Raymond Kurzweil is an author, inventor and futurist who has published numerous books and works on the advancement of technology in relation to humans. He is the 1999 recipient of the National Medal of Technology for his work in image scanning and character recognition systems that assist the blind and disabled. Other awards include the MIT Lemelson Prize for innovation, twenty honorary doctorates and induction into the National Inventors Hall of Fame in 2002. His experience encompasses both the academic and private sector, and is currently the Director of Engineering at Google.
In his book The Singularity is Near, Kurzweil reviews and analyzes the progress of technology in the areas of nanotechnology, artificial intelligence and genetics in relation to the evolution of the human condition with predictions for the impact of what he refers to as the “Singularity.” Kurzweil defines the singularity as the point at which technology advances so rapidly that the human species as we will know it will never be the same similar to event horizon of a black which once crossed an acceleration begins towards a singular point at an unimaginable rate. Kurzweil describes this point as “the culmination of the merger of our biological thinking and existence with our technology, resulting in a world that is still human but that transcends our biological roots” (Kurzweil 2005, p. 5-9).
The Six Epochs
Kurzweil categorizes the evolution of the universe in what he refers to as the “Six Epochs” (Kurzweil 2005, p. 14). In the first two epochs, information is first stored in atomic structures until life ushers in DNA based biology which stores the building blocks of life. We entered the third epoch as animals began to develop neural systems to store information on our environment. Humans brought into being the fourth epoch with the development of technology with stored information in analog and later in digital form computerized technology. Kurzweil states that we are entering the fifth epoch now as we begin to merge technology with our own biology which will culminate into the point of singularity where we transcend biology and live digitally. The final epoch is where our digital world spreads throughout the universe and the universe “wakes up” similar to how complex systems such as ant colonies work together as a single individual. (Kurzweil 2015, p. 14-30)
The author discusses the technology that will lay the pre-requisite groundwork for achieving this singularity. This includes continued development of nanotube technologies, increases in speed using various strategies to achieve computation at the molecular level, and a variety of other biological and technical hurdles. He also begins to reverse engineer the computational requirements needed to match and then outperform the human brain in all of its functions. He estimates that this threshold will be reached in the 2030s, but pushes the point of singularity further back to 2045 to account for adoption and possible setbacks (Kurzweil 2015, p. 111-136).
Kurzweil compares human intelligence to that of a software system. The brain has many parallels to how a computer works, but there are also a number of key differences as well which he discusses. The internal circuitry of the brain is very slow in comparison to a computer, but unlike a modern computer it works in a much more parallel manner when compared to the sequential or limited parallel processing strategies of a computer as each connection of the brain has the capability to work independently. Our brain operates on both an analog and digital system as opposed to digitally based computing systems. The brain also has the ability to reconfigure its internal network as needed. Our brain works primarily in pattern recognition as a result of evolution holding information in a more holographic nature. Lastly, the brain operates in a way that is more along the lines of organized chaos as opposed to the interwoven, methodical executional approach of computers which in turn can allow for a degree of creativity in execution. Additional advantages of the human brain include reasoning, complex concept understanding and pattern recognition, resilience and adaptability with limitations resulting from its biological evolution in that many of the systems within the brain were developed for survival in situations that may no longer be relevant.
Step one in understanding is through neural scanning (p. 144-145). Our current scanning systems are still very primitive and rudimentary, but as nanotechnology evolves, we will be able to scan the brain at the molecular level allowing the mapping of the flow of information in the brain on a synaptic level (Kurzweil 2015, p. 157-167). He argues that the method with the most potential is to use nanobots of sufficiently small size to penetrate the blood-brain barrier without damaging this barrier. This could be done through a variety of techniques and strategies which he hypothesizes will be available in the late 2020s.
Kurzweil identifies three primary pre-requisites for our breaching the threshold of the event horizon that leads to the singularity. These advancements include in advanced genetics, nanotechnology and robotics.
We are reaching a point where many of the diseases that have plagued the human race are in a near perpetual retreat, pushing back the life expectancy of humans. As we enter the Genetic revolution, Kurzweil states that we will be able to live indefinitely if given the proper maintenance. He makes the analogy of a house. If you have a house that is in disrepair and left to the elements, it will eventually fail, but if you maintain the house, the dwelling can persist indefinitely outside of an external catastrophic event. The tools that will allow this to take place range from RNA interference and gene chips to somatic gene therapy, and perhaps given time, human cloning could allow for permanent sustainable life. Ahead of his time, Kurzweil also speaks of using cloning as a solution to world hunger (Kurzweil 2015, p. 206-224).
A key to ushering in his fifth epoch will be the ability to effectively develop nanotechnology capable both of scanning and controlling matter at the near-atomic level. Kurzweil details the work of Eric Drexler who laid the foundation for what he called a “molecular assembler” (Kurzweil, p.228). These are built upon a framework of the following subcomponents: A computer, instruction architecture, instruction transmission, a constructor and arm tip, a protective field, and an energy source. While the development of these machines may seem to border on the edge of science fiction, Kurzweil states that the proof that development is possible lies in the existence of life which itself operates on the molecular level.
If we can achieve a machine capable of modifying structures at the molecular level, he details the benefits that this technology could bring. Much of the aging process is due to degradation of DNA and RNA over time due to external factors ranging from biological intervention to low level accumulation of radiation, and Kurzweil makes the case that these errors could be corrected which would prevent or reverse diseases such as cancer. Other benefits include the mitigation of malicious genetic traits that may lead to eventual genetically linked diseases.
Kurzweil addresses many of the criticisms to Drexler’s proposal including a strong argument from Nobelist Richard Smalley, and he maintains that despite the challenges involved, we should see this theory become a reality by the 2020s (Kurzweil 2015, p. 236-240). The author believes the introduction of this technology will have benefits far outside of biology including the ability to create clean manufacturing, environmentally friendly energy production, and enhanced communications with its overall effects reaching every part of our civilization.
When Kurzweil discusses robotics, the most important component is the artificial intelligence (AI) behind the machinery. A debate rages between whether nanobots will usher in strong AI, or whether instead, AI will complete the final steps in nanobot development. Kurzweil sees these two branches of the dawn of the singularity as intertwined as we reach the breach of the next epoch. At the time of writing, Kurzweil notes that AI is very narrow in focus and designed to complete specific tasks. The next generation of AI is thought to be more of a holistic problem solving intelligence that can be applied to a variety of problems with a dynamically shifting set of variables (Kurzweil 2015, p. 259-295).
While the majority of AI is task focused and goal oriented, Kurzweil postulates using the human brain as an alternative model will allow for a next level of artificial intelligence which he refers to as “Strong AI” (Kurzweil p.289). This leap will allow AI to think more exoterically and creatively, and in doing so, we will have a robot capable of passing the Turing Test of artificial intelligence. There is a great debate of the specifics of how to test a machine, but in essence, the Turing tests examines whether a machine intelligence is indistinguishable from that of a human in regards to intelligence, creativity, engagement, and reasoning (Kurzweil p.294-295).
The author makes many assumptions during to his book in regards to time lines, feasibility and needs. While he makes a strong case for the need for nanobots, genetics and artificial intelligence, he tends to take a more optimistic approach with predicting timelines and stating the absolute feasibility of the technology. Kurzweil makes the claim that we have proof that nanobots are possible by drawing parallels to the nature of cells in the human body. While there is some merit to this analogy, the versatility of the nanobots exceeds that of the cells of the human body in both purpose and scope. An example of such a limitation of scope is advances in using nanobots to kill cancer cells in mice. Rather than relying on motors and power sources as referenced by Kurzweil, researchers at Arizona State University are developing DNA based nanobots specifically designed to kill cancerous cells. These limited, designer nanobots seem to be the limit of current nanobot usage rather than the more versatile robots Kurzweil describes coming to reality within a decade. (Shearman, 2018)
While Kurzweil may take an optimistic approach to his projections, he gives credibility to his claims by discussing criticisms and conflicts with his assertions. As an example, Kurzweil views both sides of the argument for whether nanobots are even feasible by providing the two opposing viewpoints of Eric Drexler and Nobelist Richard Smalley. He follows their debate over a period of time, and then draws conclusions on the strengths of each argument. While there does seem to be a slight bias towards the feasibility of nanobots which is a key component of Kurzweil’s projections, he provides due diligence in this approach (Kurzweil 2005, p.236-242). Kurzweil later provides an in depth of review of the criticisms of the technology and theories that he relies on in his books closing sections including a strong debate on the Turing Test (Kurzweil 2005, p. 427-490).
Kurzweil’s review of our current understanding of the brain and its functions emphasizes the limits of our current observational tools. While we are able to view the synaptic firings of neurons, we do not yet have the ability to follow the flow of information throughout the brain and nervous system which is fully needed if we are ever going to map the brain to the point of mind transference to a digital system. Kurzweil views the keys to this being nanobots implemented to internal scan the brain using a variety of methods.
If we can cross this breach, this brings into question how learning will evolve as a result. If we have the capacity to follow the flow of information throughout the brain, we may be possible to reverse the process and upload information. Furthermore, learning could transcend individual to true group learning if the nano-enabled minds can be networked together in hive-like structure.
Repetition of learning is also referenced. Kurzweil states that while the neural network of the brain is extensive, it has in it a series of redundancies to mitigate knowledge loss due to injury or degradation. While these redundancies may not be needed when as we approach the singularity, this concept does reinforce the need for repetition in course instruction as not just a strategy for learning, but essential also as a necessity to provide layers of redundancy as mental systems degrade with aging.
Overall, I found the book to be very enlightening. Having a background in computer science with a focus on data science, I had a strong understanding of the technical concepts that Kurzweil discusses coming into this reading, and while I found myself in opposition to many his theories at first, I found myself more at ease as he introduced and addressed these criticisms in detail. Given that we our technology is advancing at an accelerated rate, I must concede that his timelines, while optimistic, may be feasible. Similarly, our course provided a strong background to better understand and appreciate his discussions on the biological side of the equation. It enhanced my understanding, and I found myself appreciating how complex our neural systems are. Popular culture and science fiction in books and movies such as Neuromancer and The Matrix and subsequent sequels leave with you a view that you simply would need to link a cortex to an receiving device, but Kurzweil left me realizing that the level of complexity of our brains would require an equally advanced and complex approach than simple cerebral links and brain scans. All in all, this book kept me engaged and asking new questions as I progressed.
Kurzweil, Ray. (2005). The singularity is near : when humans transcend biology. New York: Penguin Books.
Kurzweil, Raymond. (2012). Ray Kurzweil biography. Retrieved October 20, 2019, from Kurzweilai.net website: https://www.kurzweilai.net/ray-kurzweil-biography
This is an autobiographical website listing the works, publications and background of Ray Kurweil.
Shearman, S. (2018, March 5). Nanobots kill off cancerous tumours as fiction becomes reality. Retrieved April 26, 2019, from Financial Times website: https://www.ft.com/content/57c9f432-de6d-11e7-a0d4-0944c5f49e46.
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