My thoughts on Transmediale 2020 festival​​​​​​​, Berlin, Germany

Exchange #2: empires and ecologies of the cloud, Ulises Ali Mejias

Transmediale 2020: “End to End”, focuses on Network. A topic that arouses discussion about the effects of the network and the history, current situation and the potential future possibilities of it in the contexts of politics, society, and digital culture.
As a student trip from university, I traveled to Berlin and took part in the Transmediale Festival for the first time.
In this article I try to give a glance at some terms that were used in the festival, and also try to dig deep into few talks that were most interesting for me and give my notions about them.​​​​​​​
What does “End to End” means
“End to End: A principle of designing a networked communication so that it allows for an exchange of information that is as direct and uninterrupted as possible”
End to End is a network idealism which means no intermediaries, no surveillance or better to say no capitalism surveillance, no manipulation of information and also no propaganda and no addiction.
It emphasizes on our data privacy and try to face us with the irreversible danger of the political and economic control over our data.
End to End also discusses the effect of data and digital network on today's urgent issue, climate change.
Personally, I think in the age of digital culture and capitalism that digital networks have penetrated every aspect of our life and we are so immersed in it, mostly unconsciously, it is important to put on critical thinking into the different networks and the ways we are engaged with them if we want to stay free as HUMAN beings.
Ulises Ali Mejias
In his great talk, Ulises A. Mejias, speaks about the the concept, Data Colonialism, which is the subject of his second book, The Costs of Connection: How Data Is Colonizing Human Life and Appropriating It for Capitalism.
As he says, the data, in our networked-age is being used for the new form of colonialism which he calls it Data Colonialism. Just like that in colonialism a country seeks to extend or retains its authority over other people or territories, generally with the aim of economic dominance, in data colonialism also they use our data for their own profits. Through surveillance over our data they control our life and make money from it. He also points out to the connection of colonialism and capitalism since the former always pave the way for the latter, but we tend to think that they are separated from each other.
He points out to the different similarities between historic colonialism and data colonialism.
Just like the historic colonialism that the colonialist uses other countries materials and process them to use them and make profit from them in a way that is presented like its for the colony’s benefit, data colonialism is repeating the same pattern. Companies give us free services like google, Facebook and etc. But in order to let us use that service there are terms of services that we should accept it at the beginning. They use misleading language that they sure the audience will not understand and at the same time they set it up so that the way they extract our data is justifiable. Then they are allowed to use our data.​​​​​​​
He explain about the concept, digital native informant. As he says informants are the figures who their role is providing data to be interpreted by someone else. We are digital informants who informing ourselves. the colony is our social life, the colony is our time. We betray ourselves by exchanging our social life for a filter that puts funny dog faces our faces. We betray ourselves by the time that we are spending in front of screens.
He points out to the role of abstraction in the context of capitalism. Abstraction is the fundamental characteristic of capitalism, since it is in the process of capitalism that the things are being taken from outside of the economy and through abstraction they become part of capitalist economy.
"Data is abstracting life, so ordinary social life becomes a direct factor of the capitalist."
Stephanie Dick
Stephanie Dick starts with the short summery of AI history.
Then she gives her critique about the term "Artificial Intelligence" and elaborates how it is impossible to have a system which is truly intelligent. Because in order to have an intelligent system it must be given human reasoning to each task and it is not possible because human reasoning is not algorithmic, Since every person reasoning is different regarding his/her sex, history, genes, body and many other factors. So how can we apply a reasoning to each task?
As she says in her talk, there is not one universal reasoning faculty
In the term of "Machine Learning", she emphasizes on the differences between human and machine, rather than the similarities between them.
"Machine learning uses computers to do work that we could never do, to make sense of data that we could never do ourselves and also they do works that we do not understand"
Since the major task of machine learning is making Prediction based on all of the data, she discusses about this issue and put on her critiques on it, which is considerable.
"when we make decisions based on predictions that are trained on our historic data we create condition to make that predictions come true. We ask to make situation that make those predictions true. Machine learning can enforce the parts of our history that we wish to unmake."
As she says, with the big data we can decrease the probability of error of predictions, but that causes building of huge Data Centers which causes many negative effects such as irreversible damages to our ecology and climate change.​​​​​​​

NSA Data Center in Bluffdale, Utah, US

She finishes her speech by asking a few questions:
"what can we get computers to do? who do we become? what will the world look like? what parts of our past do we want to get rid of and how do we do that? "
Whilst these questions are considerable, there is another question which arose on my mind after this talk, and that is, Why do we need prediction at all?! Isn't it the prediction that enables governments to control our minds?
For sure the prediction has some benefits for us, but do advantages outweigh disadvantages? Or it is just another tool for governments to make more money from us?
Katharine Jarmul
Katharine Jarmul speaks about the vulnerabilities of AI systems and the art of hacking it. She explains in detail why and how we should poison our data.
"we don't want to be part of a system that one person's data becomes another person's money."
She introduces us some methods such as Privacy Possum to falsify our data and raise a potential for error.
I, personally, haven't tried that yet and I should carry out research about it. at first glance, it looks elegant and good enough as a minor action to falsify our data, but since it is so "legal" and has been introduced by Google and Mozilla, I'm skeptical about it.
While I found Jarmul's talk so informative and inspiring and I believe taking any action to make our data worthless is good, but I think it will not inspires the change we hope to see unless more people know about it. It is not enough to talk about it in just a group of homogeneous people, but rather it should be discussed in a broader range of people.
Here I would like to point out to one of the critiques I have of Transmediale, that it is like a club, it seems that there are just a circle group of people knows about it and take part in it every year. So it is quite ironic that although one of the main focuses of Transmedial 2020 was on decentralizing the network, the festival itself was centralized. The question is, while we are keeping excluded this knowledge to small group of people, would it be really effective at all?
Speaking of decentralization, due to the compact timetable of the symposiums there was no time for socializing and sharing ideas with others between the talks. Moreover the time for Q&A at the end of each speech was also so short, and all these made the symposium days so unilateral.
After all, I really liked Transmediale in terms of that it brought up many new concepts and ideas (at least for me). Although it was more like raising questions in my mind rather than answering any of them, and that made me so confused and anxious at the end of it. But here I am, writing about them, thinking about them, searching about them and learning so many new things.
Thank you for taking time to read through this article, and feel free to connect with me if you enjoyed it.

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