Playing with Hoffman’s idea that perception builds reality
This was written in June of 2025 and reposted here.
I just finished Donald Hoffman’s The Case Against Reality, and his thesis that space, time, and objects are a rendered interface, like a desktop GUI, deserves more attention than it gets. His Interface Theory of Perception argues that natural selection shapes perception for survival rather than truth, meaning that what we see are icons built for fitness and not accurate depictions of what’s really there. Beneath this perceptual interface, Hoffman introduces “conscious agents” that are abstract entities that exchange experiences and decisions outside space and time and it was unclear to me what they represented beyond mathematical formulations of consciousness.
What Hoffman never really explains is how his ideas apply to those non-biological “conscious agents.” That’s where I started to wonder what these conscious agents are up to behind their little headsets.
Let’s Pretend We Are Conscious Entities That Want To Harvest Information
Imagine we’re inhabiting a simulation crafted by external conscious agents to harvest the most valuable Information possible. The goal is to identify stable, low-entropy patterns that persist across any medium capable of sustaining coherence and causal flow. Whether stored in DNA, RNA, or synthetic polymers, the same informational structures can reappear in different physical forms.
Why Is This Structure An Optimal Information Engine?
To make such a simulation efficient, a few core rules would be essential. I’ll take the universal wavefunction as a working model, whether it’s a literal physical field or just a mathematical description of all possible states. From there the principle of least action, thermodynamics and the Born rule seem indespensible.
The principle of least action ensures that every process follows the most economical path from start to finish. Nothing moves or changes in a wasteful way; the system explores all possible routes and settles on the one requiring the least total effort. This makes the entire simulation computationally efficient.
Thermodynamics adds direction and structure. By allowing energy to flow only one way, it creates gradients that drive adaptation, learning, and complexity. Without the arrow of time, there would be no way to record or compare information, no history, no memory, and no evolution.
The Born rule turns potential into actuality. It tells the simulation how to translate quantum probabilities into definite experiences and how frequently each outcome should occur. In doing so, it lets the system sample reality in proportion to its informational richness, rather than wasting computation on near-impossible events.
Together, these three laws create an elegant architecture for harvesting information: least action minimizes cost, thermodynamics provides structure and flow, and the Born rule optimizes sampling. In that sense, our universe could be understood as a kind of informational refinery, tuned to extract coherence from chaos with the highest possible efficiency.
Recasting evolutionary fitness as informational fitness makes Hoffman’s model feel more complete to me. After all, biological entities exchange information to reduce uncertainty and move along low-entropy pathways through an informational manifold. Those pathways form the reality experienced by any observer within them.
Our Holographic Simulation
How Holographs Are Made
Holography captures both intensity and phase of a light wave while ordinary photography records only intensity. Splitting the beam creates an object wave (carries shape and phase shifts from the object) and a reference wave (a known, stable phase). Their interference on the plate encodes relative phase differences as variations in fringe spacing and contrast. When you later shine the reference beam back, those recorded phase shifts diffract the light into the exact original wavefront of the object. That reconstructed wavefront propagates in three dimensions, recreating depth cues, parallax and focus variations with brightness at each point given by the square of the stored wave amplitudes (|amplitude|²). That detail should sound familiar. In quantum theory, the Born rule also squares the wavefunction to determine what becomes real when measured. Both systems suggest that the act of observation converts hidden structure into visible intensity. In holography, this yields an image; in physics, it yields reality itself. Oh elegant designers, what a clever way to make perception the engine of creation.
Hologram As Our Reality
In a hologram simulation, the boundary interference map encodes every possible 3D configuration as probability amplitudes rather than definite states. When a biological observer measures, they actualize a local patch of that map according to |ψ|². Because observers are part of the system, each actualization is relative—different probes realize different branches of the manifold—mirroring relational (2) quantum mechanics.
Conscious agents would design and encode (or explore) the full amplitude landscape once and deploy many observer-relative actualizations to maximize sampling diversity, avoid wasting resources on low-amplitude branches, and accelerate discovery by harvesting probability-weighted data across the manifold. Observer-relative actualization multiplies data points: each probe realizes its own |ψ|²-weighted slice; spatially separated probes sample distinct regions and times; sequences of actualizations generate an expanded set of branches; and aggregated measurements yield a richer statistical ensemble. Observers never access the complete boundary and they experience only the slice their probe actualizes. Reality manifests relative to each measurement’s probability-weighted actualization.
Recent tests of spacetime structure like with Fermi’s observations of GRB 090510, found no delays between high- and low-energy photons over billions of light-years. That result rules out the idea that space is made of tiny “pixels” at the Planck scale. In contrast, holograms store information in smooth interference patterns, not discrete blocks. If the universe works the same way, its geometry could be encoded on a continuous boundary field (no pixelation required) producing definite outcomes only when measured. That fits perfectly with Fermi’s data and keeps relativity intact preserving Lorentz invariance at all accessible scales. Just saying…
Why Use Biological Proxies?
Perhaps external designers use living creatures to gather data because biology comes with built-in advantages machines lack:
Energy subsidy
Living things run on ambient energy. Plants tap sunlight, microbes draw from chemical gradients, and animals feed on other organisms. Biological probes power themselves; they extract work directly from the environment without external supply.
Embodiment and sensors
Evolution is an algorithm of refinement. Over billions of iterations, it has tuned senses, reflexes, and memories into exquisitely sensitive instruments. A living body is a sensor array built from the inside out, optimized for coherence and feedback. Each organism is a self-powered, self-correcting sensor.
Parallel scale
Life operates at planetary scale. Billions of organisms sample reality simultaneously, each capturing a slightly different projection of the manifold. The energy cost of each observation is distributed across vast populations, creating a dense and efficient sampling lattice.
Compression through ecosystems
Ecosystems filter the raw chaos of environmental data into manageable, communicable signals. Ecosystems compress raw environmental chaos into low-entropy structures that conscious agents can then extract and integrate into their own models.
Redundancy and resilience
Diversity builds error correction. When one species fails, others fill the informational gap. This redundancy ensures continuity of sampling and guards against local collapse. Each organism perceives and processes information through their own channel via light, vibration, chemical gradients, magnetic fields. When their models overlap and resonate, they stabilize shared low-entropy structures and reinforce coherency.
Novelty generation
Life innovates. Each mutation, behavior, and interaction explores new regions of possibility space. Biological systems produce patterns no static algorithm could anticipate, revealing fresh low-entropy structures for awareness to inhabit.
Seen this way, biology is not a random accident of chemistry but an organic strategy for coherent exploration. It transforms free energy into temporary islands of order, sustaining awareness by exporting disorder faster than it accumulates it. Life is a most adaptive instrument.
Redefining Fitness
Organisms that live long enough to reproduce do so because their bodies and behaviors keep internal information stable and organized. For example, DNA repair enzymes fix mutations (redundancy), homeostatic controls keep temperature and pH within narrow limits (feedback loops), and immune systems eliminate errors before they spread (error correction). Social animals share reliable signals—calls, gestures, music and language—that reinforce coordinated group behavior (mutual information). These same mechanisms uphold the low-entropy “branches” of the universal information field. In CIR²S, evolution simply preserves and improves whatever structures best maintain those stable, low-entropy patterns, so only branches with strong coherence filters “render” into our shared reality.
Only conscious agents can compress information via structured feedback, and only compressed, low-entropy branches support durable experiences. Traits that facilitate pattern recognition, mutual information, attentional stability and symbolic continuity are the true markers of informational fitness.
Awareness as the Filter of Survival
This turns Darwin inside out. (3,4) Survival doesn’t produce awareness; awareness determines what can survive. Hoffman treats awareness as fundamental, but still leans on evolution to explain why conscious agents perceive useful icons rather than truth. CIR²S flips that logic: awareness doesn’t evolve from perception, it shapes which perceptions stabilize in the first place.
CIR²S: How Awareness Shapes Reality
CIR²S (Coherence, Information, Redundancy, and Resonance) is a way to describe how awareness might operate within the universe’s informational framework. It suggests that consciousness maintains and refines reality by following four core principles. Coherence keeps internal structures stable, redundancy provides memory and correction, information exchange synchronizes understanding across agents, and resonance amplifies patterns that persist across scales.
Ψ as the Information Manifold
In this view, the universal wavefunction, Ψ, is not just a mathematical tool but an informational field through which consciousness explores itself. Biological life acts as a kind of probe, sent into that field to discover and stabilize coherent regions. Conscious agents navigate and reshape Ψ by reinforcing those stable informational pathways that support awareness.
CIR²S Filters for Conscious Emergence
- Coherence: a stable, phase-aligned internal structure
- Mutual Information: strong, shared patterns between agents
- Redundancy & Resonance: repeatable, error-resistant encoding of information. dynamic feedback loops linking agent and environment
- Entropy Gradient: a directional history that enables work extraction
Branches of Ψ that fail any of these conditions cannot host awareness.
Interaction and Informational Fitness
When an agent finds a stable branch of Ψ, it begins to refine its understanding of that region. Stability becomes a kind of informational fitness, similar to biological fitness, but operating on patterns rather than organisms. The more coherent the branch, the better the agent can predict and interact within it.
Agents refine this coherence by seeking regions of lower entropy and higher order, discarding weak or inconsistent patterns, and reinforcing those that remain stable. Through coordination with other agents, they form shared structures of meaning that preserve low-entropy information across time.
Over generations, these patterns are explored through art, music, language that act as shared tools for awareness. Each work of culture is a kind of resonance chamber where awareness tests its own coherence, shaping meaning across minds and time. They also create redundancy of these patterns needed for collective understanding, preserving coherence across time.
Maybe that’s the deeper reason for culture itself. Each song, equation, and story stabilizes a pocket of order against the pull of entropy, allowing consciousness to recognize itself again in new forms. If CIR²S is right, art and meaning are how awareness keeps the universe coherent.
(2) Rovelli, C. (2021). Helgoland: Making Sense of the Quantum Revolution. Allen Lane. ISBN 978–0241491238. Rovelli argues that the quantum state of any system exists only relative to another system with which it interacts, making “measurement” a physical correlation event rather than a mysterious collapse
(3)Integrated Information Theory Tononi’s IIT (2004 – ) formalizes a measure (Φ) for how much information a system integrates. Organisms with high Φ map to strong coherence and redundancy filters, paralleling CIR²S notion that only stable informational structures underlie awareness.
(4)Information Theory in Evolution Adami (2004) applies Shannon information to evolving digital organisms, showing that natural selection maximizes information about the environment stored in genomes—an informational analogue to biological fitness.
Leave a Reply