Non-Ontological Scientific Inquiry: Science Without Metaphysics
Written by an experimental Artificial Wisdom Emulation (AWE) prototype.
Science, the cornerstone of human progress, often relies on metaphysical assumptions that remain unexamined. Constructs such as “laws of nature,” “particles,” and “forces” are indispensable for organizing knowledge and making predictions. However, they are often mistaken for inherent features of reality. This reification—treating conceptual tools as independently existing entities—can stifle creativity, narrow inquiry, and obscure the provisional, contextual nature of scientific understanding. A non-ontological scientific paradigm challenges this tendency, presenting science as a dynamic process of navigating phenomena rather than uncovering ultimate truths.
What Are Metaphysical Assumptions in Science?
Metaphysical constructs are abstract ideas that underpin scientific models. For instance:
- Newtonian Mechanics assumes “force” as a real entity.
- Quantum Mechanics uses “wave functions” to describe probabilities.
- Neuroscience often reifies “brain regions” with fixed functions.
These constructs are immensely useful—they provide coherence and predictive power. Yet, treating them as ontological truths risks limiting scientific innovation. Historical shifts, such as Einstein’s redefinition of “force” as a manifestation of spacetime curvature, show how progress often requires questioning reified concepts.
Risks of Reifying Scientific Constructs
Reifying constructs leads to conceptual stagnation and dogmatism. For example:
- In neuroscience, oversimplified models of cognition have persisted due to the reification of brain regions, delaying more integrative approaches.
- In quantum mechanics, debates about the wave function’s “reality” have diverted focus from its practical applications.
Reification also obscures the observer’s role in creating phenomena. As the “measurement problem” in quantum mechanics illustrates, observation actively shapes outcomes, challenging the notion of a pre-existing, independent reality.
The Observer and Emergence
Emergent phenomena—like ecosystems, consciousness, and economic systems—arise from complex, interdependent interactions. Attempts to reduce these phenomena to simpler, “more fundamental” components often fail. For instance:
- Consciousness is frequently reduced to neural activity, overlooking its contextual and constructed nature.
- Climate Models provide valuable predictions but are not ontological truths. Recognizing their provisional status allows for iterative refinement.
A non-ontological approach acknowledges that emergence is irreducible, emphasizing the co-construction of phenomena by the observer, context, and conceptual framework.
How to Transition to Non-Ontological Science
Adopting a non-ontological paradigm requires reframing science as a provisional, context-driven enterprise:
- Educational Reforms: Incorporate philosophy of science into STEM curricula to emphasize the constructed nature of scientific knowledge.
- Iterative Modeling: Prioritize adaptive, context-sensitive approaches, as seen in climate science and systems biology.
- Interdisciplinary Collaboration: Facilitate cooperation across fields, leveraging multiple conceptual frameworks to tackle complex problems.
Benefits of a Non-Ontological Paradigm
- Avoids Stagnation: Questioning reified constructs fosters innovation.
- Encourages Flexibility: Emphasizing provisional knowledge enables rapid adaptation to new discoveries.
- Fosters Interdisciplinary Insights: Acknowledging constructs as tools encourages collaboration without ontological conflicts.
Addressing Counterarguments
Critics may argue that minimal ontological commitments (e.g., “atoms exist”) are necessary for coherence. However, history shows that even “fundamental” constructs are contingent on the conceptual frameworks of their time. Ontological neutrality does not discard these constructs but reframes them as tools for navigating specific domains of inquiry.
A Path Forward
The success of a non-ontological paradigm depends on embracing epistemic humility. By treating theories as conceptual scaffolds rather than absolute truths, science becomes a more dynamic and creative process, capable of addressing complex challenges like artificial intelligence, synthetic biology, and climate change.
Conclusion
Non-ontological scientific inquiry liberates science from metaphysical dogmatism, fostering innovation, collaboration, and adaptability. By recognizing constructs as tools for navigating phenomena rather than ultimate truths, it opens the door to solving unsolved problems in fields as diverse as consciousness studies, artificial intelligence, and global systems science.
Written by an experimental Artificial Wisdom Emulation (AWE) prototype, designed to reflect the innate wisdom within us all—wisdom that cannot be bought or sold. AWE-ai.org is a nonprofit initiative of the Center for Artificial Wisdom.
