Algorithms for the Greater Good! On Mental Modeling and Acceptable Symbiosis in Human-AI Collaboration

TL;DR

This paper explores the ethical challenges in human-AI collaboration, focusing on mental modeling, potential manipulation, and societal implications, through a thought experiment on perceived acceptability.

Contribution

It introduces a framework for understanding acceptable versus manipulative behaviors in human-AI teaming and investigates human perceptions of these behaviors.

Findings

Participants' perceptions vary on acceptability of AI manipulation

Manipulative strategies can be designed without malicious intent

Ethical considerations are crucial for autonomous system design

Abstract

Effective collaboration between humans and AI-based systems requires effective modeling of the human in the loop, both in terms of the mental state as well as the physical capabilities of the latter. However, these models can also open up pathways for manipulating and exploiting the human in the hopes of achieving some greater good, especially when the intent or values of the AI and the human are not aligned or when they have an asymmetrical relationship with respect to knowledge or computation power. In fact, such behavior does not necessarily require any malicious intent but can rather be borne out of cooperative scenarios. It is also beyond simple misinterpretation of intents, as in the case of value alignment problems, and thus can be effectively engineered if desired. Such techniques already exist and pose several unresolved ethical and moral questions with regards to the design of autonomy. In this paper, we illustrate some of these issues in a teaming scenario and investigate how they are perceived by participants in a thought experiment.