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Monday, December 25, 2023

Technological singularity

From Wikipedia, the free encyclopedia

The first person to use the concept of a "singularity" in the technological context was the 20th-century Hungarian-American mathematician John von Neumann. Stanislaw Ulam reports in 1958 an earlier discussion with von Neumann "centered on the 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". Subsequent authors have echoed this viewpoint.

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 later 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 would advance technologically at an incomprehensible rate. He wrote that he would be surprised if it occurred before 2005 or after 2030. Another significant contributor to wider circulation of the notion was Ray Kurzweil's 2005 book The Singularity Is Near, predicting singularity by 2045.

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

Prominent technologists and academics dispute the plausibility of a technological singularity and the associated artificial intelligence explosion, including Paul Allen, Jeff Hawkins, John Holland, Jaron Lanier, Steven Pinker, Theodore Modis, and Gordon Moore. One claim made was that the artificial intelligence growth is likely to run into decreasing returns instead of accelerating ones, as was observed in previously developed human technologies.

Intelligence explosion

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. However, with the increasing power of computers and other technologies, it might eventually be possible to build a machine that is significantly more intelligent than humans.

If a superhuman intelligence were to be invented—either through the amplification of human intelligence or through artificial intelligence—it would vastly improve over human problem-solving and inventive skills. Such an AI is referred to as Seed AI because if an AI were created with engineering capabilities that matched or surpassed those of its human creators, it would have the potential to 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 any upper limits imposed by the laws of physics or theoretical computation set in. It is speculated that over many iterations, such an AI would far surpass human cognitive abilities.

I. J. Good speculated in 1965 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 need ever make, provided that the machine is docile enough to tell us how to keep it under control.

One version of intelligence explosion is where computing power approaches infinity in a finite amount of time. In this version, once AIs are doing 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 literally 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).

Emergence of superintelligence

A superintelligence, hyperintelligence, or superhuman intelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds. "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.

The related concept "speed superintelligence" describes an AI that can function like a human mind, only much faster. For example, with a million-fold increase in the speed of information processing relative to that of humans, a subjective year would pass in 30 physical seconds. Such a difference in information processing speed could drive the singularity.

Technology forecasters and researchers disagree regarding 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. 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. The book The Age of Em by Robin Hanson describes a hypothetical future scenario 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.

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 specifically state that without superintelligence, such changes would not qualify as a true singularity.

Predictions

In 1965, I. J. Good wrote that it is more probable than not that an ultraintelligent machine would be built in the twentieth century. In 1993, Vinge predicted greater-than-human intelligence between 2005 and 2030. In 1996, Yudkowsky predicted a singularity in 2021. In 2005, Kurzweil predicted human-level AI around 2029, and the singularity in 2045. In a 2017 interview, Kurzweil reaffirmed his estimates. In 1988, Moravec predicted that if the rate of improvement continues, the computing capabilities for human-level AI would be available in supercomputers before 2010. In 1998, Moravec predicted human-level AI by 2040, and intelligence far beyond human by 2050.

Four polls of AI researchers, conducted in 2012 and 2013 by Nick Bostrom and Vincent C. Müller, suggested a confidence of 50% that human-level AI would be developed by 2040–2050.

In 2023 Ben Goertzel, CEO of SingularityNET—who holds a Ph.D. from Temple University and has worked as a leader of Humanity+ and the Artificial General Intelligence Society—told Decrypt that he predicted that Singularity would happen by 2031.

Plausibility

Prominent technologists and academics dispute the plausibility of a technological singularity, including 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.

Most proposed methods for creating superhuman or transhuman minds fall into one of 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 multiple possible paths to an intelligence explosion, all of which will presumably be pursued, makes a singularity more likely.

Robin Hanson 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. Despite all of the speculated ways for amplifying human intelligence, non-human artificial intelligence (specifically seed AI) is the most popular option among the hypotheses that would advance the singularity.

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. Contrariwise, 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 towards 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. 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. An analogy to Moore's Law suggests that if the first doubling of speed took 18 months, the second would take 18 subjective months; or 9 external months, whereafter, four months, two months, and so on towards a speed singularity. Some upper limit on speed may eventually be reached. Jeff Hawkins has stated that a self-improving computer system would inevitably run into upper 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 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.

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 that the exponential growth curve could be extended back through earlier computing technologies prior to the integrated circuit.

Ray Kurzweil postulates a law of accelerating returns in which 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), medical technology and others. 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 the 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 for example that "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 his predicted date of the singularity (2045) in terms of when he expects computer-based intelligences to significantly exceed the sum total of human brainpower, writing that advances in computing before that date "will not represent the Singularity" because they do "not yet correspond to a profound expansion of our intelligence."

Accelerating change

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

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 will 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 approximately 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 April 2000 Wired magazine article "Why The Future Doesn't Need Us".

Algorithm improvements

Some intelligence technologies, like "seed AI", may also have the potential to not just make themselves 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. Eliezer Yudkowsky compares it to the changes that human intelligence brought: humans changed the world thousands of times more rapidly than evolution had done, and in totally different ways. Similarly, the evolution of life was a massive departure and acceleration from the previous geological rates of change, and improved intelligence could cause change to be as different again.

There are substantial dangers 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.

Secondly, AIs could compete for the same scarce 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 completely.

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

Criticism

Some critics, like philosopher Hubert Dreyfus and philosopher John Searle, assert that computers or machines cannot achieve human intelligence. Others, like physicist Stephen Hawking, 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 stated 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."

Martin Ford postulates a "technology paradox" in that before the singularity could occur most routine jobs in the economy 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 technologies that would be required to bring about the Singularity. Job displacement is increasingly no longer limited to those types of work traditionally considered to be "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 build-up from the chip, which cannot be dissipated quickly enough to prevent the chip 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.

Theodore Modis holds 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 pointed out 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 twenty years while five of them would have been expected according to the exponential trend advocated by the proponents of the technological singularity.

AI researcher Jürgen Schmidhuber stated 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 could create an illusion of accelerating change where none exists.

Microsoft co-founder Paul Allen argued the opposite of accelerating returns, the complexity brake; the more progress science makes towards 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, 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".

Hofstadter (2006) raises concern that Ray Kurzweil is not sufficiently scientifically 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 the light of ChatGPT and other recent advancements has revised his opinion significantly towards dramatic technological change in the near future.

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

Economist Robert J. Gordon points out that measured economic growth slowed around 1970 and slowed even further since the financial crisis of 2007–2008, and argues that the economic data show no trace of a coming Singularity as imagined by mathematician I. J. Good.

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."

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 that Kurzweil chooses to use. 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 x-axis having time before 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.

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

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."

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. In the current era, beginning with the Industrial Revolution, the world's economic output doubles every fifteen years, sixty 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 on a weekly basis.

Uncertainty and risk

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. 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, a number of organizations pursue a technical theory of aligning AI goal-systems with human values, including the Future of Humanity Institute, the Machine Intelligence Research Institute, the Center for Human-Compatible Artificial Intelligence, and the Future of Life Institute.

Physicist Stephen Hawking said in 2014 that "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." Hawking 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 an 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 also elaborated on this scenario, 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 artificial intelligence is likely to be much easier to create than friendly AI. While both require large advances in recursive optimisation process design, 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 social impacts of AI and testing AI. His 2001 book Super-Intelligent Machines advocates the need for public education about AI and public control over AI. It also proposed a simple design that was vulnerable to corruption of the reward generator.

Next step of sociobiological evolution

Schematic Timeline of Information and Replicators in the Biosphere: Gillings et al.'s "major evolutionary transitions" in information processing.
Amount of digital information worldwide (5×1021 bytes) versus human genome information worldwide (1019 bytes) in 2014

While the technological singularity is usually seen as a sudden event, some scholars argue the current speed of change already fits this description.

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 the 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 cognitive 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 having a genome of 6.2 billion nucleotides. Since one byte can encode four nucleotide pairs, the individual genomes of every human on the planet 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, 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 across a total time period of just 150 years".

Implications for human society

In February 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 potential impact of the hypothetical possibility that robots could become self-sufficient and able to make their own decisions. They discussed the extent to which computers and robots might be able to 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 systems are able to share data more directly than humans, and predicts that this would result in a global network of super-intelligence that would dwarf human capability. Robinson also discusses how vastly different the future would potentially look after such an intelligence explosion.

Hard vs. 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).

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 scenario, 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 the AI's 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!" However, 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" 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.

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. Goerzel refers to this scenario as a "semihard takeoff".

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 super-human intelligence, although the rate of progress would increase. More further argues that a superintelligence would not transform the world overnight: a superintelligence would need to engage with existing, slow human systems to accomplish physical impacts 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

Drexler (1986), one of the founders of nanotechnology, postulates cell repair devices, including ones operating within cells and using as yet hypothetical biological machines. According to Richard Feynman, it was his former graduate student and collaborator Albert Hibbs who 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 reduced in size 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.

Moravec (1988) predicts 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.

Kurzweil (2005) suggests that medical advances would allow people to protect their bodies from the effects of aging, making the life expectancy limitless. Kurzweil argues that the technological advances in medicine would allow us to continuously repair and replace defective components in our bodies, prolonging life to an undetermined age. Kurzweil further buttresses his argument by discussing current bio-engineering advances. Kurzweil suggests somatic gene therapy; after synthetic viruses with specific genetic information, the next step would be 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."

History of the concept

A paper by Mahendra Prasad, published in AI Magazine, asserts that the 18th-century mathematician Marquis de Condorcet was the first person to hypothesize and mathematically model 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 von Neumann 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) who obtains consciousness and starts to increase his own intelligence, moving towards 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.

In 1983, Vernor Vinge addressed Good's intelligence explosion in print in the January 1983 issue of Omni magazine. In this op-ed piece, Vinge seems to have been the first to use the term "singularity" (although not "technological singularity") in a way that was 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 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", artificial intelligence 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.

In 1986, Vernor 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, the author states 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" (including "technological") in the short story collection Threats and Other Promises, writing in the introduction to his story "The Whirligig of Time" (p. 72): 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.

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 to 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 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 would be beyond the ability of humans 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 that 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. As 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 will build enormously powerful computers, people will be "emulated" in computers, life will reach every galaxy and people will achieve immortality when they reach 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 1996, Yudkowsky predicted a singularity by 2021. 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. 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.

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, a nonaccredited private institute whose stated mission is "to educate, inspire and empower leaders to apply exponential technologies to address humanity's grand challenges." 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 during summer that covers ten different technology and allied tracks, and a series of executive programs throughout the year.

Phylotypic stage

From Wikipedia, the free encyclopedia
 
In Embryology a phylotypic stage or phylotypic period is a particular developmental stage or developmental period during mid-embryogenesis where embryos of related species within a phylum express the highest degree of morphological and molecular resemblance. Recent molecular studies in various plant and animal species were able to quantify the expression of genes covering crucial stages of embryo development and found that during the morphologically defined phylotypic period the evolutionary oldest genes, genes with similar temporal expression patterns, and genes under strongest purifying selection are most active throughout the phylotypic period.

Historical origins of concept

Haeckel's drawings, reproduced by G.J. Romanes in 1892. Early embryologists, including Haeckel and von Baer, noted that embryos of different animals pass through a similar stage in which they resemble one another very closely.
Karl Ernst von Baer, whose third law of embryology gave the basis for the idea of the phylotypic stage

The idea that embryos of different species have similar morphologies at some point during development can be traced back to Aristotle. Aristotle observed a number of developing vertebrate embryos, noting in his text The Generation of Animals that the morphological differences among the different embryos arose late in development. In 1828, Karl Ernst von Baer created his laws of embryology, which summarized the results of his comparative embryogenesis studies. In his first law, he proposed that the more general characters of a group appear earlier in their embryos than the more special characters. In 1866, Ernst Haeckel proposed that each developing organism passes through the evolutionary stages of its ancestors, i.e., ontogeny recapitulates phylogeny. The hypothesis that different organisms pass through the developmental stages of closely related organisms is outdated. However, the idea that early stages of development are conserved among species, with increasing divergence as development progresses, has influenced modern evolutionary and developmental biology. The early conservation or funnel model of development (see below) is closely tied to these historical origins.

Phylotypic period

The first formulation of the phylotypic period concept came in 1960 from Friedrich Seidel's Körpergrundgestalt, which translates to “basic body shape.” In 1977, Cohen defined the phyletic stage as the first stage that reveals the general characters shared by all members of that phylum. Klaus Sander revised this concept in 1983 and named it the phylotypic stage, which is ‘‘the stage of greatest similarity between forms which, during evolution, have differently specialized both in their modes of adult life and with respect to the earliest stages of ontogenesis." Note that this definition demonstrates his support for the hourglass model (see below). Recent papers refer to the phylotypic period, or the phylotypic stage, as a period of maximal similarity between species within each animal phylum.

While this concept was originally devised using morphological comparisons of developing embryos from different species, the period of maximal similarity has recently been identified using molecular evidence. The phylotypic period has been identified using conservation of gene expression, estimates of gene age, gene sequence conservation, the expression of regulatory genes and transcription factors, and the interconnectivity of genes and proteins.

Funnel and hourglass models

The funnel model is the hypothesis that the most conserved stage of development (the phylotypic period) occurs at the beginning of embryogenesis, with increasing divergence as development progresses. This is also known as the early conservation model of development.

Evidence for an alternative model arose from careful comparisons of the temporal divergence in morphology of the embryos of different species. For example, Klaus Sander noticed that the “incredible variation in larvae and adults” of insects occurs after they "develop from nearly identical rudiments in the germ band stage". The most conserved stage of development, the germ band stage, occurs near the middle of development rather than at the beginning, supporting a mid-developmental period of maximal similarity between species. This model, called the hourglass model, is the idea that early embryos of different species display divergent forms but their morphologies converge in the middle of development, followed by a period of increasing divergence.

Support for hourglass model

Contrary to the early morphological work by von Baer and Haeckel, recent morphological studies have demonstrated the greatest divergence among closely related species both early in development (gastrulation) and late in development, supporting the hourglass model. Further support for the hourglass model came from the discovery that Hox genes, a group of sequentially activated genes that regulate anterior-posterior body axis formation, are activated during the middle of development at the phylotypic stage. Because these genes are highly conserved and are involved in body axis formation, the activation of Hox genes could be an important player in the heightened conservation among embryos of closely related species during mid-development.

The advent of next-generation sequencing enabled scientists to use molecular methods to identify the period of development that has the most conserved gene expression patterns among different species. In 2010, two studies found molecular evidence that supports the hourglass model. Kalinka et al. sequenced the transcriptome of six Drosophila species over developmental time, identifying the most conserved gene expression in mid-development during the arthropod germ band developmental stage. Genes that were enriched in the developing embryos at the germ band stage are involved in cellular and organismal development. Domazet-Lošo and Tautz analyzed the transcriptome of zebrafish (Danio rerio) over developmental time, from unfertilized eggs to adults. They used a method called genomic phylostratigraphy to estimate the age of each gene during development. In zebrafish, as well as in additional transcriptomic datasets of Drosophila, the mosquito Anopheles and the nematode Caenorhabditis elegans, the authors found that genes expressed during mid-development are older than those expressed at the beginning and end of development, supporting the hourglass model.

Other recent genomic studies have supported a mid-developmental phylotypic stage in vertebrates and in the plant Arabidopsis thaliana. The temporal gene expression profiles for a developing mouse (Mus musculus), chicken (Gallus gallus), frog (Xenopus laevis) and zebrafish (Danio rerio) revealed that the most conserved gene expression in vertebrates occurs in mid-development at the pharyngular embryo stage. The pharyngula stage occurs when the four distinguishing features of vertebrates (notochord, dorsal hollow nerve cord, post-anal tail, and a series of paired branchial slits) have developed.

Support for early conservation (funnel) model

Recent molecular data also provide support for the early conservation model. For example, Piasecka et al. re-analyzed the zebrafish dataset published by Domazet-Lošo and Tautz. They found that applying a log-transformation to the gene expression data changed the results to support highest conservation in early development. Further, after clustering the zebrafish gene expression data into “transcription modules” reflecting each stage of development, they found multiple lines of evidence supporting the early conservation model (gene sequence, age, gene family size, and expression conservation) while only the analysis of gene regulatory regions supported the hourglass model.

One hypothesis for the evolutionary conservation during the phylotypic period is that it is a period characterized by a high level of interactions as the body plan is being established. In zebrafish, the interconnectivity of proteins over developmental time was found to be highest in early development, supporting the early conservation model. Another way to examine the point in development at which developmental constraints are the strongest is through experimental gene loss, because the removal of a gene should be more deleterious when it is expressed at a developmental stage with stronger evolutionary constraints. Gene knockout experiments from mice and zebrafish demonstrated that the ratio of essential genes to non-essential genes decreases over developmental time, suggesting that there are stronger constraints in early development that are relaxed over time. Despite increasing evidence supporting the hourglass model, identifying the point in development that is most conserved among species with a phylum (the phylotypic period) is a controversy in the field of developmental biology.

Intra-phylum vs. inter-phylum phylotypic period

The phylotypic period is defined as a period of maximal similarity between species within a phylum, but a recent study compared the phylotypic period across different phyla to examine whether the same conserved periods during development have been maintained across deeper phylogenetic relationships. Levin et al. compared the developmental gene expression patterns among ten individuals from ten different animal phyla and found evidence for an inverse hourglass model of gene expression divergence among different phyla. This inverse hourglass model reflects the observation that gene expression was significantly more divergent among species at the mid-developmental transition, while gene expression was more conserved in early and late stages of development. While this intriguing pattern could have implications for our definition of a phylum, a follow-up paper argued that there are a few methodical issues that must be addressed to test the hypothesis that the timing of developmental constraints are different among phyla compared to within a phylum. First, the comparison of a single representative of ten different phyla could reflect differences between phyla as well as the deeper or shallower phylogenetic branches that fall between those ten individuals, so greater sampling within each phyla is necessary. Second, pairwise comparisons treat each of the ten species as independent observations, but some species are more closely related than others.

Homeobox

From Wikipedia, the free encyclopedia
 
Homeodomain
The Antennapedia homeodomain protein from Drosophila melanogaster bound to a fragment of DNA. The recognition helix and unstructured N-terminus are bound in the major and minor grooves respectively.

A homeobox is a DNA sequence, around 180 base pairs long, that regulates large-scale anatomical features in the early stages of embryonic development. Mutations in a homeobox may change large-scale anatomical features of the full-grown organism.

Homeoboxes are found within genes that are involved in the regulation of patterns of anatomical development (morphogenesis) in animals, fungi, plants, and numerous single cell eukaryotes. Homeobox genes encode homeodomain protein products that are transcription factors sharing a characteristic protein fold structure that binds DNA to regulate expression of target genes.Homeodomain proteins regulate gene expression and cell differentiation during early embryonic development, thus mutations in homeobox genes can cause developmental disorders.

Homeosis is a term coined by William Bateson to describe the outright replacement of a discrete body part with another body part, e.g. antennapedia—replacement of the antenna on the head of a fruit fly with legs. The "homeo-" prefix in the words "homeobox" and "homeodomain" stems from this mutational phenotype, which is observed when some of these genes are mutated in animals. The homeobox domain was first identified in a number of Drosophila homeotic and segmentation proteins, but is now known to be well-conserved in many other animals, including vertebrates.

Discovery

Drosophila with the antennapedia mutant phenotype exhibit homeotic transformation of the antennae into leg-like structures on the head.

The existence of homeobox genes was first discovered in Drosophila by isolating the gene responsible for a homeotic transformation where legs grow from the head instead of the expected antennae. Walter Gehring identified a gene called antennapedia that caused this homeotic phenotype. Analysis of antennapedia revealed that this gene contained a 180 base pair sequence that encoded a DNA binding domain, which William McGinnis termed the "homeobox". The existence of additional Drosophila genes containing the antennapedia homeobox sequence was independently reported by Ernst Hafen, Michael Levine, William McGinnis, and Walter Jakob Gehring of the University of Basel in Switzerland and Matthew P. Scott and Amy Weiner of Indiana University in Bloomington in 1984. Isolation of homologous genes by Edward de Robertis and William McGinnis revealed that numerous genes from a variety of species contained the homeobox. Subsequent phylogenetic studies detailing the evolutionary relationship between homeobox-containing genes showed that these genes are present in all bilaterian animals.

Homeodomain structure

The characteristic homeodomain protein fold consists of a 60-amino acid long domain composed of three alpha helixes. The following shows the consensus homeodomain (~60 amino acid chain):

            Helix 1          Helix 2         Helix 3/4
         ______________    __________    _________________
RRRKRTAYTRYQLLELEKEFHFNRYLTRRRRIELAHSLNLTERHIKIWFQNRRMKWKKEN
....|....|....|....|....|....|....|....|....|....|....|....|
         10        20        30        40        50        60
The vnd/NK-2 homeodomain-DNA complex. Helix 3 of the homeodomain binds in the major groove of the DNA and the N-terminal arm binds in the minor groove, in analogy with other homeodomain-DNA complexes.

Helix 2 and helix 3 form a so-called helix-turn-helix (HTH) structure, where the two alpha helices are connected by a short loop region. The N-terminal two helices of the homeodomain are antiparallel and the longer C-terminal helix is roughly perpendicular to the axes established by the first two. It is this third helix that interacts directly with DNA via a number of hydrogen bonds and hydrophobic interactions, as well as indirect interactions via water molecules, which occur between specific side chains and the exposed bases within the major groove of the DNA.

Homeodomain proteins are found in eukaryotes. Through the HTH motif, they share limited sequence similarity and structural similarity to prokaryotic transcription factors, such as lambda phage proteins that alter the expression of genes in prokaryotes. The HTH motif shows some sequence similarity but a similar structure in a wide range of DNA-binding proteins (e.g., cro and repressor proteins, homeodomain proteins, etc.). One of the principal differences between HTH motifs in these different proteins arises from the stereochemical requirement for glycine in the turn which is needed to avoid steric interference of the beta-carbon with the main chain: for cro and repressor proteins the glycine appears to be mandatory, whereas for many of the homeotic and other DNA-binding proteins the requirement is relaxed.

Sequence specificity

Homeodomains can bind both specifically and nonspecifically to B-DNA with the C-terminal recognition helix aligning in the DNA's major groove and the unstructured peptide "tail" at the N-terminus aligning in the minor groove. The recognition helix and the inter-helix loops are rich in arginine and lysine residues, which form hydrogen bonds to the DNA backbone. Conserved hydrophobic residues in the center of the recognition helix aid in stabilizing the helix packing. Homeodomain proteins show a preference for the DNA sequence 5'-TAAT-3'; sequence-independent binding occurs with significantly lower affinity. The specificity of a single homeodomain protein is usually not enough to recognize specific target gene promoters, making cofactor binding an important mechanism for controlling binding sequence specificity and target gene expression. To achieve higher target specificity, homeodomain proteins form complexes with other transcription factors to recognize the promoter region of a specific target gene.

Biological function

Homeodomain proteins function as transcription factors due to the DNA binding properties of the conserved HTH motif. Homeodomain proteins are considered to be master control genes, meaning that a single protein can regulate expression of many target genes. Homeodomain proteins direct the formation of the body axes and body structures during early embryonic development. Many homeodomain proteins induce cellular differentiation by initiating the cascades of coregulated genes required to produce individual tissues and organs. Other proteins in the family, such as NANOG are involved in maintaining pluripotency and preventing cell differentiation.

Regulation

Hox genes and their associated microRNAs are highly conserved developmental master regulators with tight tissue-specific, spatiotemporal control. These genes are known to be dysregulated in several cancers and are often controlled by DNA methylation. The regulation of Hox genes is highly complex and involves reciprocal interactions, mostly inhibitory. Drosophila is known to use the polycomb and trithorax complexes to maintain the expression of Hox genes after the down-regulation of the pair-rule and gap genes that occurs during larval development. Polycomb-group proteins can silence the Hox genes by modulation of chromatin structure.

Mutations

Mutations to homeobox genes can produce easily visible phenotypic changes in body segment identity, such as the Antennapedia and Bithorax mutant phenotypes in Drosophila. Duplication of homeobox genes can produce new body segments, and such duplications are likely to have been important in the evolution of segmented animals.

Evolution

The homeobox itself may have evolved from a non-DNA-binding transmembrane domain at the C-terminus of the MraY enzyme. This is based on metagenomic data acquired from the transitional archaeon, Lokiarchaeum, that is regarded as the prokaryote closest to the ancestor of all eukaryotes.

Phylogenetic analysis of homeobox gene sequences and homeodomain protein structures suggests that the last common ancestor of plants, fungi, and animals had at least two homeobox genes. Molecular evidence shows that some limited number of Hox genes have existed in the Cnidaria since before the earliest true Bilatera, making these genes pre-Paleozoic. It is accepted that the three major animal ANTP-class clusters, Hox, ParaHox, and NK (MetaHox), are the result of segmental duplications. A first duplication created MetaHox and ProtoHox, the latter of which later duplicated into Hox and ParaHox. The clusters themselves were created by tandem duplications of a single ANTP-class homeobox gene. Gene duplication followed by neofunctionalization is responsible for the many homeobox genes found in eukaryotes. Comparison of homeobox genes and gene clusters has been used to understand the evolution of genome structure and body morphology throughout metazoans.

Types of homeobox genes

Hox genes

Hox gene expression in Drosophila melanogaster.

Hox genes are the most commonly known subset of homeobox genes. They are essential metazoan genes that determine the identity of embryonic regions along the anterior-posterior axis. The first vertebrate Hox gene was isolated in Xenopus by Edward De Robertis and colleagues in 1984. The main interest in this set of genes stems from their unique behavior and arrangement in the genome. Hox genes are typically found in an organized cluster. The linear order of Hox genes within a cluster is directly correlated to the order they are expressed in both time and space during development. This phenomenon is called colinearity.

Mutations in these homeotic genes cause displacement of body segments during embryonic development. This is called ectopia. For example, when one gene is lost the segment develops into a more anterior one, while a mutation that leads to a gain of function causes a segment to develop into a more posterior one. Famous examples are Antennapedia and bithorax in Drosophila, which can cause the development of legs instead of antennae and the development of a duplicated thorax, respectively.

In vertebrates, the four paralog clusters are partially redundant in function, but have also acquired several derived functions. For example, HoxA and HoxD specify segment identity along the limb axis. Specific members of the Hox family have been implicated in vascular remodeling, angiogenesis, and disease by orchestrating changes in matrix degradation, integrins, and components of the ECM. HoxA5 is implicated in atherosclerosis. HoxD3 and HoxB3 are proinvasive, angiogenic genes that upregulate b3 and a5 integrins and Efna1 in ECs, respectively. HoxA3 induces endothelial cell (EC) migration by upregulating MMP14 and uPAR. Conversely, HoxD10 and HoxA5 have the opposite effect of suppressing EC migration and angiogenesis, and stabilizing adherens junctions by upregulating TIMP1/downregulating uPAR and MMP14, and by upregulating Tsp2/downregulating VEGFR2, Efna1, Hif1alpha and COX-2, respectively. HoxA5 also upregulates the tumor suppressor p53 and Akt1 by downregulation of PTEN. Suppression of HoxA5 has been shown to attenuate hemangioma growth. HoxA5 has far-reaching effects on gene expression, causing ~300 genes to become upregulated upon its induction in breast cancer cell lines. HoxA5 protein transduction domain overexpression prevents inflammation shown by inhibition of TNFalpha-inducible monocyte binding to HUVECs.

LIM genes

LIM genes (named after the initial letters of the names of three proteins where the characteristic domain was first identified) encode two 60 amino acid cysteine and histidine-rich LIM domains and a homeodomain. The LIM domains function in protein-protein interactions and can bind zinc molecules. LIM domain proteins are found in both the cytosol and the nucleus. They function in cytoskeletal remodeling, at focal adhesion sites, as scaffolds for protein complexes, and as transcription factors.

Pax genes

Most Pax genes contain a homeobox and a paired domain that also binds DNA to increase binding specificity, though some Pax genes have lost all or part of the homeobox sequence. Pax genes function in embryo segmentation, nervous system development, generation of the frontal eye fields, skeletal development, and formation of face structures. Pax 6 is a master regulator of eye development, such that the gene is necessary for development of the optic vesicle and subsequent eye structures.

POU genes

Proteins containing a POU region consist of a homeodomain and a separate, structurally homologous POU domain that contains two helix-turn-helix motifs and also binds DNA. The two domains are linked by a flexible loop that is long enough to stretch around the DNA helix, allowing the two domains to bind on opposite sides of the target DNA, collectively covering an eight-base segment with consensus sequence 5'-ATGCAAAT-3'. The individual domains of POU proteins bind DNA only weakly, but have strong sequence-specific affinity when linked. The POU domain itself has significant structural similarity with repressors expressed in bacteriophages, particularly lambda phage.

Plant homeobox genes

As in animals, the plant homeobox genes code for the typical 60 amino acid long DNA-binding homeodomain or in case of the TALE (three amino acid loop extension) homeobox genes for an atypical homeodomain consisting of 63 amino acids. According to their conserved intron–exon structure and to unique codomain architectures they have been grouped into 14 distinct classes: HD-ZIP I to IV, BEL, KNOX, PLINC, WOX, PHD, DDT, NDX, LD, SAWADEE and PINTOX. Conservation of codomains suggests a common eukaryotic ancestry for TALE and non-TALE homeodomain proteins.

Body plan

From Wikipedia, the free encyclopedia
Modern groups of animals can be grouped by the arrangement of their body structures, so are said to possess different body plans.

A body plan, Bauplan (pl. German: Baupläne), or ground plan is a set of morphological features common to many members of a phylum of animals. The vertebrates share one body plan, while invertebrates have many.

This term, usually applied to animals, envisages a "blueprint" encompassing aspects such as symmetry, layers, segmentation, nerve, limb, and gut disposition. Evolutionary developmental biology seeks to explain the origins of diverse body plans.

Body plans have historically been considered to have evolved in a flash in the Ediacaran biota; filling the Cambrian explosion with the results, and a more nuanced understanding of animal evolution suggests gradual development of body plans throughout the early Palaeozoic. Recent studies in animals and plants started to investigate whether evolutionary constraints on body plan structures can explain the presence of developmental constraints during embryogenesis such as the phenomenon referred to as phylotypic stage.

History

Among the pioneering zoologists, Linnaeus identified two body plans outside the vertebrates; Cuvier identified three; and Haeckel had four, as well as the Protista with eight more, for a total of twelve. For comparison, the number of phyla recognised by modern zoologists has risen to 36.

Linnaeus, 1735

In his 1735 book Systema Naturæ, Swedish botanist Linnaeus grouped the animals into quadrupeds, birds, "amphibians" (including tortoises, lizards and snakes), fish, "insects" (Insecta, in which he included arachnids, crustaceans and centipedes) and "worms" (Vermes). Linnaeus's Vermes included effectively all other groups of animals, not only tapeworms, earthworms and leeches but molluscs, sea urchins and starfish, jellyfish, squid and cuttlefish.

Cuvier, 1817

Haeckel's 'Monophyletischer Stambaum der Organismen' from Generelle Morphologie der Organismen (1866) with the three branches Plantae, Protista, Animalia

In his 1817 work, Le Règne Animal, French zoologist Georges Cuvier combined evidence from comparative anatomy and palaeontology to divide the animal kingdom into four body plans. Taking the central nervous system as the main organ system which controlled all the others, such as the circulatory and digestive systems, Cuvier distinguished four body plans or embranchements:

  1. with a brain and a spinal cord (surrounded by skeletal elements)
  2. with organs linked by nerve fibres
  3. with two longitudinal, ventral nerve cords linked by a band with two ganglia below the oesophagus
  4. with a diffuse nervous system, not clearly discernible

Grouping animals with these body plans resulted in four branches: vertebrates, molluscs, articulata (including insects and annelids) and zoophytes or radiata.

Haeckel, 1866

Ernst Haeckel, in his 1866 Generelle Morphologie der Organismen, asserted that all living things were monophyletic (had a single evolutionary origin), being divided into plants, protista, and animals. His protista were divided into moneres, protoplasts, flagellates, diatoms, myxomycetes, myxocystodes, rhizopods, and sponges. His animals were divided into groups with distinct body plans: he named these phyla. Haeckel's animal phyla were coelenterates, echinoderms, and (following Cuvier) articulates, molluscs, and vertebrates.

Gould, 1979

Stephen J. Gould explored the idea that the different phyla could be perceived in terms of a Bauplan, illustrating their fixity. However, he later abandoned this idea in favor of punctuated equilibrium.

Origin

20 out of the 36 body plans originated in the Cambrian period, in the "Cambrian explosion". However, complete body plans of many phyla emerged much later, in the Palaeozoic or beyond.

The current range of body plans is far from exhaustive of the possible patterns for life: the Precambrian Ediacaran biota includes body plans that differ from any found in currently living organisms, even though the overall arrangement of unrelated modern taxa is quite similar. Thus the Cambrian explosion appears to have more or less completely replaced the earlier range of body plans.

Genetic basis

Genes, embryos and development together determine the form of an adult organism's body, through the complex switching processes involved in morphogenesis.

Developmental biologists seek to understand how genes control the development of structural features through a cascade of processes in which key genes produce morphogens, chemicals that diffuse through the body to produce a gradient that acts as a position indicator for cells, turning on other genes, some of which in turn produce other morphogens. A key discovery was the existence of groups of homeobox genes, which function as switches responsible for laying down the basic body plan in animals. The homeobox genes are remarkably conserved between species as diverse as the fruit fly and humans, the basic segmented pattern of the worm or fruit fly being the origin of the segmented spine in humans. The field of animal evolutionary developmental biology ('Evo Devo'), which studies the genetics of morphology in detail, is rapidly expanding with many of the developmental genetic cascades, particularly in the fruit fly Drosophila, catalogued in considerable detail.

Slave health on plantations in the United States

From Wikipedia, the free encyclopedia

The health of slaves on American plantations was a matter of concern to both slaves and their owners. Slavery had associated with it the health problems commonly associated with poverty. It was to the economic advantage of owners to keep their working slaves healthy, and those of reproductive age reproducing. Those who could not work or reproduce because of illness or age were sometimes abandoned by their owners, expelled from plantations, and left to fend for themselves.

Life expectancy

A broad and common measure of the health of a population is its life expectancy. The life expectancy in 1850 of a White person in the United States was forty; for a slave, it was twenty-two. Mortality statistics for Whites were calculated from census data; statistics for slaves were based on small sample-sizes.

Diseases among slaves

European physicians in the West Indies frequently shared their knowledge of black-related diseases with North American colleagues. Diseases that were thought to be "negro diseases" included, but were not limited to:

While working on plantations in the Southern United States, many slaves faced serious health problems. Improper nutrition, the unsanitary living conditions, and excessive labor made them more susceptible to diseases than their owners; the death rates among the slaves were significantly higher due to diseases.

Considered today to be abuse based on pseudo-science, two alleged mental illnesses of negros were described in scientific literature: drapetomania, the mental illness that made slaves desire to run away, and dysaesthesia aethiopica, laziness or "rascality". Both were treated with whippings.

Slave diet

There are contrasting views on slave's diets and access to food. Some portray slaves as having plenty to eat, while others portray "the fare of the plantation [as] coarse and scanty". For the most part, slaves' diet consisted of a form of fatty pork and corn or rice. Historian Ulrich Bonnell Phillips found that slaves received the following standard, with little or no deviation: "a quart (1 liter) of cornmeal and half-pound (300 gm) of salt pork per day for each adult and proportionally for children, commuted or supplemented with sweet potatoes, field peas, syrup, rice, fruit, and 'garden sass' [vegetables]". Scholars came to realize that the slave's diets were quantitatively satisfactory, but not qualitatively sufficient. The poor quality of food led to slaves that were either "physically impaired or chronically ill".

Antebellum plantations had a larger population of hogs than cows, therefore producing more pork than beef. There are a few reasons behind having more pigs than cows: a stereotype that slaves preferred pork over beef, pigs were easier to feed, beef was harder to preserve so it was typically only served fresh (which happened more often in the winter because the cold slowed spoiling), a fear of fresh meat because it was believed that it caused disease among blacks (which it was probably not that fresh), and the planters' conviction that "hog was the only proper meat for laborers".

Due to the shortage of cows, slave diets lacked milk. There was often a stereotype in the Antebellum South that slaves were lactose intolerant. However, many slaves had trouble digesting lactose (in dairy products) because it was not a staple in African diets. Due to the summer heat and the poor quality of the animals themselves, milk became a scarce product only available seasonally. When it did become available, it was first given to Whites and if any remained, then to slave children. Additionally, there is some scientific hypotheses behind blacks more often being lactose intolerant than Whites today. In West Africa, the presence of the tsetse fly made raising cattle practically impossible, creating a historical situation in which there was no need for humans to develop higher levels of the lactate enzyme (which allows the body to digest lactate).

Due to slaves' diets lacking quality, there were many vitamin and nutrient insufficiencies that lead to sicknesses. These were not recognized at the time as caused by poor diet.

  • Vitamin A deficiency led to weakened eyesight. (Vitamin A was not identified until the 20th century.)
  • Lack of milk contributed to diseases such as rickets and calcium deficiency, causing weakened bones.
  • Inadequate iron led to anemia.

Clothing

The masters only gave slaves pairs of "gator shoes" or "brogans" for footwear, and sometimes children and adults who were not working had to walk around barefoot. These clothes and shoes were insufficient for field work; they did not last very long for field slaves. It is judged that the health of male workers broke down rapidly after they joined the field gangs.

Medical attentions

Page from Francis T. Tennille Slave Medical Care Accounts, 1859-1860

"Evidence exists that many...masters provided some health care for their slave investments.... Some planters employed doctors to come every two weeks to check on slaves' health and give them any needed medicine." This was quite lucrative for the physicians.

However, slave masters often tried to cure their ill slaves before they called for a doctor. Planters wishing to save money relied on their own self-taught skills and the help of their wives to address the health care needs of slaves. Some Black people developed or retained from African heritage their own brand of care, complete with special remedies, medical practitioners, and rituals. If the home treatment did not help to improve the slave's condition, they would then send them to the physician or ask the doctor to come to the plantation. A slave who became ill meant loss of working time; death an even greater loss. Given the cost of slaves and their importance to plantation economies, planters organized slave hospitals to treat their serious health problems. There were also separate physicians for slaves and whites because it was believed that slaves' bodies were fundamentally different from whites'. Due to this thinking, many slaves became the subjects of physician's experimental interests to help expand both the physician's knowledge and reputation, often resulting in slave's mutilation and death.

Slave hospitals

Slave hospitals were thought to be an essential part of plantation life by Dr. A. P. Merrill and Dr. Samuel A. Cartwright. The physicians believed that the slaves' bodies were biologically and physiologically different than those of Whites; therefore, they should have their own resource for medical attention and treatment. In some histories of the Antebellum South, like William Scarborough's Masters of the Big House (2006), slaveholders are depicted as going to great lengths to protect the health of their slaves. Examples of this include vaccinating slave infants against smallpox, paying hundreds of thousands of dollars in medical expenses, and dispensing sherry or madeira wine to sick slaves. Dr. Merrill provides a detailed description of what he thought slave hospitals should be like in an 1853 article about plantation hygiene. However, in reality, the hospitals were representations of the way slaves were viewed: as chattel. They were often a slave cabin used to isolate those with a fever or illness to make sure that the slave was not faking an illness in an attempt to run away. Frances Kemble's recollection of the slave infirmary at Butler Island, Georgia, paints a stark reality of slave women lying on the floor in "tattered and filthy blankets". Dr. J. Marion Sims set up, in his back yard in Montgomery, Alabama,the first hospital in the United States for black females, on whom he developed techniques and materials (silver suture) for gynecological surgery. In the later 20th century, Sims' surgical experimentation on enslaved women, who could not consent because they could not refuse, was criticized as unethical.

Experimentation

Southern medical education's predisposition for use of black bodies to teach anatomy and be subjects of clinical experiments led to a major distrust of White physicians among slaves. The exploitation of slave's bodies for medical knowledge created a horrific doctor-patient relationship that involved a third party: the slave owner. This relationship often left the slave voiceless and deemed "medically incompetent", therefore taking control of their own bodies away from them.

Gynecology

A major field of experimentation that involved slaves was gynecology under Dr. J. Marion Sims in Montgomery, Alabama between 1845 and 1849. Dr. Sims is known for being a pioneer in the treatment of clubfoot, advances in "women's medicine", his role in the founding of the Women's Hospital in New York, and as the "father of American gynecology". Sims routinely operated on nine slave women, of which only three are known: Anarcha, Betsy, and Lucy. The purpose of the operations was to try and fix conditions called vesico-vaginal fistula and recto-vaginal fistula, i.e. a tear in the vaginal wall resulting in chronic leakage from the bladder or colon. These conditions were common results of childbirth during Sims' time. However, these conditions do not include symptoms of chronic pain, just discomfort and most likely embarrassment, suggesting that Sims was exaggerating their conditions to gain a competitive edge over his colleagues.

Betsy, Anarcha, and Lucy survived multiple attempts to fix their condition, and although Sims was able to close the fistula, small perforations remained after healing, leakage continued, and often the sutures became infected. It was not until after the thirtieth surgery that Sims was successful on Anarcha. During these surgeries, the women were not under anesthesia, only an ineffective opium that resulted in constipation and nausea instead of anesthetic. After the success of Anarcha, many White women came to Sims to have the procedure, yet none of them endured a single operation, noting the intense pain associated with the surgery.

Other

Dr. Sims also performed other surgical experimentations on slaves, including facial operations. Slave owners came to Sims in last attempt efforts to save their investments. One particular case that was published in The American Journal of the Medical Sciences involved a slave named Sam whose owner thought he had a gumboil on his face that was a result of syphilis medication. Surgery was attempted on Sam before by another physician, but was unsuccessful because "at the first incision…Sam had leaped from is chair and absolutely refused to submit to further cutting". Sims knew of the attempted surgery and was "determined not to be foiled in the attempt" of his own. Sims attempted to dissect the patient's jaw-bone over the course of a forty-minute operation. In this time, Sims removed a tooth to make room and after unsuccessful attempts with a "small, long, narrow saw" and "Liston's bone forceps", Sims resorted to the chain-saw to remove the diseased bone. Infirmaries, like Sims', allowed physicians to be successful businessmen in the slavery-based Southern economy, but also to create professional reputations as clinical medical researchers.

Weathering hypothesis

From Wikipedia, the free encyclopedia

The weathering hypothesis was proposed to account for early health deterioration as a result of cumulative exposure to experiences of social, economic and political adversity. It is well documented that minority groups and marginalized communities suffer from poorer health outcomes. This may be due to a multitude of stressors including prejudice, social alienation, institutional bias, political oppression, economic exclusion and racial discrimination. The weathering hypothesis proposes that the cumulative burden of these stressors as individuals age is "weathering," and the increased weathering experienced by minority groups compared to others can account for differences in health outcomes. In recent years, the biological plausibility of the weathering hypothesis has been investigated in studies evaluating the physiological effects of social, environmental and political stressors among marginalized communities. This has led to more widespread use of the weathering hypothesis as a framework for explaining health disparities on the basis of differential exposure to racially based stressors. Researchers have also identified patterns connecting weathering to biological phenomena associated with stress and aging, such as allostatic load, epigenetics, telomere shortening, and accelerated brain aging.

Origins

The weathering hypothesis was initially formulated by Dr. Arline T. Geronimus to explain the poor maternal health and birth outcomes of African American women that she observed in correspondence with increased age. While working part-time at a school for pregnant teenagers in Trenton, New Jersey, Geronimus first noticed that the teens who came to the school tended to have far more health problems than her classmates at Princeton University. She thus began to wonder whether the health conditions of the teens at that clinic may have been caused by their environment. Subsequent research on the disparity in maternal health between African American and white women led Geronimus to propose the weathering hypothesis. She proposed that the accumulation of cultural, social and economic disadvantages may lead to earlier deterioration of health among African American women compared to their non-Hispanic, white counterparts. Geronimus specifically chose the term weathering as a metaphor for the effects she perceived that exposure to stress was having on the health of marginalized people. While the weathering hypothesis was initially proposed based on observations of patterns in maternal health, academics have expanded its application as a framework to examine other health disparities as well.

Geronimus' research

While conducting research in the Department of Public Health Policy and Administration as a graduate student at the University of Michigan in 1992, Geronimus noticed a trend in disparities between the fertility of African American women versus their white counterparts. She noted that while the average white woman experiences her point of highest fertility and lowest risk of pregnancy complications or neonatal mortality in her 20's and 30's, this generalization did not apply to African American women. Instead, among African American women, teen mothers are most likely to have healthy pregnancies and offspring. The data indicated a widening disparity in black-white infant mortality as maternal ages increase. Subsequently, Geronimus proposed the "weathering hypothesis," which she initially conceived as a potential explanation for the patterns of racial variation in infant mortality with increasing maternal age.

Health disparities

In the context of the weathering hypothesis, individual health is dynamic and shaped over time by social, economic, and environmental influences. These social determinants dictate what different demographics are exposed to as they develop and age. Racism and discrimination are two specific social determinants that lay the foundation for systemic inequality in access and upward mobility. This entrenchment of social inequities disproportionately impacts minorities and communities of color, who remain in environments of poverty that have significantly more stressors than those of wealthier, predominantly white communities. These stressors—and the associated burden of coping with them—manifest as physiological responses that have detrimental effects on individual health, often leading to a disproportionately high occurrence of chronic illness and shorter life expectancy in minority communities. Multiethnic studies have yielded significant data demonstrating that weathering—accumulated health risk due to social, economic and environmental stressors—is a manifestation of social stratification that systemically influences disparities in health and mortality between dominant and minority communities.

Maternal health

Maternal mortality is three to four times higher for Black mothers than white mothers in the United States. Infant mortality is also twice as high for infants born to non-Hispanic Black mothers compared to infants born to non-Hispanic white mothers. Additionally, there are racial disparities for negative birth outcomes like low birth weight, which has been found to influence risk of infant mortality and developmental outcomes after birth, and preterm birth. Across all women, older maternal age is associated with higher rates of these negative outcomes during pregnancy, but studies have consistently found that rates rise more rapidly for Black women than white women. The weathering hypothesis proposes that the accumulation of racial stress over Black women's lives contributes to this observed pattern of racial disparities in maternal health and birth outcomes that increase with maternal age. Research has consistently identified an association between preterm birth and low birth weight in Black women and maternal stress caused by experiences of racism, systemic bias, socioeconomic disadvantage, segregated neighborhoods, and high rates of violent crime. There is biological evidence of weathering, including the finding that Black women have shorter telomeres, a biological indicator of age, when compared with white women of the same chronological age. Though increased socioeconomic status serves as a protective factor against negative birth outcomes for non-Hispanic white mothers, disproportionate rates of preterm birth and low birth weight for non-Hispanic Black mothers have been found at every education and income level. The weathering hypothesis has also been used to explain this trend because upward socioeconomic mobility is associated with increased exposure to discrimination for women of color.

There is modest evidence supporting the effects of weathering on mothers from other minority groups, including for high birth weight outcomes among American Indian/Alaska Native women. Research has started to explore whether the weathering hypothesis could also explain racial disparities in the outcomes of assisted reproductive technologies, but so far the findings are inconsistent.

Mental health

Research shows that mental health disparities among marginalized communities exist. Daily discrimination faced by marginalized groups have been found to be associated with increased depressive symptoms and feelings of loneliness. Low-income communities are more likely to have severe mental illnesses, which is frequently heightened by the inaccessibility to quality healthcare. Researchers found that persisting epigenetic changes lead to increased risk of postpartum depression as a result of adverse life events and cumulative life stress among Black, Latinx, and low-income women. In a study assessing African American men, experiences of racism were linked to a poorer mental health state.

Cognition

Black Americans often show mean level differences in cognition across multiple cognitive domains compared to non-Hispanic Whites. These cognitive disparities often are reduced or eliminated when factoring various social determinants of health such as stress, education quality, economic stability, or quality of healthcare. Black Americans also have higher rates of Alzheimer's disease and related dementias than non-Hispanic Whites. These higher rates of Alzheimer's disease might be due to the impact of more negative and pronounced social determinants of health, including racial discrimination, that might accelerate brain aging disproportionately in Black Americans.

Intersectionality of systems of oppression

Intersectionality is a term coined by Kimberlé Crenshaw to describe the interconnected nature of different systems of oppression, the layered effects of which can be seen in the healthcare system. Research indicates that lower class status and increased depressive symptoms are associated with higher levels of biological weathering among Black individuals in comparison to white individuals. In a study exploring disparities in mental health, researchers found that Black sexual minority women reported higher frequencies of discrimination and decreased levels of social and psychological well-being than their white sexual minority women counterparts. Black sexual minority women had decreased levels of social well-being and increased levels of depressive symptoms in comparison to Black sexual minority men. African American women are also more likely to contract COVID-19 than African American men and white women. The prevalence of medical racism and sexism (lack of quality healthcare, harmful experimentation, etc.) has led to negative relationships with healthcare systems and increased risk of negative sexual and reproductive health outcomes among African American women. Existing research show how systems of oppression work together to oppress marginalized groups within the healthcare system and, as a result, these groups disproportionately experience negative health effects. Aging adults experience further intersections with health, health care, and structural inequalities that exacerbates health in marginalized groups.

Criticism and related theories

Arline Geronimus faced significant pushback for the weathering hypothesis, including from members of the medical community who believed there was a genetic or evolutionary explanation for racial differences in health outcomes. There was some early criticism regarding the quality of her data, though the evidence of weathering and health disparities has grown since. Others pushed back against the weathering hypothesis because its application to racial disparities in maternal health seemed to contradict what advocacy groups had been saying about the negative consequences of teen pregnancy on young mothers. A further criticism of this theory believes that Geronimus and others have not sufficiently demonstrated a link between weathering and racial and gender disparities in life expectancy.

The weathering hypothesis was initially proposed as a sociological explanation for health disparities, but it is closely related to biological theories like the allostatic load model, which proposes that an individual's exposure to repeated or chronic stress over their lifetime has physiological consequences which can be measured through various biomarkers. Research has tended to discuss allostasis and allostatic load as the molecular mechanism behind the weathering hypothesis, and Geronimus herself went on to study racial differences in allostatic load. Another related theory is the life course approach, which emphasizes focus on cumulative life experiences rather than maternal risk factors as an explanation for birth outcome disparities. Researchers have also been interested in studying the possibility of children inheriting the epigenetic changes which result from their mother's cumulative life stress, which could relate the weathering hypothesis with transgenerational trauma.

Magnetization

From Wikipedia, the free encyclopedia https://en.wikipedia.org/wiki/Magnetizat...