Michael J. Behe's Blog, page 22

At Quanta: What Does It Mean to Align AI With Human Values?

Making sure our machines understand the intent behind our instructions is an important problem that requires understanding intelligence itself.

Melanie Mitchell writes:

Many years ago, I learned to program on an old Symbolics Lisp Machine. The operating system had a built-in command spelled “DWIM,” short for “Do What I Mean.” If I typed a command and got an error, I could type “DWIM,” and the machine would try to figure out what I meant to do. A surprising fraction of the time, it actually worked.

The DWIM command was a microcosm of the more modern problem of “AI alignment”: We humans are prone to giving machines ambiguous or mistaken instructions, and we want them to do what we mean, not necessarily what we say.

[AI researchers] believe that the machines’ inability to discern what we really want them to do is an existential risk. To solve this problem, they believe, we must find ways to align AI systems with human preferences, goals and values.

This view gained prominence with the 2014 bestselling book Superintelligence by the philosopher Nick Bostrom, which argued in part that the rising intelligence of computers could pose a direct threat to the future of humanity. Bostrom never precisely defined intelligence, but, like most others in the AI alignment community, he adopted a definition later articulated by the AI researcher Stuart Russell as: “An entity is considered to be intelligent, roughly speaking, if it chooses actions that are expected to achieve its objectives, given what it has perceived.”

For Bostrom and others in the AI alignment community, this prospect spells doom for humanity unless we succeed in aligning superintelligent AIs with our desires and values. Bostrom illustrates this danger with a now-famous thought experiment: Imagine giving a superintelligent AI the goal of maximizing the production of paper clips. According to Bostrom’s theses, in the quest to achieve this objective, the AI system will use its superhuman brilliance and creativity to increase its own power and control, ultimately acquiring all the world’s resources to manufacture more paper clips. Humanity will die out, but paper clip production will indeed be maximized.

It’s a familiar trope in science fiction — humanity being threatened by out-of-control machines who have misinterpreted human desires. Now a not-insubstantial segment of the AI research community is deeply concerned about this kind of scenario playing out in real life. Dozens of institutes have already spent hundreds of millions of dollars on the problem, and research efforts on alignment are underway at universities around the world and at big AI companies such as Google, Meta and OpenAI.

To many outside these specific communities, AI alignment looks something like a religion — one with revered leaders, unquestioned doctrine and devoted disciples fighting a potentially all-powerful enemy (unaligned superintelligent AI). Indeed, the computer scientist and blogger Scott Aaronson recently noted that there are now “Orthodox” and “Reform” branches of the AI alignment faith. The former, he writes, worries almost entirely about “misaligned AI that deceives humans while it works to destroy them.” In contrast, he writes, “we Reform AI-riskers entertain that possibility, but we worry at least as much about powerful AIs that are weaponized by bad humans, which we expect to pose existential risks much earlier.”

Many researchers are actively engaged in alignment-based projects, ranging from attempts at imparting principles of moral philosophy to machines, to training large language models on crowdsourced ethical judgments. None of these efforts has been particularly useful in getting machines to reason about real-world situations. Many writers have noted the many obstacles preventing machines from learning human preferences and values: People are often irrational and behave in ways that contradict their values, and values can change over individual lifetimes and generations. After all, it’s not clear whose values we should have machines try to learn.

Note: “Crowdsourced ethical judgments” could be something similar to “mob rule” or “the party line” or “social relativism”. Anybody want to enlist in a future governed by machines making value-based decisions with such criteria?

Many in the alignment community think the most promising path forward is a machine learning technique known as inverse reinforcement learning (IRL). With IRL, the machine is not given an objective to maximize; such “inserted” goals, alignment proponents believe, can inadvertently lead to paper clip maximizer scenarios. Instead, the machine’s task is to observe the behavior of humans and infer their preferences, goals and values. 

However, I think this underestimates the challenge. Ethical notions such as kindness and good behavior are much more complex and context-dependent than anything IRL has mastered so far. Consider the notion of “truthfulness” — a value we surely want in our AI systems. Indeed, a major problem with today’s large language models is their inability to distinguish truth from falsehood. At the same time, we may sometimes want our AI assistants, just like humans, to temper their truthfulness: to protect privacy, to avoid insulting others, or to keep someone safe, among innumerable other hard-to-articulate situations.

Moreover, I see an even more fundamental problem with the science underlying notions of AI alignment. Most discussions imagine a superintelligent AI as a machine that, while surpassing humans in all cognitive tasks, still lacks humanlike common sense and remains oddly mechanical in nature. And importantly, in keeping with Bostrom’s orthogonality thesis, the machine has achieved superintelligence without having any of its own goals or values, instead waiting for goals to be inserted by humans.

Yet could intelligence work this way? Nothing in the current science of psychology or neuroscience supports this possibility. In humans, at least, intelligence is deeply interconnected with our goals and values, as well as our sense of self and our particular social and cultural environment. The intuition that a kind of pure intelligence could be separated from these other factors has led to many failed predictions in the history of AI. From what we know, it seems much more likely that a generally intelligent AI system’s goals could not be easily inserted, but would have to develop, like ours, as a result of its own social and cultural upbringing.

Note: How could this possibly go wrong? Surely, programming an AI system to develop its own goals (for the good of humanity, of course) would lead to utopia. (Sarcasm alert!)

In his book Human Compatible, Russell argues for the urgency of research on the alignment problem: “The right time to worry about a potentially serious problem for humanity depends not just on when the problem will occur but also on how long it will take to prepare and implement a solution.” But without a better understanding of what intelligence is and how separable it is from other aspects of our lives, we cannot even define the problem, much less find a solution. Properly defining and solving the alignment problem won’t be easy; it will require us to develop a broad, scientifically based theory of intelligence.

Full article at Quanta.

The Declaration of Independence of the United States of America contains these words:

“We hold these truths to be self-evident, that all men are created equal, that they are endowed by their Creator with certain unalienable Rights, that among these are Life, Liberty and the pursuit of Happiness.”

Basing human rights on the endowment of a transcendent Creator ensures that they cannot be taken away by changes in human opinion. Human rights may be violated, but their transcendent origin means that they still exist as an immutable reality to which aspirations of freedom will strive.

Let us be warned not to cede our rights and values to public opinion or an elite few who control the programming of moral philosophy into machines.

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At Evolution News: Early Humans Were More Sophisticated than We Thought

Denyse O’Leary writes:

Recent findings suggest that some things we take for granted in human civilizations are much older than thought. Now, these findings are provisional but they are worth looking at.

Image credit: Neanderthal-Museum, Mettmann, CC BY-SA 4.0 , via Wikimedia Commons.

Some owl stones from 5,500 and 4,750 years ago may be children’s art:

But new research suggests the palm-sized plaques decorated in geometric patterns and with two engraved circles at the top might be the work of children.

Numbering in the thousands and made from slate, the owl-like objects — previously dated the stone objects to be between 5,500 and 4,750 years old — may be “the archaeological trace of playful and learning activities carried out by youngsters,” according to the team of Spanish researchers behind the new study…

They suggest kids would have been able to easily engrave slate using pointed tools made of flint, quartz, or copper, creating ‘body’ patterns that emulate the streaked plumage of owls, and the circles for eyes are unmistakably owl-like, casting an unwavering stare straight at the observer.

The “owliness” of the designs is comparable to the drawing skills of modern school children who depict owls in much the same way. 

Now, About Cooking … 70,000 Years Ago

Neanderthals were not just downing raw hunks of meat 70,000 years ago, as many of us have assumed…

Homo Naledi Used Fire, Say Researchers

Now let’s go waaay back to Homo naledi — first unearthed in 2015 in the Rising Star cave system in South Africa. The remains of the 15 individuals date to between 335,000 and 236,000 years ago. It turns out that they may have lit fires in their caves…

Let’s just say, the Neanderthals have gotten smarter as we have gotten to know them better.

Homo Naledi Used Fire, Say Researchers

Now let’s go waaay back to Homo naledi — first unearthed in 2015 in the Rising Star cave system in South Africa. The remains of the 15 individuals date to between 335,000 and 236,000 years ago. It turns out that they may have lit fires in their caves…

One hitch is that the charred wood, bones, etc. have yet to be dated, to see if they come from the same layers as the Homo naledi fossils. But there are currently no other known groups that could have made the fires.

It’s interesting to note that the basics of human culture seem to undergo much less development than we think. The culture may appear at about the same time as the humans.

You may also wish to read: Why is Neanderthal art considered controversial? It makes sense that whenever humans started to wonder about life, we started to create art that helps us think about it. Science writer Michael Marshall reports that some researchers are accused of banning others from taking samples that would prove a Neanderthal was the artist.

Cross-posted at Mind Matters News.

Complete article at Evolution News.

Many details, even whole chapters, in the early history of humans have probably left no discernable evidence. As brought forth in the article, however, the evidence that has come to light seems to suggest that the distinction between modern and ancient humans is more external than intrinsic.

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At Science Daily: Astronomers report most distant known galaxies, detected and confirmed

An international team of astronomers has discovered the earliest and most distant galaxies confirmed to date using data from the James Webb Space Telescope (JWST). The telescope captured light emitted by these galaxies more than 13.4 billion years ago, which means the galaxies date back to less than 400 million years after the Big Bang, when the universe was only 2% of its current age.

NASA: Webb’s image covers a patch of sky approximately the size of a grain of sand held at arm’s length by someone on the ground – and reveals thousands of galaxies in a tiny sliver of vast universe.

Initial observations from JWST yielded several candidate galaxies at extreme distances, as had earlier observations with the Hubble Space Telescope. Now, four of these targets have been confirmed by obtaining long spectroscopic observations, which not only provide secure measurements of their distances, but also allow astronomers to characterize the physical properties of the galaxies.

Astronomers measure the distance to a galaxy by determining its redshift. Due to the expansion of the universe, distant objects appear to be receding from us and their light is stretched to longer, redder wavelengths by the Doppler effect. Photometric techniques based on images captured through different filters can provide redshift estimates, but definitive measurements require spectroscopy, which separates the light from an object into its component wavelengths.

The new findings focus on four galaxies with redshifts higher than 10. Two galaxies initially observed by Hubble now have confirmed redshifts of 10.38 and 11.58. The two most distant galaxies, both detected in JWST images, have redshifts of 13.20 and 12.63, making them the most distant galaxies confirmed by spectroscopy to date. A redshift of 13.2 corresponds to about 13.5 billion years ago.

“These are well beyond what we could have imagined finding before JWST,” Robertson said. “At redshift 13, the universe is only about 325 million years old.”

According to Robertson, star formation in these early galaxies would have begun about 100 million years earlier than the age at which they were observed, pushing the formation of the earliest stars back to around 225 million years after the Big Bang.

“We are seeing evidence of star formation about as early as we could expect based on our models of galaxy formation,” he said.

Full article at Science Daily.

The JWST’s observations of the earliest galaxies are consistent with estimates of the finite age of the universe of about 13.8 billion years. A key point is that our universe had a beginning. Its finite age limits the probabilistic resources of the universe. It’s beginning from a spacetime singularity brings us to the question: “How can something come from [truly] nothing?”

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A rabbi shares the insights from a new space alien friend about random evolution

This is the rabbi’s account:

I would like to introduce the noble readers of this blog to my new friend named Tuto. Tuto lives in the future and he comes from outer space. He lands on the earth after it has been totally destroyed by a cosmic extinction event. Every living organism has been destroyed. Tuto has a few days to make archaeological digs, gather specimens, and fly back to his home planet.

He discovers that on the earth there are iron ores. Then digging someplace else he uncovers an almost complete Mercedes Benz. Hey, this is amazing, he thinks. So he radios home and asks for an extension for some more time to gather more specimens. After some more digging, he finds some bottles of ink. many different colors. Then in a real strike of luck, he discovers the Mona Lisa.

He gathers all his specimens and returns home. When home a board of scientists makes the following conclusions: We have strong evidence that iron exists on planet earth. We also have strong evidence that Mercedes cars existed on planet earth. We therefore conclude that the metal morphed into the Mercedes by natural process. Everyone cheers “Hurray! Amazing”

Furthermore, therefore, we have strong evidence that colored ink existed in the past on planet earth. And we have strong evidence that there was an amazing work of art named the Mona Lisa. We, therefore, conclude that the ink self-organized to draw the detailed Mona Lisa.

After seeing the latest clip of Prof. Tour about the origins of life I see that this is more or less what these “experts” are claiming.

We have evidence that the “soup” existed (do we really??)We see in the fossil record primitive life forms after time from the above.
2a. We have no mechanism for how the soup could produce these life forms nor we cannot replicate it, nor do we have no clue about how it might have happenedTotally ignore 2a.We have strong evidence that life emerged from the soup via totally natural processes.

Dr. Lee Spetner, in his extremely informative book The Evolution Revolution, drives home the point that if you don’t have a mechanism to explain circumstantial evidence, your evidence simply doesn’t count: (bold text mine)

Consider a hypothetical murder mystery where the victim was found dead on the floor of the library of his home with a gunshot wound in the head. A gun was found on the floor in the same room. The case is brought to court and the prosecuting attorney speaks. “This is an open and shut case, your Honor. Exhibit A is the murder weapon as has been proved by ballistic tests comparing the bullet extracted from the victim with similar bullets fired from the same gun. Furthermore, the gun is owned by the accused and has been shown to have his fingerprints on it.

The circumstantial evidence is overwhelming. I recommend the jury find him guilty of murder.” The defense attorney then rises to speak. “The circumstantial evidence alone is insufficient to warrant a guilty verdict, your Honor. To make the circumstantial evidence meaningful in this case, the prosecution must show how the accused could have carried out the murder. The accused is confined to a wheelchair and we have had expert testimony that he cannot get out of the chair by himself. May I remind the court that within less than a minute after the shot was heard, family members burst into the room to find the victim dead while the accused was in his wheelchair in his room one floor above. Unless the prosecution can give a plausible account of how the accused could have performed the murder and returned to his room a floor above within less than a minute, the circumstantial evidence cannot be used to convict him. I therefore urge the jury to find him innocent.”

The same situation prevails with the attempt to use fossil evidence to support Common Descent. The fossils are circumstantial evidence requiring a theory that can account for how Common Descent could have occurred. Such a theory must account for how the information in living organisms could have been built up in the process of Common Descent. Neither the neo-Darwinian theory, nor any other theory presently known, is able to do this. One must therefore conclude that fossil evidence does not support Common Descent.

Spetner, Lee. The Evolution Revolution: Why Thinking People are Rethinking the Theory of Evolution, The Judaica Press, Inc. Kindle Edition.

But evos will go on and on and on wasting oxygen. They have the ultimate proof that we are all accidents: We are here.

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An ID-friendly sci-fi novel

Here’s an intro to An Emergent Truth (2022) by Jeff Cregg:

On the eve of introducing the world’s most advanced AI quantum computer, its creator, Carlton Redmond, summons his old friend and journalist, Roland Caymus, to his office for a favor. Upon arriving, Caymus discovers Redmond has been murdered, his top programmer is missing, and Redmond’s AI machine has mysteriously malfunctioned.

RODIN is no ordinary computer application. It was designed to be the world’s first conscious machine and can easily out-think the best and brightest human mind in a fraction of a second. It is a creation whose very existence has the potential to change not just the world of technology, but what it means to be human.

Realizing the missing programmer holds the key to solving Redmond’s murder, Caymus sets out on a quest to find him. In doing so, he encounters RODIN’s cogent, authoritative, and thoroughly researched debunking of what Caymus considers to be unassailable science: the Neo-Darwinian Synthesis. And the machine’s hat-tip to Intelligent Design only fuels his confoundment. This leads Caymus to unwittingly embark on a journey of self-discovery that ultimately brings him to a confrontation he has been avoiding his entire life.

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At Evolution News: Your Designed Body: Hearing Is a Symphony of Parts

This excerpt is from  Your Designed Body , the new book by engineer Steve Laufmann and physician Howard Glicksman.

To hear, your body must collect acoustic signals from the environment (pressure waves in the air), channel them to the right locations, convert them into nerve impulses, send them to the brain, and correctly interpret them into experiences like speech and music. And, just as with vision, if any one of those parts works incorrectly, or even just a bit less efficiently, hearing is either severely degraded or impossible. 

The human ear can detect sound when the eardrum is displaced by as little as one-tenth the diameter of a single hydrogen atom. Yet it can also hear and correctly interpret sounds with acoustic pressure levels approaching the loudest sounds produced in nature (~1 kilopascal (kPa)). 

And you can do more than register sounds of varying pitch and volume. From an early age you could tell from the sound of your mom’s voice just how much trouble you were in, and which direction she was calling from (so you knew which way to run). These and other features of human hearing require — and by now this should come as no surprise to readers — not just one or two clever engineering solutions, but a suite of ingenious solutions upon ingenious solutions. 

We have two ears for stereo sound. We can detect differences as small as ten microseconds in the time of arrival of the same sound in each ear. We can also detect subtle differences in loudness between our two ears. Coupled with the fine-grained sound-shaping done by the outer ear, this allows us to tell the direction of a noise and hear in three dimensions. That is, our minds can generate a three-dimensional understanding of what’s going on around us based solely on sounds.

The ear canal is a hollow tube about two centimeters long. It forms an acoustic channel between the pinna and the eardrum. The ear canal may not seem interesting at first glance, but its length plays a crucial role in hearing.

Much like a pipe in a pipe organ, the outer ear consists of a rigid tube open at one end and sealed at the other. Incoming waves bounce off the closed end and create standing waves in the tube (ear canal). This amplifies sounds at or near the tube’s resonant frequencies (constructive interference) and dampens sounds at other frequencies (destructive interference). This increases sensitivity to particular frequencies while diminishing the amplitude of others. Basically, it’s a passive amplifier!

For the human ear, this amplification is strongest at around 3,000 Hz. While this is higher than the central frequencies of human speech, it’s exactly the range where the percussive elements of the consonants in human speech are most prominent, and the consonants are essential for distinguishing the nuances of human speech. 

The net effect is that the outer ear preprocesses incoming sound waves to maximize sensitivity to the natural frequencies of human speech. That is, our ears are fine tuned to hear best at the same frequencies we naturally speak.

For proper hearing…the body needs to amplify the signal between the eardrum and the cochlea. The best way to do this is with a lever system. Since the malleus is attached to the eardrum and the stapes to the cochlea, this leaves the middle bone, the incus, to serve as a lever. But not just any lever will do. Only a very specific configuration of that lever will properly translate the pressure waves in the air into corresponding pressure waves in the fluid. 

Impedance Transformation

The middle ear must provide a mechanical advantage to accurately bridge the different densities of air and fluid, and do so with minimal loss of either loudness or tonality. Mechanical engineers call this impedance transformation, a tricky problem to overcome in even a simple system.

The ear’s solution involves the precise shapes and configurations of all three bones of the middle ear. The malleus has a larger surface area than the stapes. Also, the two arms of the incus’s lever have different lengths. Each provides mechanical advantage. Pressure waves hitting the large area of the eardrum are concentrated into the smaller area of the stirrup so that the force of the vibrating stirrup is nearly fifteen times greater than that of the eardrum. This makes it possible to hear even the faintest sounds.

The three bones of the middle ear, and the ways they’re held in place by various tendons, act as a four-bar mechanism. The specific configuration in the ear is called a double-crank rocker. Engineers use four-bar mechanisms to fine tune mechanical relationships in systems where exacting precision and sophistication are needed, as they most certainly are in the middle ear. To achieve the necessary mechanical advantage, the shapes of the parts and the positions of the several hinge points must be precisely tuned, with little room for error. 

So, hearing hinges on the precise configuration of these three tiny bones, with their very specific shapes which are essential to their purposes. Nowhere do we see this more clearly than in the bones of the middle ear.

See Evolution News for the complete article.

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At PopSci.com: With one snapshot, Apollo 17 transformed our vision of Earth forever

Fifty years ago, on December 7, 1972, NASA’s Saturn V rocket lifted off from Cape Canaveral, Florida, carrying the last of the Apollo-era astronauts to walk on the lunar surface. 

Apollo 17—the sixth and final mission of NASA’s history-making initiative to land human explorers on the moon—was a scientific breakthrough: During their 75-hour lunar stay, crewmembers Eugene A. Cernan, Ronald E. Evans, and Harrison H. Schmitt collected rare types of lunar rock and samples of “orange soil,” or regolith, that once formed in a lunar volcanic eruption, indicating that the moon’s past eras of geologic activity lasted longer than previously thought—which recent research has confirmed. But their most influential observation quickly became a milestone in our culture: With the help of one iconic photo, the mission vastly changed the way humans view our space environment. 

About five hours into the crew’s moon-bound journey, the shrinking sphere of our world drew someone’s gaze (it’s still up in the air which member of the three-person crew was responsible) to the window. Upon seeing the beautiful, brightly illuminated Earth, a particularly astute astronaut grabbed hold of the onboard Hasselblad film camera and began snapping. Among those images was the one now known as the Blue Marble shot, the first photograph ever taken of the planet in its entirety. 

The Blue Marble photo, showing Earth as Apollo 17 astronauts saw it. NASA

The once-in-a-lifetime shot showcases the African continent, which is almost completely visible and backed by the swirling blue ocean. Above it, chaotic, wind-swept clouds dot our atmosphere. This was Earth as humanity had never seen it before, richly detailed and alight with life.

Easily one of the most recognizable space images ever made, Blue Marble is the only picture of the entire, round Earth taken by human hands to date. It and those first few stunning images of our planet went on to inform how official space agency photographers arrange shots of Earth and other celestial bodies, and influenced the way we take and share images of space today. 

Travis Rector, an astronomer at the University of Alaska Anchorage and an astrophotographer, someone who takes photos of space phenomena in their free time, believes that all astronomers of his generation were especially inspired by the beauty of early space-age photos. “They were our first high-quality views of exotic worlds like Mars and the moon, turning these dots in the sky into real worlds we could imagine visiting in person,” he says. “The Blue Marble photo is especially important because not only does it show the spectacular beauty of our world but also its limits.” 

Those limits are all the world’s resources, like the food, air, and water that sustain us, he says. 

Apollo 17’s famous photo marked the end of an era in human spaceflight. It ended up being a hallmark in the history of space photography.

Full article at Popular Science.

This image of Earth from space has become so familiar that I’ve had to remind my astronomy students that for the vast part of human history, no one had ever seen Earth from this perspective. Today, we can realize how geographically limited our planet really is–it’s the only place in the solar system that could support our civilization. We can be thankful for how well our needs are met by Earth’s physical design and resources.

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At Quora: Is it possible to prove beyond a reasonable doubt that intelligence was required to create life?

Josh Anderson writes:

Yes, it is. Here’s the question you should ask yourself: Is symbolic code something that blind, intelligence-free physical processes could create and use? Or is mind alone up to the task?

The legendary John Von Neumann did important work on self-replicating systems. A towering giant in the history of mathematics and pioneer in computer science, he was interested in describing machine-like systems that could build faithful copies of themselves.

Von Neumann soon recognized that it would require both hardware and software. Such a system had to work from a symbolic representation of itself. That is, it must have a kind of encoded picture of itself in some kind of memory.

Crucially, this abstract picture had to include a precise description of the very mechanisms needed to read and execute the code. Makes sense, right? To copy itself it has to have a blueprint to follow. And this blueprint has to include instructions for building the systems needed to decode and implement the code.

Here’s the remarkable thing: Life is a Von Neumann Replicator. Von Neumann was unwittingly describing the DNA based genetic system at the heart of life. And yet, he was doing so years before we knew about these systems.

The implications of this are profound. Think about how remarkable this is. It’s like having the blueprints and operating system for a computer stored on a drive in digital code that can only be read by the device itself. It’s the ultimate chicken and egg scenario.

How might something like this have come about? For a system to contain a symbolic representation of itself the actualization of precise mapping between two realms, the physical realm and an abstract symbolic realm.

In view here is a kind of translation, mechanisms that can move between encoded descriptions and material things being described. This requires a system of established correlations between stuff out here and information instantiated in a domain of symbols.

Here’s the crucial question: Is this something that can be achieved by chance, physical laws, or intelligence-free material processes? The answer is decidedly NO. What’s physical cannot work out the non-physical. Only a mind can create a true code. Only a mind can conceive of and manage abstract, symbolic realities. A symbolic system has to be invented. It cannot come about in any other way.

If you think something like this – mutually interdependent physical hardware and encoded software – can arise through unguided, foresight-less material forces acting over time, think again. If I were to ask you to think of something, anything that absolutely requires intelligence to bring about, you’d be hard pressed to think of a better example. It’s not just that no one understands how it could be done, it’s that we have every reason to believe that it is impossible in principle. No intelligence-free material processes could ever give you something like this.

But wait, how can we be so sure this feature of life was not forged by evolution, built up incrementally by the unseen hand of natural selection? What’s to say this is beyond the ability of evolution to create?

The question answers itself. In order for evolution to take place you have to have a self-replicating system in place. You don’t evolve to the kind of thing we’ve been describing. That is, necessarily, where you begin.

The DNA and the dizzyingly complex molecular machinery that it both uses and describes did not evolve into existence. This much is clear. Any suggestion that it did is not based on a scintilla of empirical evidence or any credible account of how it could have come about in this way.

The conclusion is clear: The unmistakable signature of mind is literally in every cell of every living thing on earth.

Watch a few seconds of this to remind yourself of the kind of mind-bending sophistication in view here:

Quora

Note that John von Neumann mathematically showed that the information content of the simplest self-replicating machine is about 1500 bits of information. This is a vast amount of information, since information bits are counted on a logarithmic scale, and it cannot be explained by any natural process, since it far exceeds the information content of the physical (non-living) universe. Therefore, since self-replicating organisms obviously exist on Earth, their origin must come from the only known source of this level of information – an intelligent mind of capability far beyond our mental ability – consistent with the biblical view of God.

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At Science Daily: Hearing is believing: Sounds can alter our visual perception

Audio cues can not only help us to recognize objects more quickly but can even alter our visual perception. That is, pair birdsong with a bird and we see a bird — but replace that birdsong with a squirrel’s chatter, and we’re not quite so sure what we’re looking at.

Shutterstock.com

“Your brain spends a significant amount of energy to process the sensory information in the world and to give you that feeling of a full and seamless perception,” said lead author Jamal R. Williams (University of California, San Diego) in an interview. “One way that it does this is by making inferences about what sorts of information should be expected.”

Although these “informed guesses” can help us to process information more quickly, they can also lead us astray when what we’re hearing doesn’t match up with what we expect to see.”

“Even when people are confident in their perception, sounds reliably altered them away from the true visual features that were shown.”

“When sounds are related to pertinent visual features, those visual features are prioritized and processed more quickly compared to when sounds are unrelated to the visual features. So, if you heard the sound of a birdsong, anything bird-like is given prioritized access to visual perception,” Williams explained. “We found that this prioritization is not purely facilitatory and that your perception of the visual object is actually more bird-like than if you had heard the sound of an airplane flying overhead.”

Taken together, these findings suggest that sounds alter visual perception only when audio and visual input occur at the same time, the researchers concluded.

“This process of recognizing objects in the world feels effortless and fast, but in reality it’s a very computationally intensive process,” Williams said. “To alleviate some of this burden, your brain is going to evaluate information from other senses.” Williams and colleagues would like to build on these findings by exploring how sounds may influence our ability to locate objects, how visual input may influence our perception of sounds, and whether audiovisual integration is an innate or learned process.

Complete article at Science Daily.

Researchers acknowledge, “This process of recognizing objects in the world feels effortless and fast, but in reality it’s a very computationally intensive process.” So many seemingly simple aspects of our existence are found to exhibit layered depth of complexity. What is evolution’s explanation for the these marvels of functional complexity? Can undirected processes bring about the successful, “computationally intensive process” of object recognition?

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Origenes: “The Emergence of Emergentism: A Play for Two Actors”

The stage is in darkness, with sombre mood music, then light rises . . .

Origenes, 226 in the Pregnancy thread:

<

A: “I feel completely desperate. There is no way we will ever be able to explain life and consciousness.”
B: “I feel the exact same way. The main issue is that we have nothing to work with. All we have is mindless particles in the void obeying mindless regularities. Starting from that, how can we possibly explain life, not to mention personhood, freedom, and rationality? There is simply no way forward.”
A: “Exactly right. Sometimes I feel like such a loser. The other day I heard that current science cannot even explain liquidity.”
B: “What did you just say?”

**POOF**>>

THE END.

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