The Networked Condition Case Study: Vladan Joler

A complex map of inside a computer is printed in white on a black background with tiny text and line work
Anatomy of an AI System: The Amazon Echo as an anatomical map of human labor, data and planetary resources

At the start of 2020, Fast Familiar, Abandon Normal Devices and Arts Catalyst began The Networked Condition, an ongoing collaborative research project exploring the environmental impact of digital cultural production.

The project is part of The Accelerator Programme (led by Julie’s Bicycle and Arts Council England), which supports organisations to advance sustainable practices and share insights with peers and the wider sector. As part of The Networked Condition, we’ve been speaking to artists and researchers whose work uses and/or critically reflects on digital tools and environmental challenges, to gain insight into a range of ideas and approaches. We are publishing these case studies as we go along, with the intention that they will be a source of shared knowledge, inspiration or reflection for others too.

The second case study is with Vladan Joler, an artist, academic, and leader of SHARE Lab – a research and data investigation lab for exploring different technical and social aspects of algorithmic transparency, digital labor exploitation, invisible infrastructures, and technological black boxes.

We spoke to Vladan about his 2018 project, The Anatomy of An AI – an investigation into the material and human supply chains behind artificial intelligence.

Tell us about you and your research.

I’m working as a university professor in the New Media department at the Academy of Arts here in Novi Sad, Serbia. And I run an organisation called Share Foundation – a research project on internet activism and internet rights. That’s what got me investigating different kinds of infrastructures, flows of data, data centres and so on, which led me to drawing different kinds of maps – mostly trying to understand black boxes or what’s going on behind the screen. And then I met an artist called Joana Moll and through her work I became addicted to the materiality of technology. I already knew what’s behind the net, what the infrastructure looks like, but I started to really think about the deep time of infrastructure.

For me the key is not just to think about the relation between humans and technology, or society and technology, but to think about a triangle between humans, nature and technology. Because when you start to think about nature in that context, then it completely changes the picture. The more you investigate those supply chains, you see how the world’s functioning today is not optimised to think about nature; it’s just optimised for profit and speed. In my circles, no one was speaking about the relation with nature so much. I was going around internet activism conferences and for a long time it was not the topic.

For example, Fair Phone tries to be a phone that doesn’t involve exploitative labour – it’s a great idea and I love this project because they tried, but in the end they said they managed to make the phone 7% fair, and the product costs €700. They managed to do it at the last step: people in Shenzhen who assemble the phones are paid well. But if you want to make a really fair phone then you will need to pay thousands and thousands of people well. To make a fair phone you need to make a fair earth, in a sense that everyone believes in some kind of fair pay. The problem can’t be solved in a design studio in Amsterdam or London; it needs to be solved in Africa, China, Latin America, everywhere. It’s not a design problem, it’s a system problem.

Or another example: the price of electricity in Iceland is lower because they have energy from below the ground, so aluminium ore or bauxite is shipped from another part of the globe to Iceland to use cheap electricity to burn it, and then shipped back. This is completely normal in supply chains. And those ships are using cheap fuels and so on and so on, so the real price is never counted. But what we are seeing is a huge accumulation of profit without paying this price that all of us are sharing. But if you want to deconstruct that problem then you need to speak about the problem of capitalism, colonialism, all of those hard questions. It’s deep.

Anyway, then I met Kate Crawford (who previously ran The AI Now Institute) and we started an investigation into the Amazon Alexa, but from the point of view of deep time, which took me to the Anatomy of an AI project.

From doing so much research for that project, I found there are so many different angles you can read or speak about.So now I’m working on a new map called New Extractivism – it’s a similar topic but somehow more poetic, like an assemblage of different philosophical ideas around the topic. So you have a black hole sucking in users, and then you’re entering into Plato’s cave… it’s really crazy, it’s funny. That’s the direction I’m heading in this moment.

What is the Anatomy of an AI project?

If you turn back time on all our infrastructures, all of those particles were (for example) different kinds of rocks, and then those rocks and metals and materials are somehow transformed by labour, then in 50 years all of them will be some kind of rocks again. So the project is trying to explain this deep time, looking at the past, present and future, or birth, life, death.

But if you start to think about infrastructures, data centres and everything then you eventually get to the mines in Congo or elsewhere on the globe, and then the questions aren’t the same anymore. Because before it was about privacy, security, data exploitation, this kind of stuff. But when you start to think from the position of supply chains and everything, then the main problem is a problem of labour and a problem of nature. So we called the project an anatomical case study of the Amazon Echo as an artificial intelligence system made of human labour. It’s a map accompanied by an essay in 21 parts.

Supply chains are like black boxes – they’re so hard to understand, because you have hundreds and hundreds of different companies and production chains. It’s not so easy to find what’s coming from where. For example, once you melt metal it’s really hard to deconstruct where it came from. And it’s not easy to communicate your findings because they’re so complex. The map in Anatomy of an AI is a super-simplification of what’s going on.

What is really hard is to combine all the research around the topic in one image, or in one story. There were a few different elements that for me were really important to get across. One was the three phases of birth, life, death, or past, present, future. Another was to tell a story, and to have some kind of visual story. So it’s those triangles that are the main tools to tell the story - resource, labour, product. Through those, I try to lead the story from the bottom - from elements to the product and back.

I spent a lot of time in the beginning with lawyers, coders, and programmers, because I was thinking they are the ones capable of understanding how the world is functioning nowadays. But I also needed to go into some abstract research fields around labour and exploitation, so I found it was easier to use the tools and knowledge of media theory, art and philosophy, rather than rigid things like code and law. I realised we were trying to tell a different story. We are dealing with some really big, hidden complexities that are really hard to process, and I think it’s our mission in the arts and humanities, to navigate those systems through stories and mapping (well, it doesn’t need to be a map exactly).

What are your methods for approaching the research?

Academically, I was inspired by Christian Fuchs’s work on digital labour and Marxism, as well as Jussi Parikka’s book A Geology of Media, which sets out the material processes involved in making digital technology. I was going all around the world – I spent some time in India going to investigate some illegal mining operations, and then in China and I was collecting, collecting, collecting. There was some support from Mozilla Foundation, and basically I misused that to go around the world and see different places and investigate different things (a pity in the end they didn’t understand the final product, but that’s OK. I spent a lot of time visiting places, and that was great).

There’s nothing especially that I found in those places – it’s not that you’re finding some clue on the ground and following it. It’s more that you’re completely attached to the story, because if you’re going there and seeing those places then you’ll be more able to feel them. And you can feel the materiality of those places and production cycles. You feel like some kind of detective, you know, and that drives you to go further. Different places give you different feelings. So I’ve been in a village in India where they’re managing e-waste, and there was a family and the father was lying on the bed having tremors because of the fumes, but still continuing to be there. Another time, we managed to go to this Amazon storage warehouse – a place where the robots move boxes – which is the future of labour. You’re seeing people who are part of some kind of machine-process but they have no clue what they’re doing or why they’re doing it, they just have some kind of impulse to move their hand there. It was so extreme.

If you try to work as an investigative journalist, it’s really hard to do it well. I’ve worked a lot with them on other projects and they will never publish stories in the way we do as artists, because they need two or three sources for each thing. But what I learnt from them is how to go around, how to speak to people, how to investigate. As artists we have the possibility to use different methodologies - to combine investigative journalism and map-making, or whatever. I think this is good for the final thing that you’re doing. The investigating is important, but I think we have the opportunity to make it more appealing to people, to make it more interesting.

What have you learnt from the project?

For me it’s that extending the life of objects is actually the most important. When I was on Alang beach in India (one of the World's largest ship breaking yards) it felt like one of the most apocalyptic places in the world. You’re seeing hundreds of people with bare hands and ropes pulling enormous ships onto shore and then jumping on them and removing parts. It’s a really amazing place. But what was interesting for me: next to that beach you have one street that is those completely deconstructed ships arranged into shops. And then you see the furniture from those ships in homes in India. The best thing you can do is use the form as much as you can, whatever form that is. So it’s not about buying a fair phone; it’s about using the phone you have for as long as you can. There’s planned obsolescence, but I think they say 50-60% of the phones we’re throwing away are still working – why is that happening?

And there are other really interesting topics to investigate further. For example, there are people doing engineering to use the old technology as best we can. There are some really interesting YouTube channels of people fixing Apple laptops. The company are doing all they can do to stop you opening, repairing, fixing, extending the life of the device – they don’t give access to blueprints (so there’s an illegal market), and they use pentalobe screws so you can’t even open the computer with a regular screwdriver. It comes down to: who owns the thing? You or them? It’s about the well-being of the devices, if you like.

And then you can also think about “ethical AI” – the EU are spending millions or billions on this idea that they will be different to others using AI because theirs will be ethical. But ethical in which segment? Are the datasets going to be ethical? Is it going to include all of those things that are behind, all the hidden labour that goes into it? But on the other side you can say well at least the EU is speaking about ethical AI in some sense; others just want practical AI.

How are you thinking in your approach to evaluation of the project?

I’d like people to go deeper, try to oppose some things there or to create other versions of the map, because it’s just one way to represent this complexity. I’d like people to be making their own maps, making their own pictures. But in a way it’s really hard to do these long projects, to investigate something for a long time, because nothing is set up for that; everything is set to be short and effective. It’s really hard to even have the courage to try to think through, or sum up, something so complex.

Any tips for artists trying to do similar things?

That’s a very hard question.

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Vladan Joler is an academic, researcher and artist whose work blends data investigations, counter-cartography, investigative journalism, writing, data visualisation, critical design and numerous other disciplines. He explores and visualises different technical and social aspects of algorithmic transparency, digital labour exploitation, invisible infrastructures and many other contemporary phenomena in the intersection between technology and society.

He has curated and organized numerous events and gatherings of Internet activists, artists and investigators, including SHARE events in Belgrade and Beirut. His artistic pre-history is rooted in media activism and game hacking.

Vladan Joler’s work is included in the permanent collections of the Museum of Modern Art (MoMA) in New York City, the Victoria and Albert Museum and the Design Museum in London, and also in the permanent exhibition of the Ars Electronica Center.His work has been exhibited in more than a hundred international exhibitions, including institutions and events such as: ZKM, XXII Triennale di Milano‎, HKW, Vienna Biennale, V&A, Transmediale, Ars Electronica, Biennale WRO, Design Society Shenzhen, Hyundai Motorstudio Beijing, MONA, Glassroom, La Gaite Lyrique, the Council of Europe in Strasbourg and the European Parliament in Brussels.

He has received numerous awards, including the 2019 Design of the Year Award by the Design Museum in London and the S+T+ARTS Prize ’19 Honorary Mention by the European Commission and Ars Electronica.