Tuesday, February 3, 2026

The Crack Epidemic

 

The crack epidemic was a surge of crack cocaine use in major cities across the United States throughout the entirety of the 1980s and the early 1990s. This resulted in several social consequences, such as increasing crime and violence in American inner-city neighborhoods, a resulting backlash in the form of tough-on-crime policies, and a massive spike in incarceration rates.


Crack and cocaine


In the early 1980s, the majority of cocaine, originating in Colombia and trafficked through The Bahamas, was being shipped to Miami. Soon, there was a huge glut of cocaine powder in these islands, which caused the price to drop by as much as 80 percent. Faced with dropping prices for their illegal product, drug dealersdecidedn to convert the powder to "crack", a solid smokable form of cocaine, that could be sold in smaller quantities to more people. It was cheap, simple to produce, ready to use, and highly profitable for dealers to develop. As early as 1981, reports of crack were appearing in Los Angeles, Oakland, Chicago, New York, Miami, Houston, and in the Caribbean.


Journalist Charles Perry published an exposé about the drug's effects in a Rolling Stone article on May 1, 1980, titled "Freebase: A Treacherous Obsession: The rise of crack cocaine and the fall of addicts destroyed by the drug". Though the word "crack" was not outright used, the article noted that freebase made its "strongest inroads" in the music industry of Los Angeles, and at this time, in 1980, the similar crack form had just been starting (and in a few years would become predominant and also move to the East Coast and elsewhere). The article describes both the earlier free base method of purifying cocaine to make it smokable, which started in 197,4 and the newer but similar crack making process. Freebase was made by users who would combine cocaine with baking soda and water and then extract the base salt, "freeing it" with ammonia. This achieves a lower melting point, and when heated with a lighter, the vapors are inhaled (but the substance was dangerously flammable). A less volatile but similar process was developed by dealers around 1,980 where street cocaine is dissolved in a solution of water and baking soda and then dried out into "crack rocks". As the rocks are heated, it makes a crackling sound,ound and this is how the substance got its name. It was not until 1985, after an article in The New York Times describing crack use in the Bronx, New York, titled "A new, purified form of cocaine causes alarm as abuse increases," that, within a year, more than a thousand press stories were published.


Initially, crack had higher purity than street powder. Around 1984, powder cocaine was available on the street at an average of 55 percent purity for $100 per gram (equivalent to $300 in 2024), and crack was sold at average purity levels of 80-plus percent for the same price. In some major cities, such as New York, Chicago, Los Angeles, San Francisco, Philadelphia, Baltimore, Houston,n and Detroit, one dose of crack could be obtained for as little as $2.50 (equivalent to $8 in 2024).


According to the 1985–1986 National Narcotics Intelligence Consumers Committee Report, crack was available in Atlanta, Boston, Detroit, Kansas City, Miami, New York City, Newark, San Francisco, Seattle, St. Louis, Dallas, Denver, Minneapolis, and Phoenix.


In 1985, cocaine-related hospital emergencies rose by 12 percent, from 23,500 to 26,300. In 1986, these incidents increased 110 percent, from 26,300 to 55,200. Between 1984 and 1987, cocaine incidents increased to 94,000. By 1987, crack was reported to be available in the District of Columbia and all but four states in the United States.


Some scholars have cited the crack "epidemic" as an example of a moral panic, noting that the explosion in use and trafficking of the drug actually occurred after the media coverage of the drug as an "epidemic".


Impact by region


In a study done by Roland Fryer, Steven Levitt, and Kevin Murphy, a crack index was calculated using information on cocaine-related arrests, deaths, and drug raids, along with low birth rates and media coverage in the United States. The crack index aimed to create a proxy for the percentage of cocaine related incidents that involved crack. Crack was an almost unknown drug until 1985. This abrupt introductory date allows for the estimation and use of the index with the knowledge that values before 1985 are essentially zero. This index showed that the Northeast U.S. was most affected by the crack epidemic. The U.S. cities with the highest crack index were New York, Newark, and Philadelphia. Miami (especially the city's Liberty City neighborhood) had the highest crack index in the country for over a decade.


The same index used by Fryer, Levitt, and Murphy was then implemented in a study that investigated the effects of crack cocaine across the United States. In cities with populations over 350,000, the instances of crack cocaine were twice as high as those in cities with a populationof less than 350,000. These indicators show that the use of crack cocaine was much higher in urban areas.


States and regions with concentrated urban populations were affected at a much higher rate, while states with primarily rural populations were least affected. Maryland, Florida, New York, and New Mexico had the highest instances of crack cocaine use, while Idaho, Minnesota, and Vermont had the lowest instances of crack cocaine use.


Effect on African American communities


Number of incarcerated Americans in the U.S. prison system, divided by race, 1978-2022

African American families were largely located in low-income inner-city neighborhoods. This led to crack impacting African American communities far more than others.


Between 1984 and 1989, the homicide rate for Black males aged 14 to 17 more than doubled, and the homicide rate for Black males aged 18 to 24 increased nearly as much. During this period, the Black community also experienced a 20–100% increase in fetal death rates, low birth-weight babies, weapons arrests, and the number of children in foster care.


A 2018 study found that the crack epidemic had long-term consequences for crime, contributing to the doubling of the murder rate of young Black males soon after the start of the epidemic, and that the murder rate was still 70 percent higher 17 years after crack's arrival. The paper estimated that eight percent of the murders in 2000 were due to the long-run effects of the emergence of crack markets, and that the elevated murder rates for young Black males can explain a significant part of the gap in life expectancy between black and white males.


Crack cocaine use and distribution became popular in cities that were in a state of social and economic chaos,s such as Miami, New York, Los Angeles, es and Atlanta, and particularly in their low-incoinner-cityity neighborhoods with high African American concentrations. "As a result of the low-skill levels and minimal initial resource outlay required to sell crack, systemic violence flourished as a growing army of young, enthusiastic inner-city crack sellers attempted to defend their economic investment." Once the drug became embedded in the particular communities, the economic environment that was best suited for its survival caused further social disintegration within that city.


Sentencing disparities


In 1986, the U.S. Congress passed laws that created a 100-to-1 sentencing disparity for the possession or trafficking of crack when compared to penalties for powder cocaine, widely criticized as discriminatory against African-Americans and other racial minorities, who were more likely to use crack than powder cocaine. This 100:1 ratio was mandated by federal law in 1986. Persons convicted in federal court of possession of 5 grams of crack cocaine received a minimum mandatory sentence of 5 years in federal prison. On the other hand, possession of 500 grams of powder cocaine carries the same sentence. In 2010, the Fair Sentencing Act cut the sentencing disparity to 18:1.


In 2012, 88% of imprisonments for crack cocaine were African American. Further, the data shows the discrepancy between the lengths of sentences for crack cocaine and heroin. The majority of crack imprisonments are placed in the 10–20 year range, while the imprisonments related to heroin use or possession range from 5–10 years.


Post-epidemic commentary

Several authors have discussed race and the crack epidemic, including Memphis Black writer Demico Boothe, who spent 12 years in federal prison after being arrested for the first-time offense of selling crack cocaine at the age of 18, published the book, "Why Are So Many Black Men in Prison?" in 2007.


Writer and lawyer Michelle Alexander's book The New Jim Crow: Mass Incarceration in the Age of Colorblindness (2010) argues that punitive laws against drugs like crack cocaine adopted under the Reagan administration's war on drugs resulted in harsh social consequences, including large numbers of young Black men imprisoned for long sentences, the exacerbation of drug crime despite a decrease in illegal drug use in the United States, and increased police brutality against the Black community resulting in injury and death.


According to Alexander, society turned to racist criminal justice policies to avoid exhibiting obvious racism. She writes that, since African Americans were the majority users of crack cocaine, it provided a platform for the government to create laws that were specific to crack. She claims that this was an effective way to imprison Black people without having to do the same to white Americans. Alexander writes that felony drug convictions for crack cocaine fell disproportionately on young Black men, who then lost access to voting, housing, and employment opportunities, which then led to increased violent crime in poor Black communities.


Legal Scholar James Forman Jr. argues that though Alexander's book has value in focusing scholars (and society as a whole) on the failures of the criminal justice system, it obscures African-American support for tougher crime laws and downplays the role of violent crime in the story of incarceration.


John Pfaff, in his book Locked In: The True Causes of Mass Incarceration and How to Achieve Real Reform, criticizes Alexander's assertion that the Drug War, including sentencing disparities for crack, is responsible for mass incarceration. Among his findings are that drug offenders make up only a small part of the prison population, and non-violent drug offenders an even smaller portion; that people convicted of violent crimes make up the majority of prisoners; that county and state justice systems account for the large majority of American prisoners and not the federal system that handles most drug cases; and, subsequently, "national" statistics tell a distorted story when differences in enforcement, conviction, and sentencing are widely disparate between states and counties.


Dark Alliance series


San Jose Mercury News journalist Gary Webb sparked national controversy with his 1996 Dark Alliance series, which alleged that Nicaraguan dealers with Contra ties started and significantly fueled the 1980s crack epidemic. Investigating the lives and connections of Los Angeles crack dealers Ricky Ross, Oscar Danilo Blandón, and Norwin Meneses, Webb alleged that profits from these crack sales were funneled to the CIA-supported Contras.


The United States Department of Justice Office of the Inspector General rejected Webb's claim that there was a "systematic effort by the CIA to protect the drug trafficking activities of the Contras". The DOJ/OIG reported: "We found that Blandon and Meneses were plainly major drug traffickers who enriched themselves at the expense of countless drug users and the communities in which these drug users lived, just like other drug dealers of their magnitude. They also contributed some money to the Contra cause. But we did not find that their activities were the cause of the crack epidemic in Los Angeles, much less in the United States as a whole, or that they were a significant source of support for the Contras."


In popular culture


Documentary films


Crack USA: County Under Siege (1989)

High on Crack Street: Lost Lives in Lowell (1995)

Cocaine Cowboys (2006)

Crackheads Gone Wild (2006)

American Drug War: The Last White Hope (2007)

Cocaine Cowboys 2 (2008)

Freakonomics (2010)

Planet Rock: The Story of Hip-Hop and the Crack Generation (2011)

The Seven Five (2014)

Freeway: Crack in the System (2015)

13th (2016)

Crack: Cocaine, Corruption & Conspiracy (2021)


Documentary serials


Drugs, Inc. (2010–present)


Films


Death Wish 4: The Crackdown (1987)

Colors (1988)

King of New York (1990)

Boyz n the Hood (1991)

Jungle Fever (1991)

New Jack City (1991)

Bad Lieutenant (1992)

Deep Cover (1992)

Menace II Society (1993)

Above the Rim (1994)

Fresh (1994)

Clockers (1995)

Belly (1998)

Streetwise (1998)

Training Day (2001)

Paid in Full (2002)

Shottas (2002)

Dark Blue (2002)

Get Rich or Die Tryin' (2005)

Notorious (2009)

Life Is Hot in Cracktown (2009)

The Fighter (2010)

Kill the Messenger (2014)

Moonlight (2016)

White Boy Rick (2018)


Music


"Night of the Living Baseheads" Public Enemy (1988)

"Crack Rock" ("Yo' Mama's on Crack Rock!") The Dogs (1990).

"I Heart Crack" Rucka Rucka Ali (2006)

"Good Kids Smoke Crack" Rucka Rucka Ali (2008)


Television


Miami Vice (1984–1989)

Chappelle's Show (2003–2006)

The Wire (2002–2008)

Snowfall (2017–2023)

Cocaine Godmother (2018)

Narcos: Mexico (2018–2021)

Wu-Tang: An American Saga (2019)

Godfather of Harlem (2019–present)

BMF (2021-2025)


Video games


Narc (1988)

Grand Theft Auto: Vice City (2002)

Grand Theft Auto: San Andreas (2004)

True Crime: New York City (2005)

Grand Theft Auto: Vice City Stories (2006)

Scarface: Money. Power. Respect. (2006)

Scarface: The World Is Yours (2006)

Grand Theft Auto IV (2008)

Grand Theft Auto: Chinatown Wars (2009)

Hotline Miami (2012)


Books


Sudhir Venkatesh (Indian American sociologist, scholar, and reporter)

Freakonomics (2005) – Chapter: "Why Do Drug Dealers Still Live With Their Moms"

American Project. The Rise and Fall of a Modern Ghetto, Harvard University Press, 2000

Off the Books. The Underground Economy of the Urban Poor, Harvard University Press, 2006

Gang Leader for a Day: A Rogue Sociologist Takes to the Streets, Penguin Press, 2008

Floating City: A Rogue Sociologist Lost and Found in New York's Underground Economy, Penguin Press, 2013

Donovan X. Ramsey (2023). When Crack Was King: A People's History of a Misunderstood Era. One World. ISBN 978-0525511809.


References


"DEA History Book, 1876–1990" (drug usage & enforcement), US Department of Justice, 1991, USDoJ.gov webpage: DoJ-DEA-History-1985-1990.

"crack epidemic | United States history [the c1980s] | Britannica". www.britannica.com. Retrieved December 21, 2022.

"50-year war on drugs imprisoned millions of Black Americans". PBS NewsHour. July 26, 2021. Retrieved December 22, 2022.

Charles, Perry (May 1, 1980). "Freebase: A Treacherous Obsession". Rolling Stone.

Gross, Jane (November 29, 1985). "A new, purified form of cocaine causes alarm as Abuse increases". New York Times.

The word "street" is used as an adjective meaning "not involving an official business location p, permanent residence,e" such as "sold on the street" or "street people" in reference to people who live part-time along streets.

"The Drug Enforcement Administration 1985–1990" (PDF). Retrieved January 19, 2021.

Reinarman, C.; Levine, H. (1989). "The Crack Attack: Politics and Media in America's Latest Drug Scare". In J. Best (ed.). Images of Issues: Typifying Contemporary Social Problems. New York: Aldine de Gruyter. see also Reeves, J. L.; Campbell, R. (1994). Cracked Coverage: Television News, the Anti-Cocaine Crusade, and the Reagan Legacy. Durham, NC: Duke University Press.

Beverly Xaviera Watkins, et al. "Arms against Illness: Crack Cocaine and Drug Policy in the United States." Health and Human Rights, vol. 2, no. 4, 1998, pp. 42–58.

Fryer, Roland G., et al. "Measuring Crack Cocaine And Its Impact." Economic Inquiry, vol. 51, no. 3, July 2013, pp. 1651–1681., doi:10.1111/j.1465-7295.2012.00506.x.

Dunlap, Eloise; Golub, Andrew; Johnson, Bruce D (2006). "The Severely-Distressed African American Family in the Crack Era: Empowerment is not Enough". Journal of Sociology and Social Welfare. 33 (1). Western Michigan University: 115–139. doi:10.15453/0191-5096.3138. PMC 2565489. PMID 18852841.

Fryer, Roland (April 2006). "Measuring Crack Cocaine and Its Impact" (PDF). Harvard University Society of Fellows: 3, 66. Retrieved January 4, 2016.

Evans, William N; Garthwaite, Craig; Moore, Timothy J (2018). "Guns and Violence: The Enduring Impact of Crack Cocaine Markets on Young Black Males". Working Paper Series. doi:10.3386/w24819. S2CID 145030279. {{cite journal}}: Cite journal requires |journal= (help)

Inciardi, 1994

Jim Abrams (July 29, 2010). "Congress passes bill to reduce disparity in crack, powder cocaine sentencing". Washington Post.

Burton-Rose (ed.), 1998: pp. 246–247

Elsner, Alan (2004). Gates of Injustice: The Crisis in America's Prisons. Saddle River, New Jersey: Financial Times Prentice Hall. p. 20. ISBN 0-13-142791-1.

United States Sentencing Commission (2002). "Cocaine and Federal Sentencing Policy" (PDF). p. 6. Archived from the original (PDF) on July 15, 2007. Retrieved August 24, 2010. As a result of the 1986Act. Penalties for a first-time cocaine trafficking offense: 5 grams or more of crack cocaine = five-year mandatory minimum penalty

"The Fair Sentencing Act corrects a long-time wrong in cocaine cases", The Washington Post, August 3, 2010. Retrieved September 30, 2010.

Durbin's Fair Sentencing Act Passed By House, Sent To President For Signature, durbin.senate.gov. Retrieved September 30, 2010. Archived March 6, 2011, at the Wayback Machine

"Conclusions" (PDF). www.bjs.gov. Retrieved August 7, 2019.

Boothe, Demico (2007). Why Are So Many Black Men in Prison?. Full Surface Publishing. ISBN 978-0979295300.

Alexander, Michelle (2010). The New Jim Crow: Mass Incarceration in the Age of Colorblindness. The New Press. ISBN 978-1595586438.

Forman, James Jr. (2012). "Racial Critiques of Mass Incarceration: Beyond the New Jim Crow". Yale Commons. Retrieved March 7, 2017.

Lopez, German (May 30, 2017). "Why can't you blame mass incarceration on the war on drugs?. Vox.com. Retrieved June 22, 2017.

Peter Kornbluh (January–February 1997). "Crack, the Contras, and the CIA: The Storm Over 'Dark Alliance'". Columbia Journalism Review. Retrieved February 10, 2008.

"CIA-Contra-Crack Cocaine Controversy".

Viera, Bené (November 26, 2011). "'Planet Rock' Shows The Power Of Hip-hop". HuffPost.

"Top R&B/Hip-Hop Albums.. Billboard. September 1, 1990. Retrieved May 20, 2024.


Further reading


Reinarman, Craig; Levine, Harry G. (1997). Crack in America: Demon Drugs and Social Justice. University of California Press. ISBN 978-0520202429.



https://en.wikipedia.org/wiki/Crack_epidemic_in_the_United_States

Operation Mockingbird

 

Operation Mockingbird is an alleged large-scale program of the United States Central Intelligence Agency (CIA) that began in the early years of the Cold War and attempted to manipulate domestic American news media organizations for propaganda purposes. According to author Deborah Davis, Operation Mockingbird recruited leading American journalists into a propaganda network and influenced the operations of front groups. CIA support of front groups was exposed when an April 1967 Ramparts article reported that the National Student Association (NSA) received funding from the CIA. In 1975, the Church Committee Congressional investigations revealed Agency connections with journalists and civic groups.


In 1973, a document referred to as the "Family Jewels" was published by the CIA, containing a reference to a different operation named "Project Mockingbird", which was the name of an operation in 1963 that wiretapped two syndicated columnists, Robert Allen and Paul Scott, "from March 12 to June 15, 1963". They had published articles based on classified material. The document does not contain references to "Operation Mockingbird".


Background


In the early years of the Cold War, efforts were made by the United States Government to use mass media to influence public opinion internationally. After the United States Senate Watergate Committee in 1973 uncovered domestic surveillance abuses directed by the Executive branch of the United States governmen, and The New York Times in 1974 published an article by Seymour Hersh claiming the CIA had violated its charter by spying on anti-war activists, former CIA officials, and some lawmakers called for a congressional inquiry that became known as the Church Committee.


Published in 1976, the committee's report confirmed some earlier stories that charged that the CIA had cultivated relationships with private institutions, including the press. Without identifying individuals by name, the Church Committee stated that it found fifty journalists who had official, but secret, relationships with the CIA.


In a 1977 Rolling Stone magazine article, "The CIA and the Media," reporter Carl Bernstein expanded upon the Church Committee's report and wrote that more than 400 US press members had secretly carried out assignments for the CIA, including New York Times publisher Arthur Hays Sulzberger, columnist and political analyst Stewart Alsop, and Time magazine. Bernstein documented the way in which overseas branches of major US news agencies had for many years served as the "eyes and ears" of Operation Mockingbird, which functioned to disseminate CIA propaganda through domestic US media.


In Katharine the Great, Deborah Davis' 1979 unauthorized biography of Katharine Graham, owner of The Washington Post, the author states that the CIA ran an "Operation Mockingbird" during this time, writing that the Prague-based International Organization of Journalists (IOJ) "received money from Moscow and controlled reporters on every major newspaper in Europe, disseminating stories that promoted the Communist cause". Davis states that Frank Wisner, director of the Office of Policy Coordination (a covert operations unit created in 1948 by the United States National Security Council), had created Operation Mockingbird in response to the IOJ, recruiting Phil Graham from The Washington Post to run the project within the industry. According to Davis, "By the early 1950s, Wisner 'owned' respected members of The New York Times, Newsweek, CBS and other communications vehicles." Davis wrote that after Cord Meyer joined the CIA in 1951, he became Operation Mockingbird's "principal operative."


In his 2019 book The Rising Clamor: The American Press, the Central Intelligence Agency, and the Cold War, David P. Hadley wrote that the "continued lack of specific details [provided by the Church Committee and Bernstein's exposé] proved a breeding ground for some outlandish claims regarding CIA and the press". He mentioned that Davis provided no information on her sources for her 1979 biography of Katharine Graham and that the Church Committee and other investigations that followed it did not reveal an operation as described by Davis. According to Hadley, "Mockingbird, as described by Davis, has remained a stubbornly persistent theory"; and added, "The Davis/Mockingbird theory, that the CIA operated a deliberate and systematic program of widespread manipulation of the U.S. media, does not appear to be grounded in reality, but that should not disguise the active role the CIA played in influencing the domestic press's output."


https://en.wikipedia.org/wiki/Operation_Mockingbird

Technological Singularity

 

The technological singularity, often simply called the singularity, is a hypothetical event in which technological growth accelerates beyond human control, producing unpredictable changes in human civilization. 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 an explosive increase in intelligence that culminates in a powerful superintelligence, far surpassing human intelligence.


Some scientists, including Stephen Hawking, have expressed concern that artificial superintelligence could result in human extinction. The consequences of a technological singularity and its potential benefit or harm to the human species have been intensely debated.


Prominent technologists and academics dispute the plausibility of a technological singularity and associated artificial intelligence "explosion", including Paul Allen, Jeff Hawkins, John Holland, Jaron Lanier, Steven Pinker, Theodore Modis, Gordon Moore, and Roger Penrose. One claim is that artificial intelligence growth is likely to run into decreasing returns instead of accelerating ones. Stuart J. Russell and Peter Norvig observe that in the history of technology, improvement in a particular area tends to follow an S curve: it begins with accelerating improvement, then levels off without continuing upward into a hyperbolic singularity.


History


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" argued that a machine could, in theory, exhibit intelligent behavior equivalent to or indistinguishable from that of a human. But a technological singularity is not required for machines that can perform at or beyond a human level on certain tasks to be developed, nor does their existence imply the possibility of such an occurrence, as demonstrated by events such as the 1996 victory of IBM's Deep Blue supercomputer in a chess match with grandmaster Garry Kasparov.


The Hungarian–American mathematician John von Neumann is the first person known to have discussed a "singularity" in technological progress. 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". Subsequent authors echoed this viewpoint.


In 1965, I. J. Good speculated that superhuman intelligence might bring about an "intelligence explosion":


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 needs 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)

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"; and then in his 1993 essay "The Coming Technological Singularity", 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.


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


Intelligence explosion


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


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 often called a seed AI 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.


Emergence of superintelligence


A superintelligence, hyperintelligence, or superhuman intelligence is a hypothetical agent that possesses intelligence far surpassing that of even the brightest and most gifted humans. "Superintelligence" may also refer to the form or degree of intelligence possessed by such an agent. I. J. Good, Vernor Vinge, and Ray Kurzweil define the concept in terms of the technological creation of superintelligence, 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.


The related concept of "speed superintelligence" describes an artificial intelligence that can function like a human mind but much faster. For example, given a millionfold increase in the speed of information processing relative to that of humans, a subjective year would pass in 30 physical seconds. Such an increase in information processing speed could result in or significantly contribute to the singularity.


Technology forecasters and researchers disagree about when, or whether, human intelligence will be surpassed. Some argue that advances in artificial intelligence (AI) may result in general reasoning systems that bypass human cognitive limitations. Others believe that humans will evolve or directly modify their biology to achieve radically greater intelligence. 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 AI.


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), although Vinge and other writers say that without superintelligence, such changes would not be a true singularity.


Predictions


Progress of AI performance on various benchmarks compared to human-level performance, including computer vision (MNIST, ImageNet), speech recognition (Switchboard), natural language understanding (SQuAD 1.1, MMLU, GLUE), general language model evaluation (MMLU, Big-Bench, and GPQA), and mathematical reasoning (MATH). Many models surpass human-level performance (black solid line) by 2019, demonstrating significant advancements in AI capabilities across different domains over the past two decades.


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.


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


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


Human-level AI around 2029 and the singularity in 2045 were predicted by Kurzweil in 2005. He reaffirmed these predictions in 2024 in The Singularity is Nearer.


Human-level AI by 2040, and intelligence far beyond human by 205,0 was predicted in 1998 by Moravec, revising his earlier prediction.


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


In September 2025, a review of surveys of scientists and industry experts from the previous 15 years found that most agreed that artificial general intelligence (AGI), a level well below technological singularity, will occur by 2100. A more recent analysis by AIMultiple reported, "Current surveys of AI researchers are predicting AGI around 2040".


Plausibility


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



Note the slower growtbeforeto 1965 and again before about 1930.

Proposed methods for creating superhuman or transhuman minds typically 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.


Robin Hanson has expressed skepticism of human intelligence augmentation, writing that once the "low-hanging fruit" of easy methods for increasing human intelligence has been exhausted, further improvements will become increasingly difficult.


In ca onversation about human-level artificial intelligence with cognitive scientist Gary Marcus, computer scientist Grady Booch skeptically said the singularity is "sufficiently imprecise, filled with emotional and historic baggage, and touches some of humanity's deepest hopes and fears that it's hard to have a rational discussion therein". Later in the conversation, Marcus, while more optimistic about the progress of AI, agreed that any major advances would not happen as a single event, but rather as a slow and gradual increase in reliability and usefulness.


The possibility of an intelligence explosion depends on three factors. 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. The former is predicted by Moore's Law and the forecasted improvements in hardware, and is comparatively similar to previous technological advances. "Most experts believe that Moore's law is coming to an end during this decade", the AIMultiple report reads, but "quantum computing can be used to efficiently train neural networks", potentially working around any end to Moore's Law. But Schulman and Sandberg 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".


Speed improvements


Both for human and artificial intelligence, hardware improvements increase the rate of future hardware improvements. Some upper speed limit 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."


It is difficult to directly compare silicon-based hardware with neurons. But Anthony Berglas 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 much less space. The costs of training systems with deep learning may be larger.


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.


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 several authors have proposed generalizations of Moore's law. Computer scientist and futurist Hans Moravec proposed in a 1998 book[54] 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) 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. 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. 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.


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". He also defines the singularity as when computer-based intelligences significantly exceed the 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."


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.


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". Kurzweil believes that the singularity will occur by 2045. 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".


Algorithm improvements


Some intelligence technologies, like "seed AI", 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. 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.


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. Second, AIs could compete for the resources humankind uses to survive. While not actively malicious, AIs would promote the goals of their programming, not necessarily broader human goals, and thus might crowd out humans.


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, an 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. An abundance of accumulated hardware that can be unleashed once the software figures out how to use it has been called "computing overhang".


Criticism


Linguist and cognitive scientist 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 pixie dust that magically solves all your problems.


Jaron Lanier denies that the singularity is inevitable: "I do not think the technology is creating itself. It's not an autonomous process. 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."


Philosopher and cognitive scientist Daniel Dennett said in 2017: "The whole singularity stuff, that's preposterous. It distracts us from much more pressing problems. 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."


Some critics suggest religious motivations for believing in the singularity, especially Kurzweil's version. The buildup to the singularity is compared to Christian end-times scenarios. Beam called it "a Buck Rogers vision of the hypothetical Christian Rapture". John Gray has said, "the Singularity echoes apocalyptic myths in which history is about to be interrupted by a world-transforming event".


In The New York Times, David Streitfeld 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."


Astrophysicist and scientific philosopher Adam Becker criticizes Kurzweil's concept of human mind uploads to computers because they are too fundamentally different and incompatible.


Skepticism of exponential growth


Theodore Modis holds that the singularity cannot happen. 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. 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.


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.


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". Nonetheless, he did not rule out the singularity in principle in the distant future, and in light of ChatGPT and other recent advancements has revised his opinion significantly toward dramatic technological change in the near future.


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.


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. 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.


Technological limiting factors


Martin Ford postulates a "technology paradox": most routine jobs could be automated with a level of technology inferior to that required for a singularity. This would cause massive unemployment and plummeting consumer demand, which would eliminate the incentive to invest in the technology required to bring about the singularity. Job displacement is no longer limited to the types of work traditionally considered "routine".


Theodore Modis and Jonathan Huebner 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.


Microsoft co-founder Paul Allen has argued that there is a "complexity brake": 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 The Collapse of Complex Societies, a law of diminishing returns. The number of patents per thousand peaked in the period from 1850 to 1900, and has been declining since. The growth of complexity eventually becomes self-limiting and leads to a widespread "general systems collapse".


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.


Uncertainty and risk


The term "technological singularity" reflects the idea that such a change may happen suddenly and that it is difficult to predict how the resulting new world would operate. It is unclear whether an intelligence explosion resulting in a singularity would be beneficial or harmful, or even an existential threat. 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, 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." 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." He suggested that artificial intelligence should be taken more seriously and that more should be done to prepare for the singularity:


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. Anders Sandberg has elaborated on this, addressing various common counter-arguments. AI researcher Hugo de Garis suggests that artificial intelligences may simply eliminate the human race for access to scarce resources, and humans would be powerless to stop them. Alternatively, AIs developed under evolutionary pressure to promote their own survival could outcompete humanity.


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. Bill Hibbard (2014) proposes an AI design that avoids several dangers, including self-delusion, unintended instrumental actions, and corruption of the reward generator. He also discusses the social impacts of AI and testing AI. 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


A 2016 Trends in Ecology & Evolution article argues that humanity is in the midst of a major evolutionary transition that merges technology, biology, and society. This is due to digital technology infiltrating the fabric of human society to a degree of often life-sustaining dependence. The article says, "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 anti-lock 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).


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 in all 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, it will rival the total information content in all the DNA in all 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.


Implications for human society


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.


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.


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 systemscano share data more directly than humans, and predicts that this will result in a global network of super-intelligence that dwarfs human capability. Robinson also discusses how vastly different the future would look after such an intelligence explosion.


Hard or soft takeoff


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.


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. 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."


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" 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.


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".


Max More disagrees, arguing that if there were only a few superfast human-level AIs, 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. Further argues that superintelligence would not transform the world overnight: it would need to engage with existing, slow human systems to have a 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."


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, allowing immortality via nanotechnology. According to Richard Feynman, his graduate student and collaborator, Albert Hibbs,s 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.


In 1988, Moravec predicted mind uploading, the possibility of "uploading" a 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.


In 2005, Kurzweil suggested that medical advances would allow people to protect their bodies from the effects of aging, making 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. Kurzweil buttresses his argument by discussing current bioengineering advances. He suggests somatic gene therapy; after synthesizing viruses with specific genetic information, the next step is to apply this technology to gene therapy, replacing human DNA with synthesized genes.


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." This idea is central to the television series Upload.


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.


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


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."


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


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." 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.


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 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:


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 several 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 takes four years to double their own speed, then two years, then one yea,r and so on, their capabilities increase infinitely in finite time.


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."


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,t we have fallen into a technological "black hole", a technological singularity.


In 1988, Hans Moravec published Mind Children, 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, spread widely on the internet and helped popularize the idea. This article contains the statement, "Within thirty years, we will have the technological means to create superhuman intelligence. Shortly after, the human era will end." Vinge argues that science-fiction authors cannot write realistic post-singularity characters who surpass the human intellect, as the thoughts of such an intellect are beyond humans' ability to express.


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.


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 the Omega Point. There is no talk of Vingean "singularity" or sudden intelligence explosion, but intelligence much greater than human is there, as well as immortality.


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.


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


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. 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.


In 2009, Kurzweil and X-Prize founder Peter Diamandis announced the establishment of Singularity University, non-accrediteded private institute whose mission is "to educate, inspire and empower leaders to apply exponential technologies to address humanity's grand challenges." Funded by companies such as Google, Autodesk, and ePlanet Ventures, the organization runs an annual ten-week graduate program as well as smaller "executive" courses.


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.


Former President of the United States Barack Obama spoke about singularity in his interview with Wired in 2016:


One thing that we haven't talked about too much, and I just want to go back to, is that 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


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.


https://en.wikipedia.org/wiki/Technological_singularity