Artificial intelligence and evolution
In our information age, the development of computerized technology has been astonishing. Many believe ‘the sky is the limit’, especially in the field of artificial intelligence (AI). Not surprisingly, it has been the subject of several films.
In the Terminator series, defence systems of the future US are handled by Skynet, a swarm intelligence. This develops consciousness and decides to wipe out all humanity with nuclear strikes. In a war against humanity, the terminators are machines near perfection.
In Ex Machina, an engineer working for a (fictional) world-renowned search engine is invited to an isolated research facility which is also the home of the company’s founder. This founder has secretly developed a robot which seems conscious—feelings and all. The engineer gets the task of evaluating the artificial intelligence (AI), but the opposite happens.
In Transcendence, a brilliant AI researcher becomes terminally ill but is ‘saved’ when his consciousness is uploaded into a quantum computer. Without physical limits, this brilliant mind ends up producing a physical copy of his late self, which is really just an extension of the AI.
The list could go on. The public mind is also moulded by news headlines about ‘how computers beat humans’. It started when IBM’s Deep Blue computer beat world chess champion Garry Kasparov in a 1997 match. More recently, in 2017, Google’s AI AlphaGo defeated the world No. 1, Ke Jie, 3–0 at Go, a complex ancient Chinese board game. The New York Times started their article by declaring: “It’s all over for humanity”.1
So, is it only a matter of time before the machines take over?
Nothing to worry about
Computers—and robots—are composed of physical components called the hardware. However, this is not enough. Without something to give instructions—the software (also called a ‘program’)—computers won’t operate and robots won’t move.
Imagine you have a surveillance camera in the doorway of your home, connected to a computer containing ID information about you and your family. When you approach, the camera identifies you before letting you in with a personal greeting. In addition to all the hardware, it requires purposefully- created software for the actual work of identifying the people and letting them in.
Software does what it is made for—what it is instructed to do—and only that. Even where it is able to ‘learn’, that is only because it has had that capacity programmed into it. The software will blindly follow the algorithm (a sequence of instructions for carrying out a task) given to it. This defines how the program would (in our example) calculate the identifying information and how to compare it with your stored profile. Note that software and algorithms are human intelligence conveyed to a computer.
We live in an imperfect world, and a large part of software code deals with various types of error situations. In our example, a mistake in programming could open your door to unknown persons—or not open it for you! And even if it all works right now, will it still do so in a year’s time? Ten years from now? As in the biological world, experience and observation affirm decay. Exposing the surveillance system to changing weather or lightning can cause breakdown or malfunction. If you need to replace your camera in the future, will the software still work with the new one? And so on.
Software is comprehensively tested to catch errors and ensure proper operation. Still, the news unfortunately often reveals problems with different information systems. NASA lost a space probe in 1999 due to an information system failure, and entire airports have been shut down. The Internet abounds with similar examples.
Artificial Intelligence (AI)
Artificial Intelligence (or Machine Intelligence) is a term for synthetic ‘intelligence’. This includes understanding human speech, playing strategic games (such as chess and GO) against human experts, self-driving cars, and interpreting complex information from videos or photos.
This often includes what is known as machine learning, the ability to learn, e.g. from mistakes, to perform a task better. E.g. Google’s AI AlphaZero learned chess, go, and shogi (Japanese chess), starting from scratch. That means nothing more than the rules of the games and playing games with itself. Yet in a few days, it supposedly surpassed AlphaGo and leading computer ‘engines’ of the other games.
So some researchers consider the emergence in machines of super intelligence, above that of humans, to be only a matter of time. However, no matter how advanced the industry becomes, it still boils down to programming by human intelligence. Of course, a garbage-sorting robot, e.g., can learn to sort and recognize garbage better. But only if it is pre-programmed to learn this. A robot doesn’t dream about retirement on a tropical island—let alone world conquest!
What’s behind the idea of machine coups? It’s not just the idea of higher intelligence emerging. It also includes the idea that the machines will become aware, i.e. conscious, of what they are doing and why. That is, given enough complex software with the ability to refine itself through machine learning, eventually ‘consciousness’ will emerge. Machine consciousness is a field of technology research to try to find out what is required to achieve consciousness artificially.2
Driving it all: naturalism
Underlying all this is the belief that humans (together with our consciousness) came about from natural processes—by themselves, with no guiding intelligence. This was by small gradual changes from some primitive creature which allegedly came from a primordial soup billions of years ago.
So everything, including consciousness, must be able to be reduced to the material—atoms in various arrangements and motions. That is, there is ultimately nothing ‘special’ about intelligence, consciousness. So why shouldn’t a similar, or even a superior arrangement of matter/energy emerge within machines, especially as they learn to get better at tasks?
Similarly, many also believe that with enough advanced technology, one could perfectly duplicate a person, along with their consciousness, memories, experiences etc. All it would need is all the atoms in the right order. The Terasem organization, dedicated to the development of AI, states: “Nobody dies so long as enough information about them is preserved.” By developing the technology to one day ‘upload’ our consciousness, declares this organization, “We are making God.”3
It’s easy to see the connection to the ‘promise’ given in Eden’s garden: “You will be like God” (Genesis 3:5). All this is only one demonstration of the truth of anticreationist philosopher Michael Ruse’s affirmation: “Evolution is a religion. This was true of evolution in the beginning, and it is true of evolution still today.”4
Information science, software engineering and AI research are a part of the God-given dominion mandate we have over the creation. Any alleviation of the effects of the Fall through them is a good and God-honouring thing, but not the exaltation of man and the worship of the objects of our creation, in this case ‘AI Almighty’.
Microbic mastery over microbytes
In 2012, Stanford University researchers reported they had modelled the ‘simplest’ bacterium, Mycoplasma genitalium, on computers. Using a cluster of 128 computers for the simulation, it took almost ten hours to model a single cell division!5 The bacterium (as an obligate parasite, already a degenerate version of its God-designed precursor) does everything faster, better, and in conditions where computers couldn’t operate. It even makes copies of itself that can make copies of themselves. Human attempts to imitate even this ‘simplest’ creature are crawling light-years behind the Master Programmer’s original.
When we turn to consider a human, the challenges of similar computer modelling expand by orders of magnitude—not to mention the idea that we could even remotely model, let alone create, true consciousness!
Computers are of course good at handling and analyzing large amounts of data, in relatively simple tasks requiring precision and repetition, and their development is ongoing. However, this requires a huge amount of intelligent design. As a software engineer, I find biological systems to be much more ingenious and complex than the most sophisticated human-fiddled software. All creatures are programmed with the stunningly ingenious DNA language,6 with more and more baffling brilliance discovered as it is studied.
Even ‘simple’ life is beyond the reach of chance
Numerous engineers have used their ingenious minds and worked together for years in coordinated, purposeful ways to mimic remotely human-like ‘intelligence’. What a contrast with the evolutionary narrative, relying on an aimless, blind process of error-inducing mutations plus natural selection. But it asserts that this resulted in humans with consciousness and intelligence.
In reality, natural selection requires reproduction, so the ‘fittest’ can pass on the ‘fit’ features. But even the simplest self-reproducing creature requires hundreds of proteins. But the chance of forming even one of these proteins by randomly combining its building blocks is incredibly tiny. Astrophysicist Sir Fred Hoyle famously compared it to the chance of a solar system full of blind people shuffling Rubik’s cubes, all solving it at the same time.7 It requires an unimaginably strong, blind faith to maintain the evolutionary claim that a blind, purposeless process was the cause of humans, the human brain, intelligence and consciousness.
References and notes
- Mozur, P., Google’s A.I. program rattles Chinese Go master as it wins match, New York Times; nytimes.com, 25 May 2017. Return to text.
- Aleksander, Igor: Artificial neuro-consciousness: An update, IWANN, 1995. Return to text.
- Showalter, B., Artificial intelligence, transhumanism and the church: How should Christians respond? christianpost.com, 27 Jan 2018. See also creation.com/transhumanism. Return to text.
- Ruse, M., How evolution became a religion: creationists correct? National Post, pp. B1,B3,B7, 13 May 2000; creation.com/ruse. Return to text.
- Karr, J.R. et al., A whole-cell computational model predicts phenotype from genotype, Cell 150(2):389–401, 12 Jul 2012. See also Cellular complexity “nearly unbelievable”, Focus, Creation 35(1):11, 2013; creation.com/focus-351#128-computers. Return to text.
- Statham, D., The remarkable language of DNA, Creation 36(2):52–55, 2015; creation.com/dna-remarkable-language. Return to text.
- Hoyle, F., The big bang in astronomy, New Scientist 92(1280):527, 1981, quoted in Batten, D., Cheating with chance, Creation 17(2):14–15; creation.com/cheating-with-chance. Return to text.