In my last post, I lamented a bit the potential for advanced technologies to reinforce existing biases at a quicker and larger scale, without either our awareness nor consent.

The issue of algorithmically detecting gender that I briefly mentioned is one that I’ve been struggling with this semester. Inferring gender can be crucial in revealing lags at publications and harmful disparities in behavior where diversity data is not provided, yet the act of classification can be morally and socially harmful.

Nathan Matias is a Ph.D student at the neighboring Civic Media Lab who has been a great ally in helping soften the steep learning curve of grad school and also in tackling gender/identity related projects. His master’s thesis work in Open Gender Tracker has led to many great posts on the Guardian’s Datablog.

Like a truly great friend, he not only answered my questions with regard to ethically detecting gender, he wrote a comprehensive blogpost about it. He highlights the practical realities of keeping work both computationally effective and ethically responsible. A must-read for anyone considering work in this area. Thank you Nathan!

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At the beginning of the seminar I’m taking in Race and Racism, we examined the historical origins of race– smirking at 19th century attempts to neatly classify and digest mankind into square boxes of color, things like Blumenbach‘s 5 categories (Caucasian, Mongolian, Ethiopian, American, Malay) and his offensive descriptions of the capabilities of each, how misguided they were, how clearly politically incorrect they are to us now.

One image stands out in particular– a chart, on the left axis, the races; on the right, a marking in each category of human competence, such that, summing up the checked boxes, one might literally rank different humans against another by racial category. The White man wins, in every grouping. It’s a glaring embodiment of early racist ideology, printed on paper, long since dismissed. It would be improbable to imagine a chart like that printed in a 21st century publication; the author would be fired, no doubt.

Yet the chart seemed eerily familiar to me. At first I couldn’t place it; I hadn’t seen it before. Then I realized: what it reminded me of was my own education, not in sociology or anthropology, but in Computer Science. As a graduate student, with a focus on Machine Learning and social applications, the very core of many of the algorithms I study and write is statistical classification, a major topic of research. What we are doing now– what Google does with its personalized search, what Facebook does with its unsettlingly accurate ads– is automating that same thought process of 19th century anthropologists. We look at a person, here, her technological imprint on the web, the traces she leaves, her purchase history, friends, and log-ins, then say: “what sort of human being are you”? And then, using our charts and tables– no longer printed ones, but weights on variables in our algorithms and databases of records– we first classify her, and after, yes, we rank her (sometimes we rank her first and then classify her, as well).

Users are commonly classified by gender, or what a machine can predict your gender to be, often quite accurately, and yes, different genders are ranked very differently. In the goods-driven world of online advertisement, a woman is worth differently than a man depending on what the product is, sometimes more, sometimes less. This entire pipeline is problematic to say the least; first, in the binary classification of gender; and then, in the ranking of different gendered individuals against one another; but our algorithms only reflect the constructs already driving these approaches.

Algorithms don’t quite yet classify users by race, or at least not outloud, because race is such a charged issue in most countries. But that doesn’t mean that when an algorithm doesn’t label a category outright, it doesn’t profile users. Algorithms, which learn, much like humans, based on history, only reinforce existing social constructs wherever they are used, because that is what they do: digest data, find a pattern, and make predictions according to that pattern. Harvard Professor Latanya Sweeney discovered that searches for racially-associated names were disproportionately causing targeted ads for criminal background checks and records to appear. These searches could go beyond offensive because targeted ads are reinforced by user behavior; if I click on that ad, I tell the machine that it was effective in targeting, reinforcing prejudiced thinking. Automated selection processes, which are beginning to gain popularity, such as automated admissions to schools and credit ratings, could cause real, harmful, physical ramifications.

This isn’t to say that there is anything inherently “evil” in Machine Learning itself; it’s a fascinating field of study, and could become a major tool in public health, disaster relief, and poverty alleviation. The machine is doing nothing new in its actions; it is merely a force multiplier of human behavior. I believe that classification is core to human cognition; and yes, we label others upon contact, always. Whether we like it or not, there is no way to escape being classified and classifying others. It’s impossible to meet someone without assigning some kind of underlying worth to them; it sounds ugly out loud, but our classification are essentially value-laden in order to be useful.

Ultimately, our machines only reflect our selves: it is vital to realize that computers are human, raised on human values, and there is no such thing as objective computation. The question that remains is: what kind of value systems will we feed our algorithms?

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Go here now, read and weep. To people who think that sexism in STEM is just hype, let me tell you that unfortunately, I have *NEVER* worked in a single lab or workplace of a technical nature where I have not experienced some sort of sexism– ranging from inappropriate comments to outright harassment. That is right– not a SINGLE lab or company. I would say my resume contains places people would consider inspiring, cutting edge, and liberal. Please be respectful and think about that.

Hattip @Mathbabe !

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twitter X MIT

01 Oct 2014

we’re launched!

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There is something about Trains that I Like. Out of planes and trains and automobiles they to me are the most romantic. Nine-eleven sort of killed flying and even before that I always hated being in the air. What a cruel trick this was, I thought, as a child, to call it flying but being so utterly trapped in my seat, the opposite of free.

Cars were nice enough; I just didn’t like driving them. It was as if all the worst stereotypes joined forces (Asian; woman; short-tempered; small) and at 5’1” I could barely look over the steering wheel clearly. Once I had a conversation in the basement of a boy I convinced myself I loved in high school, about what the spirit of a car looked like. The beer was brown and in a glass (this was in the end of college when I first learned that beer was meant for a cold tall glass) and he said the spirit of a car in its highest form was a thing of beauty, because really, this was the spirit of a free man. And when you drove that car, really, you were just taking that thing of beauty where it wanted to most go. I thought that was fine as long as a thing of beauty was driving the car itself and I was free to look at both.

But trains. Trains were lovely because you were always moving but you never had to worry about how. There was something blue collar about them and it was great; you ran down the stairs in Penn Station onto the platform with all the hordes of tired businessmen with their beer in brown paper bags the smell of artificial butter popcorn in the air; shooting the shit with the conductors, sometimes jolly more often tired. And best of all you could look out the window and see the grass roll by; it was best especially in New England when the leaves changed and when you rolled past Connecticut dreaming of what doctors and dolled-up wives were behind those white picket fences. Then you thought it would be nice to be invited somewhere fancy for a change because then you could wear sparkly things like the best of them and be admired, but you were raised too pridefully to ever desire such things. To be rich. To be a decorative. It was folly.

And you were always going somewhere. I am talking only about American trains, I can’t speak for any other kinds. It was the American train I loved with those dreams of railroads and going to New York with just a backpack, a handle of bourbon in it and a note from your sweetheart. Maybe going up North through Appalachians and all you had was some E.E. Cummings with you and some pen and paper to write the next big thing. You with all the drunks and suits and so long as it wasn’t St. Patrick’s day on the New Jersey transit it was all beautifully coarse. It was so Americana; and this to a little Chinese American girl was somehow the best thing of all, even if the Amtrak was making nothing but debt and really the tracks weren’t very safe, and no one could afford a damn ticket anyway.

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Preface: I am taking a class in Race and Racism this semester with Sally Haslanger at MIT, fulfilling my deepest desires of having classes in philosophy count towards my degree. I figured I would cross-post my weekly responses and thoughts here, so that you may read them and form a few thoughts of your own.

As we continue our discussion of race and its existence, I’m beginning to wonder if the question is of race itself at all but rather ethnicity, which seems to be far less of a hot topic in the national conversation.

If the past few weeks have been any indicator, there are literally centuries of philosophical, social, biological, and anthropological thought dedicated to the existence of race itself. All of it goes to show that the concept of race is one thing for certain– unclear and likely socially constructed if it exists at all, or some tricky combination of social and biological, as Philip Kitcher argues in “Race, Ethnicity, Biology, Culture”.

The concept of race in America is billed, literally and figuratively, as black-and-white, yet many of the problems of prejudice that make us uncomfortable refer to issues in shades of gray. Blanketing the discussion in a term which might not be defined in the first place obscures the conversations about what exactly it is that causes us unrest, and also leads to oversimplification, causing more harm than good.

Take for example the complex bio-ethical issue of racial profiling and racial categorization for the sake of medicine. Now, there are two strains of racial thinking to take into consideration: one is the examination of race and health for the sake of research, and the other, more immediate use for racial categorization is in individual patient treatment. If a patient engages with a health-care provider and self-provides racial information, is it appropriate to take that into consideration? Now, what if the patient does not explicitly denote his or her race? And what if a patient is found unconscious and unresponsive? In which (if any) of these cases is racial information relevant ?

Burchard (“The importance of Race and Ethnic Background in Biomedical Research and Clinical Practice”) argues that because genetic clustering corresponds roughly to the five major racial groups, and genetic variation accounts for medically significant differences in disease outcome, by transitive property it is important to consider race as a factor in treatment and research.

Root (“The Use of Race in Medicine as a Proxy for Genetic Differences”), in response, would classify the above as an example of mistakenly using race as a proxy for other, more accurate genetic factors. Such habits are dangerous at the individual level, leading to statistical discrimination. Furthermore, racial data should not be considered even at the research level, because this reinforces racial groupings that are detrimental and politically harmful. Racial profiling is unacceptable in medicine because it is often a bad indicator of ancestry or other more import factors, such as environment.

But what if race was taken out of the arguments entirely, and substituted with ethnicity? By the logic above, it seems that at least part of Roots argument for the immorality of race considerations disperses for ethnic categorization is far more associated with hereditary factors and cultural practices, and thus a better indicator of health. Burchard’s argument in favor of racial information due to the correlation of socioeconomic factors still holds if we were instead to consider ethnicity in lieu of race. Would we still feel moral discomfort towards the blatant use of ethnicity as a factor in healthcare?

My instinct tells me yes; profiling is still discriminatory under any name. It seems already that Burchard’s examples point to ethnic groups rather than racial groups; “Ashkenazi Jews, French Canadians, the Amish, or European gypsies” are not a race and neither are Japanese people. But would a patient willingly be labeled as a “Jew” or a “Mexican”, and “American” or a “French Canadian”, even if that label provides more accurate insight into his or her health than a broader category? Such a practice would appear to dig up a whole slew of political and social issues; possibly concerns of anti-Semitism and nationalist interests.

Too often, it seems that the topic of race serves as a proxy for the real issues that we fear to discuss– issues of xenophobia, class, and social categorization, none of which are black and white, and exist whether or not race does.

 

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Preface: I am taking a class in Race and Racism this semester with Sally Haslanger at MIT, fulfilling my deepest desires of having classes in philosophy count towards my degree. I figured I would cross-post my weekly responses and thoughts here, so that you may read them and form a few thoughts of your own.

In this past week of class, we continued to mull on foundational questions of race itself core to the discussion of racism. Once again, we asked– what is race, and does it exist, at all?

These are not questions that I had really considered before our class readings, and goes to show how ingrained racial thinking is on our minds. Even though I am quite aware of the notion of gender as a social construct, not once did the idea of race as a social construct occur to me, even after four years of schooling in a progressive college, whilst living in one of the most liberal and metropolitan cities in the world.

Sally drew this chart on the board classifying the views of some of the authors we read that I found very helpful.

 

Beliefs

Real 

 

Not

Biological

Race Realist

Race Eliminativist

Social

Social Constructionist

???

Thus, someone who believes that race is not biological is a race eliminativist; someone who believes that race is real, but only socially is a social constructionist, someone who believes that race is a real biological phenomenon is a race realist, and as far as we are aware there isn’t much of a name for people who believe that race is not socially real, since there are probably very few who think of it as such. Then there are also various combinations of the boxes above, and partial beliefs, such as race naturalists who believe that there are races biologically, but they could be very, very different from what we assume of races (and that is socially constructed).

Appiah, one of the thinkers we discussed, argues against the existence of race from two fronts– both ideationally (there exist no human beings that satisfy our assumptions of race) and refrentially (our usage of the term “race” have no human groupings to back them up). He might be someone we call a “race eliminativist”, although he approaches the concept from the usage of the term itself.

Yet, again, I argue, does this make the term any less valid? The ideational theorest would say that the concept/ideas associated with a term can be wrong and not apply to the referent– for example, when I say “I have arthiritis in my thigh”, when in fact, no one does. But clearly, there is some sort of pain in my thigh, and whether or not I refer to it as arthritis, it still exists.

What strikes me the most of all the authors we have read and discussed so far, along with our own discussions of race, is what appears the desire to seek biological or logical proof, of the existence or non-existence of race. There is such a great emphasis to dispute, with sequential logical proofs, whether or not race exists, when the ramifications of race existing and all the issues that come with it are overwhelmingly related to the fields of politics, economics, and social class that have very little to do with biology (aside from testing and treatment of certain diseases and genetics, which is not to be dismissed). We seek a logical, scientific proof of the existence of race, yet issues of racial thinking and racism clearly cannot be approached in such matters.

In the 21st century we laugh easily at the Social Darwanist who so ignorantly argues about the skull size and brain size of different races, as this is clearly “scientifically incorrect” and racist thinking. Yet, we neglect that the science was in fact “correct” in that era, for science is never an absolute truth, but a function of time and place. That is something we often forget– that science, is not objective but subjective, and grounded in its own system of human beliefs and ideologies. Behind every hypothesis is an inquiry about what we consider even worthwhile researching at all, and in every algorithm, human-chosen features to evaluate.

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Preface: I am taking a class in Race and Racism this semester with Sally Haslanger at MIT, fulfilling my deepest desires of having classes in philosophy count towards my degree. I figured I would cross-post my weekly responses and thoughts here, so that you may read them and form a few thoughts of your own.

This week’s readings in Race & Racism class have already brought a few new points to my mind concerning this topic, especially on the classification of “race” itself. Now, being a non-white person living in America (although the same likely applies for people of all colors, non-colors, whatever you may choose to designate yourself as) I have already spent a good deal of time (say, about 22 years) rolling this idea of “race” around my brainspace. The events of this summer certainly brought it to the forefront.

Still, in all this time, about 8,000 day’s worth minus a few years of color-blind babyhood, I never really challenged the idea of race itself as a classifier. That, I took for granted. It was handed to me on the first day of grade school: Look, you are the Asian kid in class (there was one other, a boy, I think, so if you want to be specific, I was the Asian Girl); those are the Black kids, these are the Hispanic kids, and I guess, everyone else is White. Racism is bad; everybody knows that, but yea, you’re definitely the Asian kid. Don’t call someone fat, but there’s nothing wrong with saying that someone’s White or Black, it just is.

This is what philosopher Blum (I’m not a Racist, But…, 2002) calls the “popular account”, and it is, he is very clear to state, wrong. Wrong as in false, but also wrong in the sense that it is morally detrimental. What’s wrong with racial thinking? There are a few key points:

1.Racial thinking divides us. It creates “moral distance” among those of different races. i.e. it becomes easier to antagonize the man who is not of my “type”. (102)
2. At the same time, it falsely groups us into categories all too easily stereotyped (103).
3. It suggests that we can’t escape our “racial fate” (i.e. “All Asians are good at math and like engineering”… oops) (104)
4. and finally, racial categories “evoke associations of superiority and inferiority of value”.

I think point 3 is especially important as it leads to the idea of racial immobility, i.e. you are born Asian and you die Asian because your parents are Asian, and this becomes especially harmful when considering statements 1, 2, and 4, unlike all the bad things that class categorization brings, because whereas in some places there is an idea of class mobility, really, I can’t think of many people who might believe in race mobility for a single person (at least not in America), unless they resemble closely enough another. It doesn’t matter how “whitewashed” I am, even if my entire adoptive family is white, if I wake up one morning and declare “I am white!” the person next to me might say in reply: “go the f–k to sleep”.

However, I am not sure that I am completely onboard with Blum’s rejection of racial thinking on a moral stance. It is true that there are many oddities to racial classification that suggest it to be unsound without an implicit cognitive model of race, i.e. why choose skin color and not some other physical attribute (such as hair color), why narrow the world down to essentially 5 races established a long time ago in the 18th century when there are many other groups that are quite distinct, (in fact, I admit I always considered race to be a genetic aspect, and was thoroughly surprised to learn that in fact there is very little genetic distinction between them (Does Race Exist, Bamshad & Olson, 2003)).

But I do not think it is the categorization and classification of people into races itself that is at fault, but how we do this and the assumptions we make while doing so. It is in fact precisely points 1-4 that are what’s wrong with our thinking of race itself, and not the acceptance that race exists. I am not sure there is such thing as a post-racial world. Colorblindness could be in fact, harmful.

Blum points out our reluctance to classify people by race as a hint to the incorrectness of the action, but if we did not associate certain races with negative traits then we might not hesitate so much, just as we might not feel it as taboo to point out, simply, that someone has brown or black hair, which is a way of categorization. Maybe at this point, the use of race is far too entrenched with negativity and harm that there is no more way to use the concept without hurt, but again, this is not in the categorization itself but the attributes we have prescribed to our method of doing so and the categories.

Whether or not race exists biologically, the worst possible thing would be for us to fear acknowledging that it is a very real thing in society. Even in my own conversations, I see this fear of speaking about race, fear of acknowledgment, fear of saying the word itself. This is what creates boundaries between us, not race, the concept.

Maybe the idea of race is all in our head… but that does not make it any less of a reality.

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The slides from Democratizing Data Science, the vision paper that William, Ramesh, and I presented for KDD @Bloomberg on Sunday are now available online.

What a great first conference experience! Really interesting speakers and projects all around.

Take part in the conversation by tweeting at us (@mpetitchou, @tweetsbyramesh, @williampli) or putting your own opinions and experiences out there.

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Guys! Guys! Guess what. Even though I’m practicing my April Ludgate glare in real life, today I’m going to be more like this. Why?

I co-wrote my first paper with two cool cats at MIT CSAIL, William Li and Ramesh Sridharan, and it got accepted to the KDD Conference as a highlight talk!

That means next Sunday, August 24th you can hear me taco ‘bout it in real life at 11am in the Bloomberg Building, 731 Lexington Avenue, NY, NY.

The theme of this year’s conference is “Data Mining for Social Good”, and our paper is a short vision statement on effecting positive social change with data science. We briefly define “Data Science”, ask what it means to democratize the field, and to what end that may be achieved. In other words, the current applications of Data Science, a new but growing field, in both research and industry, has the potential for great social impact, but in reality, resources are rarely distributed in a way to optimize the social good.

The conference on Sunday at Bloomberg is free, and the line-up looks promising. There are three “tracks” going on that morning, “Data Science & Policy”, “Urban Computing”, and “Data Frameworks”. Ours is in the 3rd track. Sign up here!

For the full text of the paper, click here.

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