Future[tectonics]: Exploring the intersection between technology, architecture and urbanism

In his chapter, "Garbage In, Garbage Out: How Language Models Can Reinforce Biases," Lehrer discusses how inherent bias is baked into large data sets, like those used to train massive AI algorithms, and how society will need to reconcile with the inherent biases built into systems of power. He also attempts to reconcile with it himself, delving into the mathematics behind these systems.

From Summer 2024 recommended reading from MIT (MIT News).