Bookmarked Anatomy of an AI System by an author (Anatomy of an AI System)
We offer up this map and essay as a way to begin seeing across a wider range of system extractions. The scale required to build artificial intelligence systems is too complex, too obscured by intellectual property law, and too mired in logistical complexity to fully comprehend in the moment. Yet you draw on it every time you issue a simple voice command to a small cylinder in your living room: ‘Alexa, what time is it?”
This dive into the world of the Amazon Echo provides an insight into the way that engages with vast planetary network of systems in a complicated assemblage. This includes the use of rare metals, data mining, slavery and black box of secrets. These are topics touched upon by others, such as Douglas Rushkoff and Kin Lane, where this piece differs though is the depth it goes to. Through the numerous anecdotes, it is also reminder why history matters.


Put simply: each small moment of convenience – be it answering a question, turning on a light, or playing a song – requires a vast planetary network, fueled by the extraction of non-renewable materials, labor, and data. The scale of resources required is many magnitudes greater than the energy and labor it would take a human to operate a household appliance or flick a switch.

Smartphone batteries, for example, usually have less than eight grams of this material. 5 Each Tesla car needs approximately seven kilograms of lithium for its battery pack. 6

There are deep interconnections between the literal hollowing out of the materials of the earth and biosphere, and the data capture and monetization of human practices of communication and sociality in AI.

Just as the Greek chimera was a mythological animal that was part lion, goat, snake and monster, the Echo user is simultaneously a consumer, a resource, a worker, and a product.

Media technologies should be understood in context of a geological process, from the creation and the transformation processes, to the movement of natural elements from which media are built.

According to research by Amnesty International, during the excavation of cobalt which is also used for lithium batteries of 16 multinational brands, workers are paid the equivalent of one US dollar per day for working in conditions hazardous to life and health, and were often subjected to violence, extortion and intimidation. 16 Amnesty has documented children as young as 7 working in the mines. In contrast, Amazon CEO Jeff Bezos, at the top of our fractal pyramid, made an average of $275 million a day during the first five months of 2018, according to the Bloomberg Billionaires Index. 17
A child working in a mine in the Congo would need more than 700,000 years of non-stop work to earn the same amount as a single day of Bezos’ income.

The most severe costs of global logistics are born by the atmosphere, the oceanic ecosystem and all it contains, and the lowest paid workers.

In the same way that medieval alchemists hid their research behind cyphers and cryptic symbolism, contemporary processes for using minerals in devices are protected behind NDAs and trade secrets.

Hidden among the thousands of other publicly available patents owned by Amazon, U.S. patent number 9,280,157 represents an extraordinary illustration of worker alienation, a stark moment in the relationship between humans and machines. 37 It depicts a metal cage intended for the worker, equipped with different cybernetic add-ons, that can be moved through a warehouse by the same motorized system that shifts shelves filled with merchandise. Here, the worker becomes a part of a machinic ballet, held upright in a cage which dictates and constrains their movement.

As human agents, we are visible in almost every interaction with technological platforms. We are always being tracked, quantified, analyzed and commodified. But in contrast to user visibility, the precise details about the phases of birth, life and death of networked devices are obscured. With emerging devices like the Echo relying on a centralized AI infrastructure far from view, even more of the detail falls into the shadows.

At every level contemporary technology is deeply rooted in and running on the exploitation of human bodies.
The new gold rush in the context of artificial intelligence is to enclose different fields of human knowing, feeling, and action, in order to capture and privatize those fields.

At this moment in the 21st century, we see a new form of extractivism that is well underway: one that reaches into the furthest corners of the biosphere and the deepest layers of human cognitive and affective being. Many of the assumptions about human life made by machine learning systems are narrow, normative and laden with error. Yet they are inscribing and building those assumptions into a new world, and will increasingly play a role in how opportunities, wealth, and knowledge are distributed.

via Doug Belshaw

Replied to Freshly Brewed Thoughts: November 2, 2018 by an author (Freshly Brewed Thoughts)
I try to believe there are good people everywhere. In Big Pharma, there are dedicated scientists who really are trying to help people, right? It’s not their fault that capitalism functions as it does. They’re just trying to help. It’s the soulless executives that use unbranded marketing to convince people that they’re sick, not the scientists.
Interesting piece about pharmaceuticals Laura, especially the onus put on the consumer to be critical:

So what can people do? Experts I asked advised paying close attention to signals of underlying financial connections, both on websites and social media posts and in messaging from seemingly benign health groups. Matthew McCoy, the medical ethics professor, says people should be vigilant if an organization’s funding sources and board members are obscured, or “if the life cycle of a group seems to perfectly match the push for FDA approval for a drug.”

It’s valuable advice. But it puts on the onus on patients, who shouldn’t have to know better.

This reminds me of the argument as to whether it is unethical to work at Google? For example, is an engineer for Docs impacted by wider choices as AI investing in the military or the development of a modified search engine for China? It would seem that from the response of workers that they are inadvertently.

I wonder if rather than trying to identify the parts in isolation, that we are better considering the various actors? I really enjoyed this breakdown of Latour’s work in this regard. For example, consider this description:

Gravity, he has argued time and again, was created and made visible by the labor and expertise of scientists, the government funding that paid for their education, the electricity that powered up the sluggish computer, the truck that transported the gravimeter to the mountaintop, the geophysicists who translated its readings into calculations and legible diagrams, and so on. Without this network, the invisible waves would remain lost to our senses.source

Not sure what this looks like in regards to Big Pharma, however I think that James Bridle’s book helps extend this conversation, especially with his discussion of Eroom’s Law:

Over the past sixty years, despite the huge growth of the pharmacological industry, and the concomitant investment in drug discovery, the rate at which new drugs are made available has actually fallen when compared to the amount of money spent on research – and it has fallen consistently and measurably.