Can objects be evil? A review of “Addiction by Design”

Bliss by Sean O'Brien
Bliss by Sean O’Brien

Schüll, Natasha Dow. (2012) Addiction by Design: Machine Gambling in Las Vegas. Princeton: Princeton University Press.

Addiction by Design is a nonfiction page-turner. A richly detailed account of the particulars of video gaming addiction, worth reading for the excellence of the ethnographic narrative alone, it is also an empirically rigorous examination of users, designers, and objects that deepens practical and philosophical questions about the capacities of players interacting with machines designed to entrance them. Many books that make worthy contributions to the theoretical literature of a particular field are slogs to read. Addiction by Design is as compelling as a horror story—a sad, smart horror story that calls off the Luddite witch hunt (Down with the machines!) in favor of an approach that examines the role of gaming designers within existing social systems of gender and class disparity.

The most popular gaming machines serve up video slots and video poker. They run on paycards because inserting cash and coinage slows down the rate of play, compromising the experience. By the mid-1990s in Las Vegas, Schüll reports, the vast majority of people at Gamblers Anonymous meetings were addicted to machines—not the table games, ponies, or lotteries previously associated with problem gambling. In 2003 it was estimated that 85 percent of industry profits nationally came from video gaming. For the people (mostly women) who become addicts, the draw of the machines has little to do with the possibility of winning big. Problem gamblers are attracted to the machines because they offer portals to an appealing parallel universe in which they can disconnect from the anxieties and pressures of everyday life. One of Schüll’s interviewees, Mollie, explains, “It’s like being in the eye of a storm, is how I’d describe it. Your vision is clear on the machine in front of you but the whole world is spinning around you, and you can’t really hear anything. You aren’t really there—you’re with the machine and that’s all you’re with.”

woman playing video slots
Woman playing video slots, 2010, Copyright Kate Krueger

Mollie’s experience is typical in at least two ways. First, she has a traumatic past that predisposes her to addictive behaviors. Second, she repeatedly spends all that she has in binges. But before we blame Mollie and other victims and then expound the benefits of 12-step programs with earnest optimism, Schüll asks readers to consider the insidious dependencies that arise between machine designers, casino owners, and gamblers, especially “problem gamblers,” whose struggle to control personal spending generates 30 to 60 percent of casino revenue. Schüll’s Addiction systematically builds on her basic argument that, “just as certain individuals are more vulnerable to addiction than others, it is also the case that some objects, by virtue of their unique pharmacologic or structural characteristics, are more likely than others to trigger or accelerate an addiction.”

Schüll describes the progression of changes the industry has introduced in search of higher profits. For a while, ergonomics was economics. Then high-priced animators were hired to design pleasing sounds and animations to reward winners. But some players were annoyed that the animations were too slow, so the animations were dropped. Play sped up. Faster play was great for increasing dopamine delivery to the brain. It also tended to speed players toward the end of their credits, which lowered their loyalty to particular machines and the casinos that housed them. Chip-driven gaming allowed designers to respond to this problem by tweaking the programs so that frequent small wins (often less than the cost of playing a single hand) kept dopamine surging while players’ cash trickled steadily into casino coffers. One player in a gambling support group compared video machines to crack cocaine, a comparison frequently repeated by researchers and psychologists.[1] By some accounts, the recidivism rate is now higher for gambling than for any other addiction.

The demons here are not the machines, though they are manifest in the machines. The demons are not the people who design the machines nor the people who build palaces in which the machines are arrayed in blinking, burbling gardens of vertiginous electronica. The demons are not located in the players’ genes or childhoods. The demons are not the state regulators who now embrace video gaming after corralling it on American Indian reservations for decades. There is no single devil here, and no particular exorcism can right the wrong, but there is something devilish about the way designers’ intentions and users’ neurology meet up to make video gaming so devastating for some and so profitable for others.

[1] Mary Sojourner, She Bets Her Life: A True Story of Gambling Addiction (New York: Seal Books, 2010).

This review is cross-posted at publicbooks.org, a new book review and visual essay website affiliated with Public Culture, a peer-reviewed academic journal.

My summer internship: On finding gender

I showed up at NERD with a set of questions about the relationship between making physical things, producing information, and being part of a community of peers that I thought I could answer by looking at food blogs. I knew only a little about food bloggers so I decided I had better start with macro-level questions about the size and network structure of the food blogosphere, mid-range questions about the demographics of food blogs and food bloggers, and then arrive at the juicier questions about how and why food bloggers do what they do.

Methodologically those questions translated to:

  1. a network crawler
  2. a survey
  3. semi-structured interviews
  4. hanging out on the blogs and twitter

In terms of publications, I was always aiming for a book, a whole stinking book.

Here’s what actually happened.

The crawler never made it in to MSR because it was deemed too risky. An intern in some other group had run a badly behaved crawler last year and Microsoft Research was not ready to go down that road again. Fine. I ran it from home with help from my CS friend.

I got lots of feedback on the survey from the entire SMC group which resulted in a shorter, tighter instrument overall. After disheartening reports that food bloggers had to fish my emailed invitation out of their spam folders, I leaned on twitter and ended up with a response rate better than 30%. As a complete stranger, it was easier to look like a real person on twitter than it was over email. Go figure.

Speaking of meeting strangers, I spent the majority of my summer interviewing 27 food bloggers about why and how they blogged about food. What mattered to them turned out to be writing, photography, and the reliability of the recipe not the taste, smell, or other physical qualities of food. I was so excited to hear about the privileging of food information over the food itself because my initial interest was in the way that the physical process of making and eating food related to the process of producing the information to recreate that experience in one way or another.

What I started to realize (like a dummy who cannot see what it right in front of her) was that the way food blogs are produced has a lot to do with the gendered history of food production. Women have historically been home cooks while professional kitchens are populated mostly by men (and even if they aren’t populated by men, they are some of the most hypermasculine spaces I have ever been in. Thank you, dissertation field work.) Devoting time and energy to the production of *information* about food in the form of writing and photography has a different gender-valence than producing food for friends family, or oneself in home kitchens. Food blogs bring the food out of the home into the public sphere, a step away from the feminine space of the kitchen, into the masculine space of participatory discourse. This move away from the feminine is further emphasized by the way food bloggers dedicate energy to writing, photography, and the technics of blogging.

Male food bloggers are few in number and I was only able to interview three of them (I am aiming to get at least three more men to speak with me). The three I talked to were all fairly ‘advanced’ food bloggers who had either been doing it for a long time or had quit their day jobs to do it or some combination of both. They all identified themselves as food professionals from the beginning of the interviews – one referred to himself as the father of food blogging. The women usually talked about the importance of external recognition in the process of professionalizing; the men I interviewed simply adopted whatever professional title they aspired to have without too much dallying in the ‘becoming’ phase.

I went into this project with the hunch that by situating my gaze at a border crossing – from the physical to the digital – I would be able to have a deeper understanding of the importance of tangibility and the cultural capital of information in relation to the physical. While that may not be exactly what I found, I think I was able to reveal something about the way gender is both structured and structuring. I chalk it up to the decision to sit at that border crossing – watching assumptions that hold up in one context fail to be translated in a different context is a good way to figure out what is holding up those assumptions in the first place.

It’s not all that surprising that by looking at a historically gendered practice – food production – I ended up finding out about the relationship between gender and professionalism. I’m so excited to write this research up – have three articles and a chapter in mind.

_*_*_*_*_

Before I head back to Brooklyn, I want to share my gratitude for the opportunity to be part of the intellectual community at Microsoft Research this summer. I recommend this internship without reservation to anyone interested in studying what happens on screens and between screens, especially when those screens are computer screens. The intellectual community is phenomenal, the space is better than any university I have ever seen, and the amount of work that fits into a day here is simply greater than what fits into a day back in my department.

Dissertation to book proposal: Four rules of thumb

We had an informative discussion with Margy from MIT Press today who was kind enough to talk with us about scholarly publishing from the perspective of an academic press. She was generous with her time (and with her back – she lugged some heavy books into the meeting for show and tell) and one list she shared with us is probably of general interest to some of the people who read this blog.

Jessa asked her for the top three things someone should NOT do when submitting a book proposal based on their dissertation and Margy did her one better and had four recommendations.

From dissertation to book proposal: Four rules of thumb


  1. Do not use the word “dissertation” anywhere in your proposal.
  2. Honestly describe the audience for your book. Avoid saying that it will both advance a scholarly field and appeal to a general audience. Generally speaking, the book is either going to be a trade book with a wide appeal or it is going to be a professional book that will have a narrower appeal but make a rigorous scholarly contribution.
  3. Be clear about how your book fits into the existing scholarly literature about your topic. Give examples of books that your book will be like.
  4. Read the proposal guidelines carefully. Different presses have similar though not identical requirements. Follow the guidelines (e.g. MIT Press guidelines). They exist for a reason.

Blog reading and writing by gender, 2000-2010

Blog reading and writing by gender, 2000 - 2010 graph | Pew Internet
Blog reading and writing by gender, 2000 - 2010 | Pew Internet

Gender and blogging

Why is food blogging so dominated by women? I don’t have exact results on this question back yet so I cannot tell you precisely how female-dominated the food blogs are, but I would confidently bet that 85% or more are written by women.

So that got me thinking: are blogs in general female-dominated?

I already knew that was not true – political blogs and tech blogs are often written by men. But I wanted to know with some evidence better than my own hunch just what the gender balance in blogging is overall. As you can see above, it’s pretty evenly split these days. About 14% of women and 14% of men contributed to their own blog or online journal the last time Pew asked that question. This shows us that blogging itself is not the gendered-gate. Equal amounts of men and women are making it into the practice of blogging but the content they blog is refracted through a gendering lens. Women appear to dominate not only food blogs but also baby blogs (aka mommy blogs), fashion blogs, and design blogs. Men appear to dominate political and tech blogs.

This study is not the only one that comes in and disproves the idea that cyber communities are doing the work of revolutionizing gender practice. But it will offer another drop in the bucket. Thanks to Pew’s long-standing commitment to researching the internet, I can at least assure myself in this case, that it isn’t technology itself which produces gendered practices. Women and men are equally likely to post blogs. They just end up in gender-homogenous topical arenas in the blogosphere.

Infographics as research tools

Food Blog Study | Linear Growth Diagram
Food Blog Study | Linear Growth Diagram

I have a potentially unhealthy obsession with information graphics. It took me a good chunk of the day to make the graphics in this post and while part of the motivation behind making them was to have something visual to post on this blog (which could have been accomplished in *much* less time), there was also a methodological motivation. I wanted to find a way to make infographics that were not only good at illustrating a point for readers, but also analytically helpful.

Here’s the challenge: the project I’m working on this summer utilizes a web crawler to scrape the connections among tens of thousands of food blogs from ye olde interwebs. This is a methodology that I have not used in the past. As anyone who has done something like this before has told me, the web crawler will pretty much just keep going and going even with the constraints that are built into it. It never sits back on its haunches and pops out a message that says something like, “That’s it, lady, the whole network is yours for the examining”. It does not tell me when it is done, I tell it when to stop. If I cut it off too soon, I risk performing analysis on an incomplete network, one that I erroneously believe to be more or less all there. If I cut it off too late, I risk building a noisier dataset, wasting time, and generating a larger database that could crash my software or my computer altogether. (I speak from experience. I have already run Excel into the ground repeatedly, something that made me proud considering how robust Excel is.)

When thinking about how to tell when the web crawler is done, I find it is helpful to think of asymptotes.

So, thinking of asymptotes, I realized that there must be some function that I could plot, a graph I could make based on the information I have about the ongoing behavior of the crawler, that would help me visualize its state of approaching done-ness. [Pardon my free reign in the word creation department. I prefer the incorrect ‘done-ness’ over the grammatically superior ‘completeness’.] My first attempt at graphing was not the burgeoning eggs you see above, it was the top half of the graph below. The eggs just turned out to be more interesting to look at and they provide just about as much useful information as the top graph (ie not that much useful information from an analytical standpoint).

Food Blog Study | Crawler Progress Graphs
Food Blog Study | Crawler Progress Graphs

The top graph shows cumulative growth in the number of nodes gathered over time – the total number of nodes is around 32,000 as of 19 July. For the eggs, I used the size (in MB) of the output file. Honestly, folks, it doesn’t really matter if I’m looking at megabytes of storage or number of nodes. This absolute size approach is analytically vacant – it does not help me determine done-ness of crawling activity. It tells me that the crawler is still gathering new nodes that pass the food blog test. Yes, I already knew that.

How can I tell if I have to spend another 3 days, 10 days, 3 weeks getting up at 5:00 to fiddle with it?

But what I really want to know is whether or not the crawler is slowing down. True enough, math wizards, I can examine the slope of the segments in the top graph and deduce that flatter slopes mean the crawler isn’t adding as many nodes. That is not satisfying enough for me. Visually, it’s not as easy to detect precise slope changes as I would like. I found it was more useful to take the number of new nodes added per crawl session and divide that by the number of hours in that crawl session. That gave me the number of new nodes added per hour of crawl time. The hourly growth rate varies from day to day (sure, it varies from hour to hour but I’m not a stickler here – the average hourly rate for an entire day is sufficiently precise).

I went ahead and plotted these hourly rates. They bounced around more than I thought they would, though they pretty much stay somewhere between 60 and 100 new nodes per hour. The day they dipped to 6 was not a true low, it was an artificial low. On that day I went back and retroactively removed all of the alcohol blogs from the existing collection of nodes because I am not studying wine, beer, or cocktail blogs. I am studying food blogs. So the boozy blogs got the boot and that made it look like the crawler spent that particular day picking its nose or otherwise dawdling. Not the case. The thing about bots is that they are never caught with their fingers up their noses. On the other hand, they may have to be taught to stay away from the swill.

The bottom graph will be more helpful as I try to figure out how the crawler is doing on any given day and if it is starting to approach an asymptote of a single digit new node augmentation rate.

If this post had a moral it would be: don’t be afraid to try new methods both at the macro-scale (like adding social network analysis to your methodological quiver) and at the micro-scale (like trying to use infographics to help guide your research).