The term "reductionist" in philosophy and science refers to the idea that complex systems can be understood by breaking them down into their simpler, constituent parts. It's a perspective that seeks to explain higher-level phenomena in terms of interactions or properties of more basic entities. Reductionism often entails explaining phenomena at one level (e.g., biological or chemical) in terms of phenomena at a more fundamental level (e.g., physical or atomic). For example, molecular biology attempts to explain biological processes in terms of interactions between molecules.
Note: While reductionism has been a highly successful paradigm in many areas of science, it's not the only perspective. Holism, for instance, posits that systems should be viewed as wholes, not just as collections of parts, and that there are emergent properties that cannot be fully understood merely by studying the components. Some phenomena, holists argue, can only be grasped when looking at the larger context in which they occur.
This idea emerged in the latter part of the 20th century and proposes that the universe is, at its core, describable by digital information or computational structures. The universe, according to this view, might be likened to a vast computer simulation.
Quantum Physics shares it as well!
Quantum physics already implies that the whole universe could be described as information. The holographic principle proposes that said information could be encoded in a 2-dimensional surface (This is a principle derived from black hole physics, suggesting that the information contained within a region of space can be described by the information on the boundary of that space. It implies a kind of "informational" description of spacetime) .
This philosophical position was developed in the early 20th century by philosophers like Bertrand Russell and Ludwig Wittgenstein. It holds that the world consists of a collection of simple, indivisible entities (logical atoms) and that complex propositions or facts can be analyzed into more basic logical structures.
The Mind as an Information Processing System
If one takes the view that cognition itself is a form of computation (as is often done in certain branches of artificial intelligence and cognitive modeling), then there's an implicit connection with digital physics. The mind, in this perspective, processes information, much like a computer. This viewpoint aligns with the computational theory of mind, which suggests that cognitive processes can be described as computations.
In cognitive science, a parallel might be drawn with the idea that complex cognitive processes can be decomposed into simpler cognitive "atoms" or primitives. For example, in linguistics, one might attempt to break down language into its most basic semantic or syntactic units, hoping to uncover the fundamental building blocks of meaning and language structure.
AI systems, particularly those inspired by neural networks, operate on a kind of digital physics premise. They take vast amounts of data (a digital representation of some aspect of reality) and process it in a computational manner to learn, make decisions, or generate outputs. Much like human cognition, AI models often reduce the complexities of their input data. For instance, convolutional neural networks, used in image recognition tasks, simplify and compress image data through their layers to extract essential features. This "reducing" process is akin to filtering out the noise and honing in on the signal, a distilled understanding of the presented reality. "Reducing Reality" serves as an umbrella theme capturing the essence of various endeavors across cognitive sciences, human cognition, and AI. Each field, in its way, grapples with the challenges and advantages of distilling the complexities of existence, thought, and information into more fundamental and comprehensible units. Whether it's the human brain simplifying sensory data, a cognitive scientist breaking down cognitive processes into elementary steps, or an AI model processing vast amounts of data, the act of reduction is a recurring motif in our quest to understand and replicate intelligence.