Towards friendly AI: a comprehensive review and new perspectives on human-AI alignment

Read full text
Authors: Qiyang Sun, Yupei Li, Emran Alturki, Sunil Munthumoduku Krishna Murthy, Bjoern W. Schuller
Cited by: 3
References: 102

Abstract

Abstract As Artificial Intelligence (AI) continues to advance rapidly, Friendly Artificial Intelligence (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 technical subfields 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.

Fields of Study & Subjects

Explainable Artificial Intelligence (XAI) Ethics and Social Impacts of AI Digital Mental Health Interventions

Publication details

Journal / source
AI and Ethics
Publisher
Springer Science and Business Media LLC
Volume
6
Issue
2
Publication date
8 March 2026
Language
EN