Implementing Advanced Knowledge
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5.5.1 IaaC Lecture Series How to read culture in the Data Society JosĂŠ Luis de Vicente
IaaC Lecture Series: How to read Culture in the Data Society (IaaC Lecture Series 3th February 2015; synopsis by Jordi Vivaldi)
One of the first urban data applications that we have seen in Spain has to do with the public network of bikes that was implemented in Barcelona in 2007. Suddenly, the city could count on a huge source of information, that was not just informing about when a bike is taken where, but also was explaining us which are the most relevant trajectories in a particular part of the city during a particular range of time. These kind of discoveries were the main focus of the Medialab Prado, a citizen lab based in Madrid, that developed several prototypes and models of how data technology can drive the city. That was the early beginning of the open data movement. It was the early moment of the idea that by gaining data we would be able to formulate new questions about reality. However, our experience in Madrid show us that data is not something completely objective. In the pollution research that we were developing in Madrid some years ago, we were using many of the sensors that the city council distributed around the capital in order to measure contamination every hour. After the firsts results, it appeared a big polemic because the city was giving incredible high pollution levels. The answer of the city council was to move some sensors that were in the middle of the street, to some locations in parks and gardens, so the levels of pollution registered were drastically reduced. This experience underlines our naif preconception that understands data as a very objective measure that has no political implications. Therefore, when we are measuring the world through data, beside being this method one of the most powerful ones, we have to be very attentive on the virus that it embeds. This was one of the main topics of the exhibition of BigBandData, where we were also underlining to what extent metaphors are still relevant in our digital culture: windows, flows, mouse, cloud... Metaphors that helps us to manage in a new territory. In this sense, most of the data that we use, tweets, messages, etc... are not in a hard-drive anymore, but somewhere up there in places that we rarely represent and that we do not have any physical link, although we have very intimate information placed there. These places are Cover - Data Center, IaaC Archive Figure 1 - Big Data Exhibition, IaaC Archive 2
Cover - Ilounge
called Data Centers and usually are not represented because there is not interest at all in doing so. We have been building discreetly a massive system that covers the whole earth to move our bits. Lulea is a good example of it. In the north of Sweden and close to the Artic Circle, it is hosting the main facilities of Facebook. They chose the Artic Circle because one of the key parameters of these spaces are its capacity to provide very low temperatures. Another example of criteria to place Data Centres are the ones that are related to financial Data. In Manhattan there is one block fully occupied by a Data Centre, and its surroundings have been conquered by financial entities that needs to be as close as possible to the Data Center in order to receive information as fast as possible. In a world were 70% of transaction are virtually done at the speed of milliseconds, to be at just 300 meters from the Data Centre is an advantage in relation to the competitors. This is the speed of the Neo-Capitalism.
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What is crucial to understand is that data driven technology is not just a system related to two or three specific domains, but absolutely multidisciplinary. In this sense, it has been used in politics like with the Obama’s campaign, or also in football by different coaches that need to have all the data of the speeds, trajectories etc of their players during any football match. This data it’s not just relevant to understand processes, but its capital to predict what is gonna happen the future and how is better to modify the present according to these predictions. However, real time data has also its dark sides. Companies like Amazon, Netflix or Spotify have developed many strategies that at the first glance seems to be just nice and efficient with the client, but that at the end are able to capture a lot of our information without us being aware of it. The case of Amazon is quite paradigmatic: from reading books to reading e-books we are giving to Amazon a lot of information of how many books are we reading,
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which paragraphs are we underlining, which books are we finishing (only 2.5 percent of the people that bought the Capital of Pitteky finished it)... From now on, when we are reading an e-book, listening music on spotify or watching our favourite serie in Netflix, we are not alone, but surrounded of thousands of cookies that are deeply tracking our activity through those devices and softwares. But until now, the activities that are being tracked have to do with simple activities like reading, but the use of this technology can lead us to model activities such as what do we eat, how many hours do we sleep, how many calories are we consuming... And what is scary, is that all this information, as the ANC Analysis said to us on june 2013, is at the disposal of structures of power. In this sense, Smart City is not just about an utopian narrative of optimisation and human happiness, but also about a system that tries to model what is happening in the public and privat space to take decisions according to certain agendas that do not necessarily try to serve the interest of citizens. One example of this case is when Facebook did an experiment with its users, trying to change and measure the mood of almost 800.000 users just by changing what Facebook was showing in their wall. However, the biggest problem is not that one, because luckily human mood is way more complex than what Facebook can achieve with its policies, but that most of us we are still thinking that what we are seeing in the wall of Facebook is what our friends are posting and not what Facebook is deciding, according to his particular agenda, that we have to see. Probably one of the most important notion that we have to be aware of is that what we see is not just what exists, but what someone wants us to see as the only reality.
Figure 3 - Installation Big Data Exhibition, IaaC Archive Figure 4 - Big Data Exhibition, IaaC Archive Figure 5 - Big Data Exhibition, IaaC Archive Figure 6 - Data Center, IaaC Archive
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IAAC BIT FIELDS: 1. Theory for Advanced Knowledge 2. Advanced Cities and Territories 3. Advanced Architecture 4. Digital Design and Fabrication 5. Interactive Societies and Technologies 6. Self-Sufficient Lands
Nader Tehrani, Architect, Director MIT School Architecture, Boston Juan Herreros, Architect, Professor ETSAM, Madrid Neil Gershenfeld, Physic, Director CBA MIT, Boston Hanif Kara, Engineer, Director AKT, London Vicente Guallart, Architect, Chief City Arquitect of Barcelona Willy Muller, Director of Barcelona Regional Aaron Betsky, Architect & Art Critic, Director Cincinnati Art Museum, Cincinnati Hugh Whitehead, Engineer, Director Foster+ Partners technology, London Nikos A. Salingaros, Professor at the University of Texas, San Antonio Salvador Rueda, Ecologist, Director Agencia Ecologia Urbana, Barcelona Artur Serra, Anthropologist, Director I2CAT, Barcelona
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