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Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Deliberation Everywhere: Simple Examples, published by Oliver Sourbut on June 27, 2022 on The AI Alignment Forum. The analysis and definitions used here are tentative. My familiarity with the concrete systems discussed ranges from rough understanding (markets and parliaments), through abiding amateur interest (biology), to meaningful professional expertise (AI/ML things). The abstractions and terminology have been refined in conversation and private reflection, and the following examples are both generators and products of this conceptual framework. We previously discussed a conceptual algorithmic breakdown of some aspects of goal-directed behaviour with the intention of inspiring insights and clarifying thought and discussion around these topics. The examples presented here include some original motivating examples, some used to refine the concepts, and others drawn from the menagerie after the concepts were mostly refined[1]. Each example is subjected to the analysis, in several cases drawing out novel insights as a consequence. Most of these examples, for all their intricacy in some cases, are relatively 'simple' as deliberators, and I am quite confident in the applicability of the framing. Analysis of more derived and sophisticated deliberative systems is reserved for upcoming posts. Brief framework summary We decompose 'deliberation' into 'proposal', 'promotion', and 'action'. Propose:S→Δ{X}nonempty (generate candidate proposals) Promote:S→{X}→{V} (promote and demote proposals according to some criterion) Act:{X×V}→A (take outcome of promotion and demotion to activity in the environment) We also identify as important whether a deliberator's actions are final, or give rise to relevantly-algorithmically-similar subsequent deliberators (iteration and replication), or create or otherwise condition heterogeneous deliberators (recursive deliberation). Reaction examples Chemical systems Innumerable basic chemical reactions, like oxidation of iron, involve actions which change the composition or configuration of some material(s). For the purposes of this analysis these are, alone, mostly uninteresting, but serve to illustrate natural systems which do not preserve their essential algorithmic form and thus do not constitute iterated systems. Some reactions, on the other hand, involve catalysis, wherein some reagents are essentially preserved or reconstituted in the action, producing the seeds of iterated algorithmic reaction, thus basic 'control'. Despite pushing in a particular 'goal' direction, these systems are reactions rather than proper deliberations, because they occur without computing alternative pathways[2]. Biological systems Even very simple organisms can react (that is, act or perform some function in response) to stimuli. No proper deliberation need be involved, no computation instantiated to consider alternatives. A reaction can take place with or without a brain, or even a nervous system: consider many motions of single-celled organisms[3] or the snapping of a Venus flytrap. The cringe of many animals from intense heat goes via nervous circuitry but takes no deliberation. Indeed, temperature changes are pervasive in nature, so it is no surprise that we find automatic heat-responsive behaviour at the protein-machinery level in every lineage of cellular life. These latter, along with other protein machinery and the organ-functions of multicellular organisms, demonstrate that, in nature, a single organism will be found to consist of many reactive and deliberative systems. The class of 'systems undergoing a transformation' in chemical or physical interactions often does not preserve the essential algorithmic characteristics of the system, but most salient biological examples are iterated (the act essentially preserves the capacity to further act in an algorith...