Showing posts with label prejudice. Show all posts
Showing posts with label prejudice. Show all posts

2025-01-02

Book Review: "Thinking, Fast and Slow" by Daniel Kahneman

I started reading the book Thinking, Fast and Slow by Daniel Kahneman in early 2024. This was initially recommended to me by a friend, and I became even more motivated to read it upon hearing positive things about it from colleagues at my previous job, as many of the subtleties described in the book are extremely relevant to the appropriate design of interviews, focus groups, and surveys of human subjects in social science research. However, because it is a long book and the middle of 2024 was made busier for me by moving back to Maryland, traveling a lot, and starting a new job (some of which I have discussed in a previous post [LINK]), I could not finish reading this book until much more recently. Because of this large gap between reading the initial 60% and remaining 40% of this book, I admit that I have since forgotten many details from the initial 60% of this book. Moreover, I started making notes to myself in this post based on that initial 60% because I assumed that I would be able to finish reading the remaining 40% soon afterwards and I would therefore remember the book as a coherent whole, but because that didn't happen, many of the notes that I have made in this post that were supposed to form the skeleton of this post now no longer make as much sense to me. For these reasons, this post may seem a bit more stilted than other book review posts in this blog and will likely seem stronger/more coherent when discussing the latter 40% of the book.

The book is a lengthy exposition of novel ideas in psychology & behavioral economics that were empirically validated by the author, most often in conjunction with his longtime academic collaborator Amos Tversky. The concluding chapter does a good job of recapitulating the main ideas of the book. Most of the book explores various facets of individual & group-based human behavior based on the idea that there are effectively 2 modes through which individuals process information, which the author refers to as Systems 1 & 2. System 1 "thinks fast", making snap judgments based on limited information, heuristics, and a bit of laziness, and is the aspect of thinking that drives most day-to-day reactions & decisionmaking, while System 2 "thinks slow", making more deliberate judgments with more of an effort to gather all relevant information but must in turn be consciously engaged and ultimately disengages from mental fatigue (in favor of System 1) if engaged for too long. The book also considers how individuals' typical behaviors when faced with outcomes that are certain competing with outcomes that have known or unknown probabilities deviate from behaviors idealized by microeconomic theories of expected utility, notably that while the commonly observed behavior choosing a certain gain with a lower value than the expected value of an uncertain gain can be explained to some degree by expected utility theory, the commonly observed behavior of choosing a gamble on losing outcomes with an expected loss of larger magnitude than a different certain loss cannot be explained by expected utility theory; this partly explains the risks that people take in business and can be explained in turn by how people in their perceptions tend to overestimate probabilities that are close to but not exactly 0 and underestimate probabilities that are close to but not exactly 1. Finally, the book partly explains notions of hedonic adaptation (the idea that one's sense of well-being is generally similar in many different good or bad medium- or long-term circumstances by adapting to those circumstances) by distinguishing how people rate pleasure or pain when experiencing those things versus in hindsight and shows how people's conceptions of their identities & well-being in the past, present, and future are intimately tied to their actual memories and their abilities to form & retain memories. These aspects of self-conception as well as perceptions of probability can also be tied to Systems 1 versus 2, as many seemingly shortsighted decisions or perceptions can be explained by System 1 making snap judgments lazily & using heuristics based on incomplete information.

Especially as I read the latter 40% of the book, I came to appreciate how many of the ideas of this book had permeated into other things that I had read & heard from others and that I had internalized into my own worldview & view of myself. Professionally, I could see how so many aspects of framing could be important when designing surveys & focus groups. Personally, I could see how especially as I have aged, I have in many cases consciously chosen to not worry too much about certain details and instead make decisions based on lazier heuristics because I didn't feel that the results of spending more mental energy making a decision based on System 2 would be worth the effort. At the same time, I have become more consciously aware of how my memories of things in my own life can be affected by the passage of time and by more recent events in my own life, and I have become more consciously aware of the deep entanglement between my perceptions of my own memories and the narratives that shape my perceptions of my own life & of the world. I thus feel more proud of maintaining detailed personal diaries where I take note (using System 2 as much as possible when considering things outside of the current moment) of how I feel about various things in the moment as well as in hindsight and carefully consider how & why my thoughts & feelings about different events in or aspects of my life have evolved over time. Moreover, I have become more aware over time of when I might be vulnerable (through System 1) to the power of suggestion or to a subconscious desire to align with groupthink, though given that it is System 1, I am not necessarily aware of these things until later (thinking about these things through System 2). Finally, especially over the last several years, I have come to see many things at a very broad conceptual/philosophical level, whether the experiences in my own life, the evolution of different aspects of human society, or the expansion of human knowledge, in terms of perdurantism [LINK from Wikipedia]; although I am not philosophically sophisticated enough to be able to think through & defend all of its implications, it intuitively makes sense to me to think about personal identities, feelings, people, and other things that can be said to exist, in terms of their existence in spacetime and not just in space at specific instants of time. Because of my philosophical inclination in this way, I was particularly pleased to see the author discuss the idea of time-integrated pleasure or pain and of looking at changing identities or overall life courses in terms of spacetime.

Although this book is not technical at the level of an academic journal article, it is fairly technical compared to most nonfiction books aimed at the general public, so I would say that it is aimed at a well-educated reader. That said, I do think that it is written with reasonable clarity for non-academic audiences. Additionally, the book covers many topics, and it is recommended to bear in mind the headings of sections that comprise groups of chapters, because otherwise, it is easy to lose track of the narrative of the book, especially because the book is long enough that I suspect that it would be impossible for most readers (even those who read books, including more technical nonfiction books, relatively quickly) to finish this book in one sitting. I would say that the concluding chapter is a nice way to reinforce the main points of the book in the reader's mind and that the details of each chapter can be treated as a reference when needed as opposed to forming a perfectly coherent narrative in the progression of chapters in the book.

It is important to remember that some aspects of this book are out of date. In some cases, that is just because this book was published in 2011 and had been written over many years before that; for example, the author gives an example of estimating the likelihood of choosing a particular major in college, but that example uses base rates that seem to be quite out-of-date. In other cases, the book is out of date because it is based on academic experimental work in psychology & behavioral economics, and other studies may find contradictory (either null or opposite) results to those presented in this book. The Wikipedia article about this book [LINK] discussed how most of the results from most of the studies discussed in one chapter (as an example) have been found to be not replicable, with the author afterwards admitting to putting too much faith in those studies and therefore falling prey to the same biases as those discussed in that chapter & elsewhere in the book. As a slightly different example, later parts of the book discuss the ideas of nudge theory and its seeming successes in public policy, but the Wikipedia article about nudge theory [LINK] has pointed out that later studies & meta-analyses have found that after correcting for publication biases in favor of positive results & against null results, nudging does not yield statistically significant (non-null) effects on human behavior; in this case, one of the primary researchers (who is named in this book as a collaborator of the author & pioneer of nudge theory) has made some counterarguments that I don't find convincing.

With these caveats in mind, I would still recommend this book to anyone interested in these ideas and with the patience to carefully consider them, though this may partly reflect my own biases in how I view issues of identity & the world. Follow the jump to see my other assorted & disjointed thoughts about this book.

2017-04-18

Book Review: "Weapons of Math Destruction" by Cathy O'Neil

I've recently read Weapons of Math Destruction by Cathy O'Neil. It is a short but dense exposition into the various ways that computer algorithms can determine the courses of people's lives and exacerbate existing societal inequities and biases/prejudices, in areas like education, civic engagement, education, health at the workplace, and many others. It argues that while many algorithms used in big data can be used for good, many instead widen inequalities and reinforce various cycles of poverty because of their opacity, lack of accountability, poor use of statistics, and lack of critical examination by those in charge (who instead use results and predictions generated by such algorithms to fire workers, deny opportunities to potential employees, financially prey on poor people, and so on, making such predictions self-fulfilling prophecies as only confirmatory data is fed back in); in particular, many of these algorithms and models use questionable proxies to predict certain attributes or behaviors (especially when the desired attributes are hard to quantify but the proxies are easy), these models are rarely transparent in what inputs are collected and how they are manipulated to produce outputs, and further research and fine-tuning are rarely performed to correct models that most humans would recognize produce incorrect results (but which computers would miss). It concludes that extensions of existing regulations on use of health and financial data are needed to curtail the misuse of such algorithms, and that simultaneously data scientists need to be scrupulous about the ways that their work is used and developed.

I rather enjoyed reading this book: it's pretty fast-paced, yet gives many detailed examples of the abuse of these algorithms to form a compelling narrative. Additionally, it in many ways follows the book The Attention Merchants by Tim Wu (which I have previously reviewed), because as that book shows the various ways that companies collect and sell customer data, this book shows the various ways that data can be used for the benefit of those companies (even if that works against some of those customers). There are only two issues that I have with this book. One is that the few times that politics comes up, the author's political bias (in favor of liberals in the US) is obvious; perhaps this is just due to the nature of the author's passionate crusade against abuse of algorithms and for institutional action uplifting poor and marginalized people, as that would necessitate regulation of such mathematical instruments, which would be (and has been) loudly opposed by large corporations maintaining their short-term profits and long-term status quo through these algorithms as well as the conservative politicians that they support. The other is that there aren't too many examples of big data and related algorithms truly working toward greater socioeconomic equity, especially when such algorithms are finding patterns that wouldn't be found by humans; while I get that the author is trying to build a brief but dense narrative warning against the excesses and abuses of such algorithms (as she professes herself to not be a big data evangelist), I would have liked to see more nuanced examples of proper uses of big data, because as this book stands, it seems just as one-sided/polemical as uncritical big data evangelism. Overall, I certainly feel like I got a better sense of the potential dangers of unchecked and uncritical use of algorithms to shape the economy and society. Plus, now that I'm about halfway through my PhD, I've started to think more about the sorts of jobs that I'd like to take after I finish. I've decided that I don't want to go into finance because (as mentioned in this book too) I'm not comfortable with playing with other people's money, as it is too easy to be seduced by mathematical simplicity and elegance into doing questionable things. That said, one thing (among the many) that has caught my fancy has been studies of policy problems (especially as related to STEM fields, but as they affect ordinary people); however, the story in this book about the role of the Mathematica Policy Research company in developing the arbitrary and statistically unsound metrics for evaluating teachers in DC public schools has made me realize that I'll need to make sure if I end up joining a policy research organization/consultancy/think tank that the organization that I join is responsible and transparent about the data that it collects and processes as much as possible.

2010-12-26

Featured Comments: Week of 2010 December 19

Unfortunately, there were no comments on articles from the previous week (2010 December 12), so there was no accompanying "Featured Comments" article. That can be attributed to the fact that I wrote very few posts that week. Anyway, there were a whole bunch of comments this past week, so I can only post a couple.

Review: Slackware 13.1

There were many comments about this, so I'll post a couple, as well as my responses to them.
An anonymous reader writes, "You never even talked about this distro whatsoever. You just complained about what stuff you were used to that slackware didnt have. if every distro was the same then there would be one distro. Slackware is one of the most stable distros still surviving. You want a extremely stable distro here it is. While i agree that there is no dependacy checking, if you are going to slackware you are usually semi good at the command line and usually know how to install a program anyhow. so its "your" job to do it."
Reader Hannes Worst had this to say: "I think it's an ultimately unfair review. It only states the preferences of the writer and nothing about Slackware. It's like someone allergic to fruit writes a review about apples. From the first sentence on prejudice is shown. When you aren't capable of exploring and researching Slackware, don't write a review about it."
To the anonymous reader, I ask, if complaining about what isn't in the distribution isn't saying something about the distribution itself, then what is? Also, the last point leads me into my response to Hannes Worst.
I may not have made it clear in the review itself, but relatively speaking, I am a newbie to Linux. I like using Linux a lot, but I still have neither the skills nor the patience to work with something like Slackware for a long time just to get it working. I had a feeling that my experience wouldn't turn out so well for this very reason. But I wanted to test this feeling, so I did; I then wrote about the experience. Please tell me: what exactly is wrong with that? I figured that I made it abundantly clear that my issues with Slackware were never meant to reflect poorly on Slackware; quite the opposite: they reflect poorly on me as a Linux user.
I hope all that is cleared up. Next!

Familiarity Breeds Fondness, not Contempt

Reader T_Beermonster had this to say: "Probably the big one for me is the package manager. I've just got so used to APT over the years that I find other (probably equally good) systems don't feel right. Kind of like getting into someone else's car, the biting point is wrong and the seat is the wrong hight." I feel the same way as well, but I must ask, what about when familiar front-ends are applied to different back-ends? For example, PCLinuxOS uses RPMs in the back-end, but its GUI package manager is the familiar Synaptic. How would you feel about using that there? Or am I missing the point entirely?

Bad Experiences are Forever

Reader T_Beermonster wrote a long diatribe against Apple's Macs: "I have a visceral loathing of Apple Macs - not the hardware which in recent times has been quite attractive looking (if overpriced/underspecced). It's the OS."

FOLLOW-UP: Linux and Breakfast Cereals

Commenter twitter had this to say: "Diversity and choice are good, restrictions are bad. Despite the differences between distributions, they all share the same core of free software and all of it tailored to a wide variety of hardware architectures. That means that users get the software they want on the platform they want. Skype is difficult because it is not free software and the company has to do all the hard work of packaging things themselves. If you want Skype to work as well as Mozilla, ask Skype to liberate their code and rely on an honest service model that does not demand undue power over users."

Well, that's all for this week. I hope all the confusion surrounding my motivations regarding the Slackware review are cleared up, and I sincerely apologize for not delivering adequately to those who were expecting a more substantive level appropriate for an intermediate or advanced Linux user trying Slackware. As always, if you like the content, please continue commenting and subscribing. Finally, happy holidays!

2009-09-09

Socialist Education! Oh noes!

The big news this week was President Obama's address to students of all ages and their parents about education.
The bigger news was that prominent Republicans were lambasting it before they even knew what it was going to say. They claimed that Obama was going to "indoctrinate" schoolchildren in "leftist socialist ideologies".
Then, of course, Obama gave his speech. It was a speech that made sense - it was about students taking responsibility for their own education and for them to keep trying at it even when the going gets tough.
There was no hint of liberal ideology. In fact, personal responsibility is something many (now deceased) rational conservatives used to espouse. They should be proud.
Furthermore, the same conservatives who blasted the speech prior to its delivery without any basis changed course and praised it afterwards without any apology for bad prior judgment.
Why is this?