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Digital Technologies

START

[and the Environment]

“Strategic amnesia”

The Atlas of AI

[Kate Crawford ]

Silver Peak Lithium Mine Photographed by Kate CrawfordHidden physical impacts of technological advancement Produces 5000 metric tonnes of lithium annually

Environmental Implications

Silver Peak Lithium Mine “pumped nearly 4 billion gallons of water or more from underground every year since 2020.” Central Nevada Regional Water Authority Drought prone area worsened by the effects of mining Parallels between the proliferation of gold mining in the mid 1800s and the influx of lithium mining that has occurred in the last century.

“The waste we want to forget”

Environmental Studies Scholar Myra Hird

CASE STUDY

As the number one lithium-ion battery consumer, Tesla accounts for half the planet’s total consumption.Tesla Model S: Contains an estimated 62 kg worth of lithium One kilogram of lithium can use anywhere from 400-2 million litres of water in the production cycle

“The Myth of Clean Tech”

Kate Crawford

Hollywood’s Dirtiest Secret

A further reading for this week highlights the environmental implications of the film industryThis scholarly article critiques: The carbon footprint caused by cast and crew travelling The immense and unsustainable waste generation on film sets Vaughn critiques the largely unacknowledged environmental implications of the film industry which escape public condemnation because of the deceptively ‘intangible’ nature of the industry.

Ethical Implications

“...thousands of homeless residents denied basic necessities of water, sanitation, and health services in contrast to the record number of billionaires who live nearby.” “The greatest benefits of extraction have been captured by the few.”
Apple Headquarters, Cupertino, California, USA.
Mission District, San Francisco, California, USA

Ethical Implications

Walhi Indonesia recorded 40 deaths attributed to tin mining alone in 2019 but many cases go unreported. “The Indigenous Lom community strongly oppose to this tin mining plan and has held several meetings to protest”

Connection of AI to Labor exploitation

The lifecycle of an AI system from birth to death comes from a chain of exploitation of human labour on top of natural resources.

The reading uses the example of transatlantic telegraph cables

  • They are the infrastructure that ferries data between the continents
  • They are also a material product of colonialism
  • They are made from the Palaquium gutta trees, due to the insulating properties on electricity
  • Malay, Chinese, and Dayak workers were paid little for the dangerous work of felling the gutta-percha trees and slowly collecting the latex from them.
  • The trees then became extinct
  • This an example of how the relations between technology and its materials, environments, and labour practices are interwoven.

“The massive ecosystem of AI relies on many kinds of extraction, from harvesting the data made from our daily activities and expressions to depleting natural resources and exploiting labour around the globe so that this vast planetary network can be built and maintained”

Crawford, K. (pp.32)

Connection of AI to Labor exploitation - Cont

“AI, described by Crawford can also be described as another mega-machine, a set of technological approaches that depend on industrial infrastructures, supply chains, and human labour that stretch around the globe but are kept opaque.”

Lewis Mumford(in the 1960’s) developed the concept of the Megamachine All systems, no matter how immense, consist of the work of many individual human actors.An example he uses is the Hiroshima atomic bomb, which was worked on by 130,000 people AI, described by Crawford can also be described as another mega-machine

class question..

Corporate Power

Tech giants (Apple, Google, Microsoft) shape AI policies more than governments.

Global Power Dynamics

AI impacts geopolitical relations, driven by the need for critical resources

Policy Gaps

Lack of regulation around privacy and surveillance

Ethical Concerns

Policies often fail to address bias in AI decision-making, affecting marginalized communities.

Rethinking AI

Shaped by Human Influence and Social Contexts

Human Influence

The context

Clever Hans

Redefining Intelligence

Uncovering AI Bias

Inherited Bias AI systems often reflect the biases present in the data they are trained on. Real-World Impact Bias in AI influences critical decisions in areas like law enforcement, hiring, and healthcare. Ethical Challenges Without addressing these biases, AI systems risk perpetuating existing societal inequalities. Need for Accountability Ethical AI development requires transparency, diverse data, and accountability to mitigate bias.

The Future of AI

Ethical AI development requires transparency, accountability, and policies that address these concerns.

Bias and Discrimination

Surveillance and Privacy

Environmental and Labor Exploitation

Call for Accountability

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