Sunday, August 1, 2010

Dental caries : Tooth decay

Dental caries

Dental caries, also known as tooth decay or cavity, is a disease wherein bacterial processes damage hard tooth structure (enamel, dentin, and cementum).[1] These tissues progressively break down, producing dental caries (cavities, holes in the teeth). Two groups of bacteria are responsible for initiating caries: Streptococcus mutans and Lactobacillus. If left untreated, the disease can lead to pain, tooth loss, infection, and, in severe cases, death.[2] Today, caries remains one of the most common diseases throughout the world. Cariology is the study of dental caries.

The presentation of caries is highly variable; however, the risk factors and stages of development are similar. Initially, it may appear as a small chalky area that may eventually develop into a large cavitation. Sometimes caries may be directly visible, however other methods of detection such as radiographs are used for less visible areas of teeth and to judge the extent of destruction.

Tooth decay is caused by specific types of acid-producing bacteria that cause damage in the presence of fermentable carbohydrates such as sucrose, fructose, and glucose.[3][4][5] The mineral content of teeth is sensitive to increases in acidity from the production of lactic acid. Specifically, a tooth (which is primarily mineral in content) is in a constant state of back-and-forth demineralization and remineralization between the tooth and surrounding saliva . When the pH at the surface of the tooth drops below 5.5, demineralization proceeds faster than remineralization (meaning that there is a net loss of mineral structure on the tooth's surface). This results in the ensuing decay. Depending on the extent of tooth destruction, various treatments can be used to restore teeth to proper form, function, and aesthetics, but there is no known method to regenerate large amounts of tooth structure, though stem cell related research suggests one possibility. Instead, dental health organizations advocate preventive and prophylactic measures, such as regular oral hygiene and dietary modifications, to avoid dental caries. [6]

[ oroma.info] Classification

Caries can be classified by location, etiology, rate of progression, and affected hard tissues.[7] These classification can be used to characterize a particular case of tooth decay in order to more accurately represent the condition to others and also indicate the severity of tooth destruction.

G.V. Black Classification of Restorations

[ oroma.info] Location

Generally, there are two types of caries when separated by location: caries found on smooth surfaces and caries found in pits and fissures.[8] The location, development, and progression of smooth-surface caries differ from those of pit and fissure caries. G.V. Black created a classification system that is widely used and based on the location of the caries on the tooth. The original classification distinguished caries into five groups, indicated by the word "Class", and a Roman numeral . Pit and fissure caries is indicated as Class I; smooth surface caries is further divided into Class II, Class III, Class IV, and Class V.[9] A Class VI was added onto Black's Classification of Caries Lesions and also represents a smooth-surface carious lesion.

The pits and fissures of teeth provide a location for caries formation.

[ oroma.info] Pit and fissure caries (class I dental caries)

Pits and fissures are anatomic landmarks on a tooth where the enamel folds inward. Fissures are formed during the development of grooves but the enamel in the area is not fully fused. As a result, a deep linear depression forms in the enamel's surface structure, which forms a location for dental caries to develop and flourish. Fissures are mostly located on the occlusal (chewing) surfaces of posterior (rear) teeth and palatal surfaces of maxillary anterior (front) teeth. Pits are small, pinpoint depressions that are most commonly found at the ends or cross-sections of grooves.[10] In particular, buccal pits are found on the facial surfaces of molars. For all types of pits and fissures, the deep infolding of enamel makes oral hygiene along these surfaces difficult, allowing dental caries to develop more commonly in these areas.

The occlusal surfaces of teeth represent 12.5% of all tooth surfaces but are the location of over 50% of all dental caries.[11] Among children, pit and fissure caries represent 90% of all dental caries.[12] Pit and fissure caries can sometimes be difficult to detect. As the decay progresses, caries in enamel nearest the surface of the tooth spreads gradually deeper. Once the caries reaches the dentin at the dentino-enamel junction (DEJ), the decay quickly spreads laterally. Within the dentin, the decay follows a triangle pattern that points to the tooth's pulp . This pattern of decay is typically described as two triangles (one triangle in enamel, and another in dentin) with their bases conjoined to each other at the DEJ. This base-to-base pattern is typical of pit and fissure caries, unlike smooth-surface caries (where base and apex of the two triangles join).

[ oroma.info] Smooth-surface caries

There are three types of smooth-surface caries. Proximal caries, also called interproximal caries, form on the smooth surfaces between adjacent teeth. Root caries form on the root surfaces of teeth. The third type of smooth-surface caries occur on any other smooth tooth surface.

In this radiograph, the dark spots in the adjacent teeth show proximal caries.

Proximal caries are the most difficult type to detect.[13] Frequently, this type of caries cannot be detected visually or manually with a dental explorer. Proximal caries form cervically (toward the roots of a tooth) just under the contact between two teeth. As a result, radiographs are needed for early discovery of proximal caries. [14] Under Black's classification system, proximal caries on posterior teeth (premolars and molars) are designated as Class II caries.[15] Proximal caries on anterior teeth (incisors and canines) are indicated as Class III if the incisal edge (chewing surface) is not included and Class IV if the incisal edge is included.

Root caries, which are sometimes described as a category of smooth-surfaces caries, are the third most common type of caries and usually occur when the root surfaces have been exposed due to gingival recession. When the gingiva is healthy, root caries is unlikely to develop because the root surfaces are not as accessible to bacterial plaque. The root surface is more vulnerable to the demineralization process than enamel because cementum begins to demineralize at 6.7 pH, which is higher than enamel's critical pH. [16] Regardless, it is easier to arrest the progression of root caries than enamel caries because roots have a greater reuptake of fluoride than enamel. Root caries are most likely to be found on facial surfaces, then interproximal surfaces, then lingual surfaces. Mandibular molars are the most common location to find root caries, followed by mandibular premolars, maxillary anteriors, maxillary posteriors, and mandibular anteriors.

Lesions on other smooth surfaces of teeth are also possible. Since these occur in all smooth surface areas of enamel except for interproximal areas, these types of caries are easily detected and are associated with high levels of plaque and diets promoting caries formation.[13] Under Black's classification system, caries near the gingiva on the facial or lingual surfaces is designated Class V.[15] Class VI is reserved for caries confined to cusp tips on posterior teeth or incisal edges of anterior teeth.

[ oroma.info] Other general descriptions

Besides the two previously mentioned categories, carious lesions can be described further by their location on a particular surface of a tooth. Caries on a tooth's surface that are nearest the cheeks or lips are called "facial caries", and caries on surfaces facing the tongue are known as "lingual caries". Facial caries can be subdivided into buccal (when found on the surfaces of posterior teeth nearest the cheeks) and labial (when found on the surfaces of anterior teeth nearest the lips). Lingual caries can also be described as palatal when found on the lingual surfaces of maxillary teeth because they are located beside the hard palate.

Caries near a tooth's cervix—the location where the crown of a tooth and its roots meet—are referred to as cervical caries. Occlusal caries are found on the chewing surfaces of posterior teeth. Incisal caries are caries found on the chewing surfaces of anterior teeth. Caries can also be described as "mesial" or "distal." Mesial signifies a location on a tooth closer to the median line of the face, which is located on a vertical axis between the eyes, down the nose, and between the contact of the central incisors. Locations on a tooth further away from the median line are described as distal.

[ oroma.info] Etiology

Rampant caries.

In some instances, caries are described in other ways that might indicate the cause. "Baby bottle caries", "early childhood caries", or "baby bottle tooth decay" is a pattern of decay found in young children with their deciduous (baby) teeth. The teeth most likely affected are the maxillary anterior teeth, but all teeth can be affected.[17] The name for this type of caries comes from the fact that the decay usually is a result of allowing children to fall asleep with sweetened liquids in their bottles or feeding children sweetened liquids multiple times during the day. Another pattern of decay is "rampant caries", which signifies advanced or severe decay on multiple surfaces of many teeth.[18] Rampant caries may be seen in individuals with xerostomia, poor oral hygiene, stimulant use (due to drug-induced dry mouth[19]), and/or large sugar intake. If rampant caries is a result of previous radiation to the head and neck, it may be described as radiation-induced caries. Problems can also be caused by the self destruction of roots and whole tooth resorption when new teeth erupt or later from unknown causes. Dr. Miller stated in 1887 that "Dental decay is chemico-parasitic process consisting of two stages, the decalcification of enamel, which results in its total destruction and the decalcification of dentin as a preliminary stage followed by dissolution of the softened residue." In his hypothesis, Dr.Miller assigned essential roles to three factors:

  1. Carbohydrate substrate.
  2. Acid which caused dissolution of tooth minerals.
  3. Oral micro organisms which produce acid and also cause proteolysis.

[ oroma.info] Rate of progression

Temporal descriptions can be applied to caries to indicate the progression rate and previous history. "Acute" signifies a quickly developing condition, whereas "chronic" describes a condition which has taken an extended time to develop where thousands of meals and snacks, many causing some acid demineralisation that is not remineralized and eventually results in cavities. Fluoride treatment can help recalcification of tooth enamel.

Recurrent caries, also described as secondary, are caries that appears at a location with a previous history of caries. This is frequently found on the margins of fillings and other dental restorations. On the other hand, incipient caries describes decay at a location that has not experienced previous decay. Arrested caries describes a lesion on a tooth which was previously demineralized but was remineralized before causing a cavitation. Using fluoride treatments can help with recalcification.

[ oroma.info] Affected hard tissue

Depending on which hard tissues are affected, it is possible to describe caries as involving enamel, dentin, or cementum. Early in its development, caries may affect only enamel. Once the extent of decay reaches the deeper layer of dentin, "dentinal caries" is used. Since cementum is the hard tissue that covers the roots of teeth, it is not often affected by decay unless the roots of teeth are exposed to the mouth. Although the term "cementum caries" may be used to describe the decay on roots of teeth, very rarely does caries affect the cementum alone. Roots have a very thin layer of cementum over a large layer of dentin, and thus most caries affecting cementum also affects dentin.

[ oroma.info] Signs and symptoms

The tip of a dental explorer, which is used for caries diagnosis.

A person experiencing caries may not be aware of the disease.[20] The earliest sign of a new carious lesion is the appearance of a chalky white spot on the surface of the tooth, indicating an area of demineralization of enamel. This is referred to as incipient decay. As the lesion continues to demineralize, it can turn brown but will eventually turn into a cavitation ("cavity"). Before the cavity forms, the process is reversible, but once a cavity forms, the lost tooth structure cannot be regenerated. [citation needed] A lesion which appears brown and shiny suggests dental caries were once present but the demineralization process has stopped, leaving a stain. A brown spot which is dull in appearance is probably a sign of active caries.

As the enamel and dentin are destroyed, the cavity becomes more noticeable. The affected areas of the tooth change color and become soft to the touch. Once the decay passes through enamel, the dentinal tubules, which have passages to the nerve of the tooth, become exposed and causes pain in the tooth. The pain may worsen with exposure to heat, cold, or sweet foods and drinks. [1] Dental caries can also cause bad breath and foul tastes.[21] In highly progressed cases, infection can spread from the tooth to the surrounding soft tissues. Complications such as cavernous sinus thrombosis and Ludwig's angina can be life-threatening.[22][23][24]

[ oroma.info] Causes

There are four main criteria required for caries formation: a tooth surface (enamel or dentin); caries-causing bacteria; fermentable carbohydrates (such as sucrose); and time.[25] The caries process does not have an inevitable outcome, and different individuals will be susceptible to different degrees depending on the shape of their teeth, oral hygiene habits, and the buffering capacity of their saliva. Dental caries can occur on any surface of a tooth which is exposed to the oral cavity, but not the structures which are retained within the bone.[26]

[ oroma.info] Teeth

There are certain diseases and disorders affecting teeth which may leave an individual at a greater risk for caries. Amelogenesis imperfecta , which occurs between 1 in 718 and 1 in 14,000 individuals, is a disease in which the enamel does not fully form or forms in insufficient amounts and can fall off a tooth.[27] In both cases, teeth may be left more vulnerable to decay because the enamel is not able to protect the tooth.[28]

In most people, disorders or diseases affecting teeth are not the primary cause of dental caries. Ninety-six percent of tooth enamel is composed of minerals.[29] These minerals, especially hydroxyapatite, will become soluble when exposed to acidic environments. Enamel begins to demineralize at a pH of 5.5.[30] Dentin and cementum are more susceptible to caries than enamel because they have lower mineral content.[31] Thus, when root surfaces of teeth are exposed from gingival recession or periodontal disease, caries can develop more readily. Even in a healthy oral environment, however, the tooth is susceptible to dental caries.

The anatomy of teeth may affect the likelihood of caries formation. Where the deep grooves of teeth are more numerous and exaggerated, pit and fissure caries are more likely to develop. Also, caries are more likely to develop when food is trapped between teeth.

A gram stain image of Streptococcus mutans.

[ oroma.info] Bacteria

The mouth contains a wide variety of oral bacteria, but only a few specific species of bacteria are believed to cause dental caries: Streptococcus mutans and Lactobacilli among them.[3][5] Lactobacillus acidophilus, Actinomyces viscosus, Nocardia spp., and Streptococcus mutans are most closely associated with caries, particularly root caries. Bacteria collect around the teeth and gums in a sticky, creamy-coloured mass called plaque, which serves as a biofilm. Some sites collect plaque more commonly than others. The grooves on the biting surfaces of molar and premolar teeth provide microscopic retention, as does the point of contact between teeth. Plaque may also collect along the gingiva.

[ oroma.info] Fermentable carbohydrates

Bacteria in a person's mouth convert glucose, fructose, and most commonly sucrose (table sugar) into acids such as lactic acid through a glycolytic process called fermentation.[4] If left in contact with the tooth, these acids may cause demineralization, which is the dissolution of its mineral content. The process is dynamic, however, as remineralization can also occur if the acid is neutralized by saliva or mouthwash. Fluoride toothpaste or dental varnish may aid remineralization. [32] If demineralization continues over time, enough mineral content may be lost so that the soft organic material left behind disintegrates, forming a cavity or hole. The impact such sugars have on the progress of dental caries is called cariogenicity. Sucrose, although a bound glucose and fructose unit, is in fact more cariogenic than a mixture of equal parts of glucose and fructose. This is due to the bacteria utilising the energy in the saccharide bond between the glucose and fructose subunits. S.mutans adheres to the biofilm on the tooth by converting sucrose into an extremely adhesive substance called dextran polysaccharide by the enzyme dextransucranase.[33]

[ oroma.info] Time

The frequency of which teeth are exposed to cariogenic (acidic) environments affects the likelihood of caries development.[34] After meals or snacks, the bacteria in the mouth metabolize sugar, resulting in an acidic by-product which decreases pH. As time progresses, the pH returns to normal due to the buffering capacity of saliva and the dissolved mineral content of tooth surfaces. During every exposure to the acidic environment, portions of the inorganic mineral content at the surface of teeth dissolves and can remain dissolved for two hours.[35] Since teeth are vulnerable during these acidic periods, the development of dental caries relies heavily on the frequency of acid exposure.

The carious process can begin within days of a tooth erupting into the mouth if the diet is sufficiently rich in suitable carbohydrates. Evidence suggests that the introduction of fluoride treatments have slowed the process.[36] Proximal caries take an average of four years to pass through enamel in permanent teeth. Because the cementum enveloping the root surface is not nearly as durable as the enamel encasing the crown, root caries tends to progress much more rapidly than decay on other surfaces. The progression and loss of mineralization on the root surface is 2.5 times faster than caries in enamel. In very severe cases where oral hygiene is very poor and where the diet is very rich in fermentable carbohydrates, caries may cause cavities within months of tooth eruption. This can occur, for example, when children continuously drink sugary drinks from baby bottles.

[ oroma.info] Other risk factors

Reduced saliva is associated with increased caries since the buffering capability of saliva is not present to counterbalance the acidic environment created by certain foods. As result, medical conditions that reduce the amount of saliva produced by salivary glands, particularly the submandibular gland and parotid gland, are likely to lead to widespread tooth decay. Examples include Sjögren's syndrome, diabetes mellitus, diabetes insipidus, and sarcoidosis. [37] Medications, such as antihistamines and antidepressants, can also impair salivary flow. Stimulants, most notoriously methylamphetamine, also occlude the flow of saliva to an extreme degree. Abusers of stimulants tend to have poor oral hygiene. Tetrahydrocannabinol, the active chemical substance in cannabis, also causes a nearly complete occlusion of salivation, known colloquially as "cotton mouth". This, combined with heavy intake of heavily sugared drinks and much junk food among cannabis smokers leads to a large increase in the prevalence of caries. [38] Moreover, sixty-three percent of the most commonly prescribed medications in the United States list dry mouth as a known side effect.[37] Radiation therapy of the head and neck may also damage the cells in salivary glands, increasing the likelihood of caries formation.[39]

The use of tobacco may also increase the risk for caries formation. Some brands of smokeless tobacco contain high sugar content, increasing susceptibility to caries.[40] Tobacco use is a significant risk factor for periodontal disease, which can cause the gingiva to recede.[41] As the gingiva loses attachment to the teeth, the root surface becomes more visible in the mouth. If this occurs, root caries is a concern since the cementum covering the roots of teeth is more easily demineralized by acids than enamel.[16] Currently, there is not enough evidence to support a causal relationship between smoking and coronal caries, but evidence does suggest a relationship between smoking and root-surface caries.[42]

Intrauterine and neonatal lead exposure promote tooth decay.[43][44][45][46][47][48][49] Besides lead, all atoms with electrical charge and ionic radius similar to bivalent calcium,[50] such as cadmium, mimic the calcium ion and therefore exposure may promote tooth decay.[51]

[ oroma.info] Pathophysiology

The progression of pit and fissure caries resembles two triangles with their bases meeting along the junction of enamel and dentin.

[ oroma.info] Enamel

Enamel is a highly mineralized acellular tissue, and caries act upon it through a chemical process brought on by the acidic environment produced by bacteria. As the bacteria consume the sugar and use it for their own energy, they produce lactic acid. The effects of this process include the demineralization of crystals in the enamel, caused by acids, over time until the bacteria physically penetrate the dentin. Enamel rods , which are the basic unit of the enamel structure, run perpendicularly from the surface of the tooth to the dentin. Since demineralization of enamel by caries generally follows the direction of the enamel rods, the different triangular patterns between pit and fissure and smooth-surface caries develop in the enamel because the orientation of enamel rods are different in the two areas of the tooth.[52]

As the enamel loses minerals, and dental caries progresses, the enamel develop several distinct zones, visible under a light microscope. From the deepest layer of the enamel to the enamel surface, the identified areas are the: translucent zone, dark zones, body of the lesion, and surface zone.[53] The translucent zone is the first visible sign of caries and coincides with a one to two percent loss of minerals.[54] A slight remineralization of enamel occurs in the dark zone, which serves as an example of how the development of dental caries is an active process with alternating changes.[55] The area of greatest demineralization and destruction is in the body of the lesion itself. The surface zone remains relatively mineralized and is present until the loss of tooth structure results in a cavitation.

[ oroma.info] Dentin

Unlike enamel, the dentin reacts to the progression of dental caries. After tooth formation, the ameloblasts, which produce enamel, are destroyed once enamel formation is complete and thus cannot later regenerate enamel after its destruction. On the other hand, dentin is produced continuously throughout life by odontoblasts, which reside at the border between the pulp and dentin. Since odontoblasts are present, a stimulus, such as caries, can trigger a biologic response. These defense mechanisms include the formation of sclerotic and tertiary dentin.[56]

In dentin from the deepest layer to the enamel, the distinct areas affected by caries are the translucent zone, the zone of destruction, and the zone of bacterial penetration.[52] The translucent zone represents the advancing front of the carious process and is where the initial demineralization begins. The zones of bacterial penetration and destruction are the locations of invading bacteria and ultimately the decomposition of dentin.

The faster spread of caries through dentin creates this triangular appearance in smooth surface caries.

[ oroma.info] Sclerotic dentin

The structure of dentin is an arrangement of microscopic channels, called dentinal tubules, which radiate outward from the pulp chamber to the exterior cementum or enamel border.[57] The diameter of the dentinal tubules is largest near the pulp (about 2.5 μm) and smallest (about 900 nm) at the junction of dentin and enamel.[58] The carious process continues through the dentinal tubules, which are responsible for the triangular patterns resulting from the progression of caries deep into the tooth. The tubules also allow caries to progress faster.

In response, the fluid inside the tubules bring immunoglobulins from the immune system to fight the bacterial infection. At the same time, there is an increase of mineralization of the surrounding tubules.[59] This results in a constriction of the tubules, which is an attempt to slow the bacterial progression. In addition, as the acid from the bacteria demineralizes the hydroxyapatite crystals, calcium and phosphorus are released, allowing for the precipitation of more crystals which fall deeper into the dentinal tubule. These crystals form a barrier and slow the advancement of caries. After these protective responses, the dentin is considered sclerotic.

Fluids within dentinal tubules are believed to be the mechanism by which pain receptors are triggered within the pulp of the tooth.[60] Since sclerotic dentin prevents the passage of such fluids, pain that would otherwise serve as a warning of the invading bacteria may not develop at first. Consequently, dental caries may progress for a long period of time without any sensitivity of the tooth, allowing for greater loss of tooth structure.

[ oroma.info] Tertiary dentin

In response to dental caries, there may be production of more dentin toward the direction of the pulp. This new dentin is referred to as tertiary dentin.[58] Tertiary dentin is produced to protect the pulp for as long as possible from the advancing bacteria. As more tertiary dentin is produced, the size of the pulp decreases. This type of dentin has been subdivided according to the presence or absence of the original odontoblasts.[61] If the odontoblasts survive long enough to react to the dental caries, then the dentin produced is called "reactionary" dentin. If the odontoblasts are killed, the dentin produced is called "reparative" dentin.

In the case of reparative dentin, other cells are needed to assume the role of the destroyed odontoblasts. Growth factors, especially TGF-β,[61] are thought to initiate the production of reparative dentin by fibroblasts and mesenchymal cells of the pulp.[62] Reparative dentin is produced at an average of 1.5 μm/day, but can be increased to 3.5 μm/day. The resulting dentin contains irregularly shaped dentinal tubules which may not line up with existing dentinal tubules. This diminishes the ability for dental caries to progress within the dentinal tubules.

[ oroma.info] Diagnosis

(A) A small spot of decay visible on the surface of a tooth. (B) The radiograph reveals an extensive region of demineralization within the dentin (arrows). (C) A hole is discovered on the side of the tooth at the beginning of decay removal. (D) All decay removed.

Primary diagnosis involves inspection of all visible tooth surfaces using a good light source, dental mirror and explorer. Dental radiographs (X-rays) may show dental caries before it is otherwise visible, particularly caries between the teeth. Large dental caries are often apparent to the naked eye, but smaller lesions can be difficult to identify. Visual and tactile inspection along with radiographs are employed frequently among dentists, particularly to diagnose pit and fissure caries.[63] Early, uncavitated caries is often diagnosed by blowing air across the suspect surface, which removes moisture and changes the optical properties of the unmineralized enamel.

Some dental researchers have cautioned against the use of dental explorers to find caries.[13] In cases where a small area of tooth has begun demineralizing but has not yet cavitated, the pressure from the dental explorer could cause a cavity. Since the carious process is reversible before a cavity is present, it may be possible to arrest the caries with fluoride and remineralize the tooth surface. When a cavity is present, a restoration will be needed to replace the lost tooth structure.

At times, pit and fissure caries may be difficult to detect. Bacteria can penetrate the enamel to reach dentin, but then the outer surface may remineralize, especially if fluoride is present.[64] These caries, sometimes referred to as "hidden caries", will still be visible on x-ray radiographs, but visual examination of the tooth would show the enamel intact or minimally perforated.

[ oroma.info] Treatment

An amalgam used as a restorative material in a tooth.

See also: Dental restoration and Tooth extraction

Destroyed tooth structure does not fully regenerate, although remineralization of very small carious lesions may occur if dental hygiene is kept at optimal level.[1] For the small lesions, topical fluoride is sometimes used to encourage remineralization. For larger lesions, the progression of dental caries can be stopped by treatment. The goal of treatment is to preserve tooth structures and prevent further destruction of the tooth.

Generally, early treatment is less painful and less expensive than treatment of extensive decay. Anesthetics—local, nitrous oxide ("laughing gas"), or other prescription medications—may be required in some cases to relieve pain during or following treatment or to relieve anxiety during treatment.[65] A dental handpiece ("drill") is used to remove large portions of decayed material from a tooth. A spoon is a dental instrument used to remove decay carefully and is sometimes employed when the decay in dentin reaches near the pulp. [66] Once the decay is removed, the missing tooth structure requires a dental restoration of some sort to return the tooth to functionality and aesthetic condition.

Restorative materials include dental amalgam, composite resin, porcelain, and gold.[67] Composite resin and porcelain can be made to match the color of a patient's natural teeth and are thus used more frequently when aesthetics are a concern. Composite restorations are not as strong as dental amalgam and gold; some dentists consider the latter as the only advisable restoration for posterior areas where chewing forces are great.[68] When the decay is too extensive, there may not be enough tooth structure remaining to allow a restorative material to be placed within the tooth. Thus, a crown may be needed. This restoration appears similar to a cap and is fitted over the remainder of the natural crown of the tooth. Crowns are often made of gold, porcelain, or porcelain fused to metal.

A tooth with extensive caries eventually requiring extraction.

In certain cases, endodontic therapy may be necessary for the restoration of a tooth.[69] Endodontic therapy, also known as a "root canal", is recommended if the pulp in a tooth dies from infection by decay-causing bacteria or from trauma. During a root canal, the pulp of the tooth, including the nerve and vascular tissues, is removed along with decayed portions of the tooth. The canals are instrumented with endodontic files to clean and shape them, and they are then usually filled with a rubber-like material called gutta percha. [70] The tooth is filled and a crown can be placed. Upon completion of a root canal, the tooth is now non-vital, as it is devoid of any living tissue.

An extraction can also serve as treatment for dental caries. The removal of the decayed tooth is performed if the tooth is too far destroyed from the decay process to effectively restore the tooth. Extractions are sometimes considered if the tooth lacks an opposing tooth or will probably cause further problems in the future, as may be the case for wisdom teeth. [71] Extractions may also be preferred by patients unable or unwilling to undergo the expense or difficulties in restoring the tooth.

[ oroma.info] Medicinal plants in the treatment of dental caries

[72]

S. No↓
Botanical Name↓
Part used↓
Inhibition Organisms↓
1. Acacia leucophloea
Bark Streptococcus mutans
2. Albizia lebbeck
Bark Streptococcus mutans
3. Abies canadensis
Whole plant Streptococcus mutans
4. Aristolochia cymbifera
Whole plant Streptococcus mutans
5. Annona senegalensis
Whole plant Streptococcus mutans
6. Albizia julibrissin
Whole plant Streptococcus mutans
7. Allium sativum
Bulbs Streptococcus mutans
8. Anacyclus pyrethrum
Root Streptococcus mutans
9. Areca catechu
Nuts Streptococcus mutans
10. Breynia nivosus
Whole plant Streptococcus mutans
14. Citrus medica
Roots Streptococcus mutans
15. Coptidis rhizoma
Whole plant Streptococcus mutans
16. Caesalpinia martius
Fruits Streptococcus mutans, Streptococcus oralis, Lactobacillus casei
17. Cocos nucifera
Whole plant Streptococcus mutans
18. Caesalpinia pyramidalis
Whole plant Streptococcus mutans
19. Chelidonium majus
Whole plant Streptococcus mutans
20. Drosera peltata
Whole plant Streptococcus mutans, Streptococcus sobrinus
21. Embelia ribes
Fruit Streptococcus mutans
22. Erythrina variegata
Root Streptococcus mutans, Streptococcus sanguis
23. Euclea natalensis
Whole plant Streptococcus mutans
24. Fiscus microcarpa
Aerial part Streptococcus mutans
25. Gymnema Sylvester
Leaves,Roots Streptococcus mutans
27. Glycyrrhiza glabra
Root Streptococcus mutans
28. Hamamelis virginiana
Leaves Preveotella spp., Actinomyces odontolitycus
29. Harungana madagascariensis
Leaves Actinomyces, Fusobacterium, Lactobacillus, Prevotella, Propioni bacterium, Streptococcus spp.
30. Helichrysum italicum
Whole plant Streptococcus mutans, Streptococcus sanguis, Streptococcus sobrinus
31. Ginkgo biloba
Whole plant Streptococcus mutans
32. Juniperus virginiana
Whole plant Streptococcus mutans
33. Kaemperia pandurata
Dried rhizomes, root Streptococcus mutans
34. Legenaria sicerania
Leaves Streptococcus mutans
35. Mentha arvensis
Leaves Streptococcus mutans
36. Mikania lavigata
Aerial parts Streptococcus mutans, Streptococcus sobrinus
37. Mikania glomerata
Whole plant Streptococcus cricetus
38. Melissa officinalis
Whole plant Streptococcus mutans, Streptococcus sanguis
39. Magnolia grandiflora
Whole plant Streptococcus mutans, Streptococcus sanguis
40. Melissa officinalis
Whole plant Streptococcus mutans, Streptococcus sanguis
41. Magnolia grandiflora
Whole plant Streptococcus mutans, Streptococcus sanguis
42. Nicotiana tabacum
leaves Streptococcus mutans
43. Physalis angulata
Flower Streptococcus mutans
44. Pinus virginiana
Whole plant Streptococcus mutans
45. Pistacia lentiscus
mastic gum Porphyromonas gingivalis
46. Pistacia vera
Whole plant oral Streptococci
47. Piper cubeba
Whole plant periodontal pathogens
48. Polygonum cuspidatum
Root Streptococcus mutans, Streptococcus sobrinus
49. Rheedia brasiliensis
Fruit Streptococcus mutans
50. Rhus corriaria
Whole plant Streptococcus mutans, Streptococcus sanguis
51. Rhus corriaria
Whole plant Streptococcus mutans, Streptococcus sanguis
52. Rosmarinus officinalis
Whole plant Streptococcus mutans
53. Quercus infectoria
Gall Streptococcus mutans
54. Rhus corriaria
Whole plant Streptococcus mutans, Streptococcus sanguis
55. Syzygium cumini
Bark Streptococcus mutans
56. Sassafras albidum
Whole plant Streptococcus mutans
57. Solanum xathaocarpum
Whole plant Streptococcus mutans
58. Syzygium aromaticum
Dried flower Staphylococcus aureus
59. Thymus vulgaris
Whole plant Streptococcus mutans, Streptococcus sanguis
60. Tanacetum vulgare
Whole plant Staphylococcus aureus
61. Thuja plicata
Whole plant Staphylococcus aureus
62. Ziziphus joazeiro
Whole plant Staphylococcus aureus

[ oroma.info] Prevention

Toothbrushes are commonly used to clean teeth.

[ oroma.info] Oral hygiene

Personal hygiene care consists of proper brushing and flossing daily.[6] The purpose of oral hygiene is to minimize any etiologic agents of disease in the mouth. The primary focus of brushing and flossing is to remove and prevent the formation of plaque. Plaque consists mostly of bacteria. [73] As the amount of bacterial plaque increases, the tooth is more vulnerable to dental caries when carbohydrates in the food are left on teeth after every meal or snack. A toothbrush can be used to remove plaque on accessible surfaces, but not between teeth or inside pits and fissures on chewing surfaces. When used correctly, dental floss removes plaque from areas which could otherwise develop proximal caries. Other adjunct hygiene aids include interdental brushes, water picks, and mouthwashes.

However oral hygiene is probably more effective at preventing gum disease than tooth decay. The brush and fluoride toothpaste have no access inside pits and fissures, where chewing forces food to be trapped. (Occlusal caries accounts for between 80 and 90 percent of caries in children (Weintraub, 2001). The teeth at highest risk for carious lesions are the first and second permanent molars.)

Professional hygiene care consists of regular dental examinations and cleanings. Sometimes, complete plaque removal is difficult, and a dentist or dental hygienist may be needed. Along with oral hygiene, radiographs may be taken at dental visits to detect possible dental caries development in high risk areas of the mouth.

[ oroma.info] Dietary modification

For dental health, frequency of sugar intake is more important than the amount of sugar consumed.[34] In the presence of sugar and other carbohydrates, bacteria in the mouth produce acids which can demineralize enamel, dentin, and cementum. The more frequently teeth are exposed to this environment, the more likely dental caries are to occur. Therefore, minimizing snacking is recommended, since snacking creates a continual supply of nutrition for acid-creating bacteria in the mouth. Also, chewy and sticky foods (such as dried fruit or candy) tend to adhere to teeth longer, and consequently are best eaten as part of a meal. Brushing the teeth after meals is recommended. For children, the American Dental Association and the European Academy of Paediatric Dentistry recommend limiting the frequency of consumption of drinks with sugar, and not giving baby bottles to infants during sleep.[74][75] Mothers are also recommended to avoid sharing utensils and cups with their infants to prevent transferring bacteria from the mother's mouth.[76]

It has been found that milk and certain kinds of cheese like Cheddar can help counter tooth decay if eaten soon after the consumption of foods potentially harmful to teeth.[34] Also, chewing gum containing xylitol (a sugar alcohol) is widely used to protect teeth in some countries, being especially popular in the Finnish candy industry.[77] Xylitol's effect on reducing plaque is probably due to bacteria's inability to utilize it like other sugars.[78] Chewing and stimulation of flavour receptors on the tongue are also known to increase the production and release of saliva, which contains natural buffers to prevent the lowering of pH in the mouth to the point where enamel may become demineralised.[79]

Common dentistry trays used to deliver fluoride.

[ oroma.info] Other preventive measures

The use of dental sealants is a means of prevention. A sealant is a thin plastic-like coating applied to the chewing surfaces of the molars. This coating prevents food being trapped inside pits and fissures in grooves under chewing pressure so resident plaque bacteria are deprived of carbohydrate that they change to acid demineralisation and thus prevents the formation of pit and fissure caries, the most common form of dental caries. Sealants are usually applied on the teeth of children, shortly after the molars erupt. Older people may also benefit from the use of tooth sealants, but their dental history and likelihood of caries formation are usually taken into consideration.

Calcium, as found in food such as milk and green vegetables, are often recommended to protect against dental caries. It has been demonstrated that calcium and fluoride supplements decrease the incidence of dental caries. Fluoride helps prevent decay of a tooth by binding to the hydroxyapatite crystals in enamel.[80] The incorporated calcium makes enamel more resistant to demineralization and, thus, resistant to decay.[81] Topical fluoride is also recommended to protect the surface of the teeth. This may include a fluoride toothpaste or mouthwash. Many dentists include application of topical fluoride solutions as part of routine visits.

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Other products with little or less supportive scientific evidence for effectiveness for the purpose of remineralization include DCPD, ACP, calcium compounds, fluoride, and Enamelon.

Remineralization can also be performed professionally at the dentist.

Furthermore, recent research shows that low intensity laser radiation of argon ion lasers may prevent the susceptibility for enamel caries and white spot lesions.[82]

As bacteria are a major factor contributing to poor oral health, there is currently research to find a vaccine for dental caries. As of 2004, such a vaccine has been successfully tested on animals,[83] and is in clinical trials for humans as of May 2006.[84]

Chewing gum after eating promotes the flow of saliva which naturally reduces the acidic pH environment and promotes remineralization.

Xylitol lollies and gum also inhibit the growth of Streptococcus mutans.

[ oroma.info] Epidemiology

Disability-adjusted life year for dental caries per 100,000 inhabitants in 2004.[85]

no data less than 50 50-60 60-70 70-80 80-90 90-100 100-115 115-130 130-138 138-140 140-142 more than 142

Worldwide, most children and an estimated ninety percent of adults have experienced caries, with the disease most prevalent in Asian and Latin American countries and least prevalent in African countries.[86] In the United States, dental caries is the most common chronic childhood disease, being at least five times more common than asthma.[87] It is the primary pathological cause of tooth loss in children.[88] Between twenty-nine and fifty-nine percent of adults over the age of fifty experience caries.[89]

The number of cases has decreased in some developed countries, and this decline is usually attributed to increasingly better oral hygiene practices and preventive measures such as fluoride treatment. [90] Nonetheless, countries that have experienced an overall decrease in cases of tooth decay continue to have a disparity in the distribution of the disease.[89] Among children in the United States and Europe, twenty percent of the population endures sixty to eighty percent of cases of dental caries.[91] A similarly skewed distribution of the disease is found throughout the world with some children having none or very few caries and others having a high number.[89] Australia, Nepal, and Sweden have a low incidence of cases of dental caries among children, whereas cases are more numerous in Costa Rica and Slovakia.[92]

The classic "DMF" (decay/missing/filled) index is one of the most common methods for assessing caries prevalence as well as dental treatment needs among populations. This index is based on in-field clinical examination of individuals by using a probe, mirror and cotton rolls. Because the DMF index is done withoutX-ray imaging, it underestimates real caries prevalence and treatment needs. [64]

[ oroma.info] History

An image from 1300s (A.D.) England depicting a dentist extracting a tooth with forceps.

There is a long history of dental caries. Over a million years ago, hominids such as Australopithecus suffered from cavities.[93] The largest increases in the prevalence of caries have been associated with dietary changes.[93][94] Archaeological evidence shows that tooth decay is an ancient disease dating far into prehistory. Skulls dating from a million years ago through the neolithic period show signs of caries, excepting those from the Paleolithic and Mesolithic ages.[93] The increase of caries during the neolithic period may be attributed to the increased consumption of plant foods containing carbohydrates.[95] The beginning of rice cultivation in South Asia is also believed to have caused an increase in caries.

A Sumerian text from 5000 BC describes a "tooth worm" as the cause of caries.[96] Evidence of this belief has also been found in India, Egypt, Japan, and China.[94] Unearthed ancient skulls show evidence of primitive dental work. In Pakistan, teeth dating from around 5500 BC to 7000 BC show nearly perfect holes from primitive dental drills.[97] The Ebers Papyrus, an Egyptian text from 1550 BC, mentions diseases of teeth.[96] During the Sargonid dynasty of Assyria during 668 to 626 BC, writings from the king's physician specify the need to extract a tooth due to spreading inflammation.[94] In the Roman Empire, wider consumption of cooked foods led to a small increase in caries prevalence.[91] The Greco-Roman civilization, in addition to the Egyptian, had treatments for pain resulting from caries.[94]

The rate of caries remained low through the Bronze Age and Iron Age, but sharply increased during the Middle Ages.[93] Periodic increases in caries prevalence had been small in comparison to the 1000 AD increase, when sugar cane became more accessible to the Western world. Treatment consisted mainly of herbal remedies and charms, but sometimes also included bloodletting. [98] The barber surgeons of the time provided services that included tooth extractions.[94] Learning their training from apprenticeships, these health providers were quite successful in ending tooth pain and likely prevented systemic spread of infections in many cases. Among Roman Catholics, prayers to Saint Apollonia, the patroness of dentistry, were meant to heal pain derived from tooth infection. [99]

There is also evidence of caries increase in North American Indians after contact with colonizing Europeans. Before colonization, North American Indians subsisted on hunter-gatherer diets, but afterwards there was a greater reliance onmaize agriculture, which made these groups more susceptible to caries. [93]

In the medieval Islamic world, Muslim physicians such as al-Gazzar and Avicenna (in The Canon of Medicine) provided the earliest known treatments for caries, though they also believed that it was caused by tooth worms as the ancients had. This was eventually proven false in 1200 by another Muslim dentist named Gaubari, who in his Book of the Elite concerning the unmasking of mysteries and tearing of veils, was the first to reject the idea of caries being caused by tooth worms, and he stated that tooth worms in fact do not even exist. The theory of the tooth worm was thus no longer accepted in the Islamic medical community from the 13th century onwards.[100]

During the European Age of Enlightenment, the belief that a "tooth worm" caused caries was also no longer accepted in the European medical community.[101] Pierre Fauchard, known as the father of modern dentistry, was one of the first to reject the idea that worms caused tooth decay and noted that sugar was detrimental to the teeth and gingiva. [102] In 1850, another sharp increase in the prevalence of caries occurred and is believed to be a result of widespread diet changes.[94] Prior to this time, cervical caries was the most frequent type of caries, but increased availability of sugar cane, refined flour, bread, and sweetened tea corresponded with a greater number of pit and fissure caries.

In the 1890s, W.D. Miller conducted a series of studies that led him to propose an explanation for dental caries that was influential for current theories. He found that bacteria inhabited the mouth and that they produced acids which dissolved tooth structures when in the presence of fermentable carbohydrates.[103] This explanation is known as the chemoparasitic caries theory.[104] Miller's contribution, along with the research on plaque by G.V. Black and J.L. Williams, served as the foundation for the current explanation of the etiology of caries.[94] Several of the specific strains of bacteria were identified in 1921 by Fernando E. Rodriguez Vargas.

Rules For Love

Rules For Love

Never allow your partner or yourself to denigrate the other (oroma.info).

You must have personal respect and consideration for yourself (oroma.info).

Everyone deserves respect and love, but you can’t expect to get it unless you give it (oroma.info).

If you allow your partner to disparage you, expect to hear other damaging words (oroma.info).

Whatever you are willing to accept is exactly what you’re going to get (oroma.info).

Be compassionate, understanding, forgiving and merciful (oroma.info).

Patience, kindness, consideration and thoughtfulness can never be in short demand (oroma.info).

find loveNever let a person use names or words to hurt or degrade you or your partner (oroma.info).

Vow to protect yourself from thoughtless, rude, mean or punishing behavior (oroma.info).

If destructive words are being used, for whatever the reason, it must Stop (oroma.info). If not, a relationship can’t survive (oroma.info).

Once you’ve reacted you can then be proactive (oroma.info).

A controlled mouth shows a controlled mind (oroma.info). Use words for empowerment, encouragement and positive recognition (oroma.info).

Ask for respect (oroma.info). Quietly demand it (oroma.info). If your lover, partner, parent or friend can’t exhibit self control over their mouth, seriously consider looking elsewhere for a relationship (oroma.info).

Pick an appropriate the time to discuss important issues (oroma.info). This is particularly true if there is an emotional charge where feelings of anger or vexation need to be vented (oroma.info).

find loveNever enter into discussion of personal, private or intimate issues in public (oroma.info). Wait until you have privacy and the time to tackle issues (oroma.info).

If a person makes a mistake, or does something that disappoints or angers you, belittlement or badmouthing them in front of others will only lead to further resentment, anger and frustration (oroma.info).

Trying to discuss things in bed just before sleep, or while getting ready for bed is simply thoughtless, inconsiderate and a remedy for disaster (oroma.info).

Trying to discuss anything when the other person won’t cooperate or take the time to talk is a waste of time (oroma.info).

If necessary make a date to talk (oroma.info).

If the person keeps on delaying or avoiding conversation or discussion on issues that are important or significant to you, you may need to put it in writing and place it in their hands (oroma.info).

Talking is good for closure of some issues (oroma.info). And, unless allowed, will create a wound that won’t close (oroma.info).

find loveYou can never truly waste your thoughts and words on the separated or departed (oroma.info). Life and thought continues (oroma.info).

Romance doesn’t just exist, you must make it happen (oroma.info). You must make a sincere effort to keep it alive to help your relationship flourish (oroma.info).

Little things count, it doesn’t have to be a dozen roses and champagne all the time (oroma.info). A favorite piece of candy in a pocket or a little note can mean a lot (oroma.info).

Commit yourself to do something romantic every day (oroma.info). Show it (oroma.info). Demonstrate it (oroma.info). It’s the accumulative total of all the little things that in end adds up to a super special love and romance (oroma.info).

Learn Artificial Intelligence

Artificial intelligence

Artificial intelligence (AI) is the intelligence of machines and the branch of computer science that aims to create it. Textbooks define the field as “the study and design of intelligent agents”[1] where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success.[2] John McCarthy, who coined the term in 1956,[3] defines it as “the science and engineering of making intelligent machines.”[4]

The field was founded on the claim that a central property of humans, intelligence—the sapience of Homo sapiens—can be so precisely described that it can be simulated by a machine.[5] This raises philosophical issues about the nature of the mind and limits of scientific hubris, issues which have been addressed by myth, fiction and philosophy since antiquity.[6] Artificial intelligence has been the subject of optimism,[7] but has also suffered setbacks[8] and, today, has become an essential part of the technology industry, providing the heavy lifting for many of the most difficult problems in computer science.[9]

AI research is highly technical and specialized, deeply divided into subfields that often fail to communicate with each other.[10] Subfields have grown up around particular institutions, the work of individual researchers, the solution of specific problems, longstanding differences of opinion about how AI should be done and the application of widely differing tools. The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects.[11] General intelligence (or “strong AI”) is still a long-term goal of (some) research.[12]

[oroma.info] History

Main articles: History of artificial intelligence and Timeline of artificial intelligence

Thinking machines and artificial beings appear in Greek myths, such as Talos of Crete, the golden robots of Hephaestus and Pygmalion’s Galatea.[13] Human likenesses believed to have intelligence were built in every major civilization: animated statues were seen in Egypt and Greece[14] and humanoid automatons were built by Yan Shi,[15] Hero of Alexandria,[16] Al-Jazari[17] and Wolfgang von Kempelen.[18] It was also widely believed that artificial beings had been created by Jābir ibn Hayyān,[19] Judah Loew[20] and Paracelsus.[21] By the 19th and 20th centuries, artificial beings had become a common feature in fiction, as in Mary Shelley’s Frankenstein or Karel Čapek’s R.U.R. (Rossum’s Universal Robots).[22] Pamela McCorduck argues that all of these are examples of an ancient urge, as she describes it, “to forge the gods”.[6] Stories of these creatures and their fates discuss many of the same hopes, fears and ethical concerns that are presented by artificial intelligence.

Mechanical or “formal” reasoning has been developed by philosophers and mathematicians since antiquity. The study of logic led directly to the invention of the programmable digital electronic computer, based on the work of mathematician Alan Turing and others. Turing’s theory of computation suggested that a machine, by shuffling symbols as simple as “0″ and “1″, could simulate any conceivable act of mathematical deduction.[23] This, along with recent discoveries in neurology, information theory and cybernetics, inspired a small group of researchers to begin to seriously consider the possibility of building an electronic brain.[24]

The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956.[25] The attendees, including John McCarthy, Marvin Minsky, Allen Newell and Herbert Simon, became the leaders of AI research for many decades.[26] They and their students wrote programs that were, to most people, simply astonishing:[27] computers were solving word problems in algebra, proving logical theorems and speaking English.[28] By the middle of the 1960s, research in the U.S. was heavily funded by the Department of Defense[29] and laboratories had been established around the world.[30] AI’s founders were profoundly optimistic about the future of the new field: Herbert Simon predicted that “machines will be capable, within twenty years, of doing any work a man can do”[31] and Marvin Minsky agreed, writing that “within a generation … the problem of creating ‘artificial intelligence’ will substantially be solved”.[32]

They had failed to recognize the difficulty of some of the problems they faced.[33] In 1974, in response to the criticism of England’s Sir James Lighthill and ongoing pressure from Congress to fund more productive projects, the U.S. and British governments cut off all undirected, exploratory research in AI. The next few years, when funding for projects was hard to find, would later be called an “AI winter”.[34]

In the early 1980s, AI research was revived by the commercial success of expert systems,[35] a form of AI program that simulated the knowledge and analytical skills of one or more human experts. By 1985 the market for AI had reached over a billion dollars. At the same time, Japan’s fifth generation computer project inspired the U.S and British governments to restore funding for academic research in the field.[36] However, beginning with the collapse of the Lisp Machine market in 1987, AI once again fell into disrepute, and a second, longer lasting AI winter began.[37]

In the 1990s and early 21st century, AI achieved its greatest successes, albeit somewhat behind the scenes. Artificial intelligence is used for logistics, data mining, medical diagnosis and many other areas throughout the technology industry.[9] The success was due to several factors: the incredible power of computers today (see Moore’s law), a greater emphasis on solving specific subproblems, the creation of new ties between AI and other fields working on similar problems, and above all a new commitment by researchers to solid mathematical methods and rigorous scientific standards.[38]

[oroma.info] Problems

The general problem of simulating (or creating) intelligence has been broken down into a number of specific sub-problems. These consist of particular traits or capabilities that researchers would like an intelligent system to display. The traits described below have received the most attention.[11]

[oroma.info] Deduction, reasoning, problem solving

Early AI researchers developed algorithms that imitated the step-by-step reasoning that humans were often assumed to use when they solve puzzles, play board games or make logical deductions.[39] By the late 1980s and ’90s, AI research had also developed highly successful methods for dealing with uncertain or incomplete information, employing concepts from probability and economics.[40]

For difficult problems, most of these algorithms can require enormous computational resources — most experience a “combinatorial explosion”: the amount of memory or computer time required becomes astronomical when the problem goes beyond a certain size. The search for more efficient problem solving algorithms is a high priority for AI research.[41]

Human beings solve most of their problems using fast, intuitive judgments rather than the conscious, step-by-step deduction that early AI research was able to model.[42] AI has made some progress at imitating this kind of “sub-symbolic” problem solving: embodied agent approaches emphasize the importance of sensorimotor skills to higher reasoning; neural net research attempts to simulate the structures inside human and animal brains that give rise to this skill.

[oroma.info] Knowledge representation

Main articles: Knowledge representation and Commonsense knowledge

Knowledge representation[43] and knowledge engineering[44] are central to AI research. Many of the problems machines are expected to solve will require extensive knowledge about the world. Among the things that AI needs to represent are: objects, properties, categories and relations between objects;[45] situations, events, states and time;[46] causes and effects;[47] knowledge about knowledge (what we know about what other people know);[48] and many other, less well researched domains. A complete representation of “what exists” is an ontology[49] (borrowing a word from traditional philosophy), of which the most general are called upper ontologies.

Among the most difficult problems in knowledge representation are:

Default reasoning and the qualification problem
Many of the things people know take the form of “working assumptions.” For example, if a bird comes up in conversation, people typically picture an animal that is fist sized, sings, and flies. None of these things are true about all birds. John McCarthy identified this problem in 1969[50] as the qualification problem: for any commonsense rule that AI researchers care to represent, there tend to be a huge number of exceptions. Almost nothing is simply true or false in the way that abstract logic requires. AI research has explored a number of solutions to this problem.[51]
The breadth of commonsense knowledge
The number of atomic facts that the average person knows is astronomical. Research projects that attempt to build a complete knowledge base of commonsense knowledge (e.g., Cyc) require enormous amounts of laborious ontological engineering — they must be built, by hand, one complicated concept at a time.[52] A major goal is to have the computer understand enough concepts to be able to learn by reading from sources like the internet, and thus be able to add to its own ontology.
The subsymbolic form of some commonsense knowledge
Much of what people know is not represented as “facts” or “statements” that they could actually say out loud. For example, a chess master will avoid a particular chess position because it “feels too exposed”[53] or an art critic can take one look at a statue and instantly realize that it is a fake.[54] These are intuitions or tendencies that are represented in the brain non-consciously and sub-symbolically.[55] Knowledge like this informs, supports and provides a context for symbolic, conscious knowledge. As with the related problem of sub-symbolic reasoning, it is hoped that situated AI or computational intelligence will provide ways to represent this kind of knowledge.[55]

[oroma.info] Planning

Main article: Automated planning and scheduling

Intelligent agents must be able to set goals and achieve them.[56] They need a way to visualize the future (they must have a representation of the state of the world and be able to make predictions about how their actions will change it) and be able to make choices that maximize the utility (or “value”) of the available choices.[57]

In classical planning problems, the agent can assume that it is the only thing acting on the world and it can be certain what the consequences of its actions may be.[58] However, if this is not true, it must periodically check if the world matches its predictions and it must change its plan as this becomes necessary, requiring the agent to reason under uncertainty.[59]

Multi-agent planning uses the cooperation and competition of many agents to achieve a given goal. Emergent behavior such as this is used by evolutionary algorithms and swarm intelligence.[60]

[oroma.info] Learning

Main article: Machine learning

Machine learning[61] has been central to AI research from the beginning.[62] Unsupervised learning is the ability to find patterns in a stream of input. Supervised learning includes both classification and numerical regression. Classification is used to determine what category something belongs in, after seeing a number of examples of things from several categories. Regression takes a set of numerical input/output examples and attempts to discover a continuous function that would generate the outputs from the inputs. In reinforcement learning[63] the agent is rewarded for good responses and punished for bad ones. These can be analyzed in terms of decision theory, using concepts like utility. The mathematical analysis of machine learning algorithms and their performance is a branch of theoretical computer science known as computational learning theory.

[oroma.info] Natural language processing

ASIMO uses sensors and intelligent algorithms to avoid obstacles and navigate stairs.

Main article: Natural language processing

Natural language processing[64] gives machines the ability to read and understand the languages that humans speak. Many researchers hope that a sufficiently powerful natural language processing system would be able to acquire knowledge on its own, by reading the existing text available over the internet. Some straightforward applications of natural language processing include information retrieval (or text mining) and machine translation.[65]

[oroma.info] Motion and manipulation

Main article: Robotics

The field of robotics[66] is closely related to AI. Intelligence is required for robots to be able to handle such tasks as object manipulation[67] and navigation, with sub-problems of localization (knowing where you are), mapping (learning what is around you) and motion planning (figuring out how to get there).[68]

[oroma.info] Perception

Main articles: Machine perception, Computer vision, and Speech recognition

Machine perception[69] is the ability to use input from sensors (such as cameras, microphones, sonar and others more exotic) to deduce aspects of the world. Computer vision[70] is the ability to analyze visual input. A few selected subproblems are speech recognition,[71] facial recognition and object recognition.[72]

[oroma.info] Social intelligence

Main article: Affective computing

Kismet, a robot with rudimentary social skills

Emotion and social skills[73] play two roles for an intelligent agent. First, it must be able to predict the actions of others, by understanding their motives and emotional states. (This involves elements of game theory, decision theory, as well as the ability to model human emotions and the perceptual skills to detect emotions.) Also, for good human-computer interaction, an intelligent machine also needs to display emotions. At the very least it must appear polite and sensitive to the humans it interacts with. At best, it should have normal emotions itself.

[oroma.info] Creativity

Main article: Computational creativity

TOPIO, a robot that can play table tennis, developed by TOSY.

A sub-field of AI addresses creativity both theoretically (from a philosophical and psychological perspective) and practically (via specific implementations of systems that generate outputs that can be considered creative). A related area of computational research is Artificial Intuition and Artificial Imagination.

[oroma.info] General intelligence

Main articles: Strong AI and AI-complete

Most researchers hope that their work will eventually be incorporated into a machine with general intelligence (known as strong AI), combining all the skills above and exceeding human abilities at most or all of them.[12] A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project.[74]

Many of the problems above are considered AI-complete: to solve one problem, you must solve them all. For example, even a straightforward, specific task like machine translation requires that the machine follow the author’s argument (reason), know what is being talked about (knowledge), and faithfully reproduce the author’s intention (social intelligence). Machine translation, therefore, is believed to be AI-complete: it may require strong AI to be done as well as humans can do it.[75]

[oroma.info] Approaches

There is no established unifying theory or paradigm that guides AI research. Researchers disagree about many issues.[76] A few of the most long standing questions that have remained unanswered are these: should artificial intelligence simulate natural intelligence, by studying psychology or neurology? Or is human biology as irrelevant to AI research as bird biology is to aeronautical engineering?[77] Can intelligent behavior be described using simple, elegant principles (such as logic or optimization)? Or does it necessarily require solving a large number of completely unrelated problems?[78] Can intelligence be reproduced using high-level symbols, similar to words and ideas? Or does it require “sub-symbolic” processing?[79]

[oroma.info] Cybernetics and brain simulation

Main articles: Cybernetics and Computational neuroscience

There is no consensus on how closely the brain should be simulated.

In the 1940s and 1950s, a number of researchers explored the connection between neurology, information theory, and cybernetics. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter’s turtles and the Johns Hopkins Beast. Many of these researchers gathered for meetings of the Teleological Society at Princeton University and the Ratio Club in England.[24] By 1960, this approach was largely abandoned, although elements of it would be revived in the 1980s.

[oroma.info] Symbolic

Main article: Good old fashioned artificial intelligence

When access to digital computers became possible in the middle 1950s, AI research began to explore the possibility that human intelligence could be reduced to symbol manipulation. The research was centered in three institutions: CMU, Stanford and MIT, and each one developed its own style of research. John Haugeland named these approaches to AI “good old fashioned AI” or “GOFAI”.[80]

Cognitive simulation
Economist Herbert Simon and Allen Newell studied human problem solving skills and attempted to formalize them, and their work laid the foundations of the field of artificial intelligence, as well as cognitive science, operations research and management science. Their research team used the results of psychological experiments to develop programs that simulated the techniques that people used to solve problems. This tradition, centered at Carnegie Mellon University would eventually culminate in the development of the Soar architecture in the middle 80s.[81][82]
Logic based
Unlike Newell and Simon, John McCarthy felt that machines did not need to simulate human thought, but should instead try to find the essence of abstract reasoning and problem solving, regardless of whether people used the same algorithms.[77] His laboratory at Stanford (SAIL) focused on using formal logic to solve a wide variety of problems, including knowledge representation, planning and learning.[83] Logic was also focus of the work at the University of Edinburgh and elsewhere in Europe which led to the development of the programming language Prolog and the science of logic programming.[84]
“Anti-logic” or “scruffy”
Researchers at MIT (such as Marvin Minsky and Seymour Papert)[85] found that solving difficult problems in vision and natural language processing required ad-hoc solutions – they argued that there was no simple and general principle (like logic) that would capture all the aspects of intelligent behavior. Roger Schank described their “anti-logic” approaches as “scruffy” (as opposed to the “neat” paradigms at CMU and Stanford).[78] Commonsense knowledge bases (such as Doug Lenat’s Cyc) are an example of “scruffy” AI, since they must be built by hand, one complicated concept at a time.[86]
Knowledge based
When computers with large memories became available around 1970, researchers from all three traditions began to build knowledge into AI applications.[87] This “knowledge revolution” led to the development and deployment of expert systems (introduced by Edward Feigenbaum), the first truly successful form of AI software.[35] The knowledge revolution was also driven by the realization that enormous amounts of knowledge would be required by many simple AI applications.

[oroma.info] Sub-symbolic

During the 1960s, symbolic approaches had achieved great success at simulating high-level thinking in small demonstration programs. Approaches based on cybernetics or neural networks were abandoned or pushed into the background.[88] By the 1980s, however, progress in symbolic AI seemed to stall and many believed that symbolic systems would never be able to imitate all the processes of human cognition, especially perception, robotics, learning and pattern recognition. A number of researchers began to look into “sub-symbolic” approaches to specific AI problems.[79]

Bottom-up, embodied, situated, behavior-based or nouvelle AI
Researchers from the related field of robotics, such as Rodney Brooks, rejected symbolic AI and focused on the basic engineering problems that would allow robots to move and survive.[89] Their work revived the non-symbolic viewpoint of the early cybernetics researchers of the 50s and reintroduced the use of control theory in AI. This coincided with the development of the embodied mind thesis in the related field of cognitive science: the idea that aspects of the body (such as movement, perception and visualization) are required for higher intelligence.
Computational Intelligence
Interest in neural networks and “connectionism” was revived by David Rumelhart and others in the middle 1980s.[90] These and other sub-symbolic approaches, such as fuzzy systems and evolutionary computation, are now studied collectively by the emerging discipline of computational intelligence.[91]

[oroma.info] Statistical

In the 1990s, AI researchers developed sophisticated mathematical tools to solve specific subproblems. These tools are truly scientific, in the sense that their results are both measurable and verifiable, and they have been responsible for many of AI’s recent successes. The shared mathematical language has also permitted a high level of collaboration with more established fields (like mathematics, economics or operations research). Stuart Russell and Peter Norvig describe this movement as nothing less than a “revolution” and “the victory of the neats.”[38]

[oroma.info] Integrating the approaches

Intelligent agent paradigm
An intelligent agent is a system that perceives its environment and takes actions which maximizes its chances of success. The simplest intelligent agents are programs that solve specific problems. The most complicated intelligent agents are rational, thinking humans.[92] The paradigm gives researchers license to study isolated problems and find solutions that are both verifiable and useful, without agreeing on one single approach. An agent that solves a specific problem can use any approach that works — some agents are symbolic and logical, some are sub-symbolic neural networks and others may use new approaches. The paradigm also gives researchers a common language to communicate with other fields—such as decision theory and economics—that also use concepts of abstract agents. The intelligent agent paradigm became widely accepted during the 1990s.[93]
Agent architectures and cognitive architectures
Researchers have designed systems to build intelligent systems out of interacting intelligent agents in a multi-agent system.[94] A system with both symbolic and sub-symbolic components is a hybrid intelligent system, and the study of such systems is artificial intelligence systems integration. A hierarchical control system provides a bridge between sub-symbolic AI at its lowest, reactive levels and traditional symbolic AI at its highest levels, where relaxed time constraints permit planning and world modelling.[95] Rodney Brooks’ subsumption architecture was an early proposal for such a hierarchical system.

[oroma.info] Tools

In the course of 50 years of research, AI has developed a large number of tools to solve the most difficult problems in computer science. A few of the most general of these methods are discussed below.

[oroma.info] Search and optimization

Main articles: Search algorithm, Optimization (mathematics), and Evolutionary computation

Many problems in AI can be solved in theory by intelligently searching through many possible solutions:[96] Reasoning can be reduced to performing a search. For example, logical proof can be viewed as searching for a path that leads from premises to conclusions, where each step is the application of an inference rule.[97] Planning algorithms search through trees of goals and subgoals, attempting to find a path to a target goal, a process called means-ends analysis.[98] Robotics algorithms for moving limbs and grasping objects use local searches in configuration space.[67] Many learning algorithms use search algorithms based on optimization.

Simple exhaustive searches[99] are rarely sufficient for most real world problems: the search space (the number of places to search) quickly grows to astronomical numbers. The result is a search that is too slow or never completes. The solution, for many problems, is to use “heuristics” or “rules of thumb” that eliminate choices that are unlikely to lead to the goal (called “pruning the search tree”). Heuristics supply the program with a “best guess” for what path the solution lies on.[100]

A very different kind of search came to prominence in the 1990s, based on the mathematical theory of optimization. For many problems, it is possible to begin the search with some form of a guess and then refine the guess incrementally until no more refinements can be made. These algorithms can be visualized as blind hill climbing: we begin the search at a random point on the landscape, and then, by jumps or steps, we keep moving our guess uphill, until we reach the top. Other optimization algorithms are simulated annealing, beam search and random optimization.[101]

Evolutionary computation uses a form of optimization search. For example, they may begin with a population of organisms (the guesses) and then allow them to mutate and recombine, selecting only the fittest to survive each generation (refining the guesses). Forms of evolutionary computation include swarm intelligence algorithms (such as ant colony or particle swarm optimization)[102] and evolutionary algorithms (such as genetic algorithms[103] and genetic programming[104][105]).

[oroma.info] Logic

Main articles: Logic programming and Automated reasoning

Logic[106] is used for knowledge representation and problem solving, but it can be applied to other problems as well. For example, the satplan algorithm uses logic for planning[107] and inductive logic programming is a method for learning.[108]

Several different forms of logic are used in AI research. Propositional or sentential logic[109] is the logic of statements which can be true or false. First-order logic[110] also allows the use of quantifiers and predicates, and can express facts about objects, their properties, and their relations with each other. Fuzzy logic,[111] is a version of first-order logic which allows the truth of a statement to be represented as a value between 0 and 1, rather than simply True (1) or False (0). Fuzzy systems can be used for uncertain reasoning and have been widely used in modern industrial and consumer product control systems. Subjective logic models uncertainty in a different and more explicit manner than fuzzy-logic: a given binomial opinion satisfies belief + disbelief + uncertainty = 1 within a Beta distribution. By this method, ignorance can be distinguished from probabilistic statements that an agent makes with high confidence. Default logics, non-monotonic logics and circumscription[51] are forms of logic designed to help with default reasoning and the qualification problem. Several extensions of logic have been designed to handle specific domains of knowledge, such as: description logics;[45] situation calculus, event calculus and fluent calculus (for representing events and time);[46] causal calculus;[47] belief calculus; and modal logics.[48]

[oroma.info] Probabilistic methods for uncertain reasoning

Main articles: Bayesian network, Hidden Markov model, Kalman filter, Decision theory, and Utility theory

Many problems in AI (in reasoning, planning, learning, perception and robotics) require the agent to operate with incomplete or uncertain information. AI researchers have devised a number of powerful tools to solve these problems using methods from probability theory and economics.[112]

Bayesian networks[113] are a very general tool that can be used for a large number of problems: reasoning (using the Bayesian inference algorithm),[114] learning (using the expectation-maximization algorithm),[115] planning (using decision networks)[116] and perception (using dynamic Bayesian networks).[117] Probabilistic algorithms can also be used for filtering, prediction, smoothing and finding explanations for streams of data, helping perception systems to analyze processes that occur over time[118] (e.g., hidden Markov models[119] or Kalman filters[120]).

A key concept from the science of economics is “utility”: a measure of how valuable something is to an intelligent agent. Precise mathematical tools have been developed that analyze how an agent can make choices and plan, using decision theory, decision analysis,[121] information value theory.[57] These tools include models such as Markov decision processes,[122] dynamic decision networks,[122] game theory and mechanism design.[123]

[oroma.info] Classifiers and statistical learning methods

Main articles: Classifier (mathematics), Statistical classification, and Machine learning

The simplest AI applications can be divided into two types: classifiers (“if shiny then diamond”) and controllers (“if shiny then pick up”). Controllers do however also classify conditions before inferring actions, and therefore classification forms a central part of many AI systems. Classifiers are functions that use pattern matching to determine a closest match. They can be tuned according to examples, making them very attractive for use in AI. These examples are known as observations or patterns. In supervised learning, each pattern belongs to a certain predefined class. A class can be seen as a decision that has to be made. All the observations combined with their class labels are known as a data set. When a new observation is received, that observation is classified based on previous experience.[124]

A classifier can be trained in various ways; there are many statistical and machine learning approaches. The most widely used classifiers are the neural network,[125] kernel methods such as the support vector machine,[126] k-nearest neighbor algorithm,[127] Gaussian mixture model,[128] naive Bayes classifier,[129] and decision tree.[130] The performance of these classifiers have been compared over a wide range of tasks. Classifier performance depends greatly on the characteristics of the data to be classified. There is no single classifier that works best on all given problems; this is also referred to as the “no free lunch” theorem. Determining a suitable classifier for a given problem is still more an art than science.[131]

[oroma.info] Neural networks

Main articles: Neural networks and Connectionism

A neural network is an interconnected group of nodes, akin to the vast network of neurons in the human brain.

The study of artificial neural networks[125] began in the decade before the field AI research was founded, in the work of Walter Pitts and Warren McCullough. Other important early researchers were Frank Rosenblatt, who invented the perceptron and Paul Werbos who developed the backpropagation algorithm.[132]

The main categories of networks are acyclic or feedforward neural networks (where the signal passes in only one direction) and recurrent neural networks (which allow feedback). Among the most popular feedforward networks are perceptrons, multi-layer perceptrons and radial basis networks.[133] Among recurrent networks, the most famous is the Hopfield net, a form of attractor network, which was first described by John Hopfield in 1982.[134] Neural networks can be applied to the problem of intelligent control (for robotics) or learning, using such techniques as Hebbian learning and competitive learning.[135]

Jeff Hawkins argues that research in neural networks has stalled because it has failed to model the essential properties of the neocortex, and has suggested a model (Hierarchical Temporal Memory) that is loosely based on neurological research.[136]

[oroma.info] Control theory

Main article: Intelligent control

Control theory, the grandchild of cybernetics, has many important applications, especially in robotics.[137]

[oroma.info] Languages

Main article: List of programming languages for artificial intelligence

AI researchers have developed several specialized languages for AI research, including Lisp[138] and Prolog.[139]

[oroma.info] Evaluating progress

Main article: Progress in artificial intelligence

In 1950, Alan Turing proposed a general procedure to test the intelligence of an agent now known as the Turing test. This procedure allows almost all the major problems of artificial intelligence to be tested. However, it is a very difficult challenge and at present all agents fail.

Artificial intelligence can also be evaluated on specific problems such as small problems in chemistry, hand-writing recognition and game-playing. Such tests have been termed subject matter expert Turing tests. Smaller problems provide more achievable goals and there are an ever-increasing number of positive results.

The broad classes of outcome for an AI test are:

  • Optimal: it is not possible to perform better
  • Strong super-human: performs better than all humans
  • Super-human: performs better than most humans
  • Sub-human: performs worse than most humans

For example, performance at draughts is optimal,[140] performance at chess is super-human and nearing strong super-human,[141] and performance at many everyday tasks performed by humans is sub-human.

A quite different approach measures machine intelligence through tests which are developed from mathematical definitions of intelligence. Examples of these kinds of tests start in the late nineties devising intelligence tests using notions from Kolmogorov Complexity and data compression.[142] [143] Similar definitions of machine intelligence have been put forward by Marcus Hutter in his book Universal Artificial Intelligence (Springer 2005), an idea further developed by Legg and Hutter.[144] Two major advantages of mathematical definitions are their applicability to nonhuman intelligences and their absence of a requirement for human testers.

[oroma.info] Applications

Wiki letter w.svg This section requires expansion.
Main article: Applications of artificial intelligence

Artificial intelligence has successfully been used in a wide range of fields including medical diagnosis, stock trading, robot control, law, scientific discovery, video games, toys, and Web search engines. Frequently, when a technique reaches mainstream use, it is no longer considered artificial intelligence, sometimes described as the AI effect.[145] It may also become integrated into artificial life.

[oroma.info] Competitions and prizes

Main article: Competitions and prizes in artificial intelligence

There are a number of competitions and prizes to promote research in artificial intelligence. The main areas promoted are: general machine intelligence, conversational behavior, data-mining, driverless cars, robot soccer and games.

[oroma.info] Platforms

A platform (or “computing platform”)is defined as “some sort of hardware architecture or software framework (including application frameworks), that allows software to run.” As Rodney Brooks [146] pointed out many years ago, it is not just the artificial intelligence software that defines the AI features of the platform, but rather the actual platform itself that affects the AI that results, i.e., we need to be working out AI problems on real world platforms rather than in isolation.

A wide variety of platforms has allowed different aspects of AI to develop, ranging from expert systems, albeit PC-based but still an entire real-world system to various robot platforms such as the widely available Roomba with open interface.[147]

[oroma.info] Philosophy

Main article: Philosophy of artificial intelligence

Artificial intelligence, by claiming to be able to recreate the capabilities of the human mind, is both a challenge and an inspiration for philosophy. Are there limits to how intelligent machines can be? Is there an essential difference between human intelligence and artificial intelligence? Can a machine have a mind and consciousness? A few of the most influential answers to these questions are given below.[148]

Turing’s “polite convention”
If a machine acts as intelligently as a human being, then it is as intelligent as a human being. Alan Turing theorized that, ultimately, we can only judge the intelligence of a machine based on its behavior. This theory forms the basis of the Turing test.[149]
The Dartmouth proposal
“Every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it.” This assertion was printed in the proposal for the Dartmouth Conference of 1956, and represents the position of most working AI researchers.[150]
Newell and Simon’s physical symbol system hypothesis
“A physical symbol system has the necessary and sufficient means of general intelligent action.” Newell and Simon argue that intelligences consists of formal operations on symbols.[151] Hubert Dreyfus argued that, on the contrary, human expertise depends on unconscious instinct rather than conscious symbol manipulation and on having a “feel” for the situation rather than explicit symbolic knowledge. (See Dreyfus’ critique of AI.)[152][153]
Gödel’s incompleteness theorem
A formal system (such as a computer program) can not prove all true statements. Roger Penrose is among those who claim that Gödel’s theorem limits what machines can do. (See The Emperor’s New Mind.)[154][155]
Searle’s strong AI hypothesis
“The appropriately programmed computer with the right inputs and outputs would thereby have a mind in exactly the same sense human beings have minds.”[156] Searle counters this assertion with his Chinese room argument, which asks us to look inside the computer and try to find where the “mind” might be.[157]
The artificial brain argument
The brain can be simulated. Hans Moravec, Ray Kurzweil and others have argued that it is technologically feasible to copy the brain directly into hardware and software, and that such a simulation will be essentially identical to the original.[158]

[oroma.info] Prediction

Main articles: Artificial intelligence in fiction, Ethics of artificial intelligence, Transhumanism, and Technological singularity

AI is a common topic in both science fiction and projections about the future of technology and society. The existence of an artificial intelligence that rivals human intelligence raises difficult ethical issues, and the potential power of the technology inspires both hopes and fears.

In fiction, AI has appeared fulfilling many roles, including a servant (R2D2 in Star Wars), a law enforcer (K.I.T.T. “Knight Rider”), a comrade (Lt. Commander Data in Star Trek: The Next Generation), a conqueror/overlord (The Matrix), a dictator (With Folded Hands), an assassin (Terminator), a sentient race (Battlestar Galactica/Transformers), an extension to human abilities (Ghost in the Shell) and the savior of the human race (R. Daneel Olivaw in the Foundation Series).

Mary Shelley’s Frankenstein[159] considers a key issue in the ethics of artificial intelligence: if a machine can be created that has intelligence, could it also feel? If it can feel, does it have the same rights as a human? The idea also appears in modern science fiction, including the films I Robot, Blade Runner and A.I.: Artificial Intelligence, in which humanoid machines have the ability to feel human emotions. This issue, now known as “robot rights”, is currently being considered by, for example, California’s Institute for the Future,[160] although many critics believe that the discussion is premature.[161]

The impact of AI on society is a serious area of study for futurists. Academic sources have considered such consequences as a decreased demand for human labor,[162] the enhancement of human ability or experience,[163] and a need for redefinition of human identity and basic values.[164] Andrew Kennedy, in his musing on the evolution of the human personality,[165] considered that artificial intelligences or ‘new minds’ are likely to have severe personality disorders, and identifies four particular types that are likely to arise: the autistic, the collector, the ecstatic, and the victim. He suggests that they will need humans because of our superior understanding of personality and the role of the unconscious.

Several futurists argue that artificial intelligence will transcend the limits of progress. Ray Kurzweil has used Moore’s law (which describes the relentless exponential improvement in digital technology) to calculate that desktop computers will have the same processing power as human brains by the year 2029. He also predicts that by 2045 artificial intelligence will reach a point where it is able to improve itself at a rate that far exceeds anything conceivable in the past, a scenario that science fiction writer Vernor Vinge named the “technological singularity”.[163]

Robot designer Hans Moravec, cyberneticist Kevin Warwick and inventor Ray Kurzweil have predicted that humans and machines will merge in the future into cyborgs that are more capable and powerful than either.[163] This idea, called transhumanism, which has roots in Aldous Huxley and Robert Ettinger, has been illustrated in fiction as well, for example in the manga Ghost in the Shell and the science-fiction series Dune.

Edward Fredkin argues that “artificial intelligence is the next stage in evolution,”[166] an idea first proposed by Samuel Butler’s “Darwin among the Machines” (1863), and expanded upon by George Dyson in his book of the same name in 1998.

Pamela McCorduck writes that all these scenarios are expressions of the ancient human desire to, as she calls it, “forge the gods”.[6]