Pictorial Analogy and Ultimate Reality

Big Picture Analogies: The Universe as Supercomputer
“What is genuinely sought in a big picture may well be missed, because the assumption it must be reducible to reason is untenable from the outset. Whether one pursues a super-symmetrical or an inelegantly piecemeal explanation of total reality, the destination is seldom doubted. But what is invariably found is only what can be understood in concepts, or contrived to fit in them. All concepts and theories require fashioned tools, and all tools, queerly and consistently, take on not only the shape of the thing they supposedly touch but also the mind that made them.” ~from Omar's letter, Chapter Five of Icarus Transfigured

A scientist may postulate on the possibility of mental processes originating at the quantum level of matter,* but even if science were to demonstrate that the brain is something on the order of a quantum computer, it would still not explain how or why subatomic particles should form thought and order it. Here we are simply pushing back the threshold of consciousness and will—not lifting a veil. Two insurmountable difficulties hobble science in achieving a Theory of Everything. There are questions of ontology, which deal with the nature of being; and questions of epistemology, where we want to know how we know and what we know.

With theories like John Wheeler’s It from Bit, the Universe is equated with information, where answers to questions come in the form of bits: yes or no, one or zero. This crude form of consciousness is likened to the binary language of a computer. Yet, again, where is the will in information, digital bits, and their computation? Why should reality be self-willing simply because analogizing it to a supercomputer plugged into an electrical outlet is attractive to the technologically enamored imagination? It goes without saying, computers do not build or program themselves, or produce their own electrical supply.

Setting aside will, where we suppose consciousness to be programmable, and the Universe to be programmed, a more fundamental problem exists. In The Chinese Room Problem, we see how syntax and semantics are critically different things: a man in a room is given Chinese characters under a door. These are presented as questions, to which, by referring to a book of translation, the man replies with appropriate characters under the same door. Though the responder does not understand the semantics of the characters, he nevertheless provides the proper syntax in his reply. Those outside the room assume the man is a native speaker of Chinese, because the syntax does not violate the semantics of their understanding. A computer cannot understand the context of its response, or the context of the question; and where a word has more than one definition, how would a computer understand which form to use? Additional rules may be developed to deal with this, but this too is only a syntactical solution to the problem. If the Universe functioned like a computer, one would be hard-pressed to regard it as “conscious” in any meaningful sense of the word.

(*“The problem is that the matter inside our skulls is warm and ever-changing on an atomic scale, an environment that dooms any nascent quantum computation before it can affect our thought patterns. For quantum effects to become important, the brain would have to be a tiny fraction of a degree above absolute zero.” ~Intro by Lonnie Brown, Problems with Quantum Mind Theory)

Big Picture Analogies: The Universe as Computer Simulation
A variation on this is to suppose the Universe is a computer simulation. This comparison is feeble if you seriously think about how even the most sophisticated video game software does not remotely resemble the minute physical and mental gradations found in real-time reality; and as if the computer programmer would be unarguably omniscient in replicating every detail of reality and anticipating every doubter’s attempt to discover the deception. Of course, those offering this view simply fall back on inescapable self-reinforcing delusion, where there is no thought the doubter can have that is not anticipated or preprogrammed. Here we have a strange marriage between science and solipsism taking place.

One trick employed by crafty advocates for simulated reality lies in advancing their case by limiting debate through definitions. In the case of god-like computer simulations, if one accepts such technology is feasible, one is compelled to make no distinction between “reality” and a “simulation of reality” if they look identical at a granular level. For some, this lack of a distinction must already exist, and the more complicated reality appears to our senses, this can only mean the more developed the simulation is in achieving it; and how can one begin to disprove a technology that is many light-years beyond our understanding?

This line of reasoning is an example of the informal fallacy known as Argumentum ad ignorantium, where, because a premise (reality is a computer simulation) cannot be disproved, the premise must be true.* Once more we have an unfalsifiable theory, whose primary purpose seems more to justify a tenured position in a University think-tank than to advance real technology on the assembly line.

In support of a simulated reality, some appeal to Descartes’ conundrum of a daemon deceiver. A daemon, it is argued, cannot be discovered due to the devilish cleverness of his deception. However, those employing this tactic mistake Descartes’ intention in devising his thought experiment.* Negative propositions are useful intellectual tools, but, where made ends in themselves, they set Occam’s razor on its ear. Though this is not necessarily deal breaker, in science it bodes no good. Moreover, here we not only require a daemon to advance an elaborately complex scheme, but also a mischievous intent. Intent is not necessarily an unreasonable assumption, but mischievous intent goes well beyond explaining elaborate physical means to justify elaborate psychological ends: One may argue that God does not exist with a degree of rational credibility, but to argue that God does not exist but the Devil does is an argument few would regard as serious.

(*In devising his thought experiment, where he began by doubting everything in reality, Descartes could not convince himself his physical body was not a deception, since his only experience of it was as a thought. The thought of him thinking was nonetheless something he experienced apart from any deception practiced upon him. His one object of certain knowledge was that was a doubter, and to be a doubter one must have existence, since non-existence cannot doubt. Resultantly, he concluded that matter must be at least as real as his acting upon it in thought, even if his certain thought was the only way he could be certain of it. Causality is assumed to flow through both mind and matter to connect them, yet this cannot be explained as a question of interaction or necessity. [Here Descartes anticipates Hume.] Resultantly, we are each locked in a consciousness where we can only infer the consciousness of others. As philosopher John Searle argued, we cannot understand how a bat thinks, since its perception of the world is fundamentally different from ours.

Where we suppose reality to be wholly rational, we only prove this to ourselves where we suppose (or entertain) irrationality in what we see.

(*Many complain arguments for the Existence of God commit this fallacy, although one must make a critical distinction between a metaphysical God and a physical computer simulation, where the latter appeals exclusively to empirical criteria and stands or fall on empirical evidence. To restate: Argumentum ad ignorantium is an informal fallacy, which means it can neither be proven true nor untrue. Where God is concerned, this uncertain state in truth claims arises because of the paradox generated by our metaphysical dilemma, not because a lack of falsibility in the argument makes it supposition empty.)

Big Picture Analogies: A Holographic Universe
The holographic model of the Universe is not entirely without merit on reflection, at least as formulated by physicist David Bohm and neurophysiologist Karl Pribram. Both men, in a nexus of their respective fields, argued supersymmetry in quantum mechanics may arise from the Universe being holographic in nature. A universal image, as a whole, is inscribed in its parts, and as the pieces become smaller (as with subatomic particles), the image nonetheless remains intact, only becoming fuzzier.

Pribram believes that if we were deprived of the lenses of our eyes, and the lens-like processes of other sensory receptors, we would perceive the world as a holographic experience. (This echoes Schopenhauer’s dissection of optics as a means to understand how the optical brain constructs what it perceives.)

 

The Limits of Scientific Knowledge and Demonstration

A Misconception of Intelligence
“The man of talent is like the marksman who hits a mark the others cannot hit, the man of genius like the marksman who hits a mark they cannot even see.” ~Arthur Schopenhauer

First, when speaking of human intelligence, it is important to differentiate between analytical forms of thinking (call them informational) and synthetic forms of thinking (call them creative). Everyone possesses a degree of both, yet where intelligence is deemed to be exceptional, it is wrong to assume the latter is necessarily included in the former. Instrumentally, we deliberately confuse good long-term memory and deductive capability with the highest forms of intelligence. We also believe people who have a lot of facts or information at their disposal, or are “smart” within a narrow field of study, are the brightest among us. These one-sided views of intelligence are difficult to dispel since tests designed to measure human intelligence are biased towards verbal and performance skills because these traits can be measured.

Curiously, we often look to Einstein as our role model for the highest intellectual achievement, yet his intelligence was more synthetic than analytical. The spark of genius does not originate with linear information-in/ information-out deduction. Such logic assumes the answer is spelled out in the data, and what is required is only someone pointing it out, like a cat sitting on a piano that no one thought to acknowledge. When impressed by the original nature of insight, we describe it as “keenly observant.” As we will shortly discuss the role of perception in insight, we can take acute observation as a given; however, with synthetic intelligence we go well beyond seeing to imagine what is not seen.

Also, the role of autism in both analytic and synthetic intelligence cannot be underestimated. Many autistics with synesthetic, computational, and photographic-memory savant abilities report their talents come down to a form of picture thinking,* as in seeing numbers as shapes or colors instead of as pure abstract concepts. Similarly, narratives are regularly used to keep track of elaborate details and sequences. Analogous reasoning lends greater weight to the aesthetic and synthetic aspects of intelligence over purely analytical formulations.* One need only recall the clock tower’s role in generating Einstein’s insight into Relativity.

Kant was considered late bloomer, and Einstein was regarded as an undistinguished scientist until his breakthroughs. Autism, among those it graces with gifts, gives rise to uneven development and quirky individualism; neither trait is prized by institutions. Institutional learning is inadequate to explain (and too anemic to produce) such genius. It is with this background about the counter-intuitive nature of intelligence we begin to think about the popular yet untenable view that computers and robots will one day replicate or exceed the highest human intelligence.

(*“To everything that we wish to remember, we should give an image; and to every one of these images we should assign a position where it can repose peacefully until we are ready to claim it by an act of memory.” ~Matteo Ricci)

(*The pianist Bob Milne has a talent for executing, in real time, as many as four recorded symphonies concurrently in his mind. This is not simply a projection of the leading melody, but the ability to isolate each instrument in each score at any given moment. This extraordinary accomplishment is achieved not by computation, but by visualization of the orchestra’s performance, as well as an emotional response triggered by the tonal color of the notes played. As pointed out in a Radiolab podcast featuring Milne, emotion deepens memory. This hardly explains Milne’s feat of memorization, but it does cast light on the curious feature of emotion as something vital in how the mind works as opposed to a computer. [I would argue emotion is only the name we give Value when we have no better concept of what we seek to know and understand in things.] Emotion also underscores the role of narrative in understanding.

The mind is itself an artist: synthetic, adaptive, and vital in a way a cold analytical computer can never be. The picturing-thinking aspect of memory, when combined with emotion and Value, is clearly not reductive. For scientific holists, they grasp that the mind is working on multiple tiers simultaneously, but they can no more explain this integration than can material reductivists.)

The Paradox of Intuition and Meaning for Computers
The role of intuition cannot be understated, yet many in science do not consider it when formulating theories and understanding born out of it. Just about every faulty premise in science proceeds from the paradox of the thinker who imagines everything but the nature of thinking itself.

What computers do well, and better than humans, is sift through large amounts of data to find patterns. This activity is purely analytic. Nothing is being added to the data beyond a way to organize it by the input of the programmer. If human insight does not attach meaning to the presentation, little is gained. Again, the person outside the computer provides the insight, regardless if it is frontloaded or back-loaded into the data. The computer is only a means to an end it cannot envision on its own. It cannot tell you what the data means, only how the data converges.

Meaning is important, and with regard to algorithms employed by computers, the meaning behind the calculus can change over time even if the algorithm does not. Thus, the algorithm has to be modified, which the algorithm, in the most comprehensive sense possible, cannot do for itself, especially where flexibility is needed to re-prioritization data so it reflects shifting values in culture.

More essentially, the linkage between reason and emotions is becoming more apparent through scientific research into the nature of judgment, although artificial intelligence tends to address these areas as separate issues. In one light, a computer is judged to be smarter than a human by having more data on selected subjects. Where emotions are concerned, computers (or robots) are judged to be human enough by virtue of being perceived as human in selected situations. In both cases, the selectivity of criteria is biased toward the artificial intelligence experimenter.

#Our relationship with others is generally more emotive and psychological than logical, and where artificial intelligence is asserted as achieving humanness in experiments, it succeeds in deceiving someone that it is, at least momentarily, human by tapping into the syntax of emotion and psychology. A computer need not “understand” emotions or psychology to win confidence with susceptible people. Because science does not differentiate between the appearance of things and things as they exist in themselves, we see them engaging in a bait-and-switch by way of Turing’s Imitative Principle: Since reality is as it appears to be, even where appearances are deceiving, deception too deserves the moniker of reality. This is, again, a fallacy of accent, where, by crafty design, inordinate emphasis is placed on a curiously narrow definition of appearance, and as though insistence of this definition must be the inescapable starting place for any discussion.*

Ironically, we see computer science utilizing our tendency to anthropomorphize objects as a proving ground for its tailored agenda, even though science, in principle, regards this tendency as an anathema to sound scientific judgment in evaluating Evolution. Though I see anthropomorphism as a clue in apprehending design from reality, I do not accept it as a cheat where science uses it to fudge definitions. A machine is not a “human” no matter how effectively my empathy may be manipulated by the programmer of the machine. The machine does not think about me in the same way I think about it. (See next entry.)

A computer can—and never will—be insightful* or emotional, even though science fiction offers us countless stories about artificial intelligence having the first trait by design, and gaining the second by experience. Emotions, for the purposes of our discussion, constitute the most rudimentary form of Value: that is, Value in meaning. How can a computer formulate a concept of unarticulated meaning from unarticulated Value? This requires more than syntax and semantics in making difficult and imprecise decisions about what matters most in fluid situations.

(*We have seen this trick before, where Littlewood belittled coincidence by trying to quantify a “miracle” in writing his own definition of the word so it would fit into an equation, and then by example of the equation itself. We also see this, in our earlier example, where a definition of reality is drastically truncated to match the definition of a computer simulation.)

(*In the bigger puzzle, even if a computer could intuitively cough up the structure of reality in a mathematical equation, it would be about as intellectually satisfying to us as real and irrational numbers. Real and irrational numbers have demonstrated worth, but what do the mean? Remember: the Value [worth] is the meaning. We know this, not by proof, but by the aesthetic fact of the thing-in-itself.)

Computers and The Appearance of Will
Some may ask: How can we say definitively that present computers do not have consciousness in the way we do? We cannot “mind meld” with a computer to say one way or another.

Metaphysically, I agree that all matter has a “mind aspect” to it by way of the Noumenon,* but this is not what material reductivists mean. Where there is no empirical evidence to prove overt examples of computers replicating human consciousness in all its subtleties, prolonged debate rests on ad ignorantium philosophical devices for which reductivists otherwise have no use.

It can be argued that inorganic processes, such as the weather, display a dynamic that, as simple description, might be carelessly characterized as “willed” or “conscious” in appearance when in fact this determination cannot be made. Weather, as far as we know, does not “choose” its behavior. Though most reductivists would agree with this conclusion, a few, for the sake advancing the case made by computer scientists, will allow the possibility that present computers possess true consciousness simply because they appear conscious.

If, in this select instance, appearance is reality, then would not even a primitive consciousness share key attributes with my consciousness? I can, should I choose, will against impulse. What is consciousness if not a will that occasionally opposes, or purposefully wanders off-task? True, a computer may not carry out a given command, but to say consciousness is involved is untenable since only a free will, working consistently to assert itself as not being determined, would be able to demonstrate this is a deliberate way. No computer, to date, has shown this propensity to obstinacy in order to make a point, whereas any living organism, given an opportunity, will push back enough to let us know something is in there.*

(*In philosophy, this is known as panpsychism.)

(*When we see two identically cloned bacteria display separate movements in separate spaces, we assume they are identical in all regards except for coordinates. However, bacteria are not windup toys, for though they share the same genetics, the different directions and different obstacles afforded them by space, time, and causal interaction means there is some additional mechanism that we apprehend spatially, temporally, and causally playing out that itself does not have spatial or temporal dimensionality, or causal sequence. How else could we categorize this differential but to describe it as an independent feature? To describe it as Will?)

Superintelligent Machines: Is Immodesty Smarter?
Some computer scientists propose the creation of super-intelligent brain-like machines that one day will be “smarter” than their creators. Apart from the objections I have outlined, we have several assumptions working at cross-purposes here, from the idea the brain is a Turning machine that can be simulated with algorithms, to the belief brain function can be wholly described in computer language. Add to this the strange idea of singularity, where, it is presumed, as machines become smarter, they will become exponentially smarter.

Yet any plans for omniscience become bogged down in details, if one is willing to come down off the mountaintop of unrealistic expectation and look for them. For example: mechanical models of the brain do not allow for the kind of informal ad hoc remedies a biological brain might evolve in solving problems—if one insists the brain evolved its own understanding. More to my point, the logical methodology any artificial brain necessarily uses in its initial startup does not anticipate the plethora of problems logic generates. (Just take the logic of linguistics, for example, and issues raised by ambiguous words like “smarter”.)

I have touched on the thorny nature of semantics in science, but it is worth examining the notion of “smarter” to make a more general argument that makes the previous paragraph mostly unnecessary. What do we mean by smarter? Such an ill-defined term assumes there is only one kind of linear intelligence from which all knowledge flows. Since it is argued monkeys can buy and sell stocks on the stock market with the same success rate as informed traders, smarter by this measure is a nonstarter, for not only does this term pigeonhole the concept of intelligence (leaving out nonverbal and creative intelligence), but it also fails to take into account both the full-stop limitations of predictive science as well as the natural limitations of machines.*

Anyone who has never owned a computer immediately recognizes the problem. Immodest scientists place irrational faith in machines as saviors, glossing over the effects of entropy, wear-and-tear on machine parts, inescapable program bugs and glitches, as well as machines being fed (or feeding themselves) misinformation. Adding insult to injury, technology will always be plagued by politics, contentious expenses, saboteurs and viruses. More to the point, is it inconceivable smart machines can be wrong even if everything else goes right? Clearly some scientific utopians need super-intelligent machines to point out the irrationality of their faith in super-intelligent machines—or perhaps a man on the street of common sense can perform the same function with far less bother and expense.

(*Adding to the list of frailties about machines in general, there is also the gap between applied science and science fiction, as in the case of the fabled nanobot. All the difficulties robot technology face are nothing compared to compounding them by shrinking the whole shooting gallery down to a microscopic scale!)

The Future Does Not Need Us (?!)
So much theoretical scientific conjecture is based on best-case scenario, where the scenario plays out in the imagination, as if in the pristine environment of a laboratory. It is a confusion of theories with other kinds of stories, where the deliberate exclusion of details in the latter (to enhance the plot) becomes the deliberate exclusion of details in the former (to enhance the idea). Editing-out details is perfectly permissible in the art of storytelling, but in the science of science, it is sloppy.

One dystopian idea floated in scientific speculation is the notion that the future robots we create, lacking the frailty and biological requirements of humans, will replace us on the evolutionary ladder. It is proclaimed with an odd mixture of pessimism and optimism that “the future does not need us.”

Robots are truly superhuman, but we are only judging them to be so within very narrow tasks.* They are not living things, or anything like living things. Referring to my criticism of computers, robots will never possess insight, emotion, or true understanding. More essentially, they will never have metaphysical will to animate and direct their minds, and then to do the same for their bodies. Again, these components of our human condition are transcendental and noumenal—not mechanical and physical.

In the larger view, predictions about the omnipotence of technology are reliably one-dimensional in their insistence that the technology under consideration must determine the future; and the future, with its multiplicity of competing and unanticipated interests, has no say in the matter. It is the conceit and luxury of intellectualizing to be blinkered and narrow in formulating such ideas. For the sake of consistency, for the sport and thrill of speculation as an idea-generating activity, one must ignore everything else. This is as much about the nature of modernity as it is about a wise, old appreciation of human folly.

(*One example of technological utopianism is illustrated by Fermi’s Paradox, where it is presumed that higher alien intelligences would be able to create fleets of self-replicating robot-like probes that, in finite time, would exponentially multiple as they planet-hop across the Milky Way. The paradox is meant to underscore that, since this scenario must be true by virtue of technology’s manifest destiny, then why have we not made contact with extraterrestrials?

Carl Sagan, inserting 80’s nuclear politics into the equation, argued this absence of contact was perhaps due to other advanced civilizations destroying themselves before reaching this stage in their technological development.[ I argue that, long before we get to this paradox, there is another: Why should we assume technology should allow anyone to build a fleet of self-replicating robots?])

Digital, Analog, Imitation Life, and Eternal Life
A digital fascination is understandable given the power of modern computers. The Natural World, from the quantum level up, is seen as ascending from digital (granular) technology to analog (continuous) experience, as in building from binary code and limited programmatic steps to what we apprehend as something continuous in experience. Interestingly, a holographic view of the Universe uses an earlier technology in its analogy: A hologram compares better to conventional analog audio recording, where the process is more about waves and interference patterns than digital bytes. In this case, cells of the visual cortex, indicating Fourier transform-like structure in their spatial frequency encoding, makes the brain more resemble a receiver than a digital processor.

More ironic, the central goal of digital technology is to look and feel like the analog technology it initially replaced. Earlier analog technology was less boxy, and appeared more body-like as an extension of our physical will. However, the moving parts required made it cumbersome and obviously imitative. Digital technology, having fewer moving parts, is less obvious and cumbersome in its presentation, but does this mean it is less imitative? We can fit robots with synthetic hands that have the “appearance” of human responsiveness, and create data-driven voice recognition software that “appears” to understand what we say by ever-improving algorithms, but these interactions never truly approach humanness. There is no true ghost in the machine, only the appearance of one in limited, controlled situations. It is like the supercomputer than plays chess, but not Chinese checkers: The show is only meant to put the computer in the best light.

More subtly, we have a clear record of machines and computers becoming better in what they do as their builders build on a body of knowledge. However, what is generally forgotten is how it is never the same machine in the demonstration of this fact. Machines are not snakes that shed their skins,* where we are always dealing with the same snake. Each generation of improved technology replaces the generation before it, and antiquated machinery is either recycled for parts or thrown on the trash heap. We see only new machines—rarely old machines that are taught new tricks. Machines are not organic human brains that grow and evolve. We might say, in Heraclitian fashion, new cells replace old ones in our brains, so technically our brain today is not physically the same one we had ten years ago. Yet this replacement stems from the nature of biology—not from parts ordered from a warehouse supplier. Unless someone is there to develop, build, and tweak the next generation of technological hardware, the hardware fossilizes in the sediment where it is left.

Theorists insist science is rapidly closing the gap between technology and biology, yet the two spheres are clearly different. We fashioned the ontology of technology, but only manipulate the ontology of biology. We may blur the two spheres to some degree, but this blurring will never constitute a true understanding of what underlies true ontology.

(*For those who believe in self-replicating robots, they get around the entropic dilemma by having the robot replace itself, which would require the robot building the replacement parts as well as improving the design as needed. Again, these feats require will and intuition, as well as an adaptive synthetic intellect. These attributes are so fundamentally metaphysical in essence that no physical scheme ever approaches sobriety in accounting for them.)

The Past, Present, and Future That Never Was
The revolution of CGI technology, when coupled with the human imagination, has created a vision of futuristic scientific ability that far exceeds what science has (or will) achieve. It is a joke among standup comics to ask, “Where is that jet pack I was promised in the future? Or colonies on the moon?” The complaint exposes a chasm between what can be envisioned as reality in the mind of graphic animators and what can be feasibly engineered in real world terms.

Technology engenders more than one paradox, for not only does CGI generate an unrealistic view of future reality, but it also allows for a present reality that is equally unrealistic: one need only think about computerized girlfriends in Japanese culture. Furthermore, CGI generates a variety of possible realities when pondering the past. We presume to know how dinosaurs looked, behaved, and met their ends purely by speculative scenarios born out of computer animation. As technology has evolved, it has left the real world behind to create a multitude of virtual realities whose primary grounding is in imagination and emotional need.

It is perhaps a measure of decadence, and ironic history, that technology should reach its zenith just as it bottoms out, though in a philosophical view we see this evolution as proceeding naturally from mind to matter back to mind, since our ideas are both the beginning and end of our investigations. The spirit is always willing, but the flesh is weak, which is to say that though mind and matter are transcendentally the same, mind makes the world of matter infinitely will-able only as a matter of mind.

Using Science To Get Around Science’s Limitations
Interestingly, many outside the sciences hold the belief that the demonstrated limits of science to provide the kind of technology found in science fiction must arise from some furtive technology (e.g., mind control) practiced on us from without: the logic being that our masters want to bar our access to the very technology they deploy on us, so to avoid discovery. Ironically, such intervention would cut both ways since “intervention” would also account for a fine-tuned Universe, where we find ourselves insulated enough to be befuddled by our predicament. This, it is reasoned, must be evidence that a higher order of scientific understanding is at work.

We again return to the idea our Universe is a simulation run by beings of “higher intelligence”: an intelligence that has miraculously sealed itself off from all detection. (A variation on this, held by a few within science, is the idea our planet was seeded by extraterrestrials.) Even if this fatalistic resignation over the limits of our knowledge had merit, it would explain nothing about the underlying reality of simulators or seedlings. For the materially reductive mind, this should be one more version on the infinite regression of designers requiring designers argument.* How would the simulator of our reality be assured that their reality was not also simulated? And so on and so forth?

Here again we are sidestepping unanswerable questions since these ploys do not dilute or eliminate the riddle of life emerging from seeming nothingness. Simulation simply inserts an extra step between seeming life and seeming nothingness. Such moves, which can only be construed as an apology for not having a better answer, underscores the need for a metaphysical ground to life-sustaining reality that allows for both us and our remarkable accomplishments.

(*In irony of ironies, though Richard Dawkins rejects a God-like designer for Creation, he nevertheless entertains the possibility of alien designers, who would presumably work from natural rather than supernatural blueprints. [This tantamounts to a sneaking mistrust of randomness from the guru of randomness!])