Abstract This paper presents a conceptual framework that addresses a persistent problem in AI ethics scholarship: the fragmentation of bias, equity, ethics, trust, and security into separate domains that are rarely examined as a unified, interdependent system. Following Jaakkola's [25] approach to conceptual research, the contribution is theoretical rather than empirical, offering an integrative model that reorganizes these concepts within a relational architecture. The B.E.E.T.S. (BEETS) framework conceptualizes Bias, Equity, Ethics, Trust, and Security as functionally distinct yet interconnected dimensions of responsible AI. Bias identifies structural risk, Equity defines the normative goal, Ethics provides the governance layer through which accountability is operationalized, Trust emerges as a relational outcome, and Security serves as the protective infrastructure that sustains system integrity. A central contribution of the framework is its treatment of emotion as the affective substrate through which these dimensions are experienced and interpreted. Drawing on affective computing, psychology, and sociotechnical systems thinking, the paper argues that respons
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