Affects Ex-Machina: Unboxing Social Data Algorithms

Emile Denichaud1h 2min

Ariana Dongus

00:15

3d printed models of illegal ammunitions to train neural networks in order to recognize those ammunitions in video footage from Syrian war as presented yesterday panel, archives for collective resistance, tech, sky and Husky we want to explore new forms of activism and civic participation at the level of increasingly complex technological abstractions. I guess it is common sense today to say that data is the new currency of corporations, and the data medium of state control. But, of course, the situation is more complicated. For instance, yesterday in our keynote on console temporalities Jackie Wong mentioned this hypothesis of global High Tech Data panopticon that Nick Bostrom envisions that is facilitated by the alibi to protect the vulnerable planet, since technological process has made it easier than ever, to cause destruction on Cantor's scale. As much as we challenge AI as a medium of political control, we should also investigate its economic impact, its effects on labor markets, and measurement of labor. There's a new universe of precarious labor behind the avatar of AI. So my own research I have gay, I study new techniques of biometric control in refugee camps in Jordan and Iraq, where this new matrix of computation integrates with the economy of war and humanitarianism, and produces new computational measurements of labour time. our panel today examines how machine learning and askew algorithms analyze and manipulate individual effects into political sentiments, eventually amplifying class, gender, and racial bias. So these new forms of data capture the data emotional, behavioral, or biometric negative form of governments, that is our wismec, rendering new forms and levels of control and surveillance of lives possible. By that they are exposing mostly those people in our societies that are already marginalized by the dominant powers. So it's time to find ways to reclaim not only our data, but also our ethics and transform them into a new country infrastructures, if you wish, as collective forms of social resistance beyond fragmented filter bubbles. So how is it possible to reverse engineer the expanding capturing of emotional data, which forms of resistance are possible against social data algorithms for upcoming European elections in May this year, by the way, also in India, to data surveillance in India, the speakers will discuss and present new projects and strategies of algorithmic activism and data sovereignty. The people we invited work to make biases visible to show the inner logics of machines and it's designed to develop tools that serve as counter infrastructures against today's seemingly monolithic and privatized global networks of control and vision. So let me introduce the speakers now they forgive the inputs in the same order. Karen Sanders is a machine learning designer, researcher and artist. She's the founder of convocation design and research, and has worked with Amnesty International into IBM Watson and the Wikimedia Foundation. She's a research fellow at the Harvard University's Kennedy Kennedy School of Government and policy. Her work has been featured at MoMA ps1, the Euston center for contemporary art among many others.

Ariana Dongus

04:24

Claudia gase is a self taught hacker, who since the late 90s, has gradually become a techno political activists. In the last decade, he worked on whistleblower protection with global leaks, advocated against corporate surveillance and from Alex for algorithms exposed campaign, of which Facebook tracking exports or tracking expose is one of the tools he will talk about today. He's a research associate at UVA, the executive team, and vice president of the Harvard Center for Digital human rights. Nine times out of time is a researcher based in Bangalore working on feminist politics of data and speech. Core a core part of her work is building tools and resources that help situate stakes and digital rights issues for the larger human rights movements. In her talk, she will discuss the role of ethic and Facebook user, the Indian context. On shorter note, I want to say unfortunately, I won't allow can be part of this panel today because of some health issues. He writes in Berlin. But unfortunately, he cannot join us, but we wishing him a good recovery. And now, welcome to Carolyn.

Caroline Sanders

05:40

Yeah. Hi, everyone. I'm Caroline Sanders, and I am a machine learning designer, artist and Research Fellow with our university as well as a senior fellow with the Mozilla Foundation. I spent the past seven years studying online harassment networks and systems, as is I'm particularly interested in how language is so contextual, as well as conversations, digital spaces, but how language and conversation can be weaponized as far as that's understood and how it fits inside social networks. And that funding can be from a policy standpoint, how policy relates to language, or technical standpoint, or algorithms to understand or rather look at words or from design standpoint, the things, the ways in which we're able to interact on social networks are things we can post to any kind of image or content. That's fascinating because I think language is both objective and subjective is literal and figurative language is really complex. But language inside of any kind of technical system is a form of data. And I want to highlight an important project in the space when it comes to thinking about data data from an ideological standpoint or data from artistic practice. And I'm gonna highlight neowise work the library's missing datasets, which perfectly captures I think, all the nuances of data, or even the nuances of a lack of data on all rights, missing data sets or blind spots, and otherwise days after it faces. The library busy days that started in 2016 is an ongoing physical repository of these things that have been excluded in society are so much else is collected. And unsurprisingly, this lack of data typically correlate to issues affecting those that are most vulnerable. In this context. The word missing is inherently normative implies both a lack and an audit. Something that does not exist but should, that should be somewhere is not in its expected place. Established system is disrupted by distinct absence.

Unknown Speaker

07:41

Just because some type of data doesn't

Caroline Sanders

07:43

exist doesn't mean that it's missing. The idea of using data sets is inextricably tied to a more expansive climate of inevitable and routine data collection. And why does this matter? That actually more reveals more than that we get attention to it's in it's a nice things that we find cultural and colloquial pants on Wednesday, two important slots that we left blank reveal our hidden social biases and differences. News project with particular names that you see highlights different kinds of missing data sets. And at times, we can think of where the important to be seen by a system how system relates to you. If you're seeing any of this, there are many other points inside of Mimi's collection of missing data, data where we wouldn't want things captured. What would it be like to have a list of all the mosques in one city? I was very easy to find a collect. You can think of all problems in that. No, this is my I've been thinking a lot about how do we look at data beyond the cold the literal or careful? data can be messy, qualitative, complex, and quite small. conversations are data points in conversations or emotional spaces, especially in digital systems. Our conversations are caught and saved as data as emotional data. As an artist and designer explored the in betweens of conversation, how does emotion is saved in digital realms? How you take something that is inherently qualitative, like online harassment, and distill it into a quantitative data set? How do you take emotional trauma and perceive it into an Excel spreadsheet? And is this possible? Kevin Davis, open jersey, I like talking about subjective data sets, which she describes as data sets create a worldview, we have the ability to shake this worldview through working with us adaptive data, this kind of subjective data that allows us to explore the nuances of data the in between so what it is that can be my shouldn't be. I think this is a great area of data set. So sure, as you do this project I'm working on with the artists and technologists are often when I'm creating an emotional data set and a self portrait algorithm. I'm using this further now as an example a metaphor for the deeper points of this presentation. I want to refer back to the first image of this presentation. This looks just like a random regular highway. It's so mundane and seizures. And to me so completely American and then I was worried about this is this is the entry point for Water, Hurricane Katrina, what are the most devastating natural disasters in the United States? Well, there's a graph for Mississippi in 2005. It completely leveled it completely leveled the towns and the surrounding towns. And to the point where it was mostly left were slabs of concrete houses turned sideways with our system, see this image? What kind of data does this image represent? So I might get through some out of the box, Ai, computer vision demos. And let's look at some of these experiments. What is clarified sort of see, it's a struggle, transportation stack, no person, water airport. So it says some of us are right, and some of them are not right at all. And this is from Microsoft. Again, outdoor beach sky sitting Harbor, there's a train apparently, in here, that's used to me. Also a jet that's I don't see that either m, or D Grade II, which is a view of a city street at nighttime

Unknown Speaker

11:01

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