In this post, I’d like to make an argument about a way to understand how the Democratic party seems to be making messaging and policy decisions. An argument like this can’t be made in a vacuum—or in 1,500 words. Nor can any one or even ten reasons be decided upon for why the leaders of a party do what they do. But I recognize a pattern in how the DNC and leadership has acted over the past decade and I want to work that through here. So please forgive any indication that I am not a policy wonk or political analyst—I do not claim to be, nor do I wish to be either. more...
In March 2013, at Microsoft’s annual research and development event TechFest, a new project was introduced that aimed to let “users interactively explore the full chain of events whereby individual news stories, videos, images, and petitions spread from one user to the next over a social network.” The program, in effect, aims to understand how content spreads through a social network such as Twitter. By aggregating large amounts of data and tracking how users share things on their Twitter accounts, ViralSearch turns the transmission of content into a visually friendly genealogy of media, which Microsoft terms its “virality.” The more descendants a video has, for example, meaning those who have shared it (which is broken up into generations, or subsets of users that represent one wave of shares) the more viral it is according to ViralSearch’s virality percentage. More than this, it actively differentiates between virality and popularity, by looking precisely at how the information is shared. As researcher Jake Hofman says,
This is what people sort of typically have in their mind when they think about one of these viral videos, but nobody’s really been able to actually look at the structure of these things to date. And so what we’re able to do is going through these billions of events we reconstruct these trees by looking at all the followers of everyone who adopts the content and using a large cluster to reconstruct these things and then a novel scoring method to actually distinguish this tree as being viral from just being popular.
Horse-race style political opinion polling is an integral a part of western democratic elections, with a history dating back to the 1800’s. Political opinion polling originally took hold in the first quarter of the 19th century, when a Pennsylvania straw poll predicted Andrew Jackson’s victory over John Quincey Adams in the bid for President of the United States. The weekly magazine Literary Digest then began conducting national opinion polls in the early 1900s, followed finally by the representative sampling introduced the George Gallup in 1936. Gallup’s polling method is the foundation of political opinion polls to this day (even though the Gallup poll itself recently retired from presidential election predictions).
While polling has been around a long time, new technological developments let pollsters gather data more frequently, analyze and broadcast it more quickly, and project the data to wider audiences. Through these developments, polling data have moved to the center of election coverage. Major news outlets report on the polls as a compulsory part of political segments, candidates cite poll numbers in their speeches and interviews, and tickers scroll poll numbers across both social media feeds and the bottom of television screens. So central has polling become that in-the-moment polling data superimpose candidates as they participate in televised debates, creating media events in which performance and analysis converge in real time. So integral has polling become to the election process that it may be difficult to imagine what coverage would look in the absence of these widely projected metrics. more...
There has been a lot of talk about magic lately in critical, cultural and technological spaces; what it does, who it is for, and who are the ones to control or enact it. As a way of unpacking a few elements of this thinking, this essay follows on from the conversations that Tobias Revell and I, and a whole host of great participants had at Haunted Machines, a conference as part of FutureEverything 2015 which examined the proliferation of magical narratives in technology. With our speakers we discussed where these stories and mythologies reveal our anxieties around technology, who are the ones casting the spells, and where – if possible – these narratives can be applied in useful ways.
As an ex-literature student, I’m quite interested in ghost stories as analogy, because they can reveal, or be an interesting way of exploring, these anxieties; where the voices in the static are coming from, where the pipes are creaking, and what they tell us about what our technology is doing or can potentially do to us.
I’m going to use a load of slightly ham-fisted contemporary narratives to signpost the anxieties that come out of two personal and increasingly algorithmically mediated spaces: the social network and in the home. Where does the role of narrative in magic, the supernatural, and the unknown allow us to get a better grasp of technology’s power over us? Where are the uncertain terrains of our technologies creating the capacity for hauntings, and where can techniques used to imagine future scenarios better equip us for the ghosts to come? When we think of a haunting, we think of the unseen forces acting upon our domestic space, and when considering technology, a reappropriation of Clarke’s third law that Tobias Revell summoned with his work on Haunted Machines can apply– Any sufficiently advanced hacking is indistinguishable from a haunting. But where else are we haunted? more...
We’ve all been there. Sweaty palms, racing heart, left eye that winks at involuntary intervals. You’re emotionally fraught and having a physiological response. It could be an upcoming exam, a big presentation, or that one friend who can’t stop telling you about their fantastic job/spouse/kids/new shoes while wondering out loud how you manage living in such messy quarters.
Our bodies are key sources of information and guidance. Bodied reactions, coupled with culturally situated reflexive analyses, help us make sense of day-to-day events and make behavioral decisions. Feel like you’re going to vomit every time that colleague stops by your office? Maybe they’re toxic. Maybe you’re in love. The bodily response prompts you to do something, and how you interpret that response tells you what that something is. more...
Does anyone else feel like the terms ‘cyber-attack’ and ‘cyber-terrorism’ should always be accompanied by cold-war style red flashing lights? Maybe I’m just watching too much mainstream news. In any case, I argue below that the ‘cyber’ prefix is not only dated and dualist, but imprecise. I suggest ‘data’ as an alternative. This relies on the assumption that we don’t have data, we are data; an attack on our data is therefore, an attack on us. more...
Sound happens when things vibrate, displacing air and creating pressure waves that fall within the spectrum of waves the human ear can detect.
Researchers at MIT, working with Microsoft & Adobe, have developed an algorithm that reads video recordings of vibrating objects more or less like a microphone reads the vibrations of a diaphragm. I like to think it turns the world into a record: instead of vibrations etched in vinyl, the algorithm reads vibrations etched in pixels of light–it’s a video phonograph, something that lets us hear the sounds written in the recorded motion of objects. As researcher Abe Davis explains,
We’re recovering sounds from objects. That gives us a lot of information about the sound that’s going on around the object, but it also gives us a lot of information about the object itself, because different objects are going to respond to sound in different ways.
So, this process gives us info about both the ambient audio environment, and the materiality of the videorecorded objects–that’s a lot of information, info that could obviously be used for all sorts of surveillance. And that will likely be people’s primary concern with this practice.
But I think this is about a lot more than surveillance. This research reflects some general trends that cross both theory, pop culture, and media/tech:
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 walk my two dogs, Laika and Sputnik, once or sometimes twice a day. On these walks, they sniff around a lot. One day, while they were on a particularly strong sniff binge, I wondered how their olfactory interaction with the physical world translated into a metaphysics, specifically, into an understanding of time. Sputnik and Laika could smell this patch of sidewalk’s recent past–they knew that my neighbor Mickey and her dogs Bentley and Beauty had taken a walk earlier this afternoon (I’m guessing this was the case because they go nuts for their scent, as Mickey always gives them treats). That’s not something I would know unless I (a) talked to Mickey, or (b) had surveillance camera data from the car dealership by this particular patch of sidewalk. What, for me, was an imperceptible, unknowable “past” was for them a perfectly accessible fact. The past was physically present for them in a way it was not for me. Surely this different perceptual orientation to the physical world translates into a different metaphysical experience of time and, well, of reality more generally. When the world is sniffed rather than seen, different features and patterns of relationships emerge as the prominent, organizing factors of that world.
I wasn’t particularly interested in following up on that idea until I read that “sniffing” is a metaphor commonly used to describe a specific type of data surveillance.
Three articles came out this week that help me develop my concept of droning as a general type of surveilance that differs in important ways from the more traditional concept of “the gaze” or, more academically, “panopticism.” There’s Molly Crabapple’s post on Rizome, the NYTimes article about consumer surveillance, and my colleague Gordon Hull’s post about the recent NSA legal rulings over on NewAPPS. Thinking with and through these three articles helps me clarify a few things about the difference between droning and gazing: (1) droning is more like visualization than like “the gaze”–that is, droning “watches” patterns and relationships among individual “gazes,” patterns that are emergent properties of algorithmic number-crunching; and (2) though the metaphor of “the gaze” works because the micro- and macro-levels are parallel/homologous, droning exists only at the macro-level; individual people can run droning processes, but only if they’re plugged into crowds (data streams or sets aggregating multiple micro- or individual perspectives).