotify puts Werdperfect on every god damned playlist it makes for me. Facebook, Twitter, Instagram, Tiktok, and their ilk all use algorithms to show you what will keep you engaged, not what you asked to see via your following list. Amazon’s recommendations are more straightforward, giving you products its algorithm thinks you’ll buy based on other things you’ve bought.
Chayka goes one further, though, arguing that algorithmic tyranny extends into meatspace, using it to explain the ubiquity of Brooklyn-style coffee shops, with sparse décor, subway tiles, exposed wood, and industrial lighting. He uses it to explain homogeneity in Airbnb listings, arguing that property owners must determine what the algorithm wants and optimize their spaces to maximize their earnings. He is ultimately arguing that we will all look the same, sound the same, wear the same clothes, live in the same spaces, drink the same expensive lattes, and so on, because of the algorithms.
To this I say: No shit. It’s called capitalism, and the algorithm itself is not the disease, but a symptom.
Businesses exist to make money, and in a competitive marketplace, that’s generally a good thing – it drives innovation and forces individual companies to respond to customer demand or lose market share to competitors. These market forces led to the advent of mass production over a century ago, a process that depended on relatively uniform tastes across a broad spectrum of consumers, because mass-producing anything economically depends on that uniformity. You can’t mass-produce custom clothes, by definition. Companies that have invested heavily in capital to mass produce their widgets will then work to further expand their customer base by encouraging homogeneity in tastes – thus the push for certain fashions to be “in” this year (as they were twenty years prior), or the marketing put behind specific books or songs or movies to try to gain mass adoption. Coffee shops adopt similar looks because customers like that familiarity, for the same reason that McDonald’s became a global giant – you walk into any McDonald’s in the world and you by and large know what to expect, from how it looks to what’s on the menu. This isn’t new. In fact, the idea of the algorithm isn’t even new; it is the technology that is new, as companies can implement their algorithms at a speed and scale that was unthinkable two decades earlier.
Furthermore, we are living in a time of limited competition, closer to what our forefathers faced in the trust era than what our parents faced in the 1980s. There is no comparably-sized competitor to Amazon. Spotify dominates music streaming. Each social media entity I listed earlier has no direct competition; they compete with each other, but each serves a different need or desire from consumers. The decline of U.S. antitrust enforcement since the Reagan era has exacerbated the problem. Fewer producers will indeed produce less variety in products.
However, the same technology that Chayka decries throughout Filterworld has flattened more than culture – it has flattened the hierarchy that led to homogeneity in culture from the 1950s through the 1990s. Music was forced, kicking and screaming, to give up its bundling practice, where you could purchase only a few individual songs but otherwise had to purchase entire albums to hear specific titles, by Napster and other file-sharing software products. Now, through streaming services, not only can any artist bypass the traditional record-label gatekeepers, but would-be “curators” can find, identify, and recommend these artists and their songs, the way that only DJs at truly independent radio stations could do in earlier eras. (And yes, I hope that I am one of those curators. My monthly playlists are the product of endless exploration on my own, with a little help from the Spotify algorithm on the Release Radar playlists, but mostly just me messing around and looking for new music.) Goodreads is a hot mess, owned by Amazon and boosting the Colleen Hoovers of the world, but it’s also really easy to find people who read a lot of books and can recommend the ones they like. (Cough.) Movies, food, travel, television, and so on are all now easier to consume, and if you are overwhelmed by the number and variety of choices, it’s easier to find people who can guide you through it. I try to be that type of guide for you when it comes to music and books and board games, and to some extent to restaurants. When it comes to television, I read Alan Sepinwall. When it comes to movies, I listen to Will Leitch & Tim Grierson, and I read Christy Lemire, and I bother Chris Crawford. I also just talk to my friends and see what they like. I have book friends, movie friends, game friends, coffee friends, rum friends, and so on. The algorithms, and the companies that deploy them, don’t decide for me because I made the very easy choice to decide for myself.
So I didn’t really buy Chayka’s conclusions in Filterworld, even though I thought the premise was sound and deserved this sort of exploration. I also found the writing in the book to be dull, unfortunately, with the sort of dry quality of academic writing without the sort of rigor that you might see in a research paper. I could have lived with that if he’d sold me better on his arguments, but he gives too little attention to points that might truly matter, such as privacy regulations in the E.U. and the lack thereof in the U.S., and too much weight to algorithms that will only affect your life if you let them.
Next up: Angela Carter’s The Magic Toyshop.