Towards Friendly AI: A Comprehensive Review and New Perspectives on Human-AI Alignment

TL;DR

This paper provides a comprehensive review of Friendly AI, emphasizing ethical considerations, applications like XAI and fairness, and future research directions to promote ethical AI development.

Contribution

It offers a formal definition of FAI, discusses its applications, and explores ethical perspectives and future challenges in AI alignment.

Findings

Highlights the importance of FAI for ethical AI development

Identifies key challenges in current AI technologies

Suggests future research directions for FAI advancement

Abstract

As Artificial Intelligence (AI) continues to advance rapidly, Friendly AI (FAI) has been proposed to advocate for more equitable and fair development of AI. Despite its importance, there is a lack of comprehensive reviews examining FAI from an ethical perspective, as well as limited discussion on its potential applications and future directions. This paper addresses these gaps by providing a thorough review of FAI, focusing on theoretical perspectives both for and against its development, and presenting a formal definition in a clear and accessible format. Key applications are discussed from the perspectives of eXplainable AI (XAI), privacy, fairness and affective computing (AC). Additionally, the paper identifies challenges in current technological advancements and explores future research avenues. The findings emphasise the significance of developing FAI and advocate for its continued advancement to ensure ethical and beneficial AI development.