Autonomous Alignment with Human Value on Altruism through Considerate Self-imagination and Theory of Mind

TL;DR

This paper proposes a novel AI framework that incorporates Theory of Mind and self-imagination to enable autonomous, altruistic, and ethically aligned decision-making, inspired by human moral behavior and tested in complex rescue scenarios.

Contribution

It introduces a new approach for AI to autonomously align with human altruistic values using considerate self-imagination and Theory of Mind capabilities.

Findings

Agents can proactively anticipate risks and make altruistic decisions.

The framework effectively balances self-goals, altruism, and environmental safety.

Experimental scenarios demonstrate improved moral decision-making in AI.

Abstract

With the widespread application of Artificial Intelligence (AI) in human society, enabling AI to autonomously align with human values has become a pressing issue to ensure its sustainable development and benefit to humanity. One of the most important aspects of aligning with human values is the necessity for agents to autonomously make altruistic, safe, and ethical decisions, considering and caring for human well-being. Current AI extremely pursues absolute superiority in certain tasks, remaining indifferent to the surrounding environment and other agents, which has led to numerous safety risks. Altruistic behavior in human society originates from humans' capacity for empathizing others, known as Theory of Mind (ToM), combined with predictive imaginative interactions before taking action to produce thoughtful and altruistic behaviors. Inspired by this, we are committed to endow agents with considerate self-imagination and ToM capabilities, driving them through implicit intrinsic motivations to autonomously align with human altruistic values. By integrating ToM within the imaginative space, agents keep an eye on the well-being of other agents in real time, proactively anticipate potential risks to themselves and others, and make thoughtful altruistic decisions that balance negative effects on the environment. The ancient Chinese story of Sima Guang Smashes the Vat illustrates the moral behavior of the young Sima Guang smashed a vat to save a child who had accidentally fallen into it, which is an excellent reference scenario for this paper. We design an experimental scenario similar to Sima Guang Smashes the Vat and its variants with different complexities, which reflects the trade-offs and comprehensive considerations between self-goals, altruistic rescue, and avoiding negative side effects.