Tag Archives: science/technology

Apple’s Health App: Where’s the Power?

In truth, I didn’t pay a tremendous amount of attention to iOS8 until a post scrolled by on my Tumblr feed, which disturbed me a good deal: The new iteration of Apple’s OS included “Health”, an app that – among many other things – contains a weight tracker and a calorie counter.

And can’t be deleted.

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Okay, so why is this a big deal? Pretty much all “health” apps include those features. I have one (third-party). A lot of people have one. They can be very useful. Apple sticking non-removable apps into its OS is annoying, but why would it be something worth getting up in arms over? This is where it becomes a bit difficult to explain, and where you’re likely to encounter two kinds of people (somewhat oversimplified, but go with me here). One group will react with mild bafflement. The other will immediately understand what’s at stake.

The Health app is literally dangerous, specifically to people dealing with/in recovery from eating disorders and related obsessive-compulsive behaviors. Obsessive weight tracking and calorie counting are classic symptoms. These disorders literally kill people. A lot of people. Apple’s Health app is an enabler of this behavior, a temptation to fall back into self-destructive habits. The fact that it can’t be deleted makes it worse by orders of magnitude.

So why can’t people just not use it? Why not just hide it? That’s not how obsessive-compulsive behavior works. One of the nastiest things about OCD symptoms – and one of the most difficult to understand for people who haven’t experienced them – is the fact that a brain with this kind of chemical imbalance can and will make you do things you don’t want to do. That’s what “compulsive” means. Things you know you shouldn’t do, that will hurt you. When it’s at its worst it’s almost impossible to fight, and it’s painful and frightening. I don’t deal with disordered eating, but my messed-up neurochemistry has forced me to do things I desperately didn’t want to do, things that damaged me. The very presence of this app on a device is a very real threat (from post linked above):

Whilst of course the app cannot force you to use it, it cannot be deleted, so will be present within your apps and can be a source of feelings of temptation to record numbers and of guilt and judgement for not using the app.

Apple doesn’t hate people with eating disorders. They probably weren’t thinking about people with eating disorders at all. That’s the problem.

Then this weekend another post caught my attention: The Health app doesn’t include the ability to track menstrual cycles, something that’s actually kind of important for the health of people who menstruate. Again: so? Apple thinks a number of other forms of incredibly specific tracking were important enough to include:

In case you’re wondering whether Health is only concerned with a few basics: Apple has predicted the need to input data about blood oxygen saturation, your daily molybdenum or pathogenic acid intake, cycling distance, number of times fallen and your electrodermal activity, but nothing to do with recording information about your menstrual cycle.

Again: Apple almost certainly doesn’t actively hate cisgender women, or anyone else who menstruates. They didn’t consider including a cycle tracker and then went “PFFT SCREW WOMEN.” They probably weren’t thinking about women at all.

During the design phase of this OS, half the world’s population was probably invisible. The specific needs of this half of the population were folded into an unspecified default. Which doesn’t – generally – menstruate.

I should note that – of course – third-party menstrual cycle tracking apps exist. But people have problems with these (problems I share), and it would have been nice if Apple had provided an escape from them:

There are already many apps designed for tracking periods, although many of my survey respondents mentioned that they’re too gendered (there were many complaints about colour schemes, needless ornamentation and twee language), difficult to use, too focused on conceiving, or not taking into account things that the respondents wanted to track.

Both of these problems are part of a larger design issue, and it’s one we’ve talked about before, more than once. The design of things – pretty much all things – reflects assumptions about what kind of people are going to be using the things, and how those people are going to use them. That means that design isn’t neutral. Design is a picture of inequality, of systems of power and domination both subtle and not. Apple didn’t consider what people with eating disorders might be dealing with; that’s ableism. Apple didn’t consider what menstruating women might need to do with a health app; that’s sexism.

The fact that the app cannot be removed is a further problem. For all intents and purposes, updating to a new OS is almost mandatory for users of Apple devices, at least eventually. Apple already has a kind of control over a device that’s a bit worrying, blurring the line between owner and user and threatening to replace one with the other. The Health app is a glimpse of a kind of well-meaning but ultimately harmful paternalist approach to design: We know what you need, what you want; we know what’s best. We don’t need to give you control over this. We know what we’re doing.

This isn’t just about failure of the imagination. This is about social power. And it’s troubling.

Sarah Wanenchak is a PhD student at the University of Maryland, College Park. Her current research focuses on contentious politics and communications technology in a global context, particularly the role of emotion mediated by technology as a mobilizing force. She blogs at Cyborgology, where this post originally appearedand you can follow her at @dynamicsymmetry.

The No. 1 Cause of Traffic Fatalities? It’s Not Texting, It’s Driving

I don’t yet have a copy of Matt Richtel’s new book, A Deadly Wandering: A Tale of Tragedy and Redemption in the Age of Attention. Based on his Pulitzer-prize winning reporting for the New York Times, however, I’m afraid it’s unlikely to do justice to the complexity of the relationship between mobile phones and motor vehicle accidents. Worse, I fear it distracts attention from the most important cause of traffic fatalities: driving.

A bad sign

The other day Richtel tweeted a link to this old news article that claims texting causes more fatal accidents for teens than alcohol. The article says some researcher estimates “more than 3,000 annual teen deaths from texting,” but there is no reference to a study or any source for the data used to make the estimate. As I previously noted, that’s not plausible.

In fact, only 2,823 teens teens died in motor vehicle accidents in 2012 (only 2,228 of whom were vehicle occupants). So, I get 7.7 teens per day dying in motor vehicle accidents, regardless of the cause. I’m no Pulitzer-prize winning New York Times journalist, but I reckon that makes this giant factoid on Richtel’s website wrong, which doesn’t bode well for the book:

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In fact, I suspect the 11-per-day meme comes from Mother Jones (or someone they got it from) doing the math wrong on that Newsdaynumber of 3,000 per year and calling it “nearly a dozen” (3,000 is 8.2 per day). And if you Google around looking for this 11-per day statistic, you find sites like textinganddrivingsafety.com, which, like Richtel does in his website video, attributes the statistic to the “Institute for Highway Safety.” I think they mean the Insurance Institute for Highway Safety, which is the source I used for the 2,823 number above. (The fact that he gets the name wrong suggests he got the statistic second-hand.) IIHS has an extensive page of facts on distracted driving, which doesn’t have any fact like this (they actually express skepticism about inflated claims of cellphone effects).

After I contacted him to complain about that 11-teens-per-day statistic, Richtel pointed out that the page I linked to is run by his publisher, not him, and that he had asked them to “deal with that stat.” I now see that the page includes a footnote that says, “Statistic taken from the Insurance Institute for Highway Safety’s Fatality Facts.” I don’t think that’s true, however, since the “Fatality Facts” page for teenagers still shows 2,228 teens (passengers and drivers) killed in 2012. Richtel added in his email to me:

As I’ve written in previous writings, the cell phone industry also takes your position that fatality rates have fallen. It’s a fair question. Many safety advocates point to air bags, anti-lock brakes and wider roads — billions spent on safety — driving down accident rates (although accidents per miles driven is more complex). These advocates say that accidents would’ve fallen far faster without mobile phones and texting. And they point out that rates have fallen far faster in other countries (deaths per 100,000 drivers) that have tougher laws. In fact, the U.S. rates, they say, have fallen less far than most other countries. Thank you for your thoughtful commentary on this. I think it’s a worthy issue for conversation.

I appreciate his response. Now I’ll read the book before complaining about him any more.

The shocking truth

I generally oppose scare-mongering manipulations of data that take advantage of common ignorance. The people selling mobile-phone panic don’t dwell on the fact that the roads are getting safer and safer, and just let you go on assuming they’re getting more and more dangerous. I reviewed all that here, showing the increase in mobile phone subscriptions relative to the decline in traffic accidents, injuries, and deaths.

That doesn’t mean texting and driving isn’t dangerous. I’m sure it is. Cell phone bans may be a good idea, although the evidence that they save lives is mixed. But the overall situation is surely more complicated than TEXTING-WHILE-DRIVING EPIDEMIC suggests. The whole story doesn’t seem right — how can phones be so dangerous, and growing more and more pervasive, while accidents and injuries fall? At the very least, a powerful part of the explanation is being left out. (I wonder if phones displace other distractions, like eating and putting on makeup; or if some people drive more cautiously while they’re using their phones, to compensate for their distraction; or if distracted phone users were simply the worst drivers already.)

Beyond the general complaint about misleading people and abusing our ignorance, however, the texting scare distracts us (I know, it’s ironic) from the giant problem staring us in the face: our addiction to private vehicles itself costs thousands of lives a year (not including the environmental effects).

To illustrate this, I went through all the trouble of getting data on mobile phone subscriptions by state, to compare with state traffic fatality rates, only to find this: nothing:

cellphones traffic deaths with NEJM.xlsx

What does predict deaths? Driving. This isn’t a joke. Sometimes the obvious answer is obvious because it’s the answer:

cellphones traffic deaths with NEJM.xlsx

If you’re interested, I also put both of these variables in a regression, along with age and sex composition of the states, and the percentage of employed people who drive to work. Only the miles and drive-to-work rates were correlated with vehicle deaths. Mobile phone subscriptions had no effect at all.

Also, pickups?

Failing to find a demographic predictor that accounts for any of the variation after that explained by miles driven, I tried one more thing. I calculated each state’s deviation from the line predicted by miles driven (for example Alaska, where they only drive 6.3 thousand miles per person, is predicted to have 4.5 deaths per 100,000 but they actually have 8.1, putting that state 3.6 points above the line). Taking those numbers and pouring them into the Google correlate tool, I asked what people in those states with higher-than-expected death rates are searching for. And the leading answer is large, American pickup trucks. Among the 100 searches most correlated with this variable, 10 were about Chevy, Dodge, or Ford pickup trucks, like “2008 chevy colorado” (r = .68), shown here:

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I could think of several reasons why places where people are into pickup trucks have more than their predicted share of fatal accidents.

So, to sum up: texting while driving is dangerous and getting more common as driving is getting safer, but driving still kills thousands of Americans every year, making it the umbrella social problem under which texting may be one contributing factor.

I used this analogy before, and the parallel isn’t perfect, but the texting panic reminds me of the 1970s “Crying Indian” ad I used to see when I was watching Saturday morning cartoons. The ad famously pivoted from industrial pollution to littering in the climactic final seconds:

Conclusion: Keep your eye on the ball.

Philip N. Cohen is a professor of sociology at the University of Maryland, College Park, and writes the blog Family Inequality. You can follow him on Twitter or Facebook.

When Wild Animals Use Human Technology… and the End of Times

Forgive me, because this is probably better left to Cyborgology, but something amazing is happening here. In the video below, nesting swallows become trapped in a building when they add doors. The birds soon learn, though, that they can get the doors to automatically open by triggering the motion sensors. This is a story, obviously, of how smart birds are, but here’s what struck me: we often think about human technology as for humans. In this case, however, birds adapted the technology for their own very similar needs (to get in and out).

If the workers had installed an older human technology — plain old doors — the birds would have been out of luck because they don’t have thumbs and the strength to manipulate an environment built for humans. But motion activated doors make both thumbs and strength irrelevant, so now birds are our functional equals.

This is fascinating, yeah? Our technology has advanced to the point where we’re potentially undermining our own evolutionary advantages. I’m not putting a moral judgment on it. I think morality is firmly on the side of non-fitness based decisions (eh em, social Darwinism). If one wants to theorize the relationship between animals, technology, and what it means to be human, however, this looks like gold to me.

Okay Cyborgology, your turn.

Thanks to Reuben S. for the tip! Cross-posted at Pacific Standard.

Lisa Wade is a professor of sociology at Occidental College and the co-author of Gender: Ideas, Interactions, Institutions. You can follow her on Twitter and Facebook.

Tuskegee Syphilis Study Recruitment Letter

Flashback Friday.

The Tuskegee Syphilis Experiment is one of the most famous examples of unethical research. The study, funded by the federal government from 1932-1972, looked at the effects of untreated syphilis. In order to do this, a number of Black men in Alabama who had syphilis were misinformed about their illness. They were told they had “bad blood” (which was sometimes a euphemism for syphilis, though not always) and that the government was offering special free treatments for the condition. Here is an example of a letter sent out to the men to recruit them for more examinations:

The “special free treatment” was, in fact, nothing of the sort. The researchers conducted various examinations, including spinal taps, not to treat syphilis but just to see what its effects were. In fact, by the 1950s it was well established that a shot of penicillin would fully cure early-stage syphilis. Not only were the men not offered this life-saving treatment, the researchers conspired to be sure they didn’t find out about it, getting local doctors to agree that if any of the study subjects came in they wouldn’t tell them they had syphilis or that a cure was available.

The abusive nature of this study is obvious (letting men die slow deaths that could have been easily prevented, just for the sake of scientific curiosity) and shows the ways that racism can influence researchers’ evaluations of what is acceptable risk and whose lives matter. The Tuskegee experiment was a major cause for the emergence of human subjects protection requirements and oversight of federally-funded research once the study was exposed in the early 1970s. Some scholars argue that knowledge of the Tuskegee study increased African Americans’ distrust of the medical community, a suspicion that lingers to this day.

In 1997 President Clinton officially apologized for the experiment.

Originally posted in 2009.

Gwen Sharp is an associate professor of sociology at Nevada State College. You can follow her on Twitter at @gwensharpnv.

“Black and White Twins” and the Social Construction of Race

Flashback Friday.

This remarkable newspaper article illustrates how skin color (which is real) gets translated into categorical racial categories (which are not).  The children in the images below — Kian and Remee Hodgson – are fraternal twins born to two bi-racial parents:

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The story attempts to explain the biology:

Skin colour is believed to be determined by up to seven different genes working together. If a woman is of mixed race, her eggs will usually contain a mixture of genes coding for both black and white skin. Similarly, a man of mixed race will have a variety of different genes in his sperm. When these eggs and sperm come together, they will create a baby of mixed race.  But, very occasionally, the egg or sperm might contain genes coding for one skin colour. If both the egg and sperm contain all white genes, the baby will be white. And if both contain just the versions necessary for black skin, the baby will be black.

Fair enough.

But then the journalist makes a logical leap from biological determinants of skin color to racial categories. Referring now to genes for skin color as “black” and “white” genes, she writes: “Baby Kian must have inherited the black genes from both sides of the family, whilst Remee inherited the white ones.”  And, of course, while both children are, technically, mixed race*, the headline to the story, “Black and White Twins,” presents them as separate races.

We’re so committed to racial differences that the mother actually speaks about their similarities as if it is surprising that twins of different “races” could possibly have anything in common.  She says:

There are some similarities between them. They both love apples and grapes, and their favourite television programme is Teletubbies.”

This is also a nice example of a U.S.-specific racial logic. This might not have been a story in Brazil at all, where racial categories are determined more by color alone and less by who your parents are.  It is not uncommon there to have siblings of various racial designations.

The twins, by the way, are seven now.

* Of course, identifying them as mixed race also re-inscribes racial categories in that you must believe in two or more racial categories to believe that it is possible to mix them.

Originally posted in 2008.

Lisa Wade is a professor of sociology at Occidental College and the co-author of Gender: Ideas, Interactions, Institutions. You can follow her on Twitter and Facebook.

A Simple Lesson on the Social Construction of Race

Flashback Friday.

The images below are all screen shots from the fantastic American Anthropological Association website on race.  They are designed to show how we take what is in reality a nuanced spectrum of skin color and turn it into racial categories.  In this first image, they show how we could, conceivably, separate human beings into short, medium, and tall based on height:

In this second image, they show how, by adding two additional figures, both taller than the tallest in the previous image, the way in which we designate people can easily change.

And this third image demonstrates how, when we actually consider all potential heights, where we draw the line between short and medium and medium and tall is arbitrary and, ultimately, not very useful.

Skin color is like height.  If we just look at three groups with very different skin colors, there appears to be a significant and categorical difference between those three groups of people.

But, if we consider a wide range of people, it becomes clear that skin color comes in a spectrum, not in categories (such as the five from which U.S. citizens are forced to choose on the census).

Much more on the social construction of race at our Pinterest board.

This post originally appeared in 2008.

Lisa Wade is a professor of sociology at Occidental College and the co-author of Gender: Ideas, Interactions, Institutions. You can follow her on Twitter and Facebook.

One Hundred Years of the Fridge

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Since their invention in 1913, and since this Kelvinator ad first ran in 1955, refrigerators became bigger, better, and went from a luxury to a necessity. It’s nearly impossible to imagine life today without having somewhere to store your vegetables and a place to keep your leftovers: in the one hundred years it’s been around, the fridge altered our grocery shopping habits and our attitudes towards food.

Appliance companies and advertisers worked hard to transform refrigerators from “a brand new concept in luxurious living” to an everyday household object. They succeeded in the 1960s, after years of fine-tuning its features to appeal to the middle-class housewife, writes historian Shelley Nickles. Besides ensuring the fridges were spacious, easy to clean, and had adjustable shelving, designers even took care of minutiae such as including warmer compartments – so that the butter kept in them would be easier to spread. Having attracted the housewives’ attention and become affordable with ideas such as government-sponsored fridges floating around, the appliances made their way into middle-class homes.

Buying too many perishable items suddenly became a minor concern. Buy one, get one free! Get more value for your money – purchase a bigger container! As the number of fridge compartments increased, so did the number of refrigeration-dependent foods and “supersize” deals offered in stores (or the other way around). Ultimately, grocery shoppers – mainly women – returned home with more food than they otherwise would have. Fridges enabled families to stock up, and the major weekend grocery haul was born. Now we have this:

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But while having a fridge to store all the groceries made it possible to save more on “deals” at the supermarket, it also enabled us to waste more later on. That is because the fridge operates much like a time machine, but not without its limits. Sociologists Elizabeth Shove and Dale Southerton describe freezers as appliances that allow us to manage time: in addition to no longer having to shop multiple times per week, we can now prepare our meals in advance. The same holds for refrigerators.

Food has its own rhythm, however, and a fridge can only delay the inevitable for so long. Leftovers simultaneously get pushed down in the hierarchy of what we’d like to eat, and pushed back on refrigerator shelf, only to be forgotten and perhaps rediscovered when it’s already too late. An exotic fruit rots in the produce compartment after its exciting novelty wore off, and we were no longer sure what to do with it. And so they all end up in the trash. Domestic food waste only represents part of all the food thrown away in the U.S. today – about a third of all that is produced – but the way fridges altered out food purchasing and consumption habits is partly to blame.

Not all is bad, however. Fridges not only allow us to eat a greater variety of foods and be more efficient in our everyday lives, we use them as centers of communication and managing household life. And as they become smarter, more energy-efficient, and with some individuals refusing to use them altogether, these cultural objects will doubtless have more stories to tell in the next hundred years.

Teja Pristavec is a graduate student in the sociology department, and an IHHCPAR Excellence Fellow,  at Rutgers University. She blogs at A Serving of Sociology, where this post originally appeared.

Newsflash: Facebook has Always Manipulated Your Emotions

Emotional Contagion is the idea that emotions spread throughout networks. If you are around happy people, you are more likely to be happy. If you are around gloomy people, you are likely to be glum.

The data scientists at Facebook set out to learn if text-based, nonverbal/non-face-to-face interactions had similar effects.  They asked: Do emotions remain contagious within digitally mediated settings? They worked to answer this question experimentally by manipulating the emotional tenor of users’ News Feeds, and recording the results.

Public reaction was such that many expressed dismay that Facebook would 1) collect their data without asking and 2) manipulate their emotions.

I’m going to leave aside the ethics of Facebook’s data collection. It hits on an important but blurry issue of informed consent in light of Terms of Use agreements, and deserves a post all its own. Instead, I focus on the emotional manipulation, arguing that Facebook was already manipulating your emotions, and likely in ways far more effectual than algorithmically altering the emotional tenor of your News Feed.

First, here is an excerpt from their findings:

In an experiment with people who use Facebook, we test whether emotional contagion occurs outside of in-person interaction between individuals by reducing the amount of emotional content in the News Feed. When positive expressions were reduced, people produced fewer positive posts and more negative posts; when negative expressions were reduced, the opposite pattern occurred.

In brief, Facebook made either negative or positive emotions more prevalent in users’ News Feeds, and measured how this affected users’ emotionally expressive behaviors, as indicated by users’ own posts. In line with Emotional Contagion Theory, and in contrast to “technology disconnects us and makes us sad through comparison” hypotheses, they found that indeed, those exposed to happier content expressed higher rates of positive emotion, while those exposed to sadder content expressed higher rates of negative emotion.

Looking at the data, there are three points of particular interest:

  • When positive posts were reduced in the News Feed, people used .01% fewer positive words in their own posts, while increasing the number of negative words they used by .04%.
  • When negative posts were reduced in the News Feed, people used .07% fewer negative words in their own posts, while increasing the number of positive words by.06%.
  •  Prior to manipulation, 22.4% of posts contained negative words, as compared to 46.8% which contained positive words.

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Let’s first look at points 1 and 2 — the effects of positive and negative content in users’ News Feeds. These effects, though significant and in the predicted direction, are really really tiny. None of the effects even approach 1%. In fact, the effects are all below .1%. That’s so little! The authors acknowledge the small effects, but defend them by translating these effects into raw numbers, reflecting “hundreds of thousands” of emotion-laden status updates per day. They don’t, however, acknowledge how their (and I quote) “massive” sample size of 689,003 increases the likelihood of finding significant results.

So what’s up with the tiny effects?

The answer, I argue, is that the structural affordances of Facebook are such users are far more likely to post positive content anyway. For instance, there is no dislike button, and emoticons are the primary means of visually expressing emotion. Concretely, when someone posts something sad, there is no canned way to respond, nor an adequate visual representation. Nobody wants to “Like” the death of someone’s grandmother, and a Frownie-Face emoticon seems decidedly out of place.

The emotional tenor of your News Feed is small potatoes compared to the effects of structural affordances. The affordances of Facebook buffer against variations in content. This is clear in point 3 above, in which positive posts far outnumbered negative posts, prior to any manipulation. The very small effects of experimental manipulations indicates that  the overall emotional makeup of posts changed little after the study, even when positive content was artificially decreased.

So Facebook was already manipulating your emotions — our emotions — and our logical lines of action. We come to know ourselves by seeing what we do, and the selves we perform through social media become important mirrors with which we glean personal reflections. The affordances of Facebook therefore affect not just emotive expressions, but reflect back to users that they are the kind of people who express positive emotions.

Positive psychologists would say this is good; it’s a way in which Facebook helps its users achieve personal happiness. Critical theorists would disagree, arguing that Facebook’s emotional guidance is a capitalist tool which stifles rightful anger, indignation, and mobilization towards social justice. In any case, Facebook is not, nor ever was, emotionally neutral.

Jenny Davis is an Assistant Professor of Sociology at James Madison University and a weekly contributor to Cyborgology, where this post originally appeared. You can follow her on Twitter.