Learning Machine Morality through Experience and Interaction

arXiv:2312.01818v2 Announce Type: replace-cross
Abstract: Increasing interest in ensuring safety of next-generation Artificial Intelligence (AI) systems calls for novel approaches to embedding morality into autonomous agents. Traditionally, this has been done by imposing explicit top-down rules or hard constraints on systems, for example by filtering system outputs through pre-defined ethical rules. Recently, instead, entirely bottom-up methods for learning implicit preferences from human behavior have become increasingly popular, such as those for training and fine-tuning Large Language Models. In this paper, …

abstract agents artificial artificial intelligence arxiv autonomous autonomous agents constraints cs.ai cs.cy cs.lg cs.ma embedding ethical example experience filtering intelligence machine next novel rules safety systems through type