<p>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 responsible AI must account for the emotional conditions that shape human interaction with technology. In doing so, BEETS moves beyond fragmented and principle-based approaches by offering a relational, multidimensional, and human-centered model for understanding, evaluating, and governing AI systems. Unlike categorical frameworks that organize ethical principles under a common genus, BEETS treats its five dimensions as functionally distinct kinds of things, each performing a different role in the AI lifecycle, bound together by the dynamic system they collectively constitute. The framework contributes to current discussions of responsible AI by clarifying conceptual distinctions, addressing categorical ambiguity in AI ethics, and advancing a coherent structure for ethical analysis and governance.</p>