565 citations · 1.3k across the 5 of their papers we have counts for
4 papers · 1 filter
SafeLife 1.0: Exploring Side Effects in Complex Environments
Carroll L. Wainwright, Peter Eckersley
We present SafeLife, a publicly available reinforcement learning environment that tests the safety of reinforcement learning agents. It contains complex, dynamic, tunable, procedur…
Explainable Machine Learning in Deployment
Umang Bhatt, Alice Xiang, Shubham Sharma +7
Explainable machine learning offers the potential to provide stakeholders with insights into model behavior by using various methods such as feature importance scores, counterfactu…
Theories of Parenting and their Application to Artificial Intelligence
Sky Croeser, Peter Eckersley
As machine learning (ML) systems have advanced, they have acquired more power over humans' lives, and questions about what values are embedded in them have become more complex and…
Impossibility and Uncertainty Theorems in AI Value Alignment (or why your AGI should not have a utility function)
Peter Eckersley
Utility functions or their equivalents (value functions, objective functions, loss functions, reward functions, preference orderings) are a central tool in most current machine lea…