“AI systems put power in the hands of the already powerful. What we see time and again, from facial recognition to tracking and surveillance in workplaces, is these systems are empowering already powerful institutions – dictatorships, corporations, militaries and police.
The problem is that clearly AI is going to win. How people are going to adjust is a fascinating problem!
Kate Crawford studies the social and political implications of artificial intelligence.
She is a research professor of communication and science and technology studies at the University of Southern California and a senior principal researcher at Microsoft Research.
Her new book, “Atlas of AI”, looks at what it takes to make AI and what’s at stake as it reshapes our world.
A valuable corrective to much of the hype surrounding AI and a useful instruction manual for the future
The hidden costs of artificial intelligence—from natural resources and labor to privacy, equality, and freedom
AI IS NEITHER ARTIFICIAL NOR INTELLIGENT. IT IS MADE FROM NATURAL RESOURCES AND IT IS PEOPLE WHO ARE PERFORMING THE TASKS TO MAKE THE SYSTEMS APPEAR AUTONOMOUS.
What happens when artificial intelligence saturates political life and depletes the planet?
How is AI shaping our understanding of ourselves and our societies?
Drawing on more than a decade of research, award‑winning scholar Kate Crawford reveals how AI is a technology of extraction: from the minerals drawn from the earth, to the labor pulled from low-wage information workers, to the data taken from every action and expression.
This book reveals how this planetary network is fueling a shift toward undemocratic governance and increased inequity.
Rather than taking a narrow focus on code and algorithms, Crawford offers us a material and political perspective on what it takes to make AI and how it centralizes power.
This is an urgent account of what is at stake as technology companies use artificial intelligence to reshape the world.
We are commonly presented with this vision of AI that is abstract and immaterial.
Kate Crawford wanted to show how AI is made in a wider sense – its natural resource costs, its labour processes, and its classificatory logics.
Tests of natural language AIs processing models show that the bigger they are, the bigger liars they are. Should we be worried?”
