joshuawe/mlsafetycourse

ML Safety Course 2023

ML Safety Course 2023

Description:

ML systems are rapidly increasing in size, are acquiring new capabilities, and are increasingly deployed in high-stakes settings. As with other powerful technologies, safety for ML should be a leading research priority. In this course we’ll discuss how researchers can shape the process that will lead to strong AI systems and steer that process in a safer direction. We’ll cover various technical topics to reduce existential risks (X-Risks) from strong AI, namely withstanding hazards (“Robustness”), identifying hazards (“Monitoring”), reducing inherent ML system hazards (“Control”), and reducing systemic hazards (“Systemic Safety”). At the end, we will zoom out and discuss additional abstract existential hazards and discuss how to increase safety without unintended side effects.

Link:
https://course.mlsafety.org/about

Course duration:
8 weeks, beginning in June

Info: The course contains lecture videos, reading assignments, written assignments and coding assignments.
This repository will only contain the course's coding assignments.