Strengthening Ethical Artificial Intelligence Based on Behavioral Economics through the Principles of Trust, 'Adl, and Ihsan in Decision Making: A Literature Review

Abstract

This research aims to strengthen the framework of Ethical Artificial Intelligence based on behavioral economics through the integration of the principles of Amanah, 'Adl, and Ihsan in decision-making. The research background is grounded in the increasing use of artificial intelligence in decision-making, which is vulnerable to cognitive bias, while the existing literature remains dominated by technical and procedural approaches to addressing ethical issues. The research employed a conceptual literature review of 17 journal articles on behavioral economics, artificial intelligence, cognitive bias, nudging, and moral decision-making. Analysis is conducted through data extraction, thematic coding, and conceptual synthesis to map the state of the art in research, identify normative gaps, and develop an alternative, value-based framework. The results show that the integration of behavioral economics and artificial intelligence has evolved to explain and manage cognitive biases, but has not yet been systematically integrated into a substantive normative value framework. Ethics in AI systems is still understood procedurally and is not yet oriented toward substantive justice, trust, and social usefulness. This study concludes that the principles of Amanah, 'Adl, and Ihsan can be positioned as alternative conceptual frameworks to strengthen ethical artificial intelligence approaches that are more just, responsible, and socially beneficial.