Mind uploading

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Whole brain emulation (WBE), mind upload or brain upload (sometimes called "mind copying" or "mind transfer") is the hypothetical futuristic process of scanning the mental state (including long-term memory and "self") of a particular brain substrate and copying it to a computer. The computer could then run a simulation model of the brain's information processing, such that it would respond in essentially the same way as the original brain (i.e., indistinguishable from the brain for all relevant purposes) and experience having a conscious mind. [1] [2] [3]

Computer simulation simulation, run on a single computer, or a network of computers, to reproduce behavior of a system; modeling a real physical system in a computer

Computer simulation is the reproduction of the behavior of a system using a computer to simulate the outcomes of a mathematical model associated with said system. Since they allow to check the reliability of chosen mathematical models, computer simulations have become a useful tool for the mathematical modeling of many natural systems in physics, astrophysics, climatology, chemistry, biology and manufacturing, human systems in economics, psychology, social science, health care and engineering. Simulation of a system is represented as the running of the system's model. It can be used to explore and gain new insights into new technology and to estimate the performance of systems too complex for analytical solutions.

Mind Combination of cognitive faculties that provide consciousness, thinking, reasoning, perception and judgement

The mind is the set of cognitive faculties including consciousness, imagination, perception, thinking, judgement, language and memory, which is housed in the brain. It is usually defined as the faculty of an entity's thoughts and consciousness. It holds the power of imagination, recognition, and appreciation, and is responsible for processing feelings and emotions, resulting in attitudes and actions.

Contents

Substantial mainstream research in related areas is being conducted in animal brain mapping and simulation, development of faster supercomputers, virtual reality, brain–computer interfaces, connectomics and information extraction from dynamically functioning brains. [4] According to supporters, many of the tools and ideas needed to achieve mind uploading already exist or are currently under active development; however, they will admit that others are, as yet, very speculative, but still in the realm of engineering possibility. Neuroscientist Randal Koene has formed a nonprofit organization called Carbon Copies to promote mind uploading research.

A brain–computer interface (BCI), sometimes called a neural-control interface (NCI), mind-machine interface (MMI), direct neural interface (DNI), or brain–machine interface (BMI), is a direct communication pathway between an enhanced or wired brain and an external device. BCI differs from neuromodulation in that it allows for bidirectional information flow. BCIs are often directed at researching, mapping, assisting, augmenting, or repairing human cognitive or sensory-motor functions.

Connectomics is the production and study of connectomes: comprehensive maps of connections within an organism's nervous system, typically its brain or eye. Because these structures are extremely complex, methods within this field use a high-throughput application of neural imaging and histological techniques in order to increase the speed, efficiency, and resolution of maps of the multitude of neural connections in a nervous system. While the principal focus of such a project is the brain, any neural connections could theoretically be mapped by connectomics, including, for example, neuromuscular junctions. This study is sometimes referred to by its previous name of hodology.

Randal A. Koene Dutch neuroscientist

Randal A. Koene is a Dutch neuroscientist and neuroengineer, and co-founder of carboncopies.org, the outreach and roadmapping organization for advancing Substrate-Independent Minds (SIM). Between 2008 and 2010, Koene was Director of the Department of Neuroengineering at the Fatronik-Tecnalia Institute in Spain, the third largest private research organization in Europe. Koene earned his Ph.D. in Computational Neuroscience at the Department of Psychology at McGill University, and his M.Sc. in Electrical Engineering with a specialization in Information Theory at Delft University of Technology. He is a former Professor at the Center for Memory and Brain of Boston University, and is co-founder of the Neural Engineering Corporation of Massachusetts. Koene established the MindUploading.org website and first proposed the term and specific approach called whole brain emulation, the purpose of which is the technological accomplishment of mind transfer to a different substrate. His professional research objective is the implementation of whole brain emulation: creating the large-scale high-resolution representations and emulations of activity in neuronal circuitry that are needed in patient-specific neuroprostheses. He is a member of the Oxford working group that convened in 2007 to create a first roadmap toward whole brain emulation.

Mind uploading may potentially be accomplished by either of two methods: Copy-and-transfer or gradual replacement of neurons. In the case of the former method, mind uploading would be achieved by scanning and mapping the salient features of a biological brain, and then by copying, transferring, and storing that information state into a computer system or another computational device. The biological brain may not survive the copying process. The simulated mind could be within a virtual reality or simulated world, supported by an anatomic 3D body simulation model. Alternatively the simulated mind could reside in a computer inside (or connected to) a (not necessarily humanoid) robot or a biological body. [5]

Brain mapping is a set of neuroscience techniques predicated on the mapping of (biological) quantities or properties onto spatial representations of the brain resulting in maps.

Simulated reality is the hypothesis that reality could be simulated—for example by quantum computer simulation—to a degree indistinguishable from "true" reality. It could contain conscious minds which may or may not be fully aware that they are living inside a simulation. This is quite different from the current, technologically achievable concept of virtual reality. Virtual reality is easily distinguished from the experience of actuality; participants are never in doubt about the nature of what they experience. Simulated reality, by contrast, would be hard or impossible to separate from "true" reality. There has been much debate over this topic, ranging from philosophical discourse to practical applications in computing.

Humanoid Something that has an appearance resembling a human without actually being one

A humanoid is something that has an appearance resembling a human without actually being one. The earliest recorded use of the term, in 1870, referred to indigenous peoples in areas colonized by Europeans. By the 20th century, the term came to describe fossils which were morphologically similar, but not identical, to those of the human skeleton.

Among some futurists and within the transhumanist movement, mind uploading is treated as an important proposed life extension technology. Some believe mind uploading is humanity's current best option for preserving the identity of the species, as opposed to cryonics. Another aim of mind uploading is to provide a permanent backup to our "mind-file", to enable interstellar space travels, and a means for human culture to survive a global disaster by making a functional copy of a human society in a Matrioshka brain, i.e. a computing device that consumes all energy from a star. Whole brain emulation is discussed by some futurists as a "logical endpoint" [5] of the topical computational neuroscience and neuroinformatics fields, both about brain simulation for medical research purposes. It is discussed in artificial intelligence research publications as an approach to strong AI. Computer-based intelligence such as an upload could think much faster than a biological human even if it were no more intelligent. A large-scale society of uploads might, according to futurists, give rise to a technological singularity, meaning a sudden time constant decrease in the exponential development of technology. [6] Mind uploading is a central conceptual feature of numerous science fiction novels and films.

Transhumanism Philosophical movement

Transhumanism is an international philosophical movement that advocates for the transformation of the human condition by developing and making widely available sophisticated technologies to greatly enhance human intellect and physiology.

Life extension is the idea of extending the human lifespan, either modestly – through improvements in medicine – or dramatically by increasing the maximum lifespan beyond its generally settled limit of 125 years. The ability to achieve such dramatic changes, however, does not currently exist.

Cryonics Freezing of a human corpse

Cryonics is the low-temperature freezing and storage of a human corpse or severed head, with the speculative hope that resurrection may be possible in the future. Cryonics is regarded with skepticism within the mainstream scientific community. It is a pseudoscience, and its practice is quackery.

Overview

Neuron anatomical model Dendrite (PSF).svg
Neuron anatomical model
Simple artificial neural network Neural network.svg
Simple artificial neural network

The human brain contains, on average, about 86 billion nerve cells called neurons, each individually linked to other neurons by way of connectors called axons and dendrites. Signals at the junctures (synapses) of these connections are transmitted by the release and detection of chemicals known as neurotransmitters. The established neuroscientific consensus is that the human mind is largely an emergent property of the information processing of this neural network.[ citation needed ]

Axon The long process of a neuron that conducts nerve impulses, usually away from the cell body to the terminals and varicosities, which are sites of storage and release of neurotransmitter.

An axon, or nerve fiber, is a long, slender projection of a nerve cell, or neuron, in vertebrates, that typically conducts electrical impulses known as action potentials away from the nerve cell body. The function of the axon is to transmit information to different neurons, muscles, and glands. In certain sensory neurons, such as those for touch and warmth, the axons are called afferent nerve fibers and the electrical impulse travels along these from the periphery to the cell body, and from the cell body to the spinal cord along another branch of the same axon. Axon dysfunction has caused many inherited and acquired neurological disorders which can affect both the peripheral and central neurons. Nerve fibers are classed into three types – group A nerve fibers, group B nerve fibers, and group C nerve fibers. Groups A and B are myelinated, and group C are unmyelinated. These groups include both sensory fibers and motor fibers. Another classification groups only the sensory fibers as Type I, Type II, Type III, and Type IV.

Dendrite neuron projection that has a short, tapering, often branched, morphology, receives and integrates signals from other neurons or from sensory stimuli, and conducts a nerve impulse towards the axon or the cell body

Dendrites, also dendrons, are branched protoplasmic extensions of a nerve cell that propagate the electrochemical stimulation received from other neural cells to the cell body, or soma, of the neuron from which the dendrites project. Electrical stimulation is transmitted onto dendrites by upstream neurons via synapses which are located at various points throughout the dendritic tree. Dendrites play a critical role in integrating these synaptic inputs and in determining the extent to which action potentials are produced by the neuron. Dendritic arborization, also known as dendritic branching, is a multi-step biological process by which neurons form new dendritic trees and branches to create new synapses. The morphology of dendrites such as branch density and grouping patterns are highly correlated to the function of the neuron. Malformation of dendrites is also tightly correlated to impaired nervous system function. Some disorders that are associated with the malformation of dendrites are autism, depression, schizophrenia, Down syndrome and anxiety.

Synapse The junction between a nerve fiber of one neuron and another neuron, muscle fiber or glial cell. As the nerve fiber approaches the synapse it enlarges into a specialized structure, the presynaptic nerve ending, which contains mitochondria and synapti

In the nervous system, a synapse is a structure that permits a neuron to pass an electrical or chemical signal to another neuron or to the target effector cell.

Neuroscientists have stated that important functions performed by the mind, such as learning, memory, and consciousness, are due to purely physical and electrochemical processes in the brain and are governed by applicable laws. For example, Christof Koch and Giulio Tononi wrote in IEEE Spectrum :

Christof Koch

Christof Koch is a German-American neuroscientist best known for his work on the neural bases of consciousness. He is the president and chief scientist of the Allen Institute for Brain Science in Seattle. From 1986 until 2013, he was a professor at the California Institute of Technology.

Giulio Tononi Italian neuroscientist and psychiatrist

Giulio Tononi is a neuroscientist and psychiatrist who holds the David P. White Chair in Sleep Medicine, as well as a Distinguished Chair in Consciousness Science, at the University of Wisconsin.

<i>IEEE Spectrum</i> journal

IEEE Spectrum is a magazine edited by the Institute of Electrical and Electronics Engineers. The IEEE's description of it is:

IEEE Spectrum is the flagship magazine and website of the IEEE, the world’s largest professional organization devoted to engineering and the applied sciences. Our charter is to keep over 400,000 members informed about major trends and developments in technology, engineering, and science. Our blogs, podcasts, news and features stories, videos and interactive infographics engage our visitors with clear explanations about emerging concepts and developments with details they can't get elsewhere.

Consciousness is part of the natural world. It depends, we believe, only on mathematics and logic and on the imperfectly known laws of physics, chemistry, and biology; it does not arise from some magical or otherworldly quality. [7]

The concept of mind uploading is based on this mechanistic view of the mind, and denies the vitalist view of human life and consciousness.[ citation needed ]

Eminent computer scientists and neuroscientists have predicted that specially programmed[ clarification needed ] computers will be capable of thought and even attain consciousness, including Koch and Tononi, [7] Douglas Hofstadter, [8] Jeff Hawkins, [8] Marvin Minsky, [9] Randal A. Koene, and Rodolfo Llinás. [10]

However, even though uploading is dependent upon such a general capability, it is conceptually distinct from general forms of AI in that it results from dynamic reanimation of information derived from a specific human mind so that the mind retains a sense of historical identity (other forms are possible but would compromise or eliminate the life-extension feature generally associated with uploading). The transferred and reanimated information would become a form of artificial intelligence, sometimes called an infomorph or "noömorph".[ citation needed ]

Many theorists have presented models of the brain and have established a range of estimates of the amount of computing power needed for partial and complete simulations. [5] [ citation needed ] Using these models, some have estimated that uploading may become possible within decades if trends such as Moore's law continue. [11]

Theoretical benefits and applications

"Immortality" or backup

In theory, if the information and processes of the mind can be disassociated from the biological body, they are no longer tied to the individual limits and lifespan of that body. Furthermore, information within a brain could be partly or wholly copied or transferred to one or more other substrates (including digital storage or another brain), thereby – from a purely mechanistic perspective – reducing or eliminating "mortality risk" of such information. This general proposal was discussed in 1971 by biogerontologist George M. Martin of the University of Washington. [12]

Space exploration

An “uploaded astronaut” could be used instead of a "live" astronaut in human spaceflight, avoiding the perils of zero gravity, the vacuum of space, and cosmic radiation to the human body. It would allow for the use of smaller spacecraft, such as the proposed StarChip, and it would enable virtually unlimited interstellar travel distances. [13]

Relevant technologies and techniques

The focus of mind uploading, in the case of copy-and-transfer, is on data acquisition, rather than data maintenance of the brain. A set of approaches known as loosely coupled off-loading (LCOL) may be used in the attempt to characterize and copy the mental contents of a brain. [14] The LCOL approach may take advantage of self-reports, life-logs and video recordings that can be analyzed by artificial intelligence. A bottom-up approach may focus on the specific resolution and morphology of neurons, the spike times of neurons, the times at which neurons produce action potential responses.

Computational complexity

Estimates of how much processing power is needed to emulate a human brain at various levels (from Ray Kurzweil and the chart to the left), along with the fastest supercomputer from TOP500 mapped by year. Note the logarithmic scale and exponential trendline, which assumes the computational capacity doubles every 1.1 years. Kurzweil believes that mind uploading will be possible at neural simulation, while the Sandberg, Bostrom report is less certain about where consciousness arises. Estimations of Human Brain Emulation Required Performance.svg
Estimates of how much processing power is needed to emulate a human brain at various levels (from Ray Kurzweil and the chart to the left), along with the fastest supercomputer from TOP500 mapped by year. Note the logarithmic scale and exponential trendline, which assumes the computational capacity doubles every 1.1 years. Kurzweil believes that mind uploading will be possible at neural simulation, while the Sandberg, Bostrom report is less certain about where consciousness arises.

Advocates of mind uploading point to Moore's law to support the notion that the necessary computing power is expected to become available within a few decades. However, the actual computational requirements for running an uploaded human mind are very difficult to quantify, potentially rendering such an argument specious.

Regardless of the techniques used to capture or recreate the function of a human mind, the processing demands are likely to be immense, due to the large number of neurons in the human brain along with the considerable complexity of each neuron.

In 2004, Henry Markram, lead researcher of the "Blue Brain Project", stated that "it is not [their] goal to build an intelligent neural network", based solely on the computational demands such a project would have. [16]

It will be very difficult because, in the brain, every molecule is a powerful computer and we would need to simulate the structure and function of trillions upon trillions of molecules as well as all the rules that govern how they interact. You would literally need computers that are trillions of times bigger and faster than anything existing today. [17]

Five years later, after successful simulation of part of a rat brain, Markram was much more bold and optimistic. In 2009, as director of the Blue Brain Project, he claimed that “A detailed, functional artificial human brain can be built within the next 10 years.” [18]

Required computational capacity strongly depend on the chosen level of simulation model scale: [5]

LevelCPU demand
(FLOPS)
Memory demand
(Tb)
$1 million super‐computer
(Earliest year of making)
Analog network population model10151022008
Spiking neural network 10181042019
Electrophysiology 10221042033
Metabolome 10251062044
Proteome 10261072048
States of protein complexes10271082052
Distribution of complexes10301092063
Stochastic behavior of single molecules104310142111
Estimates from Sandberg, Bostrom, 2008

Simulation model scale

A high-level cognitive AI model of the brain architecture is not required for brain emulation IDA Cognitive Architecture.jpg
A high-level cognitive AI model of the brain architecture is not required for brain emulation
Simple neuron model: Black-box dynamic non-linear signal processing system ArtificialNeuronModel english.png
Simple neuron model: Black-box dynamic non-linear signal processing system
Metabolism model: The movement of positively charged ions through the ion channels controls the membrane electrical action potential in an axon. Action potential propagation animation.gif
Metabolism model: The movement of positively charged ions through the ion channels controls the membrane electrical action potential in an axon.

Since the function of the human mind and how it might arise from the working of the brain's neural network, are poorly understood issues, mind uploading relies on the idea of neural network emulation. Rather than having to understand the high-level psychological processes and large-scale structures of the brain, and model them using classical artificial intelligence methods and cognitive psychology models, the low-level structure of the underlying neural network is captured, mapped and emulated with a computer system. In computer science terminology,[ dubious ] rather than analyzing and reverse engineering the behavior of the algorithms and data structures that resides in the brain, a blueprint of its source code is translated to another programming language. The human mind and the personal identity then, theoretically, is generated by the emulated neural network in an identical fashion to it being generated by the biological neural network.

On the other hand, a molecule-scale simulation of the brain is not expected to be required, provided that the functioning of the neurons is not affected by quantum mechanical processes. The neural network emulation approach only requires that the functioning and interaction of neurons and synapses are understood. It is expected that it is sufficient with a black-box signal processing model of how the neurons respond to nerve impulses (electrical as well as chemical synaptic transmission).

A sufficiently complex and accurate model of the neurons is required. A traditional artificial neural network model, for example multi-layer perceptron network model, is not considered as sufficient. A dynamic spiking neural network model is required, which reflects that the neuron fires only when a membrane potential reaches a certain level. It is likely that the model must include delays, non-linear functions and differential equations describing the relation between electrophysical parameters such as electrical currents, voltages, membrane states (ion channel states) and neuromodulators.

Since learning and long-term memory are believed to result from strengthening or weakening the synapses via a mechanism known as synaptic plasticity or synaptic adaptation, the model should include this mechanism. The response of sensory receptors to various stimuli must also be modelled.

Furthermore, the model may have to include metabolism, i.e. how the neurons are affected by hormones and other chemical substances that may cross the blood–brain barrier. It is considered likely that the model must include currently unknown neuromodulators, neurotransmitters and ion channels. It is considered unlikely that the simulation model has to include protein interaction, which would make it computationally complex. [5]

A digital computer simulation model of an analog system such as the brain is an approximation that introduces random quantization errors and distortion. However, the biological neurons also suffer from randomness and limited precision, for example due to background noise. The errors of the discrete model can be made smaller than the randomness of the biological brain by choosing a sufficiently high variable resolution and sample rate, and sufficiently accurate models of non-linearities. The computational power and computer memory must however be sufficient to run such large simulations, preferably in real time.

Scanning and mapping scale of an individual

When modelling and simulating the brain of a specific individual, a brain map or connectivity database showing the connections between the neurons must be extracted from an anatomic model of the brain. For whole brain simulation, this network map should show the connectivity of the whole nervous system, including the spinal cord, sensory receptors, and muscle cells. Destructive scanning of a small sample of tissue from a mouse brain including synaptic details is possible as of 2010. [19]

However, if short-term memory and working memory include prolonged or repeated firing of neurons, as well as intra-neural dynamic processes, the electrical and chemical signal state of the synapses and neurons may be hard to extract. The uploaded mind may then perceive a memory loss of the events and mental processes immediately before the time of brain scanning. [5]

A full brain map has been estimated to occupy less than 2 x 1016 bytes (20,000 TB) and would store the addresses of the connected neurons, the synapse type and the synapse "weight" for each of the brains' 1015 synapses. [5] [ failed verification ] However, the biological complexities of true brain function (e.g. the epigenetic states of neurons, protein components with multiple functional states, etc.) may preclude an accurate prediction of the volume of binary data required to faithfully represent a functioning human mind.

Serial sectioning

Serial sectioning of a brain User-FastFission-brain.gif
Serial sectioning of a brain

A possible method for mind uploading is serial sectioning, in which the brain tissue and perhaps other parts of the nervous system are frozen and then scanned and analyzed layer by layer, which for frozen samples at nano-scale requires a cryo-ultramicrotome, thus capturing the structure of the neurons and their interconnections. [20] The exposed surface of frozen nerve tissue would be scanned and recorded, and then the surface layer of tissue removed. While this would be a very slow and labor-intensive process, research is currently underway to automate the collection and microscopy of serial sections. [21] The scans would then be analyzed, and a model of the neural net recreated in the system that the mind was being uploaded into.

There are uncertainties with this approach using current microscopy techniques. If it is possible to replicate neuron function from its visible structure alone, then the resolution afforded by a scanning electron microscope would suffice for such a technique. [21] However, as the function of brain tissue is partially determined by molecular events (particularly at synapses, but also at other places on the neuron's cell membrane), this may not suffice for capturing and simulating neuron functions. It may be possible to extend the techniques of serial sectioning and to capture the internal molecular makeup of neurons, through the use of sophisticated immunohistochemistry staining methods that could then be read via confocal laser scanning microscopy. However, as the physiological genesis of 'mind' is not currently known, this method may not be able to access all of the necessary biochemical information to recreate a human brain with sufficient fidelity.

Brain imaging

Process from MRI acquisition to whole brain structural network Connectome extraction procedure.jpg
Process from MRI acquisition to whole brain structural network
Magnetoencephalography Magnetoencephalography.svg
Magnetoencephalography

It may be possible to create functional 3D maps of the brain activity, using advanced neuroimaging technology, such as functional MRI (fMRI, for mapping change in blood flow), magnetoencephalography (MEG, for mapping of electrical currents), or combinations of multiple methods, to build a detailed three-dimensional model of the brain using non-invasive and non-destructive methods. Today, fMRI is often combined with MEG for creating functional maps of human cortex during more complex cognitive tasks, as the methods complement each other. Even though current imaging technology lacks the spatial resolution needed to gather the information needed for such a scan, important recent and future developments are predicted to substantially improve both spatial and temporal resolutions of existing technologies. [23]

Brain simulation

There is ongoing work in the field of brain simulation, including partial and whole simulations of some animals. For example, the C. elegans roundworm, Drosophila fruit fly, and mouse have all been simulated to various degrees.[ citation needed ]

The Blue Brain Project by the Brain and Mind Institute of the École Polytechnique Fédérale de Lausanne, Switzerland is an attempt to create a synthetic brain by reverse-engineering mammalian brain circuitry.

Issues

Philosophical issues

Underlying the concept of "mind uploading" (more accurately "mind transferring") is the broad philosophy that consciousness lies within the brain's information processing and is in essence an emergent feature that arises from large neural network high-level patterns of organization, and that the same patterns of organization can be realized in other processing devices. Mind uploading also relies on the idea that the human mind (the "self" and the long-term memory), just like non-human minds, is represented by the current neural network paths and the weights of the brain synapses rather than by a dualistic and mystic soul and spirit. The mind or "soul" can be defined as the information state of the brain, and is immaterial only in the same sense as the information content of a data file or the state of a computer software currently residing in the work-space memory of the computer. Data specifying the information state of the neural network can be captured and copied as a "computer file" from the brain and re-implemented into a different physical form. [24] This is not to deny that minds are richly adapted to their substrates. [25] An analogy to the idea of mind uploading is to copy the temporary information state (the variable values) of a computer program from the computer memory to another computer and continue its execution. The other computer may perhaps have different hardware architecture but emulates the hardware of the first computer.

These issues have a long history. In 1775 Thomas Reid wrote: [26] “I would be glad to know... whether when my brain has lost its original structure, and when some hundred years after the same materials are fabricated so curiously as to become an intelligent being, whether, I say that being will be me; or, if, two or three such beings should be formed out of my brain; whether they will all be me, and consequently one and the same intelligent being.”

A considerable portion of transhumanists and singularitarians place great hope into the belief that they may become immortal, by creating one or many non-biological functional copies of their brains, thereby leaving their "biological shell". However, the philosopher and transhumanist Susan Schneider claims that at best, uploading would create a copy of the original person's mind. [27] Susan Schneider agrees that consciousness has a computational basis, but this does not mean we can upload and survive. According to her views, "uploading" would probably result in the death of the original person's brain, while only outside observers can maintain the illusion of the original person still being alive. For it is implausible to think that one's consciousness would leave one's brain and travel to a remote location; ordinary physical objects do not behave this way. Ordinary objects (rocks, tables, etc.) are not simultaneously here, and elsewhere. At best, a copy of the original mind is created. [27] Neural correlates of consciousness, a sub-branch of neuroscience, states that consciousness may be thought of as a state-dependent property of some undefined complex, adaptive, and highly interconnected biological system. [28]

Others have argued against such conclusions. For example, Buddhist transhumanist James Hughes has pointed out that this consideration only goes so far: if one believes the self is an illusion, worries about survival are not reasons to avoid uploading, [29] and Keith Wiley has presented an argument wherein all resulting minds of an uploading procedure are granted equal primacy in their claim to the original identity, such that survival of the self is determined retroactively from a strictly subjective position. [30] [31] Some have also asserted that consciousness is a part of an extra-biological system that is yet to be discovered and cannot be fully understood under the present constraints of neurobiology. Without the transference of consciousness, true mind-upload or perpetual immortality cannot be practically achieved. [32]

Another potential consequence of mind uploading is that the decision to "upload" may then create a mindless symbol manipulator instead of a conscious mind (see philosophical zombie). [33] [34] Are we to assume that an upload is conscious if it displays behaviors that are highly indicative of consciousness? Are we to assume that an upload is conscious if it verbally insists that it is conscious? [35] Could there be an absolute upper limit in processing speed above which consciousness cannot be sustained? The mystery of consciousness precludes a definitive answer to this question. [36] Numerous scientists, including Kurzweil, strongly believe that determining whether a separate entity is conscious (with 100% confidence) is fundamentally unknowable, since consciousness is inherently subjective (see solipsism). Regardless, some scientists strongly believe consciousness is the consequence of computational processes which are substrate-neutral. On the contrary, numerous scientists believe consciousness may be the result of some form of quantum computation dependent on substrate (see quantum mind). [37] [38] [39]

In light of uncertainty on whether to regard uploads as conscious, Sandberg proposes a cautious approach: [40]

Principle of assuming the most (PAM): Assume that any emulated system could have the same mental properties as the original system and treat it correspondingly.

Verification issues

It is argued that if a computational copy of one's mind did exist, it would be impossible for one to verify this. [41] The argument for this stance is the following: for a computational mind to recognize an emulation of itself, it must be capable of deciding whether two Turing machines (namely, itself and the proposed emulation) are functionally equivalent. This task is uncomputable due to the undecidability of equivalence, thus there cannot exist a computational procedure in the mind that is capable of recognizing an emulation of itself.

The process of developing emulation technology raises ethical issues related to animal welfare and artificial consciousness. [40] The neuroscience required to develop brain emulation would require animal experimentation, first on invertebrates and then on small mammals before moving on to humans. Sometimes the animals would just need to be euthanized in order to extract, slice, and scan their brains, but sometimes behavioral and in vivo measures would be required, which might cause pain to living animals. [40]

In addition, the resulting animal emulations themselves might suffer, depending on one's views about consciousness. [40] Bancroft argues for the plausibility of consciousness in brain simulations on the basis of the "fading qualia" thought experiment of David Chalmers. He then concludes: [42] “If, as I argue above, a sufficiently detailed computational simulation of the brain is potentially operationally equivalent to an organic brain, it follows that we must consider extending protections against suffering to simulations.”

It might help reduce emulation suffering to develop virtual equivalents of anaesthesia, as well as to omit processing related to pain and/or consciousness. However, some experiments might require a fully functioning and suffering animal emulation. Animals might also suffer by accident due to flaws and lack of insight into what parts of their brains are suffering. [40] Questions also arise regarding the moral status of partial brain emulations, as well as creating neuromorphic emulations that draw inspiration from biological brains but are built somewhat differently. [42]

Brain emulations could be erased by computer viruses or malware, without need to destroy the underlying hardware. This may make assassination easier than for physical humans. The attacker might take the computing power for its own use. [43]

Many questions arise regarding the legal personhood of emulations. [44] Would they be given the rights of biological humans? If a person makes an emulated copy of themselves and then dies, does the emulation inherit their property and official positions? Could the emulation ask to "pull the plug" when its biological version was terminally ill or in a coma? Would it help to treat emulations as adolescents for a few years so that the biological creator would maintain temporary control? Would criminal emulations receive the death penalty, or would they be given forced data modification as a form of "rehabilitation"? Could an upload have marriage and child-care rights? [44]

If simulated minds would come true and if they were assigned rights of their own, it may be difficult to ensure the protection of "digital human rights". For example, social science researchers might be tempted to secretly expose simulated minds, or whole isolated societies of simulated minds, to controlled experiments in which many copies of the same minds are exposed (serially or simultaneously) to different test conditions.[ citation needed ]

Political and economic implications

Emulations could create a number of conditions that might increase risk of war, including inequality, changes of power dynamics, a possible technological arms race to build emulations first, first-strike advantages, strong loyalty and willingness to "die" among emulations, and triggers for racist, xenophobic, and religious prejudice. [43] If emulations run much faster than humans, there might not be enough time for human leaders to make wise decisions or negotiate. It is possible that humans would react violently against growing power of emulations, especially if they depress human wages. Emulations may not trust each other, and even well-intentioned defensive measures might be interpreted as offense. [43]

Emulation timelines and AI risk

There are very few feasible technologies that humans have refrained from developing. The neuroscience and computer-hardware technologies that may make brain emulation possible are widely desired for other reasons, and logically their development will continue into the future. Assuming that emulation technology will arrive, a question becomes whether we should accelerate or slow its advance. [43]

Arguments for speeding up brain-emulation research:

Arguments for slowing down brain-emulation research:

Emulation research would also speed up neuroscience as a whole, which might accelerate medical advances, cognitive enhancement, lie detectors, and capability for psychological manipulation. [49]

Emulations might be easier to control than de novo AI because

  1. We understand better human abilities, behavioral tendencies, and vulnerabilities, so control measures might be more intuitive and easier to plan for. [48] [49]
  2. Emulations could more easily inherit human motivations. [49]
  3. Emulations are harder to manipulate than de novo AI, because brains are messy and complicated; this could reduce risks of their rapid takeoff. [43] [49] Also, emulations may be bulkier and require more hardware than AI, which would also slow the speed of a transition. [49] Unlike AI, an emulation wouldn't be able to rapidly expand beyond the size of a human brain. [49] Emulations running at digital speeds would have less intelligence differential vis-à-vis AI and so might more easily control AI. [49]

As counterpoint to these considerations, Bostrom notes some downsides:

  1. Even if we better understand human behavior, the evolution of emulation behavior under self-improvement might be much less predictable than the evolution of safe de novo AI under self-improvement. [49]
  2. Emulations may not inherit all human motivations. Perhaps they would inherit our darker motivations or would behave abnormally in the unfamiliar environment of cyberspace. [49]
  3. Even if there's a slow takeoff toward emulations, there would still be a second transition to de novo AI later on. Two intelligence explosions may mean more total risk. [49]

Advocates

Ray Kurzweil, director of engineering at Google, claims to know and foresee that people will be able to "upload" their entire brains to computers and become "digitally immortal" by 2045. Kurzweil made this claim for many years, e.g. during his speech in 2013 at the Global Futures 2045 International Congress in New York, which claims to subscribe to a similar set of beliefs. [50] Mind uploading is also advocated by a number of researchers in neuroscience and artificial intelligence, such as Marvin Minsky [ citation needed ] while he was still alive. In 1993, Joe Strout created a small web site called the Mind Uploading Home Page, and began advocating the idea in cryonics circles and elsewhere on the net. That site has not been actively updated in recent years, but it has spawned other sites including MindUploading.org, run by Randal A. Koene, who also moderates a mailing list on the topic. These advocates see mind uploading as a medical procedure which could eventually save countless lives.

Many transhumanists look forward to the development and deployment of mind uploading technology, with transhumanists such as Nick Bostrom predicting that it will become possible within the 21st century due to technological trends such as Moore's law. [5]

Michio Kaku, in collaboration with Science, hosted a documentary, Sci Fi Science: Physics of the Impossible , based on his book Physics of the Impossible .  Episode four, titled "How to Teleport", mentions that mind uploading via techniques such as quantum entanglement and whole brain emulation using an advanced MRI machine may enable people to be transported to vast distances at near light-speed.

The book Beyond Humanity: CyberEvolution and Future Minds by Gregory S. Paul & Earl D. Cox, is about the eventual (and, to the authors, almost inevitable) evolution of computers into sentient beings, but also deals with human mind transfer. Richard Doyle's Wetwares: Experiments in PostVital Living deals extensively with uploading from the perspective of distributed embodiment, arguing for example that humans are currently part of the "artificial life phenotype". Doyle's vision reverses the polarity on uploading, with artificial life forms such as uploads actively seeking out biological embodiment as part of their reproductive strategy.

Skeptics

Kenneth D. Miller, a professor of neuroscience at Columbia and a co-director of the Center for Theoretical Neuroscience, raised doubts about the practicality of mind uploading. His major argument is that reconstructing neurons and their connections is in itself a formidable task, but it is far from being sufficient. Operation of the brain depends on the dynamics of electrical and biochemical signal exchange between neurons; therefore, capturing them in a single "frozen" state may prove insufficient. In addition, the nature of these signals may require modeling down to the molecular level and beyond. Therefore, while not rejecting the idea in principle, Miller believes that the complexity of the "absolute" duplication of an individual mind is insurmountable for the nearest hundreds of years. [51]

See also

Related Research Articles

Cognitive science interdisciplinary scientific study of the mind and its processes

Cognitive science is the interdisciplinary, scientific study of the mind and its processes. It examines the nature, the tasks, and the functions of cognition. Cognitive scientists study intelligence and behavior, with a focus on how nervous systems represent, process, and transform information. Mental faculties of concern to cognitive scientists include language, perception, memory, attention, reasoning, and emotion; to understand these faculties, cognitive scientists borrow from fields such as linguistics, psychology, artificial intelligence, philosophy, neuroscience, and anthropology. The typical analysis of cognitive science spans many levels of organization, from learning and decision to logic and planning; from neural circuitry to modular brain organization. The fundamental concept of cognitive science is that "thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures."

Neuroscience scientific study of the central nervous system

Neuroscience is the scientific study of the nervous system. It is a multidisciplinary branch of biology that combines physiology, anatomy, molecular biology, developmental biology, cytology, mathematical modeling and psychology to understand the fundamental and emergent properties of neurons and neural circuits. The understanding of the biological basis of learning, memory, behavior, perception, and consciousness has been described by Eric Kandel as the "ultimate challenge" of the biological sciences.

Artificial consciousness (AC), also known as machine consciousness (MC) or synthetic consciousness, is a field related to artificial intelligence and cognitive robotics. The aim of the theory of artificial consciousness is to "Define that which would have to be synthesized were consciousness to be found in an engineered artifact".

Computational neuroscience is a branch of neuroscience which uses computational approaches, to study the nervous system. Computational approaches include mathematics, statistics, computer simulations, and abstractions which are used across many subareas of neuroscience including development, structure, physiology and cognitive abilities of the nervous system.

Bio-inspired computing, short for biologically inspired computing, is a field of study that loosely knits together subfields related to the topics of connectionism, social behaviour and emergence. It is often closely related to the field of artificial intelligence, as many of its pursuits can be linked to machine learning. It relies heavily on the fields of biology, computer science and mathematics. Briefly put, it is the use of computers to model the living phenomena, and simultaneously the study of life to improve the usage of computers. Biologically inspired computing is a major subset of natural computation.

Artificial general intelligence (AGI) is the intelligence of a machine that has the capacity to understand or learn any intellectual task that a human being can. It is a primary goal of some artificial intelligence research and a common topic in science fiction and future studies. Some researchers refer to Artificial general intelligence as "strong AI", "full AI" or as the ability of a machine to perform "general intelligent action"; others reserve "strong AI" for machines capable of experiencing consciousness.

Neural circuit network or circuit of neurons

A neural circuit is a population of neurons interconnected by synapses to carry out a specific function when activated. Neural circuits interconnect to one another to form large scale brain networks. Biological neural networks have inspired the design of artificial neural networks, but artificial neural networks are usually not strict copies of their biological counterparts.

Neural network Structure in biology and artificial intelligence

A neural network is a network or circuit of neurons, or in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus a neural network is either a biological neural network, made up of real biological neurons, or an artificial neural network, for solving artificial intelligence (AI) problems. The connections of the biological neuron are modeled as weights. A positive weight reflects an excitatory connection, while negative values mean inhibitory connections. All inputs are modified by a weight and summed. This activity is referred as a linear combination. Finally, an activation function controls the amplitude of the output. For example, an acceptable range of output is usually between 0 and 1, or it could be −1 and 1.

An artificial brain is software and hardware with cognitive abilities similar to those of the animal or human brain.

The Blue Brain Project is a Swiss brain research initiative that aims to create a digital reconstruction of rodent and eventually human brains by reverse-engineering mammalian brain circuitry. The project was founded in May 2005 by the Brain and Mind Institute of École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. Its mission is to use biologically-detailed digital reconstructions and simulations of the mammalian brain to identify the fundamental principles of brain structure and function.

Mind uploading in fiction

Mind uploading, whole brain emulation, or substrate-independent minds is a use of a computer or another substrate as an emulated human brain, and the view of thoughts and memories as software information states. The term "mind transfer" also refers to a hypothetical transfer of a mind from one biological brain to another. Uploaded minds and societies of minds, often in simulated realities, are recurring themes in science-fiction novels and films since the 1950s.

Computational neurogenetic modeling (CNGM) is concerned with the study and development of dynamic neuronal models for modeling brain functions with respect to genes and dynamic interactions between genes. These include neural network models and their integration with gene network models. This area brings together knowledge from various scientific disciplines, such as computer and information science, neuroscience and cognitive science, genetics and molecular biology, as well as engineering.

Spiking neural network

Spiking neural networks (SNNs) are artificial neural networks that more closely mimic natural neural networks. In addition to neuronal and synaptic state, SNNs incorporate the concept of time into their operating model. The idea is that neurons in the SNN do not fire at each propagation cycle, but rather fire only when a membrane potential – an intrinsic quality of the neuron related to its membrane electrical charge – reaches a specific value. When a neuron fires, it generates a signal that travels to other neurons which, in turn, increase or decrease their potentials in accordance with this signal.

Neurorobotics, a combined study of neuroscience, robotics, and artificial intelligence, is the science and technology of embodied autonomous neural systems. Neural systems include brain-inspired algorithms, computational models of biological neural networks and actual biological systems. Such neural systems can be embodied in machines with mechanic or any other forms of physical actuation. This includes robots, prosthetic or wearable systems but also, at smaller scale, micro-machines and, at the larger scales, furniture and infrastructures.

Artificial Intelligence System (AIS) was a distributed computing project undertaken by Intelligence Realm, Inc. with the long-term goal of simulating the human brain in real time, complete with artificial consciousness and artificial general intelligence. They claimed to have found, in research, the "mechanisms of knowledge representation in the brain which is equivalent to finding artificial intelligence", before moving into the developmental phase.

Brain simulation is the concept of creating a functioning computer model of a brain or part of a brain. Modelling a brain involves both modelling neurons' electrical and bulk chemical properties. A model of the neural connectome of the target organism is also required. The connectome is extremely complex, and its detailed wiring is not yet understood; thus it is presently being modeled empirically in smaller mammals by projects like the Blue Brain Project.

Network of human nervous system comprises nodes that are connected by links. The connectivity may be viewed anatomically, functionally, or electrophysiologically. These are presented in several Wikipedia articles that include Connectionism, Biological neural network, Artificial neural network, Computational neuroscience, as well as in several books by Ascoli, G. A. (2002), Sterratt, D., Graham, B., Gillies, A., & Willshaw, D. (2011), Gerstner, W., & Kistler, W. (2002), and Rumelhart, J. L., McClelland, J. L., and PDP Research Group (1986) among others. The focus of this article is a comprehensive view of modeling a neural network. Once an approach based on the perspective and connectivity is chosen, the models are developed at microscopic, mesoscopic, or macroscopic (system) levels. Computational modeling refers to models that are developed using computing tools.

Hypothetical technology is technology that does not exist yet, but that could exist in the future. This article presents examples of technologies that have been hypothesized or proposed, but that have not been developed yet.

In computational neuroscience, SUPS or formerly CUPS is a measure of a neuronal network performance, useful in fields of neuroscience, cognitive science, artificial intelligence, and computer science.

Simon Stringer

Simon Stringer is a British mathematician, Director of the Oxford Centre for Theoretical Neuroscience and Artificial Intelligence, and Editor-in-Chief of Network: Computation in Neural Systems published by Taylor & Francis.

References

  1. A framework for approaches to transfer of a mind's substrate, Sim Bamford
  2. Goertzel, BEN; Ikle', Matthew (2012). "Introduction". International Journal of Machine Consciousness. 04: 1–3. doi:10.1142/S1793843012020015.
  3. Coalescing minds: brain uploading-related group mind scenarios
  4. Kay KN, Naselaris T, Prenger RJ, Gallant JL (March 2008). "Identifying natural images from human brain activity". Nature. 452 (7185): 352–5. Bibcode:2008Natur.452..352K. doi:10.1038/nature06713. PMC   3556484 . PMID   18322462.
  5. 1 2 3 4 5 6 7 8 Sandberg, Anders; Boström, Nick (2008). Whole Brain Emulation: A Roadmap (PDF). Technical Report #2008‐3. Future of Humanity Institute, Oxford University. Retrieved 5 April 2009. The basic idea is to take a particular brain, scan its structure in detail, and construct a software model of it that is so faithful to the original that, when run on appropriate hardware, it will behave in essentially the same way as the original brain.
  6. Goertzel, Ben (December 2007). "Human-level artificial general intelligence and the possibility of a technological singularity: a reaction to Ray Kurzweil's The Singularity Is Near, and McDermott's critique of Kurzweil". Artificial Intelligence. 171 (18, Special Review Issue): 1161–1173. doi:10.1016/j.artint.2007.10.011.
  7. 1 2 Koch, Christof; Tononi, Giulio (2008). "Can machines be conscious?" (PDF). IEEE Spectrum. 45 (6): 55. doi:10.1109/MSPEC.2008.4531463.
  8. 1 2 null. "Tech Luminaries Address Singularity". ieee.org.
  9. Marvin Minsky, Conscious Machines, in 'Machinery of Consciousness', Proceedings, National Research Council of Canada, 75th Anniversary Symposium on Science in Society, June 1991.
  10. Llinas, R (2001). I of the vortex: from neurons to self. Cambridge: MIT Press. pp. 261–262. ISBN   978-0-262-62163-2.
  11. Ray Kurzweil (February 2000). "Live Forever–Uploading The Human Brain...Closer Than You Think". Psychology Today.
  12. Martin GM (1971). "Brief proposal on immortality: an interim solution". Perspectives in Biology and Medicine. 14 (2): 339–340. doi:10.1353/pbm.1971.0015. PMID   5546258.
  13. Prisco, Giulio (12 December 2012). "Uploaded e-crews for interstellar missions". kurzweilai.net. Retrieved 31 July 2015.
  14. "Substrate-Independent Minds - Carboncopies.org Foundation". carboncopies.org.
  15. Roadmap p.11 "Given the complexities and conceptual issues of consciousness we will not examine criteria 6abc, but mainly examine achieving criteria 1‐5."
  16. "Bluebrain - EPFL". epfl.ch. 19 May 2015.
  17. Blue Brain Project FAQ Archived 2007-01-27 at the Wayback Machine , 2004
  18. BBC News, Artificial brain '10 years away'
  19. "New imaging method developed at Stanford reveals stunning details of brain connections". Stanford Medicine.
  20. Merkle, R., 1989, Large scale analysis of neural structures, CSL-89-10 November 1989, [P89-00173]
  21. 1 2 ATLUM Project Archived 2008-02-01 at the Wayback Machine
  22. Hagmann, Patric; Cammoun, Leila; Gigandet, Xavier; Meuli, Reto; Honey, Christopher J.; Wedeen, Van J.; Sporns, Olaf; Friston, Karl J. (2008). Friston, Karl J. (ed.). "Mapping the Structural Core of Human Cerebral Cortex". PLoS Biology. 6 (7): e159. doi:10.1371/journal.pbio.0060159. PMC   2443193 . PMID   18597554.
  23. Glover, Paul; Bowtell, Richard (2009). "Medical imaging: MRI rides the wave". Nature. 457 (7232): 971–2. Bibcode:2009Natur.457..971G. doi:10.1038/457971a. PMID   19225512.
  24. Franco Cortese (June 17, 2013). "Clearing Up Misconceptions About Mind Uploading". h+ Media.
  25. Yoonsuck Choe; Jaerock Kwon; Ji Ryang Chung (2012). "Time, Consciousness, and Mind Uploading" (PDF). International Journal of Machine Consciousness. 04 (1): 257. doi:10.1142/S179384301240015X.
  26. "The Duplicates Paradox (The Duplicates Problem)". benbest.com.
  27. 1 2 Schneider, Susan (March 2, 2014). "The Philosophy of 'Her'". The New York Times. Retrieved May 7, 2014.
  28. Fundamental neuroscience. Squire, Larry R. (3rd ed.). Amsterdam: Elsevier / Academic Press. 2008. ISBN   9780123740199. OCLC   190867431.CS1 maint: others (link)
  29. Hughes, James (2013). Transhumanism and Personal Identity. Wiley.
  30. Wiley, Keith (March 20, 2014). "Response to Susan Schneider's "Philosophy of 'Her"". H+Magazine. Retrieved 7 May 2014.
  31. Wiley, Keith (Sep 2014). A Taxonomy and Metaphysics of Mind-Uploading (1st ed.). Humanity+ Press and Alautun Press. ISBN   978-0692279847 . Retrieved 16 October 2014.
  32. Ruparel, Bhavik (2018-07-30). "On Achieving Immortality". Bhavik Ruparel. Retrieved 2018-07-31.
  33. Michael Hauskeller. "My Brain, my Mind, and I: Some Philosophical Problems of Mind-Uploading". Academia.edu. 04 (1): 187–200.
  34. George Dvorsky. "You Might Never Upload Your Brain Into a Computer". io9.
  35. Brandon Oto (2011), Seeking normative guidelines for novel future forms of consciousness (PDF), University of California, Santa Cruz
  36. Ben Goertzel (2012). "When Should Two Minds Be Considered Versions of One Another?" (PDF).
  37. Sally Morem (April 21, 2013). "Goertzel Contra Dvorsky on Mind Uploading". h+ Media.
  38. Martine Rothblatt (2012). "The Terasem Mind Uploading Experiment" (PDF). International Journal of Machine Consciousness. 4 (1): 141–158. doi:10.1142/S1793843012400070. Archived from the original (PDF) on 2013-08-27.
  39. Patrick D. Hopkins (2012). "Why Uploading Will Not Work, or, the Ghosts Haunting Transhumanism" (PDF). International Journal of Machine Consciousness. 4 (1). doi:10.1142/S179384301250014X (inactive 2019-08-20). Archived from the original (PDF) on 2012-09-06.
  40. 1 2 3 4 5 Anders Sandberg (14 Apr 2014). "Ethics of brain emulations". Journal of Experimental & Theoretical Artificial Intelligence. 26 (3): 439–457. doi:10.1080/0952813X.2014.895113.
  41. Jack McKay Fletcher (December 2015). "A computational mind cannot recognize itself". Technoetic Arts. 13 (3): 261–267. doi:10.1386/tear.13.3.261_1.
  42. 1 2 Tyler D. Bancroft (Aug 2013). "Ethical Aspects of Computational Neuroscience". Neuroethics. 6 (2): 415–418. doi:10.1007/s12152-012-9163-7. ISSN   1874-5504.
  43. 1 2 3 4 5 6 7 8 9 Peter Eckersley; Anders Sandberg (Dec 2013). "Is Brain Emulation Dangerous?". Journal of Artificial General Intelligence. 4 (3): 170–194. Bibcode:2013JAGI....4..170E. doi:10.2478/jagi-2013-0011. ISSN   1946-0163.
  44. 1 2 Kamil Muzyka (Dec 2013). "The Outline of Personhood Law Regarding Artificial Intelligences and Emulated Human Entities". Journal of Artificial General Intelligence. 4 (3): 164–169. Bibcode:2013JAGI....4..164M. doi:10.2478/jagi-2013-0010. ISSN   1946-0163.
  45. Shulman, Carl; Anders Sandberg (2010). Mainzer, Klaus (ed.). "Implications of a Software-Limited Singularity" (PDF). ECAP10: VIII European Conference on Computing and Philosophy. Retrieved 17 May 2014.
  46. 1 2 Hanson, Robin (26 Nov 2009). "Bad Emulation Advance". Overcoming Bias. Retrieved 28 June 2014.
  47. Muehlhauser, Luke; Anna Salamon (2012). "Intelligence Explosion: Evidence and Import" (PDF). In Amnon Eden; Johnny Søraker; James H. Moor; Eric Steinhart (eds.). Singularity Hypotheses: A Scientific and Philosophical Assessment. Springer.
  48. 1 2 3 Anna Salamon; Luke Muehlhauser (2012). "Singularity Summit 2011 Workshop Report" (PDF). Machine Intelligence Research Institute. Retrieved 28 June 2014.
  49. 1 2 3 4 5 6 7 8 9 10 11 12 13 Bostrom, Nick (2014). "Ch. 14: The strategic picture". Superintelligence: Paths, Dangers, Strategies. Oxford University Press. ISBN   978-0199678112.
  50. "Mind uploading & digital immortality may be reality by 2045, futurists say - KurzweilAI". kurzweilai.net.
  51. Will You Ever Be Able to Upload Your Brain?, www.nytimes.com