Vitology and Information Theory: Quantity, Meaning, Value, and the Viability Effect of Information

This article compares Vitology with information theory and adjacent scientific traditions in order to distinguish established scientific knowledge from a possible residual contribution of the Vitological approach. It is shown that quantitative information measurement, entropy, mutual information, coding, noise, channel capacity, and message transmission belong to classical information theory and cannot constitute independent Vitological novelty. Semantic information has a separate scientific tradition. The value of information relative to decision-making has been formalized within decision theory. Data quality is studied as a multidimensional construct. Functional information also has established formal representations. The strongest limitation on broad Vitological novelty claims comes from the work of Artemy Kolchinsky and David Wolpert, in which semantic information is defined in terms of the portion of statistical information between a system and its environment that is causally necessary for maintaining the system’s own existence. Their framework uses counterfactual interventions, a viability function, informational value, and semantic content. Consequently, the general proposition that the significance of information may be evaluated through its contribution to the continued existence of a system already has a direct formal scientific predecessor. After removing this established content, H4 formulates a narrower research problem: whether standardized Vitological metrology can characterize a context-dependent and temporally resolved viability effect of informational intervention, connect it with a multidimensional viability trajectory, and provide predictive information beyond strong existing models. A candidate causal-metrological construct of the viability effect of information is proposed. It explicitly includes the investigated system, initial state, informational condition, system level, temporal horizon, uncertainty, and subsequent trajectory. Particular emphasis is placed on the proposition that information has no universal positive or negative viability value outside context. The same information may have different consequences for different systems, different states of the same system, different system levels, and different temporal horizons. Eight testable hypotheses H4-1–H4-8 are formulated. The strongest requires prospectively operationalized viability variables to increase predictive performance relative to an adequate baseline model on independent data. Keywords Vitology; viability; information theory; information; entropy; mutual information; semantic information; functional information; value of information; information quality; viability effect of information; temporal architecture of viability; causal intervention; prediction; cross-domain metrology.