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Understanding the Digital World


Understanding the Digital World series we have formed under the roof of Atlas Publishing Lab is to talk to people working and producing in different fields on today's knowledge, discussions and problems. We aim to make room for thinking in this digital, accelerating, and unfocused world where we feel like we are always lagging in something. By thinking with the people we interview in this series, we form a series of dialogues about changing habits, technologies, societies, power relations, relations of production, and changing humans.



NFT, Blockchain and Digitalization of Art 1


Biçem Kaya & Mahir Yavuz


Translator: Övgü Doğangün Olson

Editors: Mehmet Ekinci & Evrim Öncül


@ This image was generated by using Midjourney AI by Mahir Yavuz.




The Cloudy Power Dynamics of the Internet

Is It a Question of the Essence? Or Designers of Technology?




Biçem Kaya: The argument over the digitalization of society has shifted its direction with Bitcoin. It stemmed from blockchain technology, which was initially formed due to the Global Economic Crisis in 2008. Digital information production and sharing modalities such as Ethereum, DeFi, DAO, and NFT came afterwards. As all these developments were starting to align around blockchains, we started to see terms like Web 3.0 and Web 3 that claimed to explain how the digital ecosystem works, its scope, and futuristic speculations more often.

I want to start with a technical question. How would you explain the basic differences between Web 3.0, which is also called “Semantic Web”, and Web 2.0, especially for those unfamiliar with the software world? We should also not overlook the nuances between Web 3.0 and Web 3. What are the differences between these two terms? And why is it crucial to understand these nuances to figure out the current internet and society relationships?


Mahir Yavuz: Web 1.0, 2.0, and 3.0 are the terms used to define the internet generations. We can think of them as Generation Y or Generation Z. Even though the transition between generations is not too clear, according to internet researchers and digital society “pundits”, certain periods have certain characteristics. For example, Web 1.0, i.e., the first stage of the internet, had much less interaction. Publishers (personal or corporate) would publish the contents they would like to share (usually as texts) on their page, and we would read and consume them. It was a period when “Read Only” mode was predominant, and users had no control over the content. Since it was a new medium with no rules, we can think of it as the most chaotic, but on the other hand, the most independent, uncontrolled, anonymous period of the internet.


Web 2.0, the social web where users have power over the content, is the period we are currently in. There is content creation and consumption that is managed over social media. The companies that have the highest market cap are generally the companies that put in work in this area. Since these contents are still distributed by large companies, they tend to be scattered. However, data still is stored, distributed, and controlled in a centralized fashion. As we sometimes see at certain places occurrences like banning YouTube or slowing access to Twitter and deleting content, we can safely say that the centralized system is not free at all.

As for the difference between Web 3.0 and Web 3, we can say that the distinction came about because different people used the same term. “Web 3.0” is an internet promise that was launched by Tim Berners-Lee, where this new network will tie everything related to the internet to each other semantically. “Web 3” is the promise of a decentralized internet formed by Gavin Wood, where data is stored on the blockchain to eliminate the centralization of large companies. In my opinion, both aim to explain what comes after Web 2. To make things simpler, I will put both in the Web 3.0 bucket.


I think Web 3.0, at this point, represents a world where the borders are not fully formed, but the internet is more semantic, more decentralized, and where the internet tools are more attached to each other. The most significant difference between Web 3.0 and Web 2.0 is the promise of decentralization. I’m calling it a promise because it is uncertain if this can be accomplished both socially and economically. Generally, this topic is discussed from a technical perspective. Current blockchain technology succeeds in providing decentralized money, economy, internet, etc. However, if this promise I mentioned happens, different companies and financial habits will emerge. I am not sure if we are prepared for this or if the entities who already have the power (global companies or the governments that control the internet infrastructure) are willing to have such a change. The best-known examples of this change are digital currencies or blockchain-based uncontrolled social networks. Is it possible to use money without the governments’ supervision? Would governments or entities permit a social network with no owner or a filtering mechanism? After all, it is about power, filtering, and controlling money flow.



B.K. Tech giants such as Google and Facebook, monitoring and recording personal information against human rights and selling it to third parties, have created colossal control mechanisms by cooperating with governments. We must accept that the notion of individual freedom cannot exist in a setting where all human action is recorded. We are going through an extensive transparency crisis caused by data asymmetry.


You have been working on open-source data projects, and you are sharing them on social media regularly. What are your thoughts on the positive impact of your open-source data studies on the data asymmetry problem? In light of your own projects and motivation, how do you evaluate where we are today?


M.Y. The keyword here is transparency. Transparency between people and entities or governments has always been limited. And now we are facing an even less transparent relationship. I think the most prominent global trend of the last ten years is collecting, storing, processing, and using personal data without consent. Not only global companies but also governments are involved in this. Twitter transparency reports, police surveillance reports, and US customs officers copying travellers’ phone numbers could be examples of this. I think there are two main issues here. First is the data collecting and processing systems, and second is the nature of the data. These two issues have a type of “fog of war” and are both quite clusters of ambiguity. Right now, none of us, including me, have any idea about which company or government has what kind of personal data about us and how this data was collected. That is “by design”, i.e., the people who designed these mechanisms do not like to expose the details.

In this context, in open-source studies, I find it more important to focus on the systems that collect and process the data rather than on a specific piece of it. Some of the projects I have participated had stemmed from this. The AI Future Commons workshop organized in 2016 is an example. There are excellent studies and books on this topic: Living in Data by Jer Thorp; Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence by Kate Crawford; The Alignment Problem Machine Learning and Human Values by Brian Christian. It is crucial to draw attention to the fact that the problem is the system rather than the data.


Unfortunately, open-source projects and initiatives developed by independent software developers, researchers, or groups do not reach many people, and people usually prefer convenience to transparency. Even though it’s a little better than the last few years, I think where we are today is not so pleasant.



@ This image was generated by using Stability AI by Mehmet Ekinci.



B.K. I would like to continue analyzing data asymmetry from a pessimistic perspective. Let me share a more global observation. We are going through a time of political polarization on a global scale between the US and China-Russia. Wars and political action plans are in motion under the tension of said polarization. So is the control of the internet. Unsurprisingly the two blocs implement different policies for controlling the internet. The US is already controlling a major part of the web through internet giants like Google and Facebook; so, it’s safe to assume that the US manages the internet. On the other hand, with the Cambridge Analytica scandal, it became obvious that the issue is not only illegally recording and using personal data but also the fact that corporations are ruling the US which means that the internet rules the US. Even though European leaders are reacting toward the democratization of the internet and supporting freedom of thought, their reactions are not strong enough, and their tone makes us question their sincerity.


China and Russia clearly state that they don’t care about democratization, and they have a more closed and controlled internet model in the country. The internet is openly working as a monitoring tool. The other neo-fascist governments are inspired by this policy, and they are limiting access to any content they like at any time, for any amount of time, without any question. And the rest of us go back and forth between these dead-end streets.


There is also the agenda that includes real-and-virtual actions such as moving along under the shadow of this polarization: projects around blockchain, dreams of Web 3, decentralization that we should discuss in the context of freedom of internet, and democratization of technology, etc. Of course, it’s hard to feel hopeful after hearing about the statistics of how the familiar “white male” profile of the blockchain ecosystem is forming another food chain of winners and losers. (Please see GEMINI’s 2021 report.) How do you evaluate the current multiple polarizations? How realistic is it to expect Web 3 to be the saviour?


M.Y. The picture you painted is realistic for the most part. Right now, there seems to be a dual internet structure between two blocs, namely the Western (mainly the US) and China-Russia blocs. (On this issue, one can read Jer Thorp’s book Living in Data: A Citizen's Guide to a Better Information Future, Kate Crawford’s Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence and Brian Christian’s The Alignment Problem: Machine Learning and Human Values.)

One is following an internet policy that claims to prioritize autonomy and independence, and the other is open about its closed and controlling internet policy.


Since the Western bloc — which the US spearheads — puts money and capitalism in the centre, the internet should be independent and uncontrolled to a certain extent. At least they should be open to new ideas and practices. Countries like China and Russia do not share the same concerns. A bipolar internet status quo is increasingly becoming realized. But these two poles consist of heterogeneous social and political factors among themselves, too. The internet bans and restrictions in Turkey and Iran can be different. Or a country like Kazakhstan can purchase a monitoring tool made in Israel. The biggest problem in the notion of a capitalist internet that the US developed is the fact that the important decisions are almost completely left in the hands of corporations. The most impactful structural changes in the internet or the decisions that affect people are the ones primarily made by companies like Google, Amazon, Facebook, or Apple.


Another issue is the infrastructure war between the US and China. At the end of the day, the internet is a system that runs through web protocols and infrastructure. Systems like cable, satellite, and 5G have significant importance. We can observe the polarization in the contention over the 5G network. China wants to market its 5G technology via Huawei to Africa and other developing countries, but the US is totally against it. They claim this is a big security issue for countries using this technology. So, there is a commercial power struggle as well as a political one.


In this current socio-technological environment, I don’t think Web 3 can take on a saviour role and can accomplish it. The ones who developed and distributed the Web 3 technology also need capital and infrastructure. Independent of the duality we are talking about and the two different superpowers, I still don’t think it’s realistic to expect Web 3 to grow. Most probably, all sides will develop Web 3 technologies they understand well, and then they will try to market those technologies to the rest of the world.



B.K. There is also the algorithmic bias side of this issue. We know that Artificial Intelligence can behave in a racist fashion. Thanks to the face recognition study by Joy Buolamwini, a significant degree of awareness has been raised around the fact that artificial intelligence does not recognize important African American females such as Michelle Obama or Serena Williams, but it has a 99% success rate on male figures.


Here is where I am going with this. Based on blockchain technology, one of the most realistic future scenarios for the post-pandemic world is e-society. The goal is to make the most critical areas of government services, such as health and education, faster and problem free. Of course, artificial intelligence is one of the most important components of the system. If we also include algorithmic bias in this mix, we can see that big problems are waiting for us in the future. Do you think we can avoid algorithmic bias? What can technology do to overcome systemic fascism, racism, and sexism? Based on your study “United Colors of Dissent” with Orkan Telhan, where do you put the “Smart City” concept in this scenario?


M.Y. The subject of algorithmic bias is very popular in the US. It is a fact that generally, there is racism towards non-white people in the algorithms in security software, job application software, criminal record ads, health, and many other areas. But in my mind, this problem stems from the data that feeds the algorithm and the society that generates the data, not the algorithm itself. Most prediction algorithms are developed to calculate a probability. If the data in the system supports a particular bias, it is not surprising that the algorithm detects it. What needs to be done is to use reasoning to determine where not to use the algorithm and not make the problems in a given society bigger by automation. Algorithmic Justice League (AJL) is a group that develops projects and studies on this subject. “AI Now” is another institution that provides research on how to use artificial intelligence and how not to use it. Another good resource is the report on algorithmic bias finding and how to compensate for it, published by the Brookings Institute.


On the smart city subject, I think many smart city projects are a marketing tool to establish an unrestricted and uncontrolled surveillance system. Of course, all may not be this way, but many were developed for this reason. Most of them suggest a centralized management and data storage system. If you look at the early versions of these projects, you will see that they are based on cameras that are connected to each other, and face recognition is the primary software they use. Maybe the reason for this is not to make the city smart but to control the people. Countries like China, the US, and the UK have made significant investments in this area because of September 11 and because the technology got cheaper in time.

In Turkey nowadays, almost all towns, large and small, have cameras at their entrance. We can’t claim that a city is smart based on these technologies.


This will sound a little pessimistic, but unfortunately today, AI applications and science fictionesque narratives such as smart cities are generally used to help global companies to make moves to raise their earnings or to make sure governments can control people and find the ones with an opposite ideology quickly. Even though these narratives look very promising, as if they will create a bright future for us, there is another story behind them. Researchers as well as the people on the street should ask these questions: 1) Who is producing this technology? Is it a company that primarily aims to make money out of it? Is it the government, or an independent group? 2) Aside from the stories we are being told, what other outcomes can come from this technology? 3) Who will make money from this technology?


If we can all ask these questions, hopefully, we can access the independent and decentralized web that is being promised in realistic terms.



Mahir Yavuz

Mahir Yavuz has a personal and professional history of working with various technology companies on data science and artificial intelligence. Currently, he is managing the artificial intelligence team of a large technology company in New York. He studied Visual Communication Design at Bilgi University and Interface Cultures at Linz Art University. He worked on specific art and design projects concerning data science and smart cities at Ars Electronica Futurelab before he moved to the US. Since 2011 he has been co-publishing a podcast called “Adaptation” with Onur Akmehmet.


Biçem Kaya

She continued his career in architecture after her undergraduate education at Mimar Sinan Fine Arts University. Alongside her work at Bant Mag. as an editor, she writes content/news and does interview. In recent years, she has focused on the reserchers on the intersection of technology and architecture.





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