Introduction to Model Dependent Ontology

Model Dependent Ontology (MDO) its an epistemic stance that introduces a pragmatic perspective concerning the nature of human beliefs. Rather than grounding them in metaphysical “truth”or “objectivity”, MDO evaluates them based on their predictive and control capacities within their respective domains. It postulates that our beliefs, even those taken as knowledge, are mere simplified representations restricted to certain domains. A model gains societal acceptance, and it is taken as “true” if it accurately describes and predicts observations within its intended domain. By emphasizing context-dependent utility, MDO distinguishes itself from other stances, like realism and relativism.

Introduction

Model Dependent Ontology delves into various ontological models formulated across human history. Scrutinizing past and present philosophical paradigms, MDO identifies contradictions between these models and the implications of such differences. The core proposition of MDO is a shift from verificationalist approaches to an emphasis on models’ pragmatic utility, sidestepping traditional debates on truth and knowledge. There is more to this, but I will not talk about it on this brief introduction.

Moving Beyond Realism and Relativism

MDO’s shift to pragmatic utility is partly due to the challenges inherent to realism (the favoured paradigm by current standards), exemplified by the Munchhausen Trilemma. This trilemma underscores the inherent challenges in grounding any truth claim: every argument eventually rests on either circular reasoning, unproven premises, or an infinite regress.

While relativism offers an alternative, it lacks a basis for a way of choosing between conflicting beliefs as it needs to consider them as equivalent at an epistemic level. Stances like Postmodernism are widely criticised because of this and for good reasons. Not all beliefs are equally valid or equally wrong.

The aforementioned problems are oversimplifications of course, I just use them to make emphasis in that MDO sidesteps these issues by focusing on value of using a pragmatic utility way to differentiate among competing models, instead of relying on any extrinsic grounding.

The Pragmatic Nature of Human Beliefs

For MDO, our beliefs can be seen as simplified models, each tailored to specific domains of our experience. Historically, a belief deemed “true”, and thus is labelled as “knowledge” if it offers consistent and accurate predictions and gives us the ability to control certain things. MDO challenges this notion, suggesting that our beliefs have value due to their utility, not their assumed “proximity” to some objective truth.

Beliefs as Simplified Guides for Action

Beliefs, by design, abstract certain aspects of phenomena. A map highlights selected features of a set of possibilities (not territories), a computer model draws an abstraction of weather patterns. Even expansive cosmological models, which tackle the universe’s vastness, operate by distilling phenomena into elemental concepts. The utility of a belief, thus, lies in its capacity for understanding, prediction, and control concerning its specific domain questions.

Context Dependent Utility

MDO advances the idea that models are assessed against observations, or even other models, not against an elusive “reality.” The historic shift from the Ptolemaic to the Copernican model illuminates this. While the geocentric model suffices for everyday observations like sunrises, the heliocentric one offers more comprehensive insights, such as explaining the retrograde motion of planets.

Examples of Context-Dependent Utility

• Geocentric vs. heliocentric models — For predicting eclipses and planetary motions, the heliocentric model proved superior. But for everyday language about sunrise and sunset, the geocentric model remains adequate.
• Newtonian vs. relativistic physics — Newtonian mechanics makes excellent predictions at ordinary velocities and sizes. But Relativity provides us with more accurate models for observations at cosmic scales or near light-speed.
• Natural selection — While useful for explaining adaptation and speciation, natural selection does not fully represent other evolutionary phenomena like genetic drift. Different models have different utilities.
• Atomic theory — Bohr’s solar system model of the atom gave way to the more accurate quantum model. But for visualizing electrons occupying shells, Bohr’s model retains pedagogical value.
• Wave vs. particle models of light — Light exhibits both wave and particle properties. These incompatible models each accurately predict different phenomena.
• Lamarckian vs. Darwinian evolution — The discredited model of inheritance of acquired traits remains useful as a metaphor for cultural evolution.
• Ego psychology vs. social psychology — The distinct models of these subfields represent incompatible assumptions about the roles of instinct and environment in human behaviour.
• Nature vs. nurture — These adversarial models simplify complex developmental interactions between genetics and environment. Integrative models aim to transcend this divide.
• The Mind-Body problem — The nature of consciousness highlights similar issues. Intuitively, we have a sense of subjective experience as real. But some ontologies reduce consciousness to physical processes in the brain, while others posit fundamental mental substances. Attempts to integrate these perspectives run aground on the intrinsic differences between first person subjective experience and third person objective modelling. We lack an overarching model to bridge this divide. The pragmatic view accepts our intuitive sense of consciousness as valid in its own domain, even if it cannot be neatly reduced to physical models. If the mind-body problem proves irreducible, we may have to pragmatically accept both psychological and neurobiological models as useful within their respective domains.

Coexistence of Incompatible Models

Certain models, though seemingly in conflict, can be concurrently valuable within their domains. Quantum mechanics and General Relativity exemplify this; each thrives in distinct realms but resist unification. MDO suggests that both can be valid, serving their respective purposes, as seen in the wave and particle models of light.

Against Claims of Absolute Truth

MDO warns against mistaking a model’s pragmatic success as a revelation of absolute reality. Models work within their predefined domains, and their success is contingent upon their utility, not on metaphysical claims about reality.

Conclusion

Model Dependent Ontology underscores the importance of utility in models. By disentangling utility from truth, MDO offers a method to assess knowledge that avoids the pitfalls of both relativism and the challenges of realism.