The Free Art and Technology Lab (F.A.T. Lab) is an organisation aiming to enrich the public domain through the research and development of creative technologies and media. After being nominated for the Transmediale Award 2010, F.A.T. Lab members met up in Berlin in the first week of February and produced a series of projects dedicated to the topic of the week: FUCK GOOGLE. In addition to producing free software, browser addons, live streams, communiques and on-site workshops, F.A.T. Lab built a fake Google Street View car they took to the streets to see what it’s like to be Google. A PDF with building instructions and a list of needed materials has been made available on the F.A.T. website, along with a host of video material. Read about all the week’s projects here.

UPDATE: Also see the collaborative article and interview with F.A.T. Lab’s Evan Roth, by Marcello Lussana and Gaia Novati: http://www.furtherfield.org/displayreview.php?review_id=384:

“An interesting outsider project at Transmediale.10 this year, was F.A.T
Lab (Free Art and Technology Lab). A collective of artists, engineers,
scientists, lawyers, musicians and trouble-makers who have been working
together for two years, on the intersections of Pop culture and Open
source. Their stapline describes them as “An organization who is
dedicated to enriching the public domain through the research and
development of creative technologies and media.

For Transmediale.10 they presented a project called Fuck Google,
focusing on reminding us all how this big company has become omnipresent
in our digital lives, refering to the risk that too much data is owned
and is going to be owned more and more, just by Google alone. It exists
as a collection of browser add-ons, open source software, theoretical
musings and direct actions.”

The Berlin Transmediale event Ideologies and Futures of the Internet that took place on Saturday, 6 February featured a keynote lecture by Conrad Wolfram, Director of Strategic and International Development at the well-known software company Wolfram Research Inc., founded by his brother Stephen. At transmediale.10 Conrad Wolfram talked about the knowledge engine Wolfram Alpha and his vision of the future of knowledge and the Web.

The video of his lecture, entitled ‘Wolfram Alpha: Information, Computation and the New Era of Knowledge’, is available here.

In May 2009, Wolfram|Alpha launched to worldwide excitement. It introduced the new concept of “computational knowledge engine” — working out specific answers to queries made rather than picking out existing information like a traditional search engine.

Yet this is just one window into the Wolfram|Alpha project and its vision for all systematic knowledge: of curating, making computable and democratizing high-level use.

Which technologies make this feasible now? Can we democratize computational expertise as successfully as the web and search have democratized information retrieval? How will this affect the Knowledge Economy—business and government information, R&D and technical education?

Conrad Wolfram addressed these questions as well as explain the concept, workings, and progress of Wolfram|Alpha and its underlying Mathematica technology—built up over 23 years—that has made it possible.

Conrad Wolfram, physicist and mathematician, is strategic director of Wolfram Research as well as European managing director. Founded by his brother Stephen, Wolfram Research is the maker of Mathematica software and spin-off Wolfram|Alpha knowledge engine. A recurring theme for Conrad Wolfram has been the democratisation of computation through automation and interactivity. He argues that this direction will be increasingly important for technical jobs and everyday living; and that in turn this changes how we should teach mathematics and related subjects. He has led the effort to move the use of Mathematica from pure computation system to development and deployment engine, instigating technology such as the Mathematica Player family and webMathematica. He serves on the Computer science committee Advisory Board at Kings College London and was on the founding committee of the IMS conferences.

On monday March 1, Dutch newspaper NRC Next devoted two pages to articles on Google. One article by Peter Teffer, ”Maakt het internet ons dommer?” (does the Internet dumb us down?) features an interview with Geert Lovink. The other article is an experiment by two NRC reporters, Teffer and Pfauth, who attempted to live and work without the use of any Google service for a week. The article and report (both in Dutch) are online here.

In the last week of January, an NYU graduate class conducted a similar experiment, see an earlier blog post on it here.

Internet board game from box.net

NYU professor Mushon Zer Aviv and his graduate class in (new) Media (networked) Culture and (distributed) Communication met quite a challenge this past week as the class assignment was to live and work for a full week without using any Google service. Read about the assignment, the rules and the outcomes on http://cultureandcommunication.org/tdm/s10/admin/a-week-without-google/, and be sure to check the comments.

The automatic classification of data, its indexing, and its evaluation are at the heart of new communication environments. What lies beneath is not just a drive to organize the world’s information, but also to classify human relations: from the management of the modern workplace and consumers in mass societies, to the bio-political management of the network society. Sociometric algorithms quantify all areas of life in order to mathematically model and predict human behavior. In today’s booming world of data mining, algorithmic methods based on large digital datasets are routinely used for determining political influence and analyzing social dispositions or contagious trends. Digital transactions provide huge amounts of private and semi-private data on personal preferences that are harvested to customize and transform everyday experiences.

A key nexus is provided by search engines, multi-purpose tools present in many dimensions of life, and the increasingly comprehensive environments of services offered by search engine providers. Understanding search-based societies does not only require an analysis of the deep history of the storing and indexing of information, but also the study of complex new forms of retrieval and data analysis. This includes the new position of search engines in a top-down control matrix as well as “bottom-up” recommendation systems, “push-search”, folksonomies and the presumed wisdom of crowds. Search can only be understood if the still evolving redistribution of power in digital networks is addressed in both its centralizing and de-centralizing dimensions.

The conference Deep Search II focuses on key issues in this fast and dynamic field. First, we want to highlight the historical dimensions of our attempts to organize information and people. Second, we want to investigate the politics of search, conflict and dimensions of power, and, finally, future classification schemes beyond search, tracking and social recommendation systems, including new forms of pattern recognition in large data sets.

Organized by the World-Information Institute
In cooperation with IRFS 2010

Reports of Deep Search l can be found here (part 1) and here (part 2).

Data Management as a signifying practice
David Gugerli, ETH Zurich
November 13, 2009, Amsterdam

Edited by: Baruch Gottlieb

Databases are operationally essential to the search society. Since the 1960’s, they have been developed, installed, and maintained by software engineers in view of a particular future user, and they have been applied and adapted by different user communities for the production of their own futures. Database systems, which, since their inception, offer powerful means for shaping and managing society, have since developed into the primary resource for search-centered signifying practice. The paper will present insights into the genesis of a society which depends on the possibility to search, find, (re-)arrange and (re-)interpret of vast amounts of data.

Download here the full lecture of David Gugerli given during the Society of the Query conference on Friday the 13th of November 2009.

The term Googlization, according to Siva Vaidhyanathan, is the process of being processed, rendered, and represented by Google.

Vaidhyanathan’s upcoming book The Googlization of Everything investigates the actions and intentions behind the Google corporation. This afternoon at The Society of the Query Vaidhyanathan choose one issue from his book: the politics and implications of Google Maps’ Street View.

According to EU law: there cannot be any identifiable information about a person in Google Street View. Google’ s standard defense up till now has been that they respect privacy by scrambling faces and license plates, to which Vaidhyanathan commented,

In my former neighborhood in New York there were probably 50 illegal gambling institutions around. Now, imagine an image of me on Google Street View taken in proximity to one of these illegal places. I’m more than two meters tall and I’m a very heavy man. You could blur my face forever, I’m still bald. In New York, usually I was walking around my neighborhood with a white dog with brown spots, everyone in the neighborhood knew that dog. So you could blur my face and it still wouldn’t matter – it’s me, I’m obviously me. Anonymization isn’t an effective measure, as we’ve already found out with data. (most likely referring to the AOL case of user #4417749)

Just this morning Swiss authorities made a statement that they plan on bringing a lawsuit against Google in the Federal Administrative Tribunal because Google isn’t meeting the country’s demands for tighter privacy protection with Google Street View. Vaidhyanathan commenting on the news said, “Google Street View has been entering so many areas of friction and resistance – this brings it to our attention that the game is over for Google.”

Vaidhyanathan’s criticism of Google Street View continued with Google’s trouble in Tokyo. “The strongest reaction against Google Street View has been in Japan,” he said, “Google will scrap all of their data from Japan and re-shoot the entire country. Google mismeasured how the Japanese deal with public space. In the older sections of Tokyo the street in front of one’s house is considered the person’s responsibility, it is seen as an extension of their house. Thus, Google Street View is actually invading someone’s private space.”

Earlier this year Google CEO Eric Schmidt made the following remark about the international appeal of Google,

The most common question I get about Google is ‘how is it different everywhere else?’ and I am sorry to tell you that it’s not. People still care about Britney Spears in these other countries. It’s really very disturbing.

Vaidhyanathan explained this as being a part of Google’s protocol imperialism,

Google isn’t particularly American, nor is it particularly American / Western European. It’s important to remember that Google is much more a factor of daily life in Europe. In the United States it is just barely 70% of the search market, in Western Europe it is around 90% and in places like Portugal it is 96% and I don’t know why.

For Vaidhyanathan the biggest problem with Google is that as it expands into more parts of the world that are less proficient, and less digitally inclined, there will be more examples of friction and harm because more people are going to lack the awareness to cleanse their record.

It’s important to note that Google does offer services for protecting and managing user data:

• Google Street View allows you to report objectionable content
• Google dashboard shows a summary of all the data Google stores about you.
• An engineering team within Google that refer to themselves as The Data Liberation Front is working to make it easier for users to control the data they store in Google’s products.

Vaidhyanathan didn’t specifically mention these options, but briefly acknowledged the existence of such tools before quickly moving onto the strongest part of his argument, “We in this room are not likely to be harmed by Google because all of us in this room are part of a techno-cosmopolitan elite. Only the elite and proficient get to opt out.”

In closing, Vaidhyanathan exemplified the problem with a photograph of a man caught on the side of a U.S. highway and commented, “This man doesn’t know that he is in Google Street View so we get to laugh at him. Not knowing is going to be the key to being a victim in this system.”

More information about Siva Vaidhyanathan and his criticism of Google can be found on his website, and in this lively Google debate at IQ2 and New York Times article from last year.

Martin Feuz is an independent researcher with a strong interest in human-information interactions. Specifically, he focuses on exploratory (Web) search and the ways in which such interactions can be meaningfully and experimentally supported. In his recent work, he undertook a critical analysis of Google personal search to open the lid of Google’s black box a little bit and to make some of its behavior more door reflection.
In Society of the Query, Feuz presents the research that lead to the development of his new website Perspectoma.com. Perspectoma is a research engine that allows us to get a glimpse into how Google Personal Search delivers ‘personalised’ search results on the basis of an users Search and Web History.
Perspectoma works by simulating Search and Web Histories. The website offers five profiles for which Search and Web Histories are developed. These profiles contain approximately the equal amount of search queries that an average user accumulates over two years of searching with Google.
When performing a search, Perspectoma’s search result page shows:

•    the search results only available for the profile
•    the search results of an anonymous user without personalization
•    the search results that are available to both, the selected profile and the anonymous user and but have a different search result ranking (blue)
•    the search results that are available to both, the selected profile and the anonymous user and share the same search result ranking (green)

Google describes personal search as ‘based on your search & web history. Your personal results will be re-ranked or swapped for more relevant ones.” However, it gives no indications whatsoever when a particular search result is personalized. Therefore you actually never really know where your returns come from, and which ones are specially there to target you as a consumer, or to help you. Google states that if you don’t want personal search, you can just sign out of your Google account, Unfortunately, this is not a very practical because in the end you seem to sign into Google very often and easily forget to sign out.

Feuz starts his presentation by posing four main questions he wanted to deal with while creating Perspectoma.

•    how soon (after how many queries) will Google Personal search play a roll in the Google search returns?
•    how do these personal returns develop in terms of frequency and intensity?
•    what underlying patterns can we identify?
•    how will grouping of profiles influence the search terms?

To find answers to these questions, Feuz describes the research he did according to the 3 ghost accounts based on the characters Kant, Foucault and Nietzsche. He trained all of the accounts equally in training sessions with the help of software that did different search queries. To do this, he had to find a way to make an artificial profile relational for subjective inspection of personalized search results. To tackle this problem, he used specific books for the different theorists. He also had to find a way to get plenty search terms to create profiles.
After training session 1 Feuz found that the search returns for Foucaults profile were personalized results quite early, but not very frequently. The search returns for Kant were a bit of personalized but not to much/to often. Feuz also considers that this could have to do with the type language Kant uses in his books. For Nietszche a lot of personalized results turned up, but this actually was the result of a small glitch in the technology.
Martin Feuz concludes that he is surprised how soon the personal search returns seem start turning up. Google personalized search is not shy. After the second training sessions the amount of personal returns seem to grow, while after 3000 search queries more than every second result is personalized. Also, it seems that there is a kind of group profiling happening.
Finally, Feuz states that personalized search does not seem to be able to lift the less dominant voices from deep down the unbiased search returns. Actually, it seems that most often personalization means that only some of the returns from the second page have been swapped into the first ten personal search returns.

Thanks for the opportunity to talk. I work at the VU and I am talking about the project Europeana. This is the result of a teamwork of the University, I am just presenting it.

Introduction
What is Europeana? It is a portal which that want to interconnect museum archives. Access to digital content. Currently there are 50 providers. and the number is growing. 10 million objects is the target. Maybe from a more practical : we want to create access but we also want create channels to other websites and so on. Such a thing does not go without challenges. The very issue of providing access that is very difficult. They are of an iterational nature. And how to get data besides the pictures? The method is to use metadata. Antoine shows the current portal, which he explains as a “basic search box” (picture needed). If a search query is done, different result are given that are linked to the search (pic, books etc). You can start refining you search by filtering (language, data and so on). This is called semantic search and it allows you to refine your search. To some extend this is not matching the richness of data that is out there in the databases. The idea is to go a step beyond semantic enables search. Some functionalities are explained, such as clustering. Antoine explains that by exploiting semantics, we can exploit relations that are stored in the objects. We can use information that is actually there already in the meta data. Some kind of organized knowledge is already there, we want to exploit it. The proper information properly accessible , that is the goal.

Example
A semantic layer on top the ‘normal’ results is presented. A graph is shown of a semantic web. It needs to become more useful for users, according to Antoine. A common concept that can aggregate for relations. A screen shot is given of the prototype. It is a mini-version of the total project: three museums are currently represented. You can start typing your search. The first difference ( from normal search engine red) is that it will be able to provide you with concepts and locations that could match your string. If you select one of the results , you get a number of new possible links and clusters via criteria. It is important to notice that the results are coming from really specific entities. We can see that the subject “egypt” for example gives a whole set of related objects. It is much more than a returned string.

This idea of having controlled entities can be used in more complex means. Users can  start exploring further knowledge and concepts.  An example is given on the search “egypt’ and the meta results. We are now searching via concept/relations.  This is an example of richer information. I also got clusters like works created by somebody who was in Egypt and so on… The reason for getting this object in the results is that in the metadata links back to the subject (query). There is a kind of person space emergent here.  Via this person, we can find out the place and we end up in Cairo. One very important point is that we benefit from existing models and vocabularies. Via labels on concepts, these concepts can be linked. It is very important because now you can access this information. We continue by determining these links (exact matches and relational matches). The main advantage of metadata is that it is heterogeneous. There a different description models. You cannot really anticipate it. Some form of alignment is required in order for the system to work, because these databases use different vocabularies. A data cloud is presented which represents the different vocabularies in the three different museums. These vocabularies are glued together.

Conclusions
The semantics in our case are getting structure in the data. It is about coupling the data.. It is a flexible architecture. It is about loading data. This makes ingestion for new data easy.  You don’t need to fully merge the workings of all the institutions/ content providers.  It is about connecting structures together. It allows easier access to the different vocabularies. You can start your search and you are provided with different vocabularies. Next, we have to bring in more vocabularies. You can have quality data in this system.  Finally, this vision  of the variable links model is nice, but some semantic matching level problems occur. This is difficult. A link is given: here you can try the portal here

Questions
Rogers: Don’t you need an army if you want to actually make the links and translation between all the records?
Isaac: you are right, we actually implemented something (the three museums vocabularies), we are not experts on library science. Until recently, however, the library scientist did not come out of their institutions. Now, they start to realize they can integrate their knowledge. I believe this is an added value.

Rogers: Is this more than digitizing library systems? Is this indexible by Google?
Isaac: Yes, it should be.
Rogers: is it deep indexible? isn’t this a huge policy question?
Isaacs: This prototype publishes the data. You can see the source of the data.

Pembleton: analogy: Tim Bernes-Lee created a website that can point to all your data. What I see here is the- same move. By linking the concepts, not the data. This provides a richer web.
Rogers: Is this a Europe-island web, then?
Cramer: We already have such a system: it is called RSS.

Audience: A method that I see here is: we need glue to link existing concepts and vocabularies. The other is to generate new vocabularies . To me that seems to be a large debate.
Pembleton: We use the same underlying technology.  I see more added value rather than competition.
Cramer: RDFA is not a vocabulary, it is a language to format the vocabulary (which is a huge difference).