Leveraging Multi-User Dungeons for Ethical AI Decision Support Systems: A Novel Approach

Open Access
Article
Conference Proceedings
Authors: Daniel PittmanKerstin HaringChris Gauthierdickey

Abstract: This paper proposes the innovative use of Multi-User Dungeons (MUDs) as a testbed for exploring and refining Artificial Intelligence (AI) ethics in decision support systems. MUDs are interactive, text-based virtual environments and offer a unique platform for studying AI behavior in a controlled yet complex environment. Our approach involves a combination of machine learning and natural language processing techniques to implement AI as a decision support system, and designs scenarios that challenge players with ethical quandaries and dilemmas. The effectiveness and ethical decision-making of players, the AI, and both together as a team are evaluated through a mix of quantitative and qualitative methods. The approaches detailed in this research aim to contribute to the broader discourse on AI ethics, stimulate a discussion on how to provide empirical evidence of AI decision-making's impact on human behavior in MUDs, and informing the design of ethically responsible AI systems in other domains.

Keywords: Artificial Intelligence Ethics, Multi-User Dungeons (MUDs), Human-AI Interaction

DOI: 10.54941/ahfe1004180

Cite this paper:

Downloads
232
Visits
281
Download