New Maps for an Inclusive Wikipedia: Plotting Strategies to Counter Systemic Bias

Can we retell history and write an encyclopedia
as if all people are equally valuable?

Yes.

On January 13, I invited to Wikimedia NYC’s celebration of the 18th birthday of Wikipedia to address this question, which I answer strongly in the affirmative. I talk about how long-running changes in the academy have created a font of high quality, well-sourced knowledge about marginalized people: women, indigenous people, Afro-descendant communities, sexual minorities, disabled people, working-class and poor people, and on and on. The challenge now—at least for Wikipedia—is to share this knowledge with the widest possible public in free form. But to do so, we will have draw new maps of geography, history, and our own collective writing process that put those who have been left out back on the map.

Here’s the talk in video form thanks to the Internet Society of New York:

Carwil-WikipediaDay.png

 

Binding Leaders to the Community: The Ethics of Bolivia’s Organic Grassroots

Just published in Journal of Latin American and Caribbean Anthropology. Bjork-James, Carwil. 2018. Binding Leaders to the Community: The Ethics of Boliva’s Organic Grassroots (full text). Journal of Latin American and Caribbean Anthropology 23, no. 2 (July): 363–82. Abstract: Bolivia’s largest social movement organizations—including its labor unions, rural communities, and neighborhood organizations—are bound together by a hierarchical […]

Blockade: The Power of Interruption

Think of this as the trailer for my ethnography, photography, and the book I’m revising for publication…

On June 23, 2008, three of us ascend an eerily empty highway from the tropical town of Coroico to Bolivia’s capital, La Paz. Foreigners, we stare at the majestic valley below as we pass above the line where the tropical tree cover of the Yungas gives way to pure rock. The so-called Death Highway has been rebuilt on a more secure footing, but it is still marked by hairpin turns, intruded upon by fallen boulders of a terrifying scale, and undermined by landslides. Its predecessor, once calculated as the world’s deadliest roadway, has been preserved as a downhill biking path for tourists seeking “100 percent adrenaline.” Where the road has fallen or washed out, drivers let their wheels dig tracks into the mud and gravel tracks, and peer over the edges of their vehicles to avoid falling off the side.

Today, however, both roads are nearly silent. None of the half dozen minibus unions are operating their vehicles, bike tours are cancelled, and the taxi we found cruises over empty roads and easily steers clear of both the rock faces and the treacherous edges. Once finally inside La Paz however, it comes to a stop at the cause of all the earlier silence: an urban road blockade. Residents of the northeastern District 13, organized through 46 neighborhood councils, have plugged the main arteries through their neighborhood with stones and their collective presence. They are calling on the municipality to meet an eight-point platform of demands concerning crime, public works, and water provision. Taxis like ours can approach the protest zone but only to discharge their passengers. Dozens of men and women walk—their goods stacked on their heads, bundled in fabric on their backs, or dragged along in suitcases—across the vehicle-free stretch of urban pavement, littered with stones and occupied by protesters who gather in the middle.

Every point along the road we have travelled is a potential chokepoint. Since the main road from La Paz to the Yungas passes through this district, a single blockade is enough to cut off all traffic to Coroico, the Yungas, Caranavi, and the northern Bolivian Amazon. Whether accomplished by simply sitting down in the street, dragging in boulders and tree limbs, or coordinating crowds of thousands to take over key thoroughfares, road blockades bring a sudden urgency to political protest. By blocking the circulation of people and goods, they ensure that the impacts of protest ripple across an entire region.

Read more at Limn Magazine…

Bad science journalism: Gay facial recognition

Journalistic accounts of soon-to-be-published study called “Deep neural networks are more accurate than humans at detecting sexual orientation from facial images” (by Michal Kosinski and Yilun Wang) have gone viral and already prompted some outraged reactions from LGBT groups GLAAD and the Human Rights Campaign. The study primed a deep neural network face recognition program on photos of white homosexual and heterosexual adults obtained on a dating website, and used it to create a “classifier” that rates which photographs were most distinctively those of gay or lesbian people. This classifier’s ability to distinguish gays and lesbian individuals was compared with human observers on test samples from the data, and on Facebook profile pictures with a stated sexual orientation.

This is all a vaguely interesting computer science project about self-presentation (all of the images were curated by the people involved and put on profiles stating an “interest in” one sex or  the other), machine learning, and perception. Interesting, that is, until it is attached to fears about artificial omniscience and ubiquitous surveillance, and debates about nature and nurture. Then it becomes at turns frightening and polemical.

Before we get there (and I’ll update this post with some comments about the authors’ dubious understanding of the many social layers that separate, say pre-natal hormones and early adult physical presentation, the fluidity of sexual orientation, and the presumed future capacity of artificial intelligence to make omniscient predictions), we have to ask whether the results of this study justify this kind of grand implications. In other words, we first need to know what exactly the study shows.

Let me begin with two simple asks for journalists reporting on science:

  1. Read the whole scientific paper and explain to readers what actual evidence is being presented!
  2. Also, remember that “discussion” sections of papers lack the scientific validity that is attached to results of the research method involved.
  3. Be literate in math.
  4. Never ever present a numerical result without explaining what that number means.

Unfortunately, major accounts of the paper (such as this one in the Guardian) fail to follow this simple rule. And, as is often the case, the problem starts with the headline:

New AI can guess whether you’re gay or straight from a photograph
An algorithm deduced the sexuality of people on a dating site with up to 91% accuracy, raising tricky ethical questions

Now, does the paper show that the AI can guess your sexuality from a photograph with 91% accuracy? Nope.

As the paper states:

The AUC = .91 does not imply that 91% of gay men in a given population can be identified, or that the classification results are correct 91% of the time.

Here’s the 91% claim. The AI is shown five photos from two individuals on the dating website. Based on what it has learned from other photos, it offers a guess as to which is more likely to be gay. In 91% of the cases where there is a gay man and a straight man being compared it guesses correctly. Accurate headline:

AI can distinguish gay men based on five dating profile pics 91% of the time.

When presented with just one pair of images of men, the AI guessed right 81% of the time. Human judges—recruited by Mechanical Turk and untrained on any images—guessed right just 61% of the time. For women, both were right less often: 71% for the AI and 54% for the humans. In this test, 50% is rock bottom, the equivalent of zero gaydar.)

But it gets worse. Let’s try to apply the paper to original question raised by the headline. How well can this AI judge an individual person’s sexuality? That’s the critical ability, from which dystopian surveillance fears arise. For this, the researchers seemed to have tuned the data very carefully. Remember too, this is still an operation performed on profile pics, this time from Facebook.

First, the AI classifier still seems to work, though not as well:

The classifier could accurately distinguish between gay Facebook users and heterosexual dating-website users in 74% of cases…
But when presented with the task not of telling a gay profile pic from a straight one, but of evaluating a whether given profile pic is gay, the machine’s performance fell apart:

The performance of the classifier depends on the desired trade-off between precision (e.g., the fraction of gay people among those classified as gay) and recall (e.g., the fraction of gay people in the population correctly identified as gay). Aiming for high precision reduces recall, and vice versa.

Let us illustrate this trade-off… We simulated a sample of 1,000 men by randomly drawing participants, and their respective probabilities of being gay, from the sample used in Study 1a. As the prevalence of same-gender sexual orientation among men in the U.S. is about 6–7%, we drew 70 probabilities from the gay participants, and 930 from the heterosexual participants. We only considered participants for whom at least 5 facial images were available; note that the accuracy of the classifier in their case reached an AUC = .91. Setting the threshold above which a given case should be labeled as being gay depends on a desired trade-off between precision and recall. To maximize precision (while sacrificing recall), one should select a high threshold or select only a few cases with the highest probability of being gay. Among 1% (i.e., 10) of individuals with the highest probability of being gay in our simulated sample, 9 were indeed gay and 1 was heterosexual, leading to the precision of 90% (9/10 = 90%). This means, however, that only 9 out of 70 gay men were identified, leading to a low recall of 13% (9/70 = 13%). To boost recall, one needs to sacrifice some of the precision. Among 30 individuals with the highest probability of being gay, 23 were gay and 7 were heterosexual (precision = 23/30= 77%; recall = 23/70= 33%). Among the top 100 males most likely to be gay, 47 were gay (precision = 47%; recall = 68%).
Tuned to its highest setting, the machine could find nine of the seventy gay men and threw one straight man in the gay box. Set to a broader setting, the machine found 47 of the 70 gay men, but also labelled 53 straight men as gay.
Now, we have a big technical problem: the artificial gaydar can only find most of the gay people when it produces a pool of “gay looking” people that is majority straight. So no matter how repressive and homophobic the society, it’s hard not to imagine that the “gay looking” 5% of the population will put up with this kind of system.
Of course, if we imagine that gay and straight people really have different faces and we just haven’t found the magic formula yet (and the authors seem to leap to this conclusion, for what it’s worth) then we can imagine a better AI figuring out how to tell the difference. But there are plenty of reasons to doubt that this ever has been or ever will be the case.

NYC lecture, October 26: Dense and Nimble Activisms in Bolivian Radical Politics

On Monday, October 26, I’ll be giving a talk on “Dense and Nimble Activisms in Bolivian Radical Politics,” hosted by the Department of Anthropology at Queens College-CUNY. The talk will be in the President’s Conference Room 2 at the Rosenthal Library (campus map) at 12:15pm. If you’re in New York City or someplace nearby, please join me.

Abstract:

This paper explores the radical political values that circulate and develop across Bolivia’s dense and nimble forms of activism, with a focus on the increasingly indigenous metropolis. Bolivia’s largest social movement organizations—including its labor unions, rural communities, and neighborhood organizations—are bound together by a hierarchical organizational structure and a countervailing ethic that subordinates leaders to the grassroots bases from which they emerge. This worldview separates an enduring, morally legitimate world of community organization (“the organic”) from a corrupted world of political parties, staffed by self-advancing, individualist politicians who engage in transactional, corrupt practices (“the political”). Inside the organic domain, unions and other mass organizations replicate and extend the ayllu, an Andean structure for community self-management of the lands inherited from ancestral spirits. They valorize ethical principles of complementarity, solidarity, anti-individualism, and obligatory participation, blending ethical and political life.

Conversely, other organizations structure themselves horizontally, without a formal hierarchy or official leadership. People join these efforts voluntarily and individually without a joint decision of the others with whom they live or work; the organization is defined by ideological and social affinity, its common purpose. They achieve their political effects by networking: that is, by interacting with a far larger numbers of people than just its membership, through public spectacles, training, writing, and open gatherings. While less internationally visible, these nimble activists participate in the global circulation of practices of decentralized decision making, ideas like the de-commodification of water, and transnational movement networks.

Rather than mutually opposed poles, organic grassroots and participatory network organizations interchange ideas and collaborate in common efforts. A former Marxist union militant in the mines explains, “Solidarity is what is called ayni, right?,” offering a translation between languages for political visioning. Across town, an urban anarchafeminist collective embraces an indigenous identity while pointing out patriarchal attitudes within both revolutionary movements and traditional communities. For at least a generation, Bolivian activists have conceptualized radical political values as of form of decolonization, as a return to ways of living that are inherently opposed to the colonial and capitalist state. At the same time, liberatory political praxis involves the incorporation of new ideas, in silent contradiction to rhetoric of cultural revival. Drawing on multiple experiences, I describe both the recovery and the innovation of ways of doing politics.

Men and women rake and shovel a plie of garbage into bags as part of the Kariobangi Waste Management Allianc

“Every day the poor people dig, scavenge, and gather.”

Poverty is there, however, unbearable and discreet. On every page it manifests itself, in three elementary actions: carrying, scavenging, pilfering.

In all the capitals of poverty, the poor carry bundles. They always keep them close by. When they sit down, they place them by their side and watch over them. What do they put in them? Everything: wood gathered in a park, hastily, crusts of bread, bits of wire pulled off a fence, scraps of cloth. If the bundle is too heavy, they drag it along, in wheelbarrows or handcarts.

Peasants rest at the foot of the ancient walls of Nanking after collecting lotus roots for fuel. In the background: Jade Mountain, and the lake where sailors received their training during the days of the Ming Emperors. In all the capitals of poverty, people scavenge. They scavenge in the soil and the subsoil; they gather round refuse bins; they slip right into the rubble: ‘What others throw away is mine; what is no longer of any use to them is good enough for me.’ On waste ground near Peking, the rubbish piles up. This is the refuse of the poor; they have sifted through everything, they have already rummaged through their own rubbish; they have only left, reluctantly, what is uneatable, unusable, unspeakable, revolting. And yet the flock is there. On all fours. They will scavenge all day, every day.

In all the capitals of poverty, there is pilfering. Is it stealing? No, just picking things up. These bales of cotton have just been unloaded. If they stay an hour longer on the dock, they will disappear. No sooner have they been put down than the crowd rushes forward and surrounds them. Everyone attempts to pull off a handful of cotton. Many handfuls of cotton, gathered day after day – that makes an item of clothing. I recognize the look on the women’s faces, I have seen it in Marseilles, in Algiers, in London, in the streets of Berlin; it is serious, quick and hounded, anguish mingles with greed. You have to grab before you are grabbed. When the bales have been loaded onto a lorry, the kids will run after it with outstretched hands.

Every day the poor people dig, scavenge and gather.

Jean-Paul Sartre
Preface to D’une Chine à l’autre,
by Henri Cartier-Bresson and Jean-Paul Sartre,
Paris, Editions Robert Delpire, 1954.
(a book of photographs taken in China by Cartier-Bresson)

The image above is from the Kariobangi Waste Management Alliance in Nairobi, Kenya, over 300 young Kenyans who have made a waste collection system for the slum of Kariobangi; photograph borrowed from this 2013 article. The image below is a photograph by Henri Cartier-Bresson taken in Nanking in April 1949. Original caption: “Peasants rest at the foot of the ancient walls of Nanking after collecting lotus roots for fuel. In the background: Jade Mountain, and the lake where sailors received their training during the days of the Ming Emperors.”

Storming the Bastille, and what makes an event revolutionary

Etching depicting the assault of the Bastille

Historian William Sewell makes a striking claim about how the taking of the Bastille, 226 years ago today, marked not just the key moment in the French revolution, but an originary point for the very concept of revolution in the Western world. “It was by this process,” Sewell claims, “that the modern concept of revolution definitively entered French political cuiture, effecting a hitherto undreamed of but henceforth enduring articulation of popular violence to popular sovereignty.” The argument takes up a whole chapter in his book Logics of History (2005), and it’s worth your time, but here are three excerpts on the Bastille and its place.Read More »