Ground Truths

Kate Crawford: A Leading Scholar and Conscience for A.I.

17 snips
May 12, 2024
Kate Crawford, a leading scholar in AI, discusses the environmental impacts of large AI systems, biases in AI data sets, exploitation of human labor in AI development, interdisciplinary collaboration in AI research, and concerns surrounding AI applications in medicine. She sheds light on the energy consumption and resource extraction involved in AI, societal biases embedded in AI, labor conditions in the industry, and ethical considerations in healthcare applications.
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INSIGHT

AI Has A Hidden Material Footprint

  • AI is deeply material, relying on extraction, energy, water, and hidden labor rather than being purely immaterial code.
  • Building giant models at planetary scale creates large environmental and social externalities that we must account for.
ANECDOTE

Field Trips That Changed Her View

  • Crawford conducted five years of field research for Atlas of AI, visiting mines, warehouses, and labeling labs.
  • Those field trips changed her view from abstract algorithms to the full extractive infrastructure of AI.
INSIGHT

Rapid Adoption Outpaced Reflection

  • The recent surge in large language models has led to exponential growth in deployment and resource use.
  • The speed of adoption risks applying models in inappropriate contexts without reflecting on societal costs.
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