<![CDATA[The rapid integration of Artificial Intelligence (AI) and Robo-advisors in Islamic wealth management has streamlined the sharia stock screening process. However, this technological advancement poses a critical ethical dilemma. This qualitative study utilizes a library research approach to philosophically and technically critique the algorithmic bias inherent in current Robo-advisors. It argues that contemporary AI systems perform sharia screening purely mechanically focusing exclusively on quantitative thresholds (e.g., debt-to asset ratios and non-halal income limits) while entirely failing to comprehend the substantive essence of Maqashid Sharia (the higher objectives of Islamic law). Consequently, a company causing severe environmental degradation or social injustice may still pass the algorithmic screening simply by meeting the numerical criteria. By synthesizing Islamic Behavioral Finance and AI Ethics, this research introduces the concept of Algorithmic Maqashid, proposing a shift from negative mechanical screening to positive substantive screening using Natural Language Processing (NLP) to evaluate ESG (Environmental, Social, and Governance) variables. The findings provide a foundational blueprint for regulatory bodies, specifically OJK and DSN-MUI, to establish new regulatory frameworks and sharia compliance audit standards tailored for Algorithmic Trading and AI technology in the Indonesian Islamic capital market.]]>
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