**5.4 Creating novel DNA algorithmically**

The way we acquire knowledge is iterative and nonlinear—we conjecture and put our conjectures on trial, that is, put them to severe critical tests (refutations). As the trial progresses, we edit, discard, refine, and add to our conjectures in a pseudorandom manner controlled by criticism, driven by instinct, hunches, inspiration, etc. Conjectures and refutations in scientific research are deemed selfand community-driven adversarial processes. We connect the dots. At every step of linking the dots, we consult the axioms (conjectures) and the rules for deriving conclusions (theorems) to ensure that we are within the axiomatic system we have put on trial. This means that the process leads us to understand the Universe solely based on our chosen beliefs (axiomatic system).

*As we learn from our mistakes our knowledge grows, even though we may never know—that is, know for certain. Since our knowledge can grow, there can be no reason here for despair of reason. And since we can never know for certain, there can be no authority here for any claim to authority, for conceit over our knowledge, or for smugness. [1, Preface]*

As far as we can tell, creating an axiomatic system is a nonmathematical and a highly intelligent act. Developing a sequence of theorems with a specific nontrivial goal in mind (developing algorithms) is also a highly intelligent act. However, executing an algorithm, once developed, can be mechanized and does not require intelligence, in fact, none at all. If the most useful aspect of intelligence

<sup>6</sup> A controversial experiment to this effect seems to have been successfully conducted by He Jiankui who recently presented his work at the Second International Summit on Human Genome Editing in Hong Kong, November 27–29, 2018, http://www.nationalacademies.org/gene-editing/2nd\_summit/index.htm [60, 61].

is algorithmic, then it must be mechanizable and converted into computation. We believe the DNA is a book of knowledge about the birth and death of life. In principle, it is in machine-readable form. AI and quantum computing are the most powerful tools we presently have to decipher it. When AI drives our lives, it is the algorithm that really drives us.

Some recent bold experiments using CRISPR gene editing have provided glimpses of DNA editing as a new source of creating a variety of biomatter and life forms. For example, experiments are in progress for producing meat (beef, pork, poultry, and sea food) without killing animals by growing meat in the laboratory from cultured stem cells by multiplying them dramatically and allowing them to differentiate into primitive fibers that then bulk up to form muscle tissue. This would substantially reduce environmental costs of meat production and eliminate much of the cruel and unethical treatment of animals [62]. Another example is producing offsprings from same-sex mice parents, again using stem cells and CRISPR gene editing technology [63].

In another development, till recently it was believed that mitochondrion DNA (mtDNA) in nearly all mammals (including humans) is inherited exclusively from the mother. However, recently, Luo et al. [64] have uncovered multiple instances of biparental inheritance of mtDNA "spanning three unrelated multiple generation families, a result confirmed by independent sequencing across multiple unrelated laboratories with different methodologies. Surprisingly, this pattern of inheritance appears to be determined in an autosomal dominant like manner." Given that the mitochondrion is an energy-producing organelle in the cell, this discovery will have profound implications in synthetic biology and in the design of new drugs.

Once humans master the art of designing DNA for self-replicating, multicellular organisms (we already know how to design cells not found in Nature and edit DNA), they will create living species of their own design. We also anticipate that when AI machines master the art of learning from mistakes (i.e., the art of making conjectures and refuting them in a spiraling process toward better knowledge, a possibility that mathematically exists), they would have taught themselves how to handily beat humans in intelligent activities and thereby break the human monopoly on intelligence. The seeds of this were sown when the AI program called AlphaGo decisively defeated the world's greatest Go players in 2016 [65, 66]. AlphaGo has achieved what many scientific researchers had dreamed of achieving. It means that a machine can teach itself in a tiny fraction of the time it takes humans to explore *ab initio* any axiomatic system. The last bastion of human supremacy over all other creatures on Earth in the form of intelligence has been cracked by AI machines. This is the world the millennials have stepped into. We have no idea how AI machines may organize themselves into networks and network with humans and *vice versa*. Will the future be written and created by humanoids with humans finding themselves relegated to footnotes and appendices once biotechnology and AI integrate? (See, e.g., [14].)

So, what comes after *Homo sapiens*? Given the accelerating march of AI and computing, everything points to the dominating power of algorithms created and executed by quantum computers. It is a matter of understanding how to create novel DNA sequences and creating an environment for it to thrive. It is about writing lengthy books of life using natural and artificial nucleotides. With AI-embedded quantum computers capable of surpassing human intelligence, and the smartest among them developing Godlike abilities, the raw material they will be hunting for is massive amounts of data and mining that data for usable information for the welfare of one or more new species to whom the *Homo sapiens* will be ancestors.

**31**

in [68].

*Synthetic Biology, Artificial Intelligence, and Quantum Computing*

7

tailless bodies to our habits and temperament."8

either evolve or be artificially created.

<sup>7</sup> The term *Homo sapiens* was coined by Carl Linnaeus in 1758.

The stage appears set for some remarkable advances in synthetic biology including artificial speciation as an alternative to the natural evolution of species. *Homo sapiens* are now poised to change the evolutionary destiny of life forms (including their own) they choose to target and even design-to-order new life forms. The ramifications are far and wide (see, e.g., [67]). Creating species that can thrive on other planets, colonizing the Moon with single-celled life, etc. are no longer science

Records of our civilization date back approximately 6000 years. Since *Homo sapiens* are still evolving, speciation may yet produce superior creatures with new attributes that can give them superior knowledge of the Universe and its origin. After all, it is speciation that made the *Homo sapiens* overwhelmingly superior in intellect from the great apes and our cousins, the chimpanzees with whom we share 96% of our DNA sequence. "Darwin wasn't just provocative in saying that we descend from the apes—he didn't go far enough. We are apes in every way, from our long arms and

span of few centuries, at the knee of the exponential curve that breathed energetic intellectual life into our neural and socioeconomic networks, we have attained such remarkable feats as formalizing and mechanizing axiomatic systems, discovering deep secrets of the Universe, partially mechanizing brain-mind activities, developing technologies that augment, supplement, and amplify our comparatively puny brain and brawn capacities. Within the past century or so, we have fathomed the power and limitations of rational thought and binary arithmetic to express it in, mechanized arithmetical calculations to unimaginable heights, and used this mechanization to develop robotics, 3D precision manufacturing, biotechnology, AI, QC, cloud computing, etc. These developments are now rapidly networking, the scale of which is such that we now see the combined effects of phase transition of graph theory in the Internet of Things (IoT) (creation and destruction of interlinked man-machine-idea components), of the logistic map in the rapidly changing socioeconomic scenarios that have increasingly made predicting the future at all levels of aggregating individuals a game of dice. The relationship between the logistic map and the Mandelbrot set implies that the future of *Homo sapiens* will indeed be so complex that a new species capable of handling that level of complexity must

The raw physical limitations of the *Homo sapiens*' brain-mind system is distressingly visible in its waning ability to earn a living. Barring exceptional *Homo sapiens*,

the Internet and not by our brains. The World Wide Web (WWW) has changed the way we think, what we think about, and how we communicate our thoughts. The millennials' cognitive abilities are very different from those they were born with and weaned on before the Internet invaded their lives. They are shaped not just by what they read but by how they read. Not only has their lifestyle changed but also has their thought style. All the work of the mind—deep thinking, exhaustive reading, deep analysis, introspection, etc.—is now delegated to AI machines. Humans have thus relinquished their right to control their individual lives and direct their souls (maybe deep inside they already know there is no soul!). If machines can outdo humans so easily without a soul, then perhaps the soul is holding humans back from

<sup>8</sup> A quote from Frans de Waal, a primate scientist at Emory University in Atlanta, Georgia, as it appeared

our search for meaning in life is now propelled by search engines roaming

have been around for about 300,000 years [17, 18].

Yet, at an intellectual level, within a

*DOI: http://dx.doi.org/10.5772/intechopen.83434*

**6. Conclusions**

fiction fantasies.

We, the *Homo sapiens*,
