Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence
ARTICLE SUMMARY
Artificial intelligence (AI) relies on natural resources, low-cost labor, and data. The production of AI technology harms the environment. AI systems rely on low-wage workers.
POLICY RELEVANCE
Assessment of the costs of AI should include costs to the environment and to workers.
KEY TAKEAWAYS
- Nonhuman systems such as computers are not analogous to human minds; AI is not really intelligent, and “machine learning” would be a better term.
- AI depends on extracting energy and mineral resources from the planet, cheap labor, and data.
- Seventeen rare elements are needed to make AI, such as lanthanum, europium, and yttrium
- Mining is associated with local and geopolitical violence, bringing war, famine, and death.
- Seventeen rare elements are needed to make AI, such as lanthanum, europium, and yttrium
- Clean technology is a myth, and portrayals of cloud-based computation should factor in costs to the environment.
- Data centers are among the largest consumers of electricity.
- China's data center industry draws 73 percent of its power from coal.
- Shipping emissions significantly affect the Earth's atmosphere.
- Data centers are among the largest consumers of electricity.
- AI systems rely on cheap crowd-sourced labor to do tasks that cannot be done by machines, such as assessing violent videos or hate speech.
- Algorithms that monitor worker productivity may assign workers very short or very long shifts, whichever is profitable; workers are unable to predict their schedules, and the algorithm does not factor in this human cost.
- As data extraction becomes more invasive and researchers access data without interacting with their subjects, the risk that research using human data will inculcate bias or do harm rises.
- The processes for classifying people by race and gender used in training AI are beset with stereotypes and error.
- People assume that race and gender can be detected by machines, but this presents political and social problems.
- Some AI systems try to detect sexuality or criminality based on headshots from drivers' licenses.
- Companies that set up classification systems operate with little oversight or public input.
- People assume that race and gender can be detected by machines, but this presents political and social problems.
- Large-scale AI surveillance originated with national security services, but now extend to classrooms, police stations, workplaces, and other everyday locales.
- Surveillance supports central control at the cost of other types of social organization.
- Surveillance systems blur the lines between law enforcement and tech firms.
- Surveillance will radically reshape civic life.
- Surveillance supports central control at the cost of other types of social organization.
- AI ethics should include consideration of the labor conditions of miners, contractors, and crowdworkers; we should consider the experiences of those harmed by AI, and the systems' carbon footprint.
QUOTE
TAGS
About Kate Crawford
Kate Crawford is a Research Professor of Communication and Science and Technology Studies at USC’s Annenberg School for Communication and Journalism and a Senior Principal Researcher at Microsoft Research in New York. Professor Crawford is a leading scholar of the social and political implications of artificial intelligence. Over her 20-year career, her work has focused on understanding large-scale data systems, machine learning and AI in the wider contexts of history, politics, labor, and the environment.
