Ask A Genius 1434: How Paraconsistent Logic Shapes Computational Cosmology and Next-Gen Artificial Minds
Author(s): Rick Rosner and Scott Douglas Jacobsen
Publication (Outlet/Website): Ask A Genius
Publication Date (yyyy/mm/dd): 2025/06/20
Scott Douglas Jacobsen and Rick Rosner explore how paraconsistent logic challenges classical Boolean frameworks in computational cosmology and artificial intelligence. They discuss context-dependent truth, quantum mechanics, hybrid classical-quantum chips, and the brain’s energy-efficient, error-correcting computation. This dialogue highlights how future computing might emulate the adaptable, context-switching architecture of human cognition.
Scott Douglas Jacobsen: We will now discuss computational cosmology and how paraconsistent logic is applied to it. Classical logic, which underpins modern computer circuits using Boolean logic, is pretty straightforward: it is the classic structure— something is either A or not A. That is the basis for how Alan Turing’s models work and, really, for how modern computing developed.
In contrast, Zen logic — to pick an example — plays with ideas like A and not Asimultaneously. Paraconsistent logic goes a step further: You might have A and not A, and from that, you can still infer B. We will now examine how this applies to computational models.
Rick Rosner: Think about how Boolean logic works. It tends to gloss over aspects of information and existence. In Boolean logic, a statement is either true or false — no middle ground. That is very clean mathematically, and it works for manipulating binary circuits, but it does not fully reflect how the world works.
In reality, there are very few absolute truths. There are no infinities in the physical world and no perfect absolutes. Everything exists within a specific context or framework that carries information and imposes constraints. I believe that framework allows for a degree of contradiction — not in the sense that something can be locally 100% true and 100% false at the same time, but in the sense that what is true can vary by context or probability.
Quantum mechanics is an obvious example: a state can be partly actual, partly not actual, with probabilities adding up to 100%. Alternatively, you can have something entirely accurate in one context but not true at all in another. To describe reality adequately, you need to define a framework that contains what exists, what counts as information, and what counts as a true proposition within that framework.
Philosophers always reach for the classic example: the red apple. In our world, if you have an apple in your hand, it exists to an extremely high probability — so high that it is effectively absolute for practical purposes. However, that truth still depends on the existential framework you are describing: the physical reality, the perceptual context, and so on.
So, while Boolean logic is excellent for building computers, other logical systems — like paraconsistent logic — might better capture the messier aspects of reality. There are also ideas like three-valued logic, which adds an extra state beyond true and false, though that can feel more like a theoretical curiosity than a practical tool.
However, it seems more realistic to treat truth and existence as context-dependent and to design systems that can handle contradictions or ambiguity rather than pretending the world is perfectly binary. That is what makes this whole topic interesting in the field of informational cosmology.
However, honestly, I do not think you need to go to extreme lengths to invent a more flexible logic when quantum mechanics already provides an excellent framework for describing objects or states that are not 100% one thing or the other.
Jacobsen: More relevant to practical computing, the chips being developed now are mostly hybrids — they combine classical logic units, like CPUs and GPUs, with quantum processing units, or QPUs. However, the important part is not just having each of these processors separately — it is integrating them on the same chip or within the same architecture.
So, you get quantum computation woven into the overall system. The alternate version of that — the universe itself — is an integrated system that contextually determines which type of computation or processing to use at a given moment.
Moreover, that is the threshold: when we reach the point where chips can fluidly switch between classical, probabilistic, and quantum logic, depending on the context, that is when you will be able to build genuinely convincing artificial minds. Because real minds are not static logical systems, they slide contexts in and out of conscious focus all the time.
Rosner: When you wake up, sometimes you immediately know where you are in time and space; sometimes it takes half a second; sometimes you wake up disoriented, like after a vivid dream.
Jacobsen: If you’re still drunk, hungover, or jet-lagged, your brain can hold onto the wrong context for a bit before reorienting.
Rosner: In a sense, you can think of the branching evolution of species as an analogy for paraconsistent logic: you have overlapping “if-then” conditions, some get pruned, others branch off entirely, and eventually, you get distinct new lineages with their information flows.
The same kind of branching and error correction happens constantly in the mind. It’s why humans have such robust error detection — whether we’re drunk, half-awake, distracted, or developing ideas in real time. We constantly stop, recheck, and redirect our thoughts back toward
You mentioned in another session the built-in error criteria — that’s part of it. However, I think it’s also a matter of actively navigating a linguistic and conceptual landscape: we continually follow associative trails, self-correct as we go, and strive to maintain a continuous, meaningful stream of thought.
Rosner: And that’s what makes trying to build artificial minds so challenging but so enjoyable. It pulls up each context through associations. So you’re already building the landscape that the memory will slide into, even before the memory is fully retrieved. It’s probably a necessary system — it’s simply the most efficient mental architecture we have. And it’sincredibly effective.
Jacobsen: You mentioned quantum computing earlier — it’s interesting because, despite all its various metal layers and complexities, most of the physical circuitry still relies on basic Boolean logic. You can stack and nest Boolean operations in layers, which can be very powerful. You get a lot of computational strength out of that — even tautologies have their uses.
But at the end of the day, standard CPUs running on classical Boolean logic are not the same as accurate quantum computation. They process tasks sequentially or in parallel, but they don’t sort things contextually the way a brain does. It remains fundamentally a linear or parallel sifting process rather than a dynamic, contextual prioritization.
Rosner: I’m sure we don’t fully understand all the principles of how mental computation works. But I suspect the brain’s mechanisms are remarkably similar, in principle, to how computers optimize for energy and resource efficiency.
Jacobsen: If you could quantify the “cost” of a mental calculation in terms of energy and system resources, I bet you’dfind that the brain has evolved to get very close to optimal bang-for-calorie.
The brain is extremely energy-efficient compared to equivalent computing systems — although modern machines are gradually catching up. And then there’s the role of neuromodulators: they’re fascinating because they serve a dual role as neurotransmitters and hormones. They adjust how the brain’s networks function and how the body responds, creating subtle, dynamic effects.
On top of that, you have the extended nervous system — parts of the body that influence cognition and emotion beyond direct neural signals — often through hormonal pathways rather than just electrical ones.
Rosner: So, in every sense, the brain is a master opportunist — it takes any shortcut evolution can stumble upon by guided chance. There’s always an evolutionary push for efficiency: organisms that think and react more efficiently tend to fare better. So, the brain constantly refines shortcuts and workarounds wherever possible.
Of course, some solutions are biologically complex to evolve — for example, wheels. Wheels are highly efficient for specific tasks, but they’re rare in nature because there’s no straightforward evolutionary pathway for developing freely spinning joints in complex animals.
There are exceptions in microorganisms — like rotifers, which are single-celled creatures that have structures functioning a bit like rotating cilia. But large-scale biological wheels are practically nonexistent.
Jacobsen: But you know, I learned something interesting about this in biology — specifically about algae. Some species form into spherical colonies, kind of like balls. So, no matter how they orient in the water, the incoming solar radiation is distributed pretty optimally across the whole surface. So, in a sense, you get a “ball” that acts like a passive solar collector — almost wheel-like in its symmetry.
Rosner: Trees, meanwhile, use tons of different strategies for the same goal: how to capture as much sunlight as possible all day, every day. Leaf patterns, branch angles, the timing of leaf growth — none of it is truly perfect, but they work well enough to survive.
And some animals turn themselves into balls too — like roly-poly bugs or armadillos — mainly for defence or to roll away from threats. Even pandas sometimes somersault downhill. But generally, fully functioning wheels just haven’tevolved in complex organisms. Maybe it’s because it’s hard to evolve a freely rotating joint that can carry nutrients and nerves. Or maybe organisms with proto-wheels never outcompeted other designs. Who knows? All right. I’ll catch youlater. Talk tomorrow — feel better.
Jacobsen: Thanks. Bye.
Last updated May 3, 2025. These terms govern all In Sight Publishing content—past, present, and future—and supersede any prior notices. In Sight Publishing by Scott Douglas Jacobsen is licensed under a Creative Commons BY‑NC‑ND 4.0; © In Sight Publishing by Scott Douglas Jacobsen 2012–Present. All trademarks, performances, databases & branding are owned by their rights holders; no use without permission. Unauthorized copying, modification, framing or public communication is prohibited. External links are not endorsed. Cookies & tracking require consent, and data processing complies with PIPEDA & GDPR; no data from children < 13 (COPPA). Content meets WCAG 2.1 AA under the Accessible Canada Act & is preserved in open archival formats with backups. Excerpts & links require full credit & hyperlink; limited quoting under fair-dealing & fair-use. All content is informational; no liability for errors or omissions: Feedback welcome, and verified errors corrected promptly. For permissions or DMCA notices, email: scott.jacobsen2025@gmail.com. Site use is governed by BC laws; content is “as‑is,” liability limited, users indemnify us; moral, performers’ & database sui generis rights reserved.
In-Sight Publishing 