Cyberbiology


     In the contemporary world, the complexity of sociotechnological systems grows at a dizzying pace. From germline genome editing to artificial intelligence to bioprinting, we are experiencing a present that once only existed in science fiction. Some futurists, perhaps most notably Raymond Kurzweil, have proposed that this increasing complexity reflects a larger exponential trend that may soon result in radical changes to our world.1 This phenomenon is known as the technological singularity. Kurzweil states, “I set the date for the Singularity – representing a profound and disruptive transformation in human capability – as 2045. The nonbiological intelligence created in that year will be one billion times more powerful than all human intelligence today.” (The Singularity is Near, pg. 122) Although this prediction may initially sound outrageous, Kurzweil has shown a remarkable ability to accurately envision future events as evidenced by his numerous successful predictions; for instance, former world chess champion Garry Kasparov losing his games against IBM’s Deep Blue chess computer in 1997. In the scenario of a technological Singularity, humans and technology could merge, leading to the profound transformation mentioned by Kurzweil. This transformative potential challenges assumptions regarding human physiology and planetary ecology. The barrier blurs between human and computer, mandrill and machine, coral reef and coral simulation. This cyborgization innervates biological matter with technological matter and vice versa, dissolving their distinction. The implications of the Singularity and the related transhumanist movement have present relevance as well. They reveal that current boundaries between flesh and innovation represent arbitrary cutoffs brought about by lesser physical integration. According to this framework, I propose that biology and technology are two names for one general phenomenon: cyberbiology.

     Throughout evolutionary history, cyberbiology has faced challenges and devised solutions. Long before the first handheld tool was invented, kinetic forces modified self-replicating patterns to develop adaptations like aerobic respiration, nervous systems, and teeth. Analogous to the rationally designed tool, a process of trial and error allowed optimization for given environments and situations. The “brain” conducting this process was an ecosystem. Rather than simulating tool design inside an individual’s cranium, these adaptations were developed by the multitude of components comprising savannahs, oceans, and jungles. Rather than evolving as abstract representations in a meshwork of neurons and glia, these tools evolved from the interplay among such constituents as herbivorous Indricotherium, carnivorous Lycopsis, ferns, lakes, and climatological factors. Using these methods, the biosphere made technologies in the form of adaptations.

     As the neocortex expanded, mammalian brains attained the ability to represent further layers of abstraction. Executive cognition strengthened, enabling planning and goal-directed behavior. Neural tissue simulated more and more complex scenarios, playing out potentialities in bioelectric code. Remarkably, the dancing molecules had developed an accelerated mode of innovation. The ecosystem was no longer the smartest entity around. Individual brains could now emulate the evolutionary process. Consider early fire use by Homo erectus.2 These hominids processed sensory data into neural representations, then accrued memories along with associated evaluations by reward learning. In an extension of the affordance competition hypothesis,3 I propose that Homo erectus and their descendants also generated “mutant” scenarios based on their recollections. For instance, they may have seen predators avoiding flames in the past. They may have observed that fire does not generally spread over rocks. As mentioned, these concepts have neural representations in brains. As the memories were replayed, neural activity cascading in waves through those hominid cerebra, the representations mutated via both noise and spike pattern recombination. In this way, the hominids may have generated new variations on preexisting data. Using the learned outcomes associated with those preexisting data, these variations would have acted as predictions. The Homo erectus may have predicted that a controlled burn in the middle of some rocks could protect them from predators. Although this example is hypothetical, it analyzes cognition from an alternative angle and so demonstrates an important principle. Cognition performs the same task as evolution, albeit much more quickly.

     In recent times, cyberbiology has further improved its problem solving abilities. The human species has developed into a global social network, with groups and organizations taking on similar roles to brains. For instance, an oncology research institute behaves, in many ways, as a single entity with the goal of developing cancer treatments. This does not mean that humans only function as hiveminds. Individuals often still contribute uniquely. These contributions are a larger-scale analogue of mutating neural patterns. Numerous creative individuals develop innovations to approach challenges, these innovations compete and a few translate into societal “motor outputs.” Some examples of societal motor outputs include biomedical technologies, software applications, policy shifts, construction projects, and widespread ideological shifts. Cyberbiology utilizes social organizations to empower cognition in a similar way to how cognition empowers evolution.

     By now, cyberbiology has constructed additional modules to augment its intelligence. Computers spend milliseconds performing data analytic tasks that would take humans thousands of years. For instance, deciphering the three billion base pairs in the human genome requires computational assistance. Computational methods also vastly improve precision in engineering, allowing growth in robotics, aerospace, industrial chemistry, and countless other areas. The internet allows global sharing of human knowledge and clever algorithmic tools. The network increases in connectivity while installing backups and failsafes, seething with complexity. All the while, the noosphere’s constituents compete and replicate across scales. Patterns arise as atoms fluctuate in a symphony of organized chaos, ideas germinate as those patterns propagate and undergo selection in neurons, societal motor behaviors occur as those ideas proliferate and mutate among minds and microprocessors. The dance of molecules has reached a crescendo, but this is only the beginning of the sonata.     

     Cyberbiology approaches an event horizon, the Singularity. This represents another level of intense evolutionary acceleration, similar to the leap from ecological evolution to cognitive evolution. In a post-singularity world, biological consciousness could transition to alternative substrates through mind uploading, nanorobots might enable seemingly magical manipulation of matter, and the cosmos could eventually saturate with intelligence. This process could lead to a form of “technological nirvana.” The Singularity may occur via artificial superintelligence or through a synthesis of human and non-biological intelligence.4 Either way, intelligence could rapidly design more powerful intelligence, which then could continue to design still more powerful intelligence. In this way, the Singularity may act as a new layer of metacognition.  

     Synthetic biology illustrates the indistinguishability of technology and biology. While all biology and technology fits under the umbrella of cyberbiology, synthetic biology provides a particularly poignant example of how the traditional boundaries dissolve. Synthetic biology involves taking an engineering approach to biology, constructing new biological systems using biological parts like promoters, plasmid backbones, thermosensitive RNA step-loop structures,5 and protein domains. These parts are arranged into machinery that performs useful tasks. Probiotic E. coli have been engineered to constitutively produce signaling molecules that downregulate virulence in Vibrio cholera.6 When mice were fed with these E. coli cells, their survival of cholera infection increased. The modular domains of polyketide synthase complexes have been rearranged to help discover and synthesize new polyketide antimicrobials.6 Transgenic mosquitos that selectively express a flight-disabling gene in females may decrease the spread of malaria and dengue. Male mosquitos do not transmit such diseases, so they serve to safely propagate the gene into mosquito populations by mating with the females.6 Such research shows that biological systems can merge seamlessly into human designs and vice versa, further demonstrating that biology and technology cannot be truly separated.

     Another informative instance of cyberbiology is neuroengineering. We are quite familiar with the human brain as the source of our art, literature, science, mathematics, and personal experiences. As a consequence of its enormous complexity, the brain’s longtime mysteriousness has provoked mystical explanations for the emergence of the mind. As they often derive from religious and naturalist thought, these explanations tend to markedly separate technological and natural systems. However, understanding of the brain is increasing through large-scale projects such as the Human Brain Project, the BRAIN Initiative, and the China Brain Project,7 paving the way for neuroengineering to continue blurring such barriers between technology and biology. Recently, there has been a surge of research in developing more advanced brain-computer interfaces. Entrepreneur Brian Johnson invested one hundred million dollars to launch a BCI startup called Kernel.8 Elon Musk has initiated a venture called Neuralink9 to help humans keep up with artificial intelligence by developing BCI technologies that will grant a more direct connection to the digital “exocortex.” Facebook has announced research on non-invasive BCIs intended to allow people to telepathically type one hundred words per minute.10 The Maharbiz group at UC Berkeley has developed prototype “neural dust,” tiny implantable devices that wirelessly transmit neural recording data using ultrasound.11 Inspired by the science fiction of Iain M. Banks, the Lieber group at Harvard has developed prototype neural lace, an injectable bioelectronic mesh that may help facilitate use of invasive neural interfaces without surgery.12 The Berger group at University of Southern California has developed a hippocampal implant for repairing and enhancing memory. This device has been tested in primates13 and recently, humans. DARPA has given out a sixty five million dollar grant to six other BCI research groups for developing better bidirectional neural interfaces.14 Such technological integration with neurobiology shows that the mind does not hold some transcendental property that renders it immutable by scientific means. Neuroengineering demonstrates that the mind is cyberbiology. 

     Although cyberbiology does not always yield a net positive after developing any given adaptation, it continually self-corrects and optimizes. Two and a half billion years ago, cyanobacteria developed photosynthesis and produced diatomic oxygen. In a world of obligate anaerobes, a massive extinction event occurred. However, detoxification technologies and oxygen utilization mechanisms evolved, allowing a transition to a largely aerobic biosphere. Early chemotherapeutic cancer treatments used toxic compounds that caused widespread damage to healthy tissue as well as tumors.15 More selective tumoricidal drugs have since developed. Now, highly specific and effective molecular immunotherapies like chimeric antigen receptor T cells are further optimizing the therapeutic arena.16 Automation in America may initially disrupt the nation’s capitalistic system by rendering many jobs obsolete. However, pure capitalism has demonstrated negative qualities, particularly in the long-term. Automation also decreases the cost of manufacturing, shifting the means of production to the robots and making essential products less expensive. This could pave the way for more governmental social spending, potentially allowing the universal basic income to be implemented.17 Evolution is an ongoing process of innovation, testing, drawback correction, and more innovation.

     Cyberbiology supports an engineering approach to contemporary challenges. This approach includes both sociopolitical solutions and technological solutions. The sociopolitical case still represents a form of technology since it requires iterative design and implementation. Consider the example of geoengineering as a potential method for combating climate change. Some oppose geoengineering on moral and precautionary grounds,18 seeing it as a violation of the sanctity of nature and a dangerously hubristic idea. According to cyberbiology, geoengineering is a manifestation of nature since it evolves as a population of self-replicating information patterns encoded in human brains and machines. From this perspective, the moral objections are invalid. While the precautionary objection still holds some value, emphasis should be placed on improving the design of geoengineering technologies to minimize negative ecological side effects rather than on moral condemnation of humans. Any problem can be solved by innovation, but these adaptations must sequentially evolve towards the solution using an engineering process.

     Biology and technology both undergo evolution. Replication, mutation, and selection applies to populations of cells, organisms, neural firing patterns, and inventions. Whenever information is propagated with error under selective conditions, regardless of that information’s substrate, it evolves. Strictly ecological evolution occurs slowly because it is mediated by kinetic forces as organisms collide, eat each other, and mate. With the development of more powerful nervous systems and social communication, simulation of hypotheses within and among minds enables a much faster form of evolution. Language, writing, the internet, and related adaptations further increase the efficiency of cognitive evolution. With the advent of intelligent systems capable of improving themselves such as AGI and cyborgs, another level of metacognitive abstraction may develop another much faster form of evolution. Synthetic biology and neurotechnology exemplify how, as more complex systems are built, assumed barriers between biology and technology lose their conviction. When a new adaptation propagates, it may have negative effects as well as positive effects, but it continues to iteratively improve and minimize the drawbacks. For this reason, a technobiological approach to problems like climate change involves optimizing innovations to circumvent negatives rather than avoiding innovation due to moral judgement or excessive caution. Biology and technology are manifestations of a fundamental evolutionary process within a cosmic network, working in synchrony as cyberbiology, quintessentially indistinguishable.

 

References

  1. Kurzweil, R. (2005). The Singularity is Near: When Humans Transcend Biology. New York: Viking.
  2. Berna, F., et al. (2012) Microstratigraphic evidence of in situ fire in the Acheulean strata of Wonderwerk Cave, Northern Cape province, South Africa. Proceedings of the National Academy of Sciences, 109(20), doi:10.1073/pnas.1117620109.
  3. Cisek, P. (2007) Cortical mechanisms of action selection: the affordance competition hypothesis. Philosophical Transactions of the Royal Society B, 362(1485), doi:10.1017/cbo9780511731525.015.
  4. Vinge, V. (1993) The Coming Technological Singularity: How to Survive in the Post-human Era. Interdisciplinary Science and Engineering in the Era of Cyberspace, https://ntrs.nasa.gov/search.jsp?R=19940022856
  5. Neupert, J., et al. (2008) Design of simple synthetic RNA thermometers for temperature-Controlled gene expression in Escherichia coli. Nucleic Acids Research, 36(19), doi:10.1093/nar/gkn545.
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  7. Okano, H., and Tetsuo, Y. (2016) How can brain mapping initiatives cooperate to achieve the same goal? Nature Reviews Neuroscience, 17(12), doi:10.1038/nrn.2016.126.
  8. Regalado, A. (2017). Silicon Valley’s race to develop a brain-computer interface. Accessed August 28, 2017 from, https://www.technologyreview.com/s/603771/the-entrepreneur-with-the-100-million-plan-to-link-brains-to-computers/
  9. Etherington, D. (2017) Elon Musk’s Neuralink wants to boost the brain to keep up with AI. TechCrunch, Accessed August 29, 2017 from, techcrunch.com/2017/03/27/elon-musks-neuralink-wants-to-boost-the-brain-to-keep-up-with-ai/.
  10. Constine, J. (2017, April 19). Facebook is building brain-computer interfaces for typing and skin-hearing. TechCrunch Accessed August 28, 2017, from https://techcrunch.com/2017/04/19/facebook-brain-interface/
  11. Seo, D., et al. (2016) Wireless Recording in the Peripheral Nervous System with Ultrasonic Neural Dust. Neuron, 91(3), doi:10.1016/j.neuron.2016.06.034.
  12. Liu, J., et al. (2015) Syringe-Injectable electronics. Nature Nanotechnology, 10(7), doi:10.1038/nnano.2015.115.
  13. Deadwyler, S. A., et al. (2017) A cognitive prosthesis for memory facilitation by closed-loop functional ensemble stimulation of hippocampal neurons in primate brain. Experimental Neurology, 287, doi:10.1016/j.expneurol.2016.05.031.
  14. Hatmaker, T. (2017) DARPA awards $65 million to develop the perfect, tiny two-way brain-computer interface. TechCrunch Accessed August 29, 2017 from, techcrunch.com/2017/07/10/darpa-nesd-grants-paradromics/.
  15. Papac, R. J. Origins of Cancer Therapy. (2001) The Yale Journal of Biology and Medicine, 74(6),
  16. Restifo, N. P., et al. (2012) Adoptive immunotherapy for cancer: harnessing the T cell response. Nature Reviews Immunology, 12(4), doi:10.1038/nri3191.
  17. Painter, A., an Chris, T. (2015) Creative citizen, creative state: the principled and pragmatic case for a Universal Basic Income. London: RSA
  18. Preston, C. J. (2012) Ethics and geoengineering: reviewing the moral issues raised by solar radiation management and carbon dioxide removal. Wiley Interdisciplinary Reviews: Climate Change, 4(1), doi:10.1002/wcc.198.

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