Today’s fare is an article I was invited to submit to Forbes.com’s AI report, and was mysteriously (and very annoyingly) yanked out at the last moment. Their loss.
Enjoy.
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It will probably come as a surprise to those who are not well acquainted with the life and work of Alan Turing that in addition to his renowned pioneering work in computer science and mathematics, he also helped to lay the groundwork in the field of mathematical biology(1). 
Why would a renowned mathematician and computer scientist find himself drawn to the biosciences?
Interestingly, it appears that Turing’s fascination with this sub-discipline of biology most probably stemmed from the same source as the one that inspired his better known research: at that time all of these fields of knowledge were in a state of flux and development, and all posed challenging fundamental questions. Furthermore, in each of the three disciplines that engaged his interest, the matters to which he applied his uniquely creative vision were directly connected to central questions underlying these disciplines, and indeed to deeper and broader philosophical questions into the nature of humanity, intelligence and the role played by evolution in shaping who we are and how we shape our world.
Central to Turing’s biological work was his interest in mechanisms that shape the development of form and pattern in autonomous biological systems, and which underlie the patterns we see in nature (2), from animal coat markings to leaf arrangement patterns on plant stems (phyllotaxis). This topic of research, which he named “morphogenesis,” (3) had not been previously studied with modeling tools. This was a knowledge gap that beckoned Turing; particularly as such methods of research came naturally to him.
In addition to the diverse reasons that attracted him to the field of pattern formation, a major ulterior motive for his research had to do with a contentious subject which, astonishingly, is still highly controversial in some countries to this day. In studying pattern formation he was seeking to help invalidate the “argument from design” (4) concept, which we know today as the hypothesis of “Intelligent Design.“
Turing was intent on demonstrating that the laws of physics are sufficient to explain our observations in the natural world; or in other words, that our findings do not need an omnipotent creator to explain them. It is ironic that Turing, whose work played a central role in laying the groundwork for the creation of Artificial Intelligence (AI), took a clear stance against creationism. This is testament to his acceptance of scientific evidence and rigorous research over weak analogy.
Unfortunately, those who did not and will not accept Darwinian natural selection as the mechanism of evolution will not see anything compelling in Turing’s work on morphogenesis. To those individuals, the development of AI can be taken as “proof,” or a convincing analogy, of the necessity and presence of a creator, the argument being that the Creator created humanity, and humanity creates AI.
However, what the supporters of intelligent design do not acknowledge is that natural selection is itself precisely the cause underlying the development of both humanity and its AI progeny. Just as natural selection resulted in the phenomena that Turing sought to model in his work on morphogenesis (which brings about the propagation of successful traits through the development of biological form and pattern), it is also the driver for the development of intelligence. Itself generated via internalized neuronal selection mechanisms (5, 6), intelligence allows organisms to adapt to their environment continually during life.
Intelligence is the ultimate tool, the development of which allows organisms to survive; it enables them to learn, respond to their environment and adapt their behavior within their own lifetime. It is the fruit of the natural process that brings about successive development over time in organisms faced with scarcity of resources. Moreover, it now allows humans to defy generational selection and develop intelligences external to our own, making use of computational techniques, including some which utilize evolutionary mechanisms (7).
The eventual development of true AI will be a landmark in many ways, notably in that these intelligences will have the ability to alter their own circuits (their version of neurons), immediately and at will. While the human body is capable of some degree of non-developmental neuronal plasticity, this takes place slowly and control of the process is limited to indirect mechanisms (such as varied forms of learning or stimulation). In contrast, the high plasticity and directly controlled design and structure of AI software and hardware will render them well suited to altering themselves and hence to developing improved subsequent AI generations.
In addition to a jump in the degree of plasticity and its control, AIs will constitute a further step forward with regard to the speed at which beneficial information can be shared. In contrast to the exceedingly slow rate at which advantageous evolutionary adaptations were spread through the populations observed by Darwin (over several generations), the rapidly increasing rates of communication in current society result in successful “adaptations” (which we call science and technology) being distributed at ever-increasing speeds. This is, of course, the principal reason why information sharing is beneficial for humans – it allows us to better adapt to reality and harness the environment to our advantage. It seems reasonable to predict that ultimately the sharing of information in AI will be practically instantaneous.
It is difficult to speculate what a combination of such rapid communication and high plasticity combined with ever-increasing processing speeds will be like. The point at which self-improving AIs emerge has been termed a technological singularity (8).
Thus, in summary: evolution begets intelligence (via evolutionary neuronal selection mechanisms); human intelligence begets artificial intelligence (using, among others, evolutionary computation methods), which at increasing cycle speeds, leads to a technological singularity – a further big step up the evolutionary ladder.
Sadly, being considerably ahead of his time and living in an environment that castigated his lifestyle and drove him from his research, meant that Turing did not live to see the full extent of his work’s influence. While he did not survive to an age in which AIs became prevalent, he did fulfill his ambition by taking part in the defeat of argument from design in the scientific community, and witnessed Darwinian natural selection becoming widely accepted. The breadth of his vision, the insight he displayed, and his groundbreaking research clearly place Turing on an equal footing with the most celebrated scientists of the previous century.
