Jiang claims that edge cases expose a core AI failure mode: systems can miss obvious real-world entities despite high aggregate performance.
Topic brief
A Jiang Lens evidence brief for this topic, built from source tags, transcript matches, and linked source refs.
ML Risks
Jiang claims that edge cases expose a core AI failure mode: systems can miss obvious real-world entities despite high aggregate performance.
Showing 3 evidence items
No matching evidence on this topic page.
Key Notes
Timestamped Evidence
"And that led to dangerous outcomes. In March 2018, a self -driving Uber killed 49 years old Aline Hasburg in Turnpike, Arizona, in the..."
Relevant Lectures And Readings
The lecture starts by warning against overconfident certainty, then rewires from literary method to a hard model of AI: today’s systems are pattern-fitters optimized for compliance, so power becomes control over what counts as...
Related Topics
How To Use And Cite This Page
This topic page is a discovery surface. For generated synthesis, cite the human-readable source reading or lens page. For Jiang-spoken claims, cite the transcript segment, source ref, and YouTube timestamp. Raw text and Markdown mirrors are fallback surfaces for tools that cannot read this HTML page.