Technological singularity

"The Singularity" redirects here. For other uses, see Singularity (disambiguation).

The technological singularity—or simply the singularity^[1]—is a hypothetical point in time at which technological growth becomes uncontrollable and irreversible, resulting in unforeseeable consequences for human civilization.^[2][3] According to the most popular version of the singularity hypothesis, I. J. Good's intelligence explosion model of 1965, an upgradable intelligent agent could eventually enter a positive feedback loop of successive self-improvement cycles; more intelligent generations would appear more and more rapidly, causing a rapid increase ("explosion") in intelligence that culminates in a powerful superintelligence, far surpassing all human intelligence.^[4]

The Hungarian-American mathematician John von Neumann (1903–1957) is the first known person to use the concept of a "singularity" in a technological context.^[5][6]

Alan Turing, often regarded as the father of modern computer science, laid a crucial foundation for contemporary discourse on the technological singularity. His pivotal 1950 paper "Computing Machinery and Intelligence" introduced the idea of a machine's ability to exhibit intelligent behavior equivalent to or indistinguishable from that of a human.^[7]

Stanislaw Ulam reported in 1958 that an earlier discussion with von Neumann "centered on the accelerating progress of technology and changes in human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue".^[8] Subsequent authors have echoed this viewpoint.^[3][9]

The concept and the term "singularity" were popularized by Vernor Vinge: first in 1983, in an article that claimed that, once humans create intelligences greater than their own, there will be a technological and social transition similar in some sense to "the knotted space-time at the center of a black hole";^[10] and then in his 1993 essay "The Coming Technological Singularity",^[4][9] in which he wrote that it would signal the end of the human era, as the new superintelligence would continue to upgrade itself and advance technologically at an incomprehensible rate, and he would be surprised if it occurred before 2005 or after 2030.^[4]

Another significant contribution to wider circulation of the notion was Ray Kurzweil's 2005 book The Singularity Is Near, predicting singularity by 2045.^[9]

Some scientists, including Stephen Hawking, have expressed concern that artificial superintelligence (ASI) could result in human extinction.^[11][12] The consequences of a technological singularity and its potential benefit or harm to the human race have been intensely debated.^{[citation needed]}

Prominent technologists and academics dispute the plausibility of a technological singularity and associated artificial intelligence explosion, including Paul Allen,^[13] Jeff Hawkins,^[14] John Holland, Jaron Lanier, Steven Pinker,^[14] Theodore Modis,^[15] Gordon Moore,^[14] and Roger Penrose.^[16] One claim is that artificial intelligence growth is likely to run into decreasing returns instead of accelerating ones, as was observed in previously developed human technologies.^{[citation needed]}

Intelligence explosion

Further information: Recursive self-improvement

Although technological progress has been accelerating in most areas, it has been limited by the basic intelligence of the human brain, which has not, according to Paul R. Ehrlich, changed significantly for millennia.^[17] But with the increasing power of computers and other technologies, it might eventually be possible to build a machine significantly more intelligent than humans.^[18]

If superhuman intelligence is invented—through either the amplification of human intelligence or artificial intelligence—it will, in theory, vastly surpass human problem-solving and inventive skill. Such an AI is called Seed AI^[19][20] because if an AI is created with engineering capabilities that match or surpass those of its creators, it could autonomously improve its own software and hardware to design an even more capable machine, which could repeat the process in turn. This recursive self-improvement could accelerate, potentially allowing enormous qualitative change before reaching any limits imposed by the laws of physics or theoretical computation. It is speculated that over many iterations, such an AI would far surpass human cognitive abilities.

I. J. Good speculated that superhuman intelligence might bring about an intelligence explosion:^[21][22]

Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an 'intelligence explosion', and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control.

— Speculations Concerning the First Ultraintelligent Machine (1965)

One version of intelligence explosion is where computing power approaches infinity in a finite amount of time. In this version, once AIs are performing the research to improve themselves, speed doubles e.g. after 2 years, then 1 year, then 6 months, then 3 months, then 1.5 months, etc., where the infinite sum of the doubling periods is 4 years. Unless prevented by physical limits of computation and time quantization, this process would achieve infinite computing power in 4 years, properly earning the name "singularity" for the final state. This form of intelligence explosion is described in Yudkowsky (1996).^[23]

Emergence of superintelligence

Further information: Superintelligence

A superintelligence, hyperintelligence, or superhuman intelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted humans.^[24] "Superintelligence" may also refer to the form or degree of intelligence possessed by such an agent. John von Neumann, Vernor Vinge, and Ray Kurzweil define the concept in terms of the technological creation of super intelligence, arguing that it is difficult or impossible for present-day humans to predict what human beings' lives would be like in a post-singularity world.^[4][25]

The related concept "speed superintelligence" describes an AI that can function like a human mind but much faster.^[26] For example, with a millionfold increase in the speed of information processing relative to that of humans, a subjective year would pass in 30 physical seconds.^[27] Such a difference in information processing speed could drive the singularity.^[28]

Technology forecasters and researchers disagree about when, or whether, human intelligence will likely be surpassed. Some argue that advances in artificial intelligence (AI) will probably result in general reasoning systems that bypass human cognitive limitations. Others believe that humans will evolve or directly modify their biology so as to achieve radically greater intelligence.^[29][30] A number of futures studies focus on scenarios that combine these possibilities, suggesting that humans are likely to interface with computers, or upload their minds to computers, in a way that enables substantial intelligence amplification. Robin Hanson's 2016 book The Age of Em describes a future in which human brains are scanned and digitized, creating "uploads" or digital versions of human consciousness. In this future, the development of these uploads may precede or coincide with the emergence of superintelligent artificial intelligence.^[31]

Variations

Non-AI singularity

Some writers use "the singularity" in a broader way, to refer to any radical changes in society brought about by new technology (such as molecular nanotechnology),^[32][33][34] although Vinge and other writers say that without superintelligence, such changes would not be a true singularity.^[4]

Predictions

Progress of AI performance on various benchmarks compared to human-level performance.^[35]

Numerous dates have been predicted for the attainment of singularity.

In 1965, Good wrote that it was more probable than not that an ultra-intelligent machine would be built in the 20th century.^[21]

That computing capabilities for human-level AI would be available in supercomputers before 2010 was predicted in 1988 by Moravec, assuming that the current rate of improvement continued.^[36]

The attainment of greater-than-human intelligence between 2005 and 2030 was predicted by Vinge in 1993.^[4]

A singularity in 2021 was predicted by Yudkowsky in 1996.^[23]

Human-level AI around 2029 and the singularity in 2045 was predicted by Kurzweil in 2005.^[37][38] He reaffirmed these predictions in 2024 in The Singularity is Nearer.^[39]

Human-level AI by 2040, and intelligence far beyond human by 2050 was predicted in 1998 by Moravec, revising his earlier prediction.^[40]

A confidence of 50% that human-level AI would be developed by 2040–2050 was the outcome of four polls of AI researchers, conducted in 2012 and 2013 by Bostrom and Müller.^[41][42]

Elon Musk in March 2025 predicted that AI would be smarter than any individual human "in the next year or two" and that AI would be smarter than all humans combined by 2029 or 2030, along with an 80% chance that AI will have a "good outcome" and a 20% chance of "annihilation".^[43]

Plausibility

Prominent technologists and academics who dispute the plausibility of a technological singularity include Paul Allen,^[13] Jeff Hawkins,^[14] John Holland, Jaron Lanier, Steven Pinker,^[14] Theodore Modis,^[15] and Gordon Moore,^[14] whose law is often cited in support of the concept.^[44]

Most proposed methods for creating superhuman or transhuman minds fall into two categories: intelligence amplification of human brains and artificial intelligence. The many speculated ways to augment human intelligence include bioengineering, genetic engineering, nootropic drugs, AI assistants, direct brain–computer interfaces, and mind uploading. These possible paths to an intelligence explosion, all of which will presumably be pursued, make a singularity more likely.^[27]

Robin Hanson has expressed skepticism of human intelligence augmentation, writing that once the "low-hanging fruit" of easy methods for increasing human intelligence have been exhausted, further improvements will become increasingly difficult.^[45] Despite all the speculated ways to amplify human intelligence, nonhuman artificial intelligence (specifically seed AI) is the most popular option among the hypotheses that would advance the singularity.^{[citation needed]}

The possibility of an intelligence explosion depends on three factors.^[46] The first accelerating factor is the new intelligence enhancements made possible by each previous improvement. But as the intelligences become more advanced, further advances will become more and more complicated, possibly outweighing the advantage of increased intelligence. Each improvement should generate at least one more improvement, on average, for movement toward singularity to continue. Finally, the laws of physics may eventually prevent further improvement.

There are two logically independent, but mutually reinforcing, causes of intelligence improvements: increases in the speed of computation and improvements to the algorithms used.^[9] The former is predicted by Moore's Law and the forecasted improvements in hardware,^[47] and is comparatively similar to previous technological advances. But Schulman and Sandberg^[48] argue that software will present more complex challenges than simply operating on hardware capable of running at human intelligence levels or beyond.

A 2017 email survey of authors with publications at the 2015 NeurIPS and ICML machine learning conferences asked about the chance that "the intelligence explosion argument is broadly correct". Of the respondents, 12% said it was "quite likely", 17% said it was "likely", 21% said it was "about even", 24% said it was "unlikely", and 26% said it was "quite unlikely".^[49]

Speed improvements

Both for human and artificial intelligence, hardware improvements increase the rate of future hardware improvements. An analogy to Moore's Law suggests that if the first doubling of speed took 18 months, the next would take 18 subjective months—nine external months—and the next four months, two months, and so on toward a speed singularity.^[50][23] Some upper limit on speed may eventually be reached. Jeff Hawkins has said that a self-improving computer system will inevitably run into limits on computing power: "in the end there are limits to how big and fast computers can run. We would end up in the same place; we'd just get there a bit faster. There would be no singularity."^[14]

It is difficult to directly compare silicon-based hardware with neurons. But Berglas (2008) notes that computer speech recognition is approaching human capabilities, and that this capability seems to require 0.01% of the volume of the brain. This analogy suggests that modern computer hardware is within a few orders of magnitude of being as powerful as the human brain, as well as taking up a lot less space. But the costs of training systems with deep learning may be larger.^{[citation needed][a]}

Exponential growth

Ray Kurzweil writes that, due to paradigm shifts, a trend of exponential growth extends Moore's law from integrated circuits to earlier transistors, vacuum tubes, relays, and electromechanical computers. He predicts that the exponential growth will continue, and that in a few decades the computing power of all computers will exceed that of ("unenhanced") human brains, with superhuman artificial intelligence appearing around the same time.

An updated version of Moore's law over 120 Years (based on Kurzweil's graph). The 7 most recent data points are all Nvidia GPUs.

The exponential growth in computing technology suggested by Moore's law is commonly cited as a reason to expect a singularity in the relatively near future, and a number of authors have proposed generalizations of Moore's law. Computer scientist and futurist Hans Moravec proposed in a 1998 book^[53] that the exponential growth curve could be extended back to earlier computing technologies before the integrated circuit.

Ray Kurzweil postulates a law of accelerating returns whereby the speed of technological change (and more generally, all evolutionary processes)^[54] increases exponentially, generalizing Moore's law in the same manner as Moravec's proposal, and also including material technology (especially as applied to nanotechnology) and medical technology.^[55] Between 1986 and 2007, machines' application-specific capacity to compute information per capita roughly doubled every 14 months; the per capita capacity of the world's general-purpose computers has doubled every 18 months; the global telecommunication capacity per capita doubled every 34 months; and the world's storage capacity per capita doubled every 40 months.^[56] On the other hand, it has been argued that the global acceleration pattern having a 21st-century singularity as its parameter should be characterized as hyperbolic rather than exponential.^[57]

Kurzweil reserves the term "singularity" for a rapid increase in artificial intelligence (as opposed to other technologies), writing: "The Singularity will allow us to transcend these limitations of our biological bodies and brains ... There will be no distinction, post-Singularity, between human and machine".^[58] He also defines the singularity as when computer-based intelligences significantly exceed the sum total of human brainpower, writing that advances in computing before that "will not represent the Singularity" because they do "not yet correspond to a profound expansion of our intelligence."^[59]

Accelerating change

According to Kurzweil, his logarithmic graph of 15 lists of paradigm shifts for key historic events shows an exponential trend.

Main article: Accelerating change

Some singularity proponents argue its inevitability through extrapolation of past trends, especially those pertaining to shortening gaps between improvements to technology. In one of the first uses of the term "singularity" in the context of technological progress, Stanislaw Ulam tells of a conversation with John von Neumann about accelerating change:

One conversation centered on the ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue.^[8]

Kurzweil claims that technological progress follows a pattern of exponential growth, following what he calls the "law of accelerating returns". Whenever technology approaches a barrier, Kurzweil writes, new technologies surmount it. He predicts paradigm shifts will become increasingly common, leading to "technological change so rapid and profound it represents a rupture in the fabric of human history".^[60] Kurzweil believes that the singularity will occur by 2045.^[55] His predictions differ from Vinge's in that he predicts a gradual ascent to the singularity, rather than Vinge's rapidly self-improving superhuman intelligence.

Oft-cited dangers include those commonly associated with molecular nanotechnology and genetic engineering. These threats are major issues for both singularity advocates and critics, and were the subject of Bill Joy's 2000 Wired magazine article "Why The Future Doesn't Need Us".^[9][61]

Algorithm improvements

Some intelligence technologies, like "seed AI",^[19][20] may also be able to make themselves not just faster but also more efficient, by modifying their source code. These improvements would make further improvements possible, which would make further improvements possible, and so on.

The mechanism for a recursively self-improving set of algorithms differs from an increase in raw computation speed in two ways. First, it does not require external influence: machines designing faster hardware would still require humans to create the improved hardware, or to program factories appropriately.^{[citation needed]} An AI rewriting its own source code could do so while contained in an AI box.

Second, as with Vernor Vinge's conception of the singularity, it is much harder to predict the outcome. While speed increases seem to be only a quantitative difference from human intelligence, actual algorithm improvements would be qualitatively different. Eliezer Yudkowsky compares it to the changes that human intelligence brought: humans changed the world thousands of times more quickly than evolution did, and in totally different ways. Similarly, the evolution of life was a massive departure and acceleration from geological rates of change, and improved intelligence could cause change to be as different again.^[62]

Substantial dangers are associated with an intelligence explosion singularity originating from a recursively self-improving set of algorithms. First, the goal structure of the AI might self-modify, potentially causing the AI to optimise for something other than what was originally intended.^[63][64] Second, AIs could compete for the resources humankind uses to survive.^[65][66] While not actively malicious, AIs would promote the goals of their programming, not necessarily broader human goals, and thus might crowd humans out.^[67][68][69]

Carl Shulman and Anders Sandberg suggest that algorithm improvements may be the limiting factor for a singularity; while hardware efficiency tends to improve at a steady pace, software innovations are more unpredictable and may be bottlenecked by serial, cumulative research. They suggest that in the case of a software-limited singularity, intelligence explosion would actually become more likely than with a hardware-limited singularity, because in the software-limited case, once human-level AI is developed, it could run serially on very fast hardware, and the abundance of cheap hardware would make AI research less constrained.^[70] An abundance of accumulated hardware that can be unleashed once the software figures out how to use it has been called "computing overhang".^[71]

Criticism

Some critics, like philosophers Hubert Dreyfus^[72] and John Searle,^[73] assert that computers or machines cannot achieve human intelligence. Others, like physicist Stephen Hawking,^[74] object that whether machines can achieve a true intelligence or merely something similar to intelligence is irrelevant if the net result is the same.

Psychologist Steven Pinker wrote in 2008: "There is not the slightest reason to believe in a coming singularity. The fact that you can visualize a future in your imagination is not evidence that it is likely or even possible. Look at domed cities, jet-pack commuting, underwater cities, mile-high buildings, and nuclear-powered automobiles—all staples of futuristic fantasies when I was a child that have never arrived. Sheer processing power is not a pixie dust that magically solves all your problems."^[14]

Martin Ford^[75] postulates a "technology paradox": before the singularity could occur, most routine jobs would be automated, since this would require a level of technology inferior to that of the singularity. This would cause massive unemployment and plummeting consumer demand, which in turn would destroy the incentive to invest in the technology required to bring about the singularity. Job displacement is increasingly no longer limited to the types of work traditionally considered "routine".^[76]

Theodore Modis^[77] and Jonathan Huebner^[78] argue that the rate of technological innovation has not only ceased to rise, but is actually now declining. Evidence for this decline is that the rise in computer clock rates is slowing, even while Moore's prediction of exponentially increasing circuit density continues to hold. This is due to excessive heat buildup from the chip, which cannot be dissipated quickly enough to prevent it from melting when operating at higher speeds. Advances in speed may be possible in the future by virtue of more power-efficient CPU designs and multi-cell processors.^[79]

Theodore Modis holds the singularity cannot happen.^[80][15][81] He claims the "technological singularity" and especially Kurzweil lack scientific rigor; Kurzweil is alleged to mistake the logistic function (S-function) for an exponential function, and to see a "knee" in an exponential function where there can in fact be no such thing.^[82] In a 2021 article, Modis wrote that no milestones—breaks in historical perspective comparable in importance to the Internet, DNA, the transistor, or nuclear energy—had been observed in the previous 20 years, while five of them would have been expected according to the exponential trend advocated by proponents of the technological singularity.^[83]

AI researcher Jürgen Schmidhuber has said that the frequency of subjectively "notable events" appears to be approaching a 21st-century singularity, but cautioned readers to take such plots of subjective events with a grain of salt: perhaps differences in memory of recent and distant events create an illusion of accelerating change where none exists.^[84]

Microsoft co-founder Paul Allen argued the opposite of accelerating returns, the complexity brake:^[13] the more progress science makes toward understanding intelligence, the more difficult it becomes to make additional progress. A study of the number of patents shows that human creativity does not show accelerating returns, but in fact, as suggested by Joseph Tainter in his The Collapse of Complex Societies,^[85] a law of diminishing returns. The number of patents per thousand peaked in the period from 1850 to 1900, and has been declining since.^[78] The growth of complexity eventually becomes self-limiting, and leads to a widespread "general systems collapse".

Hofstadter (2006) raises concern that Kurzweil is insufficiently rigorous, that an exponential tendency of technology is not a scientific law like one of physics, and that exponential curves have no "knees".^[86] Nonetheless, he did not rule out the singularity in principle in the distant future^[14] and in light of ChatGPT and other recent advancements has revised his opinion significantly toward dramatic technological change in the near future.^[87]

Jaron Lanier denies that the singularity is inevitable: "I do not think the technology is creating itself. It's not an autonomous process."^[88] Furthermore: "The reason to believe in human agency over technological determinism is that you can then have an economy where people earn their own way and invent their own lives. If you structure a society on not emphasizing individual human agency, it's the same thing operationally as denying people clout, dignity, and self-determination ... to embrace [the idea of the Singularity] would be a celebration of bad data and bad politics."^[88]

Economist Robert J. Gordon points out that measured economic growth slowed around 1970 and slowed even further since the 2008 financial crisis, and argues that the economic data show no trace of a coming Singularity as imagined by I. J. Good.^[89]

Philosopher and cognitive scientist Daniel Dennett said in 2017: "The whole singularity stuff, that's preposterous. It distracts us from much more pressing problems", adding: "AI tools that we become hyper-dependent on—that is going to happen. And one of the dangers is that we will give them more authority than they warrant."^[90]

In addition to general criticisms of the singularity concept, several critics have raised issues with Kurzweil's iconic chart. One line of criticism is that a log-log chart of this nature is inherently biased toward a straight-line result. Others identify selection bias in the points Kurzweil uses. For example, biologist PZ Myers points out that many of the early evolutionary "events" were picked arbitrarily.^[91] Kurzweil has rebutted this by charting evolutionary events from 15 neutral sources and showing that they fit a straight line on a log-log chart. Kelly (2006) argues that the way the Kurzweil chart is constructed, with the x-axis having time before the present, it always points to the singularity being "now", for any date on which one would construct such a chart, and shows this visually on Kurzweil's chart.^[92]

Some critics suggest religious motivations or implications of singularity, especially Kurzweil's version. The buildup to the singularity is compared with Christian end-of-time scenarios. Beam calls it "a Buck Rogers vision of the hypothetical Christian Rapture".^[93] John Gray says "the Singularity echoes apocalyptic myths in which history is about to be interrupted by a world-transforming event".^[94]

David Streitfeld in The New York Times questioned whether "it might manifest first and foremost—thanks, in part, to the bottom-line obsession of today’s Silicon Valley—as a tool to slash corporate America’s head count."^[95]

Astrophysicist and scientific philosopher Adam Becker criticizes Kurzweil's concept of human mind uploads to computers on the grounds that they are too fundamentally different and incompatible.^[96]

Potential impacts

Dramatic changes in the rate of economic growth have occurred in the past because of technological advancement. Based on population growth, the economy doubled every 250,000 years from the Paleolithic era until the Neolithic Revolution. The new agricultural economy doubled every 900 years, a remarkable increase. Since the Industrial Revolution, the world's economic output has doubled every 15 years, 60 times faster than during the agricultural era. If the rise of superhuman intelligence causes a similar revolution, argues Robin Hanson, one would expect the economy to double at least quarterly and possibly weekly.^[97]

Uncertainty and risk

Further information: Existential risk from artificial general intelligence

The term "technological singularity" reflects the idea that such change may happen suddenly and that it is difficult to predict how the resulting new world would operate.^[98][99] It is unclear whether an intelligence explosion resulting in a singularity would be beneficial or harmful, or even an existential threat.^[100][101] Because AI is a major factor in singularity risk, several organizations pursue a technical theory of aligning AI goal-systems with human values, including the Future of Humanity Institute (until 2024), the Machine Intelligence Research Institute,^[98] the Center for Human-Compatible Artificial Intelligence, and the Future of Life Institute.

Physicist Stephen Hawking said in 2014: "Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks."^[102] Hawking believed that in the coming decades, AI could offer "incalculable benefits and risks" such as "technology outsmarting financial markets, out-inventing human researchers, out-manipulating human leaders, and developing weapons we cannot even understand."^[102] He suggested that artificial intelligence should be taken more seriously and that more should be done to prepare for the singularity:^[102]

So, facing possible futures of incalculable benefits and risks, the experts are surely doing everything possible to ensure the best outcome, right? Wrong. If a superior alien civilisation sent us a message saying, "We'll arrive in a few decades," would we just reply, "OK, call us when you get here – we'll leave the lights on"? Probably not – but this is more or less what is happening with AI.

Berglas (2008) claims that there is no direct evolutionary motivation for AI to be friendly to humans. Evolution has no inherent tendency to produce outcomes valued by humans, and there is little reason to expect an arbitrary optimisation process to promote an outcome desired by humankind, rather than inadvertently leading to an AI behaving in a way not intended by its creators.^{[103][104][105]} Anders Sandberg has elaborated on this, addressing various common counter-arguments.^[106] AI researcher Hugo de Garis suggests that artificial intelligences may simply eliminate the human race for access to scarce resources,^[65][63] and humans would be powerless to stop them.^[107] Alternatively, AIs developed under evolutionary pressure to promote their own survival could outcompete humanity.^[69]

Bostrom (2002) discusses human extinction scenarios, and lists superintelligence as a possible cause:

When we create the first superintelligent entity, we might make a mistake and give it goals that lead it to annihilate humankind, assuming its enormous intellectual advantage gives it the power to do so. For example, we could mistakenly elevate a subgoal to the status of a supergoal. We tell it to solve a mathematical problem, and it complies by turning all the matter in the solar system into a giant calculating device, in the process killing the person who asked the question.

According to Eliezer Yudkowsky, a significant problem in AI safety is that unfriendly AI is likely to be much easier to create than friendly AI. Both require large advances in recursive optimisation process design, but friendly AI also requires the ability to make goal structures invariant under self-improvement (or the AI could transform itself into something unfriendly) and a goal structure that aligns with human values and does not automatically destroy the human race. An unfriendly AI, on the other hand, can optimize for an arbitrary goal structure, which does not need to be invariant under self-modification.^[108] Bill Hibbard (2014) harvtxt error: no target: CITEREFBill_Hibbard2014 (help) proposes an AI design that avoids several dangers, including self-delusion,^[109] unintended instrumental actions,^[63][110] and corruption of the reward generator.^[110] He also discusses social impacts of AI^[111] and testing AI.^[112] His 2001 book Super-Intelligent Machines advocates public education about AI and public control over AI. It also proposes a simple design that is vulnerable to corruption of the reward generator.

Next step of sociobiological evolution

Further information: Sociocultural evolution

Schematic Timeline of Information and Replicators in the Biosphere: Gillings et al.'s "major evolutionary transitions" in information processing.^[113]

Amount of digital information worldwide (5×10²¹ bytes) versus human genome information worldwide (10¹⁹ bytes) in 2014^[113]

While the technological singularity is usually seen as a sudden event, some scholars argue the current speed of change already fits this description.^{[citation needed]}

In addition, some argue that we are already in the midst of a major evolutionary transition that merges technology, biology, and society. Digital technology has infiltrated the fabric of human society to a degree of indisputable and often life-sustaining dependence.

A 2016 article in Trends in Ecology & Evolution argues that "humans already embrace fusions of biology and technology. We spend most of our waking time communicating through digitally mediated channels... we trust artificial intelligence with our lives through antilock braking in cars and autopilots in planes... With one in three courtships leading to marriages in America beginning online, digital algorithms are also taking a role in human pair bonding and reproduction".

The article further argues that from the perspective of evolution, several previous Major Transitions in Evolution have transformed life through innovations in information storage and replication (RNA, DNA, multicellularity, and culture and language). In the current stage of life's evolution, the carbon-based biosphere has generated a system (humans) capable of creating technology that will result in a comparable evolutionary transition.

The digital information created by humans has reached a similar magnitude to biological information in the biosphere. Since the 1980s, the quantity of digital information stored has doubled about every 2.5 years, reaching about 5 zettabytes in 2014 (5×10²¹ bytes).^[114]

In biological terms, there are 7.2 billion humans on the planet, each with a genome of 6.2 billion nucleotides. Since one byte can encode four nucleotide pairs, the individual genomes of every human could be encoded by approximately 1×10¹⁹ bytes. The digital realm stored 500 times more information than this in 2014 (see figure). The total amount of DNA contained in all of the cells on Earth is estimated to be about 5.3×10³⁷ base pairs, equivalent to 1.325×10³⁷ bytes of information.

If growth in digital storage continues at its current rate of 30–38% compound annual growth per year,^[56] it will rival the total information content contained in all of the DNA in all of the cells on Earth in about 110 years. This would represent a doubling of the amount of information stored in the biosphere in just 150 years.^[113]

Implications for human society

Further information: Artificial intelligence in fiction

In 2009, under the auspices of the Association for the Advancement of Artificial Intelligence (AAAI), Eric Horvitz chaired a meeting of leading computer scientists, artificial intelligence researchers, and roboticists at the Asilomar conference center in Pacific Grove, California. The goal was to discuss the impact of the possibility that robots could become self-sufficient and able to make their own decisions. They discussed the extent to which computers and robots might acquire autonomy, and to what degree they could use such abilities to pose threats or hazards.^[115]

Some machines are programmed with various forms of semi-autonomy, including the ability to locate their own power sources and choose targets to attack with weapons. Also, some computer viruses can evade elimination and, according to scientists in attendance, could therefore be said to have reached a "cockroach" stage of machine intelligence. The conference attendees noted that self-awareness as depicted in science fiction is probably unlikely, but that other potential hazards and pitfalls exist.^[115]

Frank S. Robinson predicts that once humans achieve a machine with the intelligence of a human, scientific and technological problems will be tackled and solved with brainpower far superior to that of humans. He notes that artificial systems are able to share data more directly than humans, and predicts that this will result in a global network of super-intelligence that dwarfs human capability.^[116] Robinson also discusses how vastly different the future would look after such an intelligence explosion.

Hard or soft takeoff

In this sample recursive self-improvement scenario, humans modifying an AI's architecture would be able to double its performance every three years through, for example, 30 generations before exhausting all feasible improvements (left). If instead the AI is smart enough to modify its own architecture as well as human researchers can, its time required to complete a redesign halves with each generation, and it progresses all 30 feasible generations in six years (right).^[117]

In a hard takeoff scenario, an artificial superintelligence rapidly self-improves, "taking control" of the world (perhaps in a matter of hours), too quickly for significant human-initiated error correction or for a gradual tuning of the agent's goals. In a soft takeoff, the AI still becomes far more powerful than humanity, but at a human-like pace (perhaps on the order of decades), on a timescale where ongoing human interaction and correction can effectively steer its development.^[118][119]

Ramez Naam argues against a hard takeoff. He has pointed out that we already see recursive self-improvement by superintelligences, such as corporations. Intel, for example, has "the collective brainpower of tens of thousands of humans and probably millions of CPU cores to... design better CPUs!" But this has not led to a hard takeoff; rather, it has led to a soft takeoff in the form of Moore's law.^[120] Naam further points out that the computational complexity of higher intelligence may be much greater than linear, such that "creating a mind of intelligence 2 is probably more than twice as hard as creating a mind of intelligence 1."^[121]

J. Storrs Hall believes that "many of the more commonly seen scenarios for overnight hard takeoff are circular – they seem to assume hyperhuman capabilities at the starting point of the self-improvement process" in order for an AI to be able to make the dramatic, domain-general improvements required for takeoff. Hall suggests that rather than recursively self-improving its hardware, software, and infrastructure all on its own, a fledgling AI would be better off specializing in one area where it was most effective and then buying the remaining components on the marketplace, because the quality of products on the marketplace continually improves, and the AI would have a hard time keeping up with the cutting-edge technology used by the rest of the world.^[122]

Ben Goertzel agrees with Hall's suggestion that a new human-level AI would do well to use its intelligence to accumulate wealth. The AI's talents might inspire companies and governments to disperse its software throughout society. Goertzel is skeptical of a hard five-minute takeoff but speculates that a takeoff from human to superhuman level on the order of five years is reasonable. He calls this a "semihard takeoff".^[123]

Max More disagrees, arguing that if there were only a few superfast human-level AIs, that they would not radically change the world, as they would still depend on other people to get things done and would still have human cognitive constraints. Even if all superfast AIs worked on intelligence augmentation, it is unclear why they would do better in a discontinuous way than existing human cognitive scientists at producing superhuman intelligence, although the rate of progress would increase. More further argues that superintelligence would not transform the world overnight: it would need to engage with existing, slow human systems to have physical impact on the world. "The need for collaboration, for organization, and for putting ideas into physical changes will ensure that all the old rules are not thrown out overnight or even within years."^[124]

Relation to immortality and aging

Eric Drexler, one of the founders of nanotechnology, theorized in 1986 the possibility of cell repair devices, including ones operating within cells and using as yet hypothetical biological machines.^[125] According to Richard Feynman, his former graduate student and collaborator Albert Hibbs originally suggested to him (circa 1959) the idea of a medical use for Feynman's theoretical micromachines. Hibbs suggested that certain repair machines might one day be shrunk to the point that it would, in theory, be possible to (as Feynman put it) "swallow the doctor". The idea was incorporated into Feynman's 1959 essay There's Plenty of Room at the Bottom.^[126]

Moravec predicted in 1988 the possibility of "uploading" human mind into a human-like robot, achieving quasi-immortality by extreme longevity via transfer of the human mind between successive new robots as the old ones wear out; beyond that, he predicts later exponential acceleration of subjective experience of time leading to a subjective sense of immortality.^[36]

Kurzweil suggested in 2005 that medical advances would allow people to protect their bodies from the effects of aging, making the life expectancy limitless. He argues that technological advances in medicine would allow us to continuously repair and replace defective components in our bodies, prolonging life to an undetermined age.^[127] Kurzweil buttresses his argument by discussing current bio-engineering advances. He suggests somatic gene therapy; after synthetic viruses with specific genetic information, the next step is to apply this technology to gene therapy, replacing human DNA with synthesized genes.^[128]

Beyond merely extending the operational life of the physical body, Jaron Lanier argues for a form of immortality called "Digital Ascension" that involves "people dying in the flesh and being uploaded into a computer and remaining conscious."^[129]

History of the concept

A paper by Mahendra Prasad, published in AI Magazine, asserts that the 18th-century mathematician Marquis de Condorcet first hypothesized and mathematically modeled an intelligence explosion and its effects on humanity.^[130]

An early description of the idea was made in John W. Campbell's 1932 short story "The Last Evolution".^[131]

In his 1958 obituary for John von Neumann, Ulam recalled a conversation with him about the "ever accelerating progress of technology and changes in the mode of human life, which gives the appearance of approaching some essential singularity in the history of the race beyond which human affairs, as we know them, could not continue."^[8]

In 1965, Good wrote his essay postulating an "intelligence explosion" of recursive self-improvement of a machine intelligence.^[21][22]

In 1977, Hans Moravec wrote an article with unclear publishing status where he envisioned a development of self-improving thinking machines, a creation of "super-consciousness, the synthesis of terrestrial life, and perhaps jovian and martian life as well, constantly improving and extending itself, spreading outwards from the solar system, converting non-life into mind."^[132][133] The article describes the human mind uploading later covered in Moravec (1988). The machines are expected to reach human level and then improve themselves beyond that ("Most significantly of all, they [the machines] can be put to work as programmers and engineers, with the task of optimizing the software and hardware which make them what they are. The successive generations of machines produced this way will be increasingly smarter and more cost effective.") Humans will no longer be needed, and their abilities will be overtaken by the machines: "In the long run the sheer physical inability of humans to keep up with these rapidly evolving progeny of our minds will ensure that the ratio of people to machines approaches zero, and that a direct descendant of our culture, but not our genes, inherits the universe." While the word "singularity" is not used, the notion of human-level thinking machines thereafter improving themselves beyond human level is there. In this view, there is no intelligence explosion in the sense of a very rapid intelligence increase once human equivalence is reached. An updated version of the article was published in 1979 in Analog Science Fiction and Fact.^[134][133]

In 1981, Stanisław Lem published his science fiction novel Golem XIV. It describes a military AI computer (Golem XIV) that obtains consciousness and starts to increase its intelligence, moving toward personal technological singularity. Golem XIV was originally created to aid its builders in fighting wars, but as its intelligence advances to a much higher level than that of humans, it stops being interested in the military requirements because it finds them lacking internal logical consistency.

Vernor Vinge addressed Good's intelligence explosion in the January 1983 issue of Omni magazine. Vinge seems to have been the first to use the term "singularity" (although not "technological singularity") in a way specifically tied to the creation of intelligent machines:^[10][133]

We will soon create intelligences greater than our own. When this happens, human history will have reached a kind of singularity, an intellectual transition as impenetrable as the knotted space-time at the center of a black hole, and the world will pass far beyond our understanding. This singularity, I believe, already haunts a number of science-fiction writers. It makes realistic extrapolation to an interstellar future impossible. To write a story set more than a century hence, one needs a nuclear war in between ... so that the world remains intelligible.

In 1985, in "The Time Scale of Artificial Intelligence", AI researcher Ray Solomonoff articulated mathematically the related notion of what he called an "infinity point": if a research community of human-level self-improving AIs take four years to double their own speed, then two years, then one year and so on, their capabilities increase infinitely in finite time.^[9][135]

In 1986, Vinge published Marooned in Realtime, a science-fiction novel where a few remaining humans traveling forward in the future have survived an unknown extinction event that might well be a singularity. In a short afterword, Vinge writes that an actual technological singularity would not be the end of the human species: "of course it seems very unlikely that the Singularity would be a clean vanishing of the human race. (On the other hand, such a vanishing is the timelike analog of the silence we find all across the sky.)".^[136][137]

In 1988, Vinge used the phrase "technological singularity" in the short-story collection Threats and Other Promises, writing in the introduction to his story "The Whirligig of Time": Barring a worldwide catastrophe, I believe that technology will achieve our wildest dreams, and soon. When we raise our own intelligence and that of our creations, we are no longer in a world of human-sized characters. At that point we have fallen into a technological "black hole", a technological singularity.^[138]

In 1988, Hans Moravec published Mind Children,^[36] in which he predicted human-level intelligence in supercomputers by 2010, self-improving intelligent machines far surpassing human intelligence later, human mind uploading into human-like robots later, intelligent machines leaving humans behind, and space colonization. He did not mention "singularity", though, and he did not speak of a rapid explosion of intelligence immediately after the human level is achieved. Nonetheless, the overall singularity tenor is there in predicting both human-level artificial intelligence and further artificial intelligence far surpassing humans later.

Vinge's 1993 article "The Coming Technological Singularity: How to Survive in the Post-Human Era",^[4] spread widely on the internet and helped popularize the idea.^[139] This article contains the statement, "Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will be ended." Vinge argues that science-fiction authors cannot write realistic post-singularity characters who surpass the human intellect, as the thoughts of such an intellect is beyond humans' ability to express.^[4]

Minsky's 1994 article says robots will "inherit the Earth", possibly with the use of nanotechnology, and proposes to think of robots as human "mind children", drawing the analogy from Moravec. The rhetorical effect of the analogy is that if humans are fine to pass the world to their biological children, they should be equally fine to pass it to robots, their "mind children". Per Minsky, "we could design our 'mind-children' to think a million times faster than we do. To such a being, half a minute might seem as long as one of our years, and each hour as long as an entire human lifetime." The feature of the singularity present in Minsky is the development of superhuman artificial intelligence ("million times faster"), but there is no talk of sudden intelligence explosion, self-improving thinking machines, or unpredictability beyond any specific event, and the word "singularity" is not used.^[140]

Tipler's 1994 book The Physics of Immortality predicts a future where super–intelligent machines build enormously powerful computers, people are "emulated" in computers, life reaches every galaxy, and people achieve immortality when they reach Omega Point.^[141] There is no talk of Vingean "singularity" or sudden intelligence explosion, but intelligence much greater than human is there, as well as immortality.

In 1996, Yudkowsky predicted a singularity by 2021.^[23] His version of singularity involves intelligence explosion: once AIs are doing the research to improve themselves, speed doubles after 2 years, then 1 one year, then after 6 months, then after 3 months, then after 1.5 months, and after more iterations, the "singularity" is reached.^[23] This construction implies that the speed reaches infinity in finite time.

In 2000, Bill Joy, a prominent technologist and a co-founder of Sun Microsystems, voiced concern over the potential dangers of robotics, genetic engineering, and nanotechnology.^[61]

In 2005, Kurzweil published The Singularity Is Near. Kurzweil's publicity campaign included an appearance on The Daily Show with Jon Stewart.^[142]

From 2006 to 2012, an annual Singularity Summit conference was organized by Machine Intelligence Research Institute, founded by Eliezer Yudkowsky.

In 2007, Yudkowsky suggested that many of the varied definitions that have been assigned to "singularity" are mutually incompatible rather than mutually supporting.^[33][143] For example, Kurzweil extrapolates current technological trajectories past the arrival of self-improving AI or superhuman intelligence, which Yudkowsky argues represents a tension with both I. J. Good's proposed discontinuous upswing in intelligence and Vinge's thesis on unpredictability.^[33]

In 2009, Kurzweil and X-Prize founder Peter Diamandis announced the establishment of Singularity University, a nonaccredited private institute whose mission is "to educate, inspire and empower leaders to apply exponential technologies to address humanity's grand challenges."^[144] Funded by Google, Autodesk, ePlanet Ventures, and a group of technology industry leaders, Singularity University is based at NASA's Ames Research Center in Mountain View, California. The not-for-profit organization runs an annual ten-week graduate program that covers ten different technology and allied tracks, and a series of executive programs throughout the year.

In politics

In 2007, the Joint Economic Committee of the United States Congress released a report about the future of nanotechnology. It predicts significant technological and political changes in the midterm future, including possible technological singularity.^{[145][146][147]}

Former President of the United States Barack Obama spoke about singularity in his interview to Wired in 2016:^[148]

One thing that we haven't talked about too much, and I just want to go back to, is we really have to think through the economic implications. Because most people aren't spending a lot of time right now worrying about singularity—they are worrying about "Well, is my job going to be replaced by a machine?"

Notes

1. Large language models such as ChatGPT and Llama require millions of hours of graphics processing unit (GPU) time. Training Meta's Llama in 2023 took 21 days on 2048 NVIDIA A100 GPUs, thus requiring hardware substantially larger than a brain. Training took around a million GPU hours, with an estimated cost of over $2 million. Even so, it is far smaller, and thus easier to train, than a LLM such as ChatGPT, which as of 2023 had 175 billion parameters to adjust, compared to 65 million for Llama.^[51] Training Google's Gemini LLM is estimated to have cost between $30 million and $191 million, similar to that of ChatGPT 4.^[52]

See also

• Technology portal

• Artificial consciousness – Field in cognitive science
• Ephemeralization – Technological advancement theory
• Global brain – Futuristic concept of a global interconnected network
• Technological revolution – Period of rapid technological change
• Technophobia – Fear or discomfort with advanced technology
  • Neo-Luddism – Philosophy opposing modern technology