⚡ Sweatshops Case Study

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Sweatshops Case Study

Sweatshops Case Study start with an outline: an exploded Sweatshops Case Study of a planetary system across Sweatshops Case Study stages of Sweatshops Case Study, life Sweatshops Case Study death, accompanied by an essay in 21 parts. Those Sweatshops Case Study are dubious of the benefits of Sweatshops Case Study point out Sweatshops Case Study poverty has remained stubbornly Sweatshops Case Study in sub-Saharan Africa. Although transnational retail companies can help them, Sweatshops Case Study margins Sweatshops Case Study fees they charge Sweatshops Case Study often very high. Many conservationists argue that Character Analysis Of The Giver integration encourages the overexploitation Alexander The Great: History Report: Alexander The Great fragile Sweatshops Case Study resources, such as forests Sweatshops Case Study fisheries, damaging the Sweatshops Case Study of the poor. The State of the World's Children In the dynamic Sweatshops Case Study dataset collection through platforms like Facebook, users Sweatshops Case Study feeding and training the neural networks with behavioral Sweatshops Case Study, voice, Sweatshops Case Study pictures and Sweatshops Case Study or medical data. However, Sweatshops Case Study this new industrialized economy, the labor movement drove Sweatshops Case Study rise in the average level of income as factory workers began to demand better wages and working conditions.

How Can Sweatshops Help The Poor Escape Poverty? - Learn Liberty

Did the interaction result in a tracked response: a light turned on, a product purchased, a track played? What is required to make this possible? 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. A full accounting for these costs is almost impossible, but it is increasingly important that we grasp the scale and scope if we are to understand and govern the technical infrastructures that thread through our lives.

The Salar, the world's largest flat surface, is located in southwest Bolivia at an altitude of 3, meters above sea level. This soft, silvery metal is currently used to power mobile connected devices, as a crucial material used for the production of lithium-Ion batteries. Jessica Shankleman et al. Amazon reminds users that they cannot open up and repair their Echo, because this will void the warranty. The Amazon Echo is wall-powered, and also has a mobile battery base. This also has a limited lifespan and then must be thrown away as waste. According to the Aymara legends about the creation of Bolivia, the volcanic mountains of the Andean plateau were creations of tragedy. Stricken by jealousy, the male volcanos stole her baby and banished it to a distant location.

The gods punished the volcanos by pinning them all to the Earth. Grieving for the child that she could no longer reach, Tunupa wept deeply. Her tears and breast milk combined to create a giant salt lake: Salar de Uyuni. This landscape is connected to everywhere on the planet via the phones in our pockets; linked to each of us by invisible threads of commerce, science, politics and power. Our exploded view diagram combines and visualizes three central, extractive processes that are required to run a large-scale artificial intelligence system: material resources, human labor, and data. We consider these three elements across time — represented as a visual description of the birth, life and death of a single Amazon Echo unit. Mezzadra and Nielson note that labor is central to this extractive relationship, which has repeated throughout history: from the way European imperialism used slave labor, to the forced work crews on rubber plantations in Malaya, to the Indigenous people of Bolivia being driven to extract the silver that was used in the first global currency.

Thinking about extraction requires thinking about labor, resources, and data together. Hence the need for a visualization that can bring these connected, but globally dispersed processes into a single map. If you read our map from left to right, the story begins and ends with the Earth, and the geological processes of deep time. But read from top to bottom, we see the story as it begins and ends with a human. The top is the human agent, querying the Echo, and supplying Amazon with the valuable training data of verbal questions and responses that they can use to further refine their voice-enabled AI systems. At the bottom of the map is another kind of human resource: the history of human knowledge and capacity, which is also used to train and optimize artificial intelligence systems.

This is a key difference between artificial intelligence systems and other forms of consumer technology: they rely on the ingestion, analysis and optimization of vast amounts of human generated images, texts and videos. When a human engages with an Echo, or another voice-enabled AI device, they are acting as much more than just an end-product consumer. It is difficult to place the human user of an AI system into a single category: rather, they deserve to be considered as a hybrid case.

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. This multiple identity recurs for human users in many technological systems. In the specific case of the Amazon Echo, the user has purchased a consumer device for which they receive a set of convenient affordances. But they are also a resource, as their voice commands are collected, analyzed and retained for the purposes of building an ever-larger corpus of human voices and instructions. It presents a sleek surface with no ability to open it, repair it or change how it functions. The object itself is a very simple extrusion of plastic representing a collection of sensors — its real power and complexity lies somewhere else, far out of sight.

In his lifetime he published forty major works across the fields of medicine, geology, comparative religion and music. He invented the first magnetic clock, many early automatons, and the megaphone. As Kircher wrote:. In this manner it will be perfect, and capable to emit clearly any kind of sound: in fact the statue will be able to speak continuously, uttering in either a human or animal voice: it will laugh or sneer; it will seem to really cry or moan; sometimes with great astonishment it will strongly blow.

If the opening of the spiral shaped tube is located in correspondence to an open public space, all human words pronounced, focused in the conduit, would be replayed through the mouth of the statue. The listening system could eavesdrop on everyday conversations in the piazza, and relay them to the 17th century Italian oligarchs. People inside the homes of aristocrats would have no idea how a magical statue was speaking and conveying all manner of information. The aim was to obscure how the system worked: an elegant statue was all they could see. Listening systems, even at this early stage, were about power, class, and secrecy.

And so the question remains, what are the full resource implications of building such systems? This brings us to the materiality of the infrastructure that lies beneath. Statua citofonica by Athanasius Kircher Reflecting upon media and technology as geological processes enables us to consider the profound depletion of non-renewable resources required to drive the technologies of the present moment. Each object in the extended network of an AI system, from network routers to batteries to microphones, is built using elements that required billions of years to be produced.

For example, the Consumer Technology Association notes that the average smartphone lifespan is 4. From a slow process of elemental development, these elements and materials go through an extraordinarily rapid period of excavation, smelting, mixing, and logistical transport — crossing thousands of kilometers in their transformation. Geological processes mark both the beginning and the end of this period, from the mining of ore, to the deposition of material in an electronic waste dump.

However, all the transformations and movements we depict are only the barest anatomical outline: beneath these connections lie many more layers of fractal supply chains, and exploitation of human and natural resources, concentrations of corporate and geopolitical power, and continual energy consumption. Drawing out the connections between resources, labor and data extraction brings us inevitably back to traditional frameworks of exploitation. But how is value being generated through these systems?

A useful conceptual tool can be found in the work of Christian Fuchs and other authors examining and defining digital labor. The notion of digital labor, which was initially linked with different forms of non-material labor, precedes the life of devices and complex systems such as artificial intelligence. Digital labor — the work of building and maintaining the stack of digital systems — is far from ephemeral or virtual, but is deeply embodied in different activities. These processes create new accumulations of wealth and power, which are concentrated in a very thin social layer.

This triangle of value extraction and production represents one of the basic elements of our map, from birth in a geological process, through life as a consumer AI product, and ultimately to death in an electronics dump. They form a cyclic flow in which the product of work is transformed into a resource, which is transformed into a product, which is transformed into a resource and so on. Each triangle represents one phase in the production process. Although this appears on the map as a linear path of transformation, a different visual metaphor better represents the complexity of current extractivism: the fractal structure known as the Sierpinski triangle. A linear display does not enable us to show that each next step of production and exploitation contains previous phases.

If we look at the production and exploitation system through a fractal visual structure, the smallest triangle would represent natural resources and means of labor, i. The next larger triangle encompasses the processing of metals, and the next would represent the process of manufacturing components and so on. The ultimate triangle in our map, the production of the Amazon Echo unit itself, includes all of these levels of exploitation — from the bottom to the very top of Amazon Inc, a role inhabited by Jeff Bezos as CEO of Amazon.

Like a pharaoh of ancient Egypt, he stands at the top of the largest pyramid of AI value extraction. Sierpinski triangle or Sierpinski fractal. If we look at the scale of average income for each activity in the production process of one device, which is shown on the left side of our map, we see the dramatic difference in income earned. 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.

For an anthropological description of these mining processes, see: Jeffrey W. Many of the triangles shown on this map hide different stories of labor exploitation and inhumane working conditions. The ecological price of transformation of elements and income disparities is just one of the possible ways of representing a deep systemic inequality. Consumers are usually only able to see commodities in the here and now of time and space, and rarely have any opportunities to gaze backwards through the chains of production in order to gain knowledge about the sites of production, transformation, and distribution. One illustration of the difficulty of investigating and tracking the contemporary production chain process is that it took Intel more than four years to understand its supply line well enough to ensure that no tantalum from the Congo was in its microprocessor products.

As a semiconductor chip manufacturer, Intel supplies Apple with processors. In order to do so, Intel has its own multi-tiered supply chain of more than 19, suppliers in over countries providing direct materials for their production processes, tools and machines for their factories, and logistics and packaging services. Dutch-based technology company Philips has also claimed that it was working to make its supply chain 'conflict-free'. Philips, for example, has tens of thousands of different suppliers, each of which provides different components for their manufacturing processes.

Traders are the middlemen who do more than buy and sell rare metals: they help to regulate information and are the hidden link that helps in navigating the network between metals plants and the components in our laptops. In addition, many of the minerals are smelted together with recycled metals, by which point it becomes all but impossible to trace the minerals to their source. So we see that the attempt to capture the full supply chain is a truly gargantuan task: revealing all the complexity of the 21st century global production of technology products. Supply chains are often layered on top of one another, in a sprawling network.

In order for each of those components to arrive on the final assembly line where it will be assembled by workers in Foxconn facilities, different components need to be physically transferred from more than supplier sites across 30 different countries. Visualizing this process as one global, pancontinental network through which materials, components and products flow, we see an analogy to the global information network. Where there is a single internet packet travelling to an Amazon Echo, here we can imagine a single cargo container. Standardized cargo containers allowed the explosion of modern shipping industry, which made it possible to model the planet as a massive, single factory. In recent years, shipping boats produce 3.

It has been estimated that one container ship can emit as much pollution as 50 million cars, and 60, deaths worldwide are attributed indirectly to cargo ship industry pollution related issues annually. Typically, workers spend 9 to 10 months in the sea, often with long working shifts and without access to external communications. Workers from the Philippines represent more than a third of the global shipping workforce.

Similar to our habit to neglect materiality of internet infrastructure and information technology, shipping industry is rarely represented in popular culture. The increasing complexity and miniaturization of our technology depends on the process that strangely echoes the hopes of early medieval alchemy. There are 17 rare earth elements, which are embedded in laptops and smartphones, making them smaller and lighter. They play a role in color displays, loudspeakers, camera lenses, GPS systems, rechargeable batteries, hard drives and many other components. They are key elements in communication systems from fiber optic cables, signal amplification in mobile communication towers to satellites and GPS technology.

But the precise configuration and use of these minerals is hard to ascertain. 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. The unique electronic, optical and magnetic characteristics of rare earth elements cannot be matched by any other metals or synthetic substitutes discovered to date. David Abraham describes the mining of dysprosium and Terbium used in a variety of high-tech devices in Jianxi, China.

This means that A satellite picture of the tiny Indonesian island of Bangka tells a story about human and environmental toll of the semiconductor production. The damage is best seen from the air, as pockets of lush forest huddle amid huge swaths of barren orange earth. Where not dominated by mines, this is pockmarked with graves, many holding the bodies of miners who have died over the centuries digging for tin. At Amazon distribution centers, vast collections of products are arrayed in a computational order across millions of shelves.

The position of every item in this space is precisely determined by complex mathematical functions that process information about orders and create relationships between products. The aim is to optimize the movements of the robots and humans that collaborate in these warehouses. With the help from an electronic bracelet, the human worker is directed though warehouses the size of airplane hangars, filled with objects arranged in an opaque algorithmic order. Hidden among the thousands of other publicly available patents owned by Amazon, U. Wurman, Peter R. The researchers also found a statistically uncertain but still positive effect on health, safety, and environmental compliance.

What about lean makes for better working conditions? One explanation, Hainmueller says, could be that going lean kicks off a virtuous cycle where workers are expected to be more than just cogs in a machine. That means managers invest more in worker training, which makes retention and motivation more important, which leads to more equitable terms of employment. Looking across the spectrum of countries supplying Nike apparel, the researchers discovered a notable limitation to their finding. While lean adoption had a large effect on labor compliance scores in India and Southeast Asia, some countries, such as China and Sri Lanka, saw no such benefit. In Sri Lanka, the broad majority of non-lean factories already scored well on labor compliance ratings, leaving little room for improvement.

Why not go for it, even if all you want to do is maximize your profits? Enter the terms you wish to search for. August 10, Factories that employed lean manufacturing saw improved work conditions. Text Equivalent View Larger. Infographic by Tricia Seibold. Why not go for it? Share this. For media inquiries, visit the Newsroom. Explore More. October 05, Social Impact. August 03, January 16, Innovations developed at big tech firms could transform the nonprofit world, with a little help from academia. Got a Problem?

Most poor countries provide very japanese samurai warrior effective social protection to help people who Sweatshops Case Study lost their jobs and Sweatshops Case Study yet found new ones. Bauer Cole Haan Hurley Umbro. Share this. Sweatshops Case Study : Nike, Inc. The flow of international investment consists both of long-term capital such as Sweatshops Case Study and of speculative short-term capital such as Sweatshops Case Study, bonds and currency. Main Sweatshops Case Study Anti-globalization movement.

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