AI - Technological Singularity

 

The emergence of technologies that could fundamentally change humans' role in society, challenge human epistemic agency and ontological status, and trigger unprecedented and unforeseen developments in all aspects of life, whether biological, social, cultural, or technological, is referred to as the Technological Singularity.

The Singularity of Technology is most often connected with artificial intelligence, particularly artificial general intelligence (AGI).

As a result, it's frequently depicted as an intelligence explosion that's pushing advancements in fields like biotechnology, nanotechnology, and information technologies, as well as inventing new innovations.

The Technological Singularity is sometimes referred to as the Singularity, however it should not be confused with a mathematical singularity, since it has only a passing similarity.

This singularity, on the other hand, is a loosely defined term that may be interpreted in a variety of ways, each highlighting distinct elements of the technological advances.

The thoughts and writings of John von Neumann (1903–1957), Irving John Good (1916–2009), and Vernor Vinge (1944–) are commonly connected with the Technological Singularity notion, which dates back to the second half of the twentieth century.

Several universities, as well as governmental and corporate research institutes, have financed current Technological Singularity research in order to better understand the future of technology and society.

Despite the fact that it is the topic of profound philosophical and technical arguments, the Technological Singularity remains a hypothesis, a guess, and a pretty open hypothetical idea.

While numerous scholars think that the Technological Singularity is unavoidable, the date of its occurrence is continuously pushed back.

Nonetheless, many studies agree that the issue is not whether or whether the Technological Singularity will occur, but rather when and how it will occur.

Ray Kurzweil proposed a more exact timeline for the emergence of the Technological Singularity in the mid-twentieth century.

Others have sought to give a date to this event, but there are no well-founded grounds in support of any such proposal.

Furthermore, without applicable measures or signs, mankind would have no way of knowing when the Technological Singularity has occurred.

The history of artificial intelligence's unmet promises exemplifies the dangers of attempting to predict the future of technology.

The themes of superintelligence, acceleration, and discontinuity are often used to describe the Technological Singularity.

The term "superintelligence" refers to a quantitative jump in artificial systems' cognitive abilities, putting them much beyond the capabilities of typical human cognition (as measured by standard IQ tests).

Superintelligence, on the other hand, may not be restricted to AI and computer technology.

Through genetic engineering, biological computing systems, or hybrid artificial–natural systems, it may manifest in human agents.

Superintelligence, according to some academics, has boundless intellectual capabilities.

The curvature of the time curve for the advent of certain key events is referred to as acceleration.

Stone tools, the pottery wheel, the steam engine, electricity, atomic power, computers, and the internet are all examples of technological advancement portrayed as a curve across time emphasizing the discovery of major innovations.

Moore's law, which is more precisely an observation that has been viewed as a law, represents the increase in computer capacity.

"Every two years, the number of transistors in a dense integrated circuit doubles," it says.

People think that the emergence of key technical advances and new technological and scientific paradigms will follow a super-exponential curve in the event of the Technological Singularity.

One prediction regarding the Technological Singularity, for example, is that superintelligent systems would be able to self-improve (and self-replicate) in previously unimaginable ways at an unprecedented pace, pushing the technological development curve far beyond what has ever been witnessed.

The Technological Singularity discontinuity is referred to as an event horizon, and it is similar to a physical idea linked with black holes.

The analogy to this physical phenomena, on the other hand, should be used with care rather than being used to credit the physical world's regularity and predictability to technological singularity.

The limit of our knowledge about physical occurrences beyond a specific point in time is defined by an event horizon (also known as a prediction horizon).

It signifies that there is no way of knowing what will happen beyond the event horizon.

The discontinuity or event horizon in the context of technological singularity suggests that the technologies that precipitate technological singularity would cause disruptive changes in all areas of human life, developments about which experts cannot even conjecture.

The end of humanity and the end of human civilization are often related with technological singularity.

According to some research, social order will collapse, people will cease to be major actors, and epistemic agency and primacy would be lost.

Humans, it seems, will not be required by superintelligent systems.

These systems will be able to self-replicate, develop, and build their own living places, and humans will be seen as either barriers or unimportant, outdated things, similar to how humans now consider lesser species.

One such situation is represented by Nick Bostrom's Paperclip Maximizer.

AI is included as a possible danger to humanity's existence in the Global Catastrophic Risks Survey, with a reasonably high likelihood of human extinction, placing it on par with global pandemics, nuclear war, and global nanotech catastrophes.

However, the AI-related apocalyptic scenario is not a foregone conclusion of the Technological Singularity.

In other more utopian scenarios, technology singularity would usher in a new period of endless bliss by opening up new opportunities for humanity's infinite expansion.

Another element of technological singularity that requires serious consideration is how the arrival of superintelligence may imply the emergence of superethical capabilities in an all-knowing ethical agent.

Nobody knows, however, what superethical abilities might entail.

The fundamental problem, however, is that superintelligent entities' higher intellectual abilities do not ensure a high degree of ethical probity, or even any level of ethical probity.

As a result, having a superintelligent machine with almost infinite (but not quite) capacities but no ethics seems to be dangerous to say the least.

A sizable number of scholars are skeptical about the development of the Technological Singularity, notably of superintelligence.

They rule out the possibility of developing artificial systems with superhuman cognitive abilities, either on philosophical or scientific grounds.

Some contend that while artificial intelligence is often at the heart of technological singularity claims, achieving human-level intelligence in artificial systems is impossible, and hence superintelligence, and thus the Technological Singularity, is a dream.

Such barriers, however, do not exclude the development of superhuman brains via the genetic modification of regular people, paving the door for transhumans, human-machine hybrids, and superhuman agents.

More scholars question the validity of the notion of the Technological Singularity, pointing out that such forecasts about future civilizations are based on speculation and guesswork.

Others argue that the promises of unrestrained technological advancement and limitless intellectual capacities made by the Technological Singularity legend are unfounded, since physical and informational processing resources are plainly limited in the cosmos, particularly on Earth.

Any promises of self-replicating, self-improving artificial agents capable of super-exponential technological advancement are false, since such systems will lack the creativity, will, and incentive to drive their own evolution.

Meanwhile, social opponents point out that superintelligence's boundless technological advancement would not alleviate issues like overpopulation, environmental degradation, poverty, and unparalleled inequality.

Indeed, the widespread unemployment projected as a consequence of AI-assisted mass automation of labor, barring significant segments of the population from contributing to society, would result in unparalleled social upheaval, delaying the development of new technologies.

As a result, rather than speeding up, political or societal pressures will stifle technological advancement.

While technological singularity cannot be ruled out on logical grounds, the technical hurdles that it faces, even if limited to those that can presently be determined, are considerable.

Nobody expects the technological singularity to happen with today's computers and other technology, but proponents of the concept consider these obstacles as "technical challenges to be overcome" rather than possible show-stoppers.

However, there is a large list of technological issues to be overcome, and Murray Shanahan's The Technological Singularity (2015) gives a fair overview of some of them.

There are also some significant nontechnical issues, such as the problem of superintelligent system training, the ontology of artificial or machine consciousness and self-aware artificial systems, the embodiment of artificial minds or vicarious embodiment processes, and the rights granted to superintelligent systems, as well as their role in society and any limitations placed on their actions, if this is even possible.

These issues are currently confined to the realms of technological and philosophical discussion.

~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram

You may also want to read more about Artificial Intelligence here.

See also: 

Bostrom, Nick; de Garis, Hugo; Diamandis, Peter; Digital Immortality; Goertzel, Ben; Kurzweil, Ray; Moravec, Hans; Post-Scarcity, AI and; Superintelligence.

References And Further Reading

Bostrom, Nick. 2014. Superintelligence: Path, Dangers, Strategies. Oxford, UK: Oxford University Press.

Chalmers, David. 2010. “The Singularity: A Philosophical Analysis.” Journal of Consciousness Studies 17: 7–65.

Eden, Amnon H. 2016. The Singularity Controversy. Sapience Project. Technical Report STR 2016-1. January 2016.

Eden, Amnon H., Eric Steinhart, David Pearce, and James H. Moor. 2012. “Singularity Hypotheses: An Overview.” In Singularity Hypotheses: A Scientific and Philosophical Assessment, edited by Amnon H. Eden, James H. Moor, Johnny H. Søraker, and Eric Steinhart, 1–12. Heidelberg, Germany: Springer.

Good, I. J. 1966. “Speculations Concerning the First Ultraintelligent Machine.” Advances in Computers 6: 31–88.

Kurzweil, Ray. 2005. The Singularity Is Near: When Humans Transcend Biology. New York: Viking.

Sandberg, Anders, and Nick Bostrom. 2008. Global Catastrophic Risks Survey. Technical Report #2008/1. Oxford University, Future of Humanity Institute.

Shanahan, Murray. 2015. The Technological Singularity. Cambridge, MA: The MIT Press.

Ulam, Stanislaw. 1958. “Tribute to John von Neumann.” Bulletin of the American Mathematical Society 64, no. 3, pt. 2 (May): 1–49.

Vinge, Vernor. 1993. “The Coming Technological Singularity: How to Survive in the Post-Human Era.” In Vision 21: Interdisciplinary Science and Engineering in the Era of Cyberspace, 11–22. Cleveland, OH: NASA Lewis Research Center.

AI - What Is Superintelligence AI? Is Artificial Superintelligence Possible?

 

 

In its most common use, the phrase "superintelligence" refers to any degree of intelligence that at least equals, if not always exceeds, human intellect, in a broad sense.

Though computer intelligence has long outperformed natural human cognitive capacity in specific tasks—for example, a calculator's ability to swiftly interpret algorithms—these are not often considered examples of superintelligence in the strict sense due to their limited functional range.

In this sense, superintelligence would necessitate, in addition to artificial mastery of specific theoretical tasks, some kind of additional mastery of what has traditionally been referred to as practical intelligence: a generalized sense of how to subsume particulars into universal categories that are in some way worthwhile.

To this day, no such generalized superintelligence has manifested, and hence all discussions of superintelligence remain speculative to some degree.

Whereas traditional theories of superintelligence have been limited to theoretical metaphysics and theology, recent advancements in computer science and biotechnology have opened up the prospect of superintelligence being materialized.

Although the timing of such evolution is hotly discussed, a rising body of evidence implies that material superintelligence is both possible and likely.

If this hypothesis is proved right, it will very certainly be the result of advances in one of two major areas of AI research: 

1. Bioengineering 
2. Computer science

The former involves efforts to not only map out and manipulate the human DNA, but also to exactly copy the human brain electronically through full brain emulation, also known as mind uploading.

The first of these bioengineering efforts is not new, with eugenics programs reaching back to the seventeenth century at the very least.

Despite the major ethical and legal issues that always emerge as a result of such efforts, the discovery of DNA in the twentieth century, together with advances in genome mapping, has rekindled interest in eugenics.

Much of this study is aimed at gaining a better understanding of the human brain's genetic composition in order to manipulate DNA code in the direction of superhuman intelligence.

Uploading is a somewhat different, but still biologically based, approach to superintelligence that aims to map out neural networks in order to successfully transfer human intelligence onto computer interfaces.

• The brains of insects and tiny animals are micro-dissected and then scanned for thorough computer analysis in this relatively new area of study.

• The underlying premise of whole brain emulation is that if the brain's structure is better known and mapped, it may be able to copy it with or without organic brain tissue.

Despite the fast growth of both genetic mapping and whole brain emulation, both techniques have significant limits, making it less likely that any of these biological approaches will be the first to attain superintelligence.

The genetic alteration of the human genome, for example, is constrained by generational constraints.

Even if it were now feasible to artificially boost cognitive functioning by modifying the DNA of a human embryo (which is still a long way off), it would take an entire generation for the changed embryo to evolve into a fully fledged, superintelligent human person.

This would also imply that there are no legal or moral barriers to manipulating the human DNA, which is far from the fact.

Even the comparatively minor genetic manipulation of human embryos carried done by a Chinese physician as recently as November 2018 sparked international outrage (Ramzy and Wee 2019).

Whole brain emulation, on the other hand, is still a long way off, owing to biotechnology's limits.

Given the current medical technology, the extreme levels of accuracy necessary at every step of the uploading process are impossible to achieve.

Science and technology currently lack the capacity to dissect and scan human brain tissue with sufficient precision to produce full brain simulation results.

Furthermore, even if such first steps are feasible, researchers would face significant challenges in analyzing and digitally replicating the human brain using cutting-edge computer technology.

Many analysts believe that such constraints will be overcome, although the timeline for such realizations is unknown.

Apart from biotechnology, the area of AI, which is strictly defined as any type of nonorganic (particularly computer-based) intelligence, is the second major path to superintelligence.

Of course, the work of creating a superintelligent AI from the ground up is complicated by a number of elements, not all of which are purely logistical in nature, such as processing speed, hardware/software design, finance, and so on.

In addition to such practical challenges, there is a significant philosophical issue: human programmers are unable to know, and so cannot program, that which is superior to their own intelligence.

Much contemporary research on computer learning and interest in the notion of a seed AI is motivated in part by this worry.

Any machine capable of changing reactions to stimuli based on an examination of how well it performs in relation to a predetermined objective is defined as the latter.

Importantly, the concept of a seed AI entails not only the capacity to change its replies by extending its base of content knowledge (stored information), but also the ability to change the structure of its programming to better fit a specific job (Bostrom 2017, 29).

Indeed, it is this latter capability that would give a seed AI what Nick Bostrom refers to as "recursive self-improvement," or the ability to evolve iteratively (Bostrom 2017, 29).

This would eliminate the requirement for programmers to have an a priori vision of super intelligence since the seed AI would constantly enhance its own programming, with each more intelligent iteration writing a superior version of itself (beyond the human level).

Such a machine would undoubtedly cast doubt on the conventional philosophical assumption that robots are incapable of self-awareness.

This perspective's proponents may be traced all the way back to Descartes, but they also include more current thinkers like John Haugeland and John Searle.

Machine intelligence, in this perspective, is defined as the successful correlation of inputs with outputs according to a predefined program.

As a result, robots differ from humans in type, the latter being characterized only by conscious self-awareness.

Humans are supposed to comprehend the activities they execute, but robots are thought to carry out functions mindlessly—that is, without knowing how they work.

Should it be able to construct a successful seed AI, this core idea would be forced to be challenged.

The seed AI would demonstrate a level of self-awareness and autonomy not readily explained by the Cartesian philosophical paradigm by upgrading its own programming in ways that surprise and defy the forecasts of its human programmers.

Indeed, although it is still speculative (for the time being), the increasingly possible result of superintelligent AI poses a slew of moral and legal dilemmas that have sparked a lot of philosophical discussion in this subject.

The main worries are about the human species' security in the case of what Bostrom refers to as a "intelligence explosion"—that is, the creation of a seed AI followed by a possibly exponential growth in intellect (Bostrom 2017).

One of the key problems is the inherently unexpected character of such a result.

Humans will not be able to totally foresee how superintelligent AI would act due to the autonomy entailed by superintelligence in a definitional sense.

Even in the few cases of specialized superintelligence that humans have been able to construct and study so far—for example, robots that have surpassed humans in strategic games like chess and Go—human forecasts for AI have shown to be very unreliable.

For many critics, such unpredictability is a significant indicator that, should more generic types of superintelligent AI emerge, humans would swiftly lose their capacity to manage them (Kissinger 2018).

Of all, such a loss of control does not automatically imply an adversarial relationship between humans and superintelligence.

Indeed, although most of the literature on superintelligence portrays this relationship as adversarial, some new work claims that this perspective reveals a prejudice against machines that is particularly prevalent in Western cultures (Knight 2014).

Nonetheless, there are compelling grounds to believe that superintelligent AI would at the very least consider human goals as incompatible with their own, and may even regard humans as existential dangers.

For example, computer scientist Steve Omohundro has claimed that even a relatively basic kind of superintelligent AI like a chess bot would have motive to want the extinction of humanity as a whole—and may be able to build the tools to do it (Omohundro 2014).

Similarly, Bostrom has claimed that a superintelligence explosion would most certainly result in, if not the extinction of the human race, then at the very least a gloomy future (Bostrom 2017).

Whatever the benefits of such theories, the great uncertainty entailed by superintelligence is obvious.

If there is one point of agreement in this large and diverse literature, it is that if AI research is to continue, the global community must take great care to protect its interests.

Hardened determinists who claim that technological advancement is so tightly connected to inflexible market forces that it is simply impossible to change its pace or direction in any major manner may find this statement contentious.

According to this determinist viewpoint, if AI can deliver cost-cutting solutions for industry and commerce (as it has already started to do), its growth will proceed into the realm of superintelligence, regardless of any unexpected negative repercussions.

Many skeptics argue that growing societal awareness of the potential risks of AI, as well as thorough political monitoring of its development, are necessary counterpoints to such viewpoints.

Bostrom highlights various examples of effective worldwide cooperation in science and technology as crucial precedents that challenge the determinist approach, including CERN, the Human Genome Project, and the International Space Station (Bostrom 2017, 253).

To this, one may add examples from the worldwide environmental movement, which began in the 1960s and 1970s and has imposed significant restrictions on pollution committed in the name of uncontrolled capitalism (Feenberg 2006).

Given the speculative nature of superintelligence research, it is hard to predict what the future holds.

However, if superintelligence poses an existential danger to human existence, caution would dictate that a worldwide collaborative strategy rather than a free market approach to AI be used.

~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram

You may also want to read more about Artificial Intelligence here.

See also: 

Berserkers; Bostrom, Nick; de Garis, Hugo; General and Narrow AI; Goertzel, Ben; Kurzweil, Ray; Moravec, Hans; Musk, Elon; Technological Singularity; Yudkowsky, Eliezer.

References & Further Reading:

• Bostrom, Nick. 2017. Superintelligence: Paths, Dangers, Strategies. Oxford, UK: Oxford University Press.

• Feenberg, Andrew. 2006. “Environmentalism and the Politics of Technology.” In Questioning Technology, 45–73. New York: Routledge.

• Kissinger, Henry. 2018. “How the Enlightenment Ends.” The Atlantic, June 2018. https://www.theatlantic.com/magazine/archive/2018/06/henry-kissinger-ai-could-mean-the-end-of-human-history/559124/.

• Knight, Heather. 2014. How Humans Respond to Robots: Building Public Policy Through Good Design. Washington, DC: The Project on Civilian Robotics. Brookings Institution.

• Omohundro, Steve. 2014. “Autonomous Technology and the Greater Human Good.” Journal of Experimental & Theoretical Artificial Intelligence 26, no. 3: 303–15.

• Ramzy, Austin, and Sui-Lee Wee. 2019. “Scientist Who Edited Babies’ Genes Is Likely to Face Charges in China.” The New York Times, January 21, 2019

Artificial Intelligence - Who Is Elon Musk?

 

Elon Musk (1971–) is an American businessman and inventor.

Elon Musk is an engineer, entrepreneur, and inventor who was born in South Africa.

He is a dual citizen of South Africa, Canada, and the United States, and resides in California.

Musk is widely regarded as one of the most prominent inventors and engineers of the twenty-first century, as well as an important influencer and contributor to the development of artificial intelligence.

Despite his controversial personality, Musk is widely regarded as one of the most prominent inventors and engineers of the twenty-first century and an important influencer and contributor to the development of artificial intelligence.

Musk's business instincts and remarkable technological talent were evident from an early age.

By the age of 10, he had self-taught himself how program computers, and by the age of twelve, he had produced a video game and sold the source code to a computer magazine.

Musk has included allusions to some of his favorite novels in SpaceX's Falcon Heavy rocket launch and Tesla's software since he was a youngster.

Musk's official schooling was centered on economics and physics rather than engineering, interests that are mirrored in his subsequent work, such as his efforts in renewable energy and space exploration.

He began his education at Queen's University in Canada, but later transferred to the University of Pennsylvania, where he earned bachelor's degrees in Economics and Physics.

Musk barely stayed at Stanford University for two days to seek a PhD in energy physics before departing to start his first firm, Zip2, with his brother Kimbal Musk.

Musk has started or cofounded many firms, including three different billion-dollar enterprises: SpaceX, Tesla, and PayPal, all driven by his diverse interests and goals.

• Zip2 was a web software business that was eventually purchased by Compaq.

• X.com: an online bank that merged with PayPal to become the online payments corporation PayPal.

• Tesla, Inc.: an electric car and solar panel maker 

• SpaceX: a commercial aircraft manufacturer and space transportation services provider (via its subsidiarity SolarCity) 

• Neuralink: a neurotechnology startup focusing on brain-computer connections 

• The Boring Business: an infrastructure and tunnel construction corporation

 • OpenAI: a nonprofit AI research company focused on the promotion and development of friendly AI Musk is a supporter of environmentally friendly energy and consumption.

Concerns over the planet's future habitability prompted him to investigate the potential of establishing a self-sustaining human colony on Mars.

Other projects include the Hyperloop, a high-speed transportation system, and the Musk electric jet, a jet-powered supersonic electric aircraft.

Musk sat on President Donald Trump's Strategy and Policy Forum and Manufacturing Jobs Initiative for a short time before stepping out when the US withdrew from the Paris Climate Agreement.

Musk launched the Musk Foundation in 2002, which funds and supports research and activism in the domains of renewable energy, human space exploration, pediatric research, and science and engineering education.

Musk's effect on AI is significant, despite his best-known work with Tesla and SpaceX, as well as his contentious social media pronouncements.

In 2015, Musk cofounded the charity OpenAI with the objective of creating and supporting "friendly AI," or AI that is created, deployed, and utilized in a manner that benefits mankind as a whole.

OpenAI's objective is to make AI open and accessible to the general public, reducing the risks of AI being controlled by a few privileged people.

OpenAI is especially concerned about the possibility of Artificial General Intelligence (AGI), which is broadly defined as AI capable of human-level (or greater) performance on any intellectual task, and ensuring that any such AGI is developed responsibly, transparently, and distributed evenly and openly.

OpenAI has had its own successes in taking AI to new levels while staying true to its goals of keeping AI friendly and open.

In June of 2018, a team of OpenAI-built robots defeated a human team in the video game Dota 2, a feat that could only be accomplished through robot teamwork and collaboration.

Bill Gates, a cofounder of Microsoft, praised the achievement on Twitter, calling it "a huge milestone in advancing artificial intelligence" (@BillGates, June 26, 2018).

Musk resigned away from the OpenAI board in February 2018 to prevent any conflicts of interest while Tesla advanced its AI work for autonomous driving.

Musk became the CEO of Tesla in 2008 after cofounding the company in 2003 as an investor.

Musk was the chairman of Tesla's board of directors until 2018, when he stepped down as part of a deal with the US Securities and Exchange Commission over Musk's false claims about taking the company private.

Tesla produces electric automobiles with self-driving capabilities.

Tesla Grohmann Automation and Solar City, two of its subsidiaries, offer relevant automotive technology and manufacturing services and solar energy services, respectively.

Tesla, according to Musk, will reach Level 5 autonomous driving capabilities in 2019, as defined by the National Highway Traffic Safety Administration's (NHTSA) five levels of autonomous driving.

Tes la's aggressive development with autonomous driving has influenced conventional car makers' attitudes toward electric cars and autonomous driving, and prompted a congressional assessment of how and when the technology should be regulated.

Musk is widely credited as a key influencer in moving the automotive industry toward autonomous driving, highlighting the benefits of autonomous vehicles (including reduced fatalities in vehicle crashes, increased worker productivity, increased transportation efficiency, and job creation) and demonstrating that the technology is achievable in the near term.

Tesla's autonomous driving code has been created and enhanced under the guidance of Musk and Tesla's Director of AI, Andrej Karpathy (Autopilot).

The computer vision analysis used by Tesla, which includes an array of cameras on each car and real-time image processing, enables the system to make real-time observations and predictions.

The cameras, as well as other exterior and internal sensors, capture a large quantity of data, which is evaluated and utilized to improve Autopilot programming.

Tesla is the only autonomous car maker that is opposed to the LIDAR laser sensor (an acronym for light detection and ranging).

Tesla uses cameras, radar, and ultrasonic sensors instead.

Though academics and manufacturers disagree on whether LIDAR is required for fully autonomous driving, the high cost of LIDAR has limited Tesla's rivals' ability to produce and sell vehicles at a pricing range that allows a large number of cars on the road to gather data.

Tesla is creating its own AI hardware in addition to its AI programming.

Musk stated in late 2017 that Tesla is building its own silicon for artificial-intelligence calculations, allowing the company to construct its own AI processors rather than depending on third-party sources like Nvidia.

Tesla's AI progress in autonomous driving has been marred by setbacks.

Tesla has consistently missed self-imposed deadlines, and serious accidents have been blamed on flaws in the vehicle's Autopilot mode, including a non-injury accident in 2018, in which the vehicle failed to detect a parked firetruck on a California freeway, and a fatal accident in 2018, in which the vehicle failed to detect a pedestrian outside a crosswalk.

Neuralink was established by Musk in 2016.

With the stated objective of helping humans to keep up with AI breakthroughs, Neuralink is focused on creating devices that can be implanted into the human brain to better facilitate communication between the brain and software.

Musk has characterized the gadgets as a more efficient interface with computer equipment, while people now operate things with their fingertips and voice commands, directives would instead come straight from the brain.

Though Musk has made major advances to AI, his pronouncements regarding the risks linked with AI have been apocalyptic.

Musk has called AI "humanity's greatest existential danger" and "the greatest peril we face as a civilisation" (McFarland 2014).

(Morris 2017).

He cautions against the perils of power concentration, a lack of independent control, and a competitive rush to acceptance without appropriate analysis of the repercussions.

While Musk has used colorful terminology such as "summoning the devil" (McFarland 2014) and depictions of cyborg overlords, he has also warned of more immediate and realistic concerns such as job losses and AI-driven misinformation campaigns.

Though Musk's statements might come out as alarmist, many important and well-respected figures, including as Microsoft cofounder Bill Gates, Swedish-American scientist Max Tegmark, and the late theoretical physicist Stephen Hawking, share his concern.

Furthermore, Musk does not call for the cessation of AI research.

Instead, Musk supports for responsible AI development and regulation, including the formation of a Congressional committee to spend years studying AI with the goal of better understanding the technology and its hazards before establishing suitable legal limits.

~ Jai Krishna Ponnappan

Find Jai on Twitter | LinkedIn | Instagram

You may also want to read more about Artificial Intelligence here.

See also: 

Bostrom, Nick; Superintelligence.

References & Further Reading:

Gates, Bill. (@BillGates). 2018. Twitter, June 26, 2018. https://twitter.com/BillGates/status/1011752221376036864.

Marr, Bernard. 2018. “The Amazing Ways Tesla Is Using Artificial Intelligence and Big Data.” Forbes, January 8, 2018. https://www.forbes.com/sites/bernardmarr/2018/01/08/the-amazing-ways-tesla-is-using-artificial-intelligence-and-big-data/.

McFarland, Matt. 2014. “Elon Musk: With Artificial Intelligence, We Are Summoning the Demon.” Washington Post, October 24, 2014. https://www.washingtonpost.com/news/innovations/wp/2014/10/24/elon-musk-with-artificial-intelligence-we-are-summoning-the-demon/.

Morris, David Z. 2017. “Elon Musk Says Artificial Intelligence Is the ‘Greatest Risk We Face as a Civilization.’” Fortune, July 15, 2017. https://fortune.com/2017/07/15/elon-musk-artificial-intelligence-2/.

Piper, Kelsey. 2018. “Why Elon Musk Fears Artificial Intelligence.” Vox Media, Novem￾ber 2, 2018. https://www.vox.com/future-perfect/2018/11/2/18053418/elon-musk-artificial-intelligence-google-deepmind-openai.

Strauss, Neil. 2017. “Elon Musk: The Architect of Tomorrow.” Rolling Stone, November 15, 2017. https://www.rollingstone.com/culture/culture-features/elon-musk-the-architect-of-tomorrow-120850/.

Artificial Intelligence - Who Is Nick Bostrom?

 

Nick Bostrom(1973–) is an Oxford University philosopher with a physics and computational neuroscience multidisciplinary academic background.

He is a cofounder of the World Transhumanist Association and a founding director of the Future of Humanity Institute.

Anthropic Bias (2002), Human Enhancement (2009), Superintelligence: Paths, Dangers, Strategies (2014), and Global Catastrophic Risks (2014) are among the works he has authored or edited (2014).

Bostrom was born in the Swedish city of Helsingborg in 1973.

Despite his dislike of formal education, he enjoyed studying.

Science, literature, art, and anthropology were among his favorite interests.

Bostrom earned bachelor's degrees in philosophy, mathematics, logic, and artificial intelligence from the University of Gothenburg, as well as master's degrees in philosophy and physics from Stockholm University and computational neuroscience from King's College London.

The London School of Economics gave him a PhD in philosophy.

Bostrom is a regular consultant or contributor to the European Commission, the United States President's Council on Bioethics, the CIA, and Cambridge University's Centre for the Study of Existential Risk.

Bostrom is well-known for his contributions to a variety of subjects, and he has proposed or written extensively on a number of well-known philosophical arguments and conjectures, including the simulation hypothesis, existential risk, the future of machine intelligence, and transhumanism.

Bostrom's concerns in the future of technology, as well as his discoveries on the mathematics of the anthropic bias, are combined in the so-called "Simulation Argument." Three propositions make up the argument.

The first hypothesis is that almost all civilizations that attain human levels of knowledge eventually perish before achieving technological maturity.

The second hypothesis is that most civilizations develop "ancestor simulations" of sentient beings, but ultimately abandon them.

The "simulation hypothesis" proposes that mankind is now living in a simulation.

He claims that just one of the three assertions must be true.

If the first hypothesis is false, some proportion of civilizations at the current level of human society will ultimately acquire technological maturity.

If the second premise is incorrect, certain civilizations may be interested in continuing to perform ancestor simulations.

These civilizations' researchers may be performing massive numbers of these simulations.

There would be many times as many simulated humans living in simulated worlds as there would be genuine people living in real universes in that situation.

As a result, mankind is most likely to exist in one of the simulated worlds.

If the second statement is true, the third possibility is also true.

It's even feasible, according to Bostrom, for a civilization inside a simulation to conduct its own simulations.

In the form of an endless regress, simulations may be living within simulated universes, inside their own simulated worlds.

It's also feasible that all civilizations would vanish, maybe as a result of the discovery of a new technology, posing an existential threat beyond human control.

Bostrom's argument implies that humanity is not blind to the truth of the external world, an argument that can be traced back to Plato's conviction in the existence of universals (the "Forms") and the capacity of human senses to see only specific examples of universals.

His thesis also implies that computers' ability to imitate things will continue to improve in terms of power and sophistication.

Computer games and literature, according to Bostrom, are modern instances of natural human fascination with synthetic reality.

The Simulation Argument is sometimes mistaken with the restricted premise that mankind lives in a simulation, which is the third argument.

Humans, according to Bostrom, have a less than 50% probability of living in some kind of artificial matrix.

He also argues that if mankind lived in one, society would be unlikely to notice "glitches" that revealed the simulation's existence since they had total control over the simulation's operation.

Simulator creators, on the other hand, would inform people that they are living in a simulation.

Existential hazards are those that pose a serious threat to humanity's existence.

Humans, rather than natural dangers, pose the biggest existential threat, according to Bostrom (e.g., asteroids, earthquakes, and epidemic disease).

He argues that artificial hazards like synthetic biology, molecular nanotechnology, and artificial intelligence are considerably more threatening.

Bostrom divides dangers into three categories: local, global, and existential.

Local dangers might include the theft of a valuable item of art or an automobile accident.

A military dictator's downfall or the explosion of a supervolcano are both potential global threats.

The extent and intensity of existential hazards vary.

They are cross-generational and long-lasting.

Because of the amount of lives that might be spared, he believes that reducing the danger of existential hazards is the most essential thing that human beings can do; battling against existential risk is also one of humanity's most neglected undertakings.

He also distinguishes between several types of existential peril.

Human extinction, defined as the extinction of a species before it reaches technological maturity; permanent stagnation, defined as the plateauing of human technological achievement; flawed realization, defined as humanity's failure to use advanced technology for an ultimately worthwhile purpose; and subsequent ruination, defined as a society reaching technological maturity but then something goes wrong.

While mankind has not yet harnessed human ingenuity to create a technology that releases existentially destructive power, Bostrom believes it is possible that it may in the future.

Human civilization has yet to produce a technology with such horrific implications that mankind could collectively forget about it.

The objective would be to go on a technical path that is safe, includes global collaboration, and is long-term.

To argue for the prospect of machine superintelligence, Bostrom employs the metaphor of altered brain complexity in the development of humans from apes, which took just a few hundred thousand generations.

Artificial systems that use machine learning (that is, algorithms that learn) are no longer constrained to a single area.

He also points out that computers process information at a far faster pace than human neurons.

Humans will eventually rely on super intelligent robots in the same manner that chimps presently rely on humans for their ultimate survival, according to Bostrom, even in the wild.

By establishing a powerful optimizing process with a poorly stated purpose, super intelligent computers have the potential to cause devastation, or possibly an extinction-level catastrophe.

By subverting humanity to the programmed purpose, a superintelligence may even foresee a human response.

Bostrom recognizes that there are certain algorithmic techniques used by humans that computer scientists do not yet understand.

As they engage in machine learning, he believes it is critical for artificial intelligences to understand human values.

On this point, Bostrom is drawing inspiration from artificial intelligence theorist Eliezer Yudkowsky's concept of "coherent extrapolated volition"—also known as "friendly AI"—which is akin to what is currently accessible in human good will, civil society, and institutions.

A superintelligence should seek to provide pleasure and joy to all of humanity, and it may even make difficult choices that benefit the whole community rather than the individual.

In 2015, Bostrom, along with Stephen Hawking, Elon Musk, Max Tegmark, and many other top AI researchers, published "An Open Letter on Artificial Intelligence" on the Future of Life Institute website, calling for artificial intelligence research that maximizes the benefits to humanity while minimizing "potential pitfalls." Transhumanism is a philosophy or belief in the technological extension and augmentation of the human species' physical, sensory, and cognitive capacity.

In 1998, Bostrom and colleague philosopher David Pearce founded the World Transhumanist Association, now known as Humanity+, to address some of the societal hurdles to the adoption and use of new transhumanist technologies by people of all socioeconomic strata.

Bostrom has said that he is not interested in defending technology, but rather in using modern technologies to address real-world problems and improve people's lives.

Bostrom is particularly concerned in the ethical implications of human enhancement and the long-term implications of major technological changes in human nature.

He claims that transhumanist ideas may be found throughout history and throughout cultures, as shown by ancient quests such as the Gilgamesh Epic and historical hunts for the Fountain of Youth and the Elixir of Immortality.

The transhumanist idea, then, may be regarded fairly ancient, with modern representations in disciplines like artificial intelligence and gene editing.

Bostrom takes a stand against the emergence of strong transhumanist instruments as an activist.

He expects that politicians may act with foresight and command the sequencing of technical breakthroughs in order to decrease the danger of future applications and human extinction.

He believes that everyone should have the chance to become transhuman or posthuman (have capacities beyond human nature and intelligence).

For Bostrom, success would require a worldwide commitment to global security and continued technological progress, as well as widespread access to the benefits of technologies (cryonics, mind uploading, anti-aging drugs, life extension regimens), which hold the most promise for transhumanist change in our lifetime.

Bostrom, however cautious, rejects conventional humility, pointing out that humans have a long history of dealing with potentially catastrophic dangers.

In such things, he is a strong supporter of "individual choice," as well as "morphological freedom," or the ability to transform or reengineer one's body to fulfill specific wishes and requirements.

~ Jai Krishna Ponnappan

You may also want to read more about Artificial Intelligence here.

See also: 

Superintelligence; Technological Singularity.

Further Reading

Bostrom, Nick. 2003. “Are You Living in a Computer Simulation?” Philosophical Quarterly 53, no. 211: 243–55.

Bostrom, Nick. 2005. “A History of Transhumanist Thought.” Journal of Evolution and Technology 14, no. 1: 1–25.

Bostrom, Nick, ed. 2008. Global Catastrophic Risks. Oxford, UK: Oxford University Press.

Bostrom, Nick. 2014. Superintelligence: Paths, Dangers, Strategies. Oxford, UK: Oxford University Press.

Savulescu, Julian, and Nick Bostrom, eds. 2009. Human Enhancement. Oxford, UK: Oxford University Press.