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Wednesday, September 6, 2023

Intellectual disability

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

Intellectual disability
Other namesIntellectual developmental disability (IDD), general learning disability
A child runs through the finishing line
Children with intellectual disabilities and other developmental conditions competing in the Special Olympics World Games
SpecialtyPsychiatry, pediatrics
Differential diagnosisAutism, ADHD, Fragile X, fetal alcohol syndrome, learning disability
Frequency153 million (2015)

Intellectual disability (ID), also known as general learning disability in the United Kingdom and formerly mental retardation, is a generalized neurodevelopmental disorder characterized by significantly impaired intellectual and adaptive functioning. It is defined by an IQ under 70, in addition to deficits in two or more adaptive behaviors that affect everyday, general living. Intellectual functions are defined under DSM-V as reasoning, problem‑solving, planning, abstract thinking, judgment, academic learning, and learning from instruction and experience, and practical understanding confirmed by both clinical assessment and standardized tests. Adaptive behavior is defined in terms of conceptual, social, and practical skills involving tasks performed by people in their everyday lives.

Intellectual disability is subdivided into syndromic intellectual disability, in which intellectual deficits associated with other medical and behavioral signs and symptoms are present, and non-syndromic intellectual disability, in which intellectual deficits appear without other abnormalities. Down syndrome and fragile X syndrome are examples of syndromic intellectual disabilities.

Intellectual disability affects about 2 to 3% of the general population. Seventy-five to ninety percent of the affected people have mild intellectual disability. Non-syndromic, or idiopathic cases account for 30 to 50% of these cases. About a quarter of cases are caused by a genetic disorder, and about 5% of cases are inherited. Cases of unknown cause affect about 95 million people as of 2013.

Signs and symptoms

Intellectual disability (ID) becomes apparent during childhood and involves deficits in mental abilities, social skills, and core activities of daily living (ADLs) when compared to same-aged peers. There often are no physical signs of mild forms of ID, although there may be characteristic physical traits when it is associated with a genetic disorder (e.g., Down syndrome).

The level of impairment ranges in severity for each person. Some of the early signs can include:

  • Delays in reaching, or failure to achieve milestones in motor skills development (sitting, crawling, walking)
  • Slowness learning to talk, or continued difficulties with speech and language skills after starting to talk
  • Difficulty with self-help and self-care skills (e.g., getting dressed, washing, and feeding themselves)
  • Poor planning or problem-solving abilities
  • Behavioral and social problems
  • Failure to grow intellectually, or continued infant childlike behavior
  • Problems keeping up in school
  • Failure to adapt or adjust to new situations
  • Difficulty understanding and following social rules

In early childhood, mild ID (IQ 50–69) may not be obvious or identified until children begin school. Even when poor academic performance is recognized, it may take expert assessment to distinguish mild intellectual disability from specific learning disability or emotional/behavioral disorders. People with mild ID are capable of learning reading and mathematics skills to approximately the level of a typical child aged nine to twelve. They can learn self-care and practical skills, such as cooking or using the local mass transit system. As individuals with intellectual disabilities reach adulthood, many learn to live independently and maintain gainful employment. About 85% of persons with ID are likely to have mild ID.

Moderate ID (IQ 35–49) is nearly always apparent within the first years of life. Speech delays are particularly common signs of moderate ID. People with moderate intellectual disabilities need considerable support in school, at home, and in the community in order to fully participate. While their academic potential is limited, they can learn simple health and safety skills and to participate in simple activities. As adults, they may live with their parents, in a supportive group home, or even semi-independently with significant supportive services to help them, for example, manage their finances. As adults, they may work in a sheltered workshop. About 10% of persons with ID are likely to have moderate ID.

People with Severe ID (IQ 20–34), accounting for 3.5% of persons with ID, or Profound ID (IQ 19 or below), accounting for 1.5% of persons with ID, need more intensive support and supervision for their entire lives. They may learn some ADLs, but an intellectual disability is considered severe or profound when individuals are unable to independently care for themselves without ongoing significant assistance from a caregiver throughout adulthood. Individuals with profound ID are completely dependent on others for all ADLs and to maintain their physical health and safety. They may be able to learn to participate in some of these activities to a limited degree.

Co-morbidity

Autism and intellectual disability

Intellectual disability and autism spectrum disorder (ASD) share clinical characteristics which can result in confusion while diagnosing. Overlapping these two disorders, while common, can be detrimental to a person's well-being. Those with ASD that hold symptoms of ID may be grouped into a co-diagnosis in which they are receiving treatment for a disorder they do not have. Likewise, those with ID that are mistaken to have ASD may be treated for symptoms of a disorder they do not have. Differentiating between these two disorders will allow clinicians to deliver or prescribe the appropriate treatments. Comorbidity between ID and ASD is very common; it was estimated that roughly 40% of those with ID also have ASD, and roughly 70% of those with ASD also have ID. More recently, research has indicated a prevalence of roughly 30% for ID in individuals with ASD. Both ASD and ID require shortfalls in communication and social awareness as defining criteria.

Defining differences

In a study conducted in 2016 surveying 2816 cases, it was found that the top subsets that help differentiate between those with ID and ASD are, "impaired non-verbal social behavior and lack of social reciprocity, [...] restricted interests, strict adherence to routines, stereotyped and repetitive motor mannerisms, and preoccupation with parts of objects". Those with ASD tend to show more deficits in non-verbal social behavior such as body language and understanding social cues. In a study done in 2008 of 336 individuals with varying levels of ID, it was found that those with ID display fewer instances of repetitive or ritualistic behaviors. It also recognized that those with ASD, when compared to those with ID, were more likely to isolate themselves and make less eye contact. When it comes to classification ID and ASD have very different guidelines. ID has a standardized assessment called the Supports Intensity Scale (SIS); this measures severity on a system built around how much support an individual will need. While ASD also classifies severity by support needed, there is no standard assessment; clinicians are free to diagnose severity at their own judgment.

Causes

An eight-year-old boy
Down syndrome is the most common genetic cause of intellectual disability.

Among children, the cause of intellectual disability is unknown for one-third to one-half of cases. About 5% of cases are inherited. Genetic defects that cause intellectual disability, but are not inherited, can be caused by accidents or mutations in genetic development. Examples of such accidents are development of an extra chromosome 18 (trisomy 18) and Down syndrome, which is the most common genetic cause. DiGeorge syndrome and fetal alcohol spectrum disorders are the two next most common causes. However, there are many other causes. The most common are:

Diagnosis

According to both the American Association on Intellectual and Developmental Disabilities and the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), three criteria must be met for a diagnosis of intellectual disability: significant limitation in general mental abilities (intellectual functioning), significant limitations in one or more areas of adaptive behavior across multiple environments (as measured by an adaptive behavior rating scale, i.e. communication, self-help skills, interpersonal skills, and more), and evidence that the limitations became apparent in childhood or adolescence. In general, people with intellectual disabilities have an IQ below 70, but clinical discretion may be necessary for individuals who have a somewhat higher IQ but severe impairment in adaptive functioning.

It is formally diagnosed by an assessment of IQ and adaptive behavior. A third condition requiring onset during the developmental period is used to distinguish intellectual disability from other conditions, such as traumatic brain injuries and dementias (including Alzheimer's disease).

Intelligence quotient

The first English-language IQ test, the Stanford–Binet Intelligence Scales, was adapted from a test battery designed for school placement by Alfred Binet in France. Lewis Terman adapted Binet's test and promoted it as a test measuring "general intelligence". Terman's test was the first widely used mental test to report scores in "intelligence quotient" form ("mental age" divided by chronological age, multiplied by 100). Current tests are scored in "deviation IQ" form, with a performance level by a test-taker two standard deviations below the median score for the test-takers age group defined as IQ 70. Until the most recent revision of diagnostic standards, an IQ of 70 or below was a primary factor for intellectual disability diagnosis, and IQ scores were used to categorize degrees of intellectual disability.

Since the current diagnosis of intellectual disability is not based on IQ scores alone, but must also take into consideration a person's adaptive functioning, the diagnosis is not made rigidly. It encompasses intellectual scores, adaptive functioning scores from an adaptive behavior rating scale based on descriptions of known abilities provided by someone familiar with the person, and also the observations of the assessment examiner, who is able to find out directly from the person what they can understand, communicate, and such like. IQ assessment must be based on a current test. This enables a diagnosis to avoid the pitfall of the Flynn effect, which is a consequence of changes in population IQ test performance changing IQ test norms over time.

Distinction from other disabilities

Clinically, intellectual disability is a subtype of cognitive deficit or disabilities affecting intellectual abilities, which is a broader concept and includes intellectual deficits that are too mild to properly qualify as intellectual disability, or too specific (as in specific learning disability), or acquired later in life through acquired brain injuries or neurodegenerative diseases like dementia. Cognitive deficits may appear at any age. Developmental disability is any disability that is due to problems with growth and development. This term encompasses many congenital medical conditions that have no mental or intellectual components, although it, too, is sometimes used as a euphemism for intellectual disability.

Limitations in more than one area

Adaptive behavior, or adaptive functioning, refers to the skills needed to live independently (or at the minimally acceptable level for age). To assess adaptive behavior, professionals compare the functional abilities of a child to those of other children of similar age. To measure adaptive behavior, professionals use structured interviews, with which they systematically elicit information about persons' functioning in the community from people who know them well. There are many adaptive behavior scales, and accurate assessment of the quality of someone's adaptive behavior requires clinical judgment as well. Certain skills are important to adaptive behavior, such as:

Other specific skills can be critical to an individual's inclusion in the community and to develop appropriate social behaviors, as for example being aware of the different social expectations linked to the principal lifespan stages (i.e., childhood, adulthood, old age). The results of a Swiss study suggest that the performance of adults with ID in recognizing different lifespan stages is related to specific cognitive abilities and to the type of material used to test this performance.

Management

By most definitions, intellectual disability is more accurately considered a disability rather than a disease. Intellectual disability can be distinguished in many ways from mental illness, such as schizophrenia or depression. Currently, there is no "cure" for an established disability, though with appropriate support and teaching, most individuals can learn to do many things. Causes, such as congenital hypothyroidism, if detected early may be treated to prevent the development of an intellectual disability.

There are thousands of agencies around the world that provide assistance for people with developmental disabilities. They include state-run, for-profit, and non-profit, privately run agencies. Within one agency there could be departments that include fully staffed residential homes, day rehabilitation programs that approximate schools, workshops wherein people with disabilities can obtain jobs, programs that assist people with developmental disabilities in obtaining jobs in the community, programs that provide support for people with developmental disabilities who have their own apartments, programs that assist them with raising their children, and many more. There are also many agencies and programs for parents of children with developmental disabilities.

Beyond that, there are specific programs that people with developmental disabilities can take part in wherein they learn basic life skills. These "goals" may take a much longer amount of time for them to accomplish, but the ultimate goal is independence. This may be anything from independence in tooth brushing to an independent residence. People with developmental disabilities learn throughout their lives and can obtain many new skills even late in life with the help of their families, caregivers, clinicians and the people who coordinate the efforts of all of these people.

There are four broad areas of intervention that allow for active participation from caregivers, community members, clinicians, and of course, the individual(s) with an intellectual disability. These include psychosocial treatments, behavioral treatments, cognitive-behavioral treatments, and family-oriented strategies. Psychosocial treatments are intended primarily for children before and during the preschool years as this is the optimum time for intervention. This early intervention should include encouragement of exploration, mentoring in basic skills, celebration of developmental advances, guided rehearsal and extension of newly acquired skills, protection from harmful displays of disapproval, teasing, or punishment, and exposure to a rich and responsive language environment. A great example of a successful intervention is the Carolina Abecedarian Project that was conducted with over 100 children from low socioeconomic status families beginning in infancy through pre-school years. Results indicated that by age 2, the children provided the intervention had higher test scores than control group children, and they remained approximately 5 points higher 10 years after the end of the program. By young adulthood, children from the intervention group had better educational attainment, employment opportunities, and fewer behavioral problems than their control-group counterparts.

Core components of behavioral treatments include language and social skills acquisition. Typically, one-to-one training is offered in which a therapist uses a shaping procedure in combination with positive reinforcements to help the child pronounce syllables until words are completed. Sometimes involving pictures and visual aids, therapists aim at improving speech capacity so that short sentences about important daily tasks (e.g. bathroom use, eating, etc.) can be effectively communicated by the child. In a similar fashion, older children benefit from this type of training as they learn to sharpen their social skills such as sharing, taking turns, following instruction, and smiling. At the same time, a movement known as social inclusion attempts to increase valuable interactions between children with an intellectual disability and their non-disabled peers. Cognitive-behavioral treatments, a combination of the previous two treatment types, involves a strategical-metastrategical learning technique that teaches children math, language, and other basic skills pertaining to memory and learning. The first goal of the training is to teach the child to be a strategical thinker through making cognitive connections and plans. Then, the therapist teaches the child to be metastrategical by teaching them to discriminate among different tasks and determine which plan or strategy suits each task. Finally, family-oriented strategies delve into empowering the family with the skill set they need to support and encourage their child or children with an intellectual disability. In general, this includes teaching assertiveness skills or behavior management techniques as well as how to ask for help from neighbors, extended family, or day-care staff. As the child ages, parents are then taught how to approach topics such as housing/residential care, employment, and relationships. The ultimate goal for every intervention or technique is to give the child autonomy and a sense of independence using the acquired skills they have. In a 2019 Cochrane review on beginning reading interventions for children and adolescents with intellectual disability, small to moderate improvements in phonological awareness, word reading, decoding, expressive and receptive language skills, and reading fluency were noted when these elements were part of the teaching intervention.

Although there is no specific medication for intellectual disability, many people with developmental disabilities have further medical complications and may be prescribed several medications. For example, autistic children with developmental delay may be prescribed antipsychotics or mood stabilizers to help with their behavior. Use of psychotropic medications such as benzodiazepines in people with intellectual disability requires monitoring and vigilance as side effects occur commonly and are often misdiagnosed as behavioral and psychiatric problems.

Epidemiology

Intellectual disability affects about 2–3% of the general population. 75–90% of the affected people have mild intellectual disability. Non-syndromic or idiopathic ID accounts for 30–50% of cases. About a quarter of cases are caused by a genetic disorder. Cases of unknown cause affect about 95 million people as of 2013. It is more common in males and in low to middle income countries.

History

Intellectual disability has been documented under a variety of names throughout history. Throughout much of human history, society was unkind to those with any type of disability, and people with intellectual disability were commonly viewed as burdens on their families.

Greek and Roman philosophers, who valued reasoning abilities, disparaged people with intellectual disability as barely human. The oldest physiological view of intellectual disability is in the writings of Hippocrates in the late fifth century BCE, who believed that it was caused by an imbalance in the four humors in the brain. In ancient Rome people with intellectual disabilities had limited rights and were generally looked down upon. They were considered property and could be kept slaves by their father. These people could also not marry, hold office, or raise children. Many of them were killed early in the childhood, and then dumped into the Tiber in order to avoid them burdening society. However, they were exempt from their crimes under Roman law,[54][55] and they were also used to perform menial labor.

Caliph Al-Walid (r. 705–715) built one of the first care homes for individuals with intellectual disabilities and built the first hospital which accommodated intellectually disabled individuals as part of its services. In addition, Al-Walid assigned each intellectually disabled individual a caregiver.

Until the Enlightenment in Europe, care and asylum was provided by families and the church (in monasteries and other religious communities), focusing on the provision of basic physical needs such as food, shelter, and clothing. Negative stereotypes were prominent in social attitudes of the time.

In the 13th century, England declared people with intellectual disabilities to be incapable of making decisions or managing their affairs. Guardianships were created to take over their financial affairs.

In the 17th century, Thomas Willis provided the first description of intellectual disability as a disease. He believed that it was caused by structural problems in the brain. According to Willis, the anatomical problems could be either an inborn condition or acquired later in life.

In the 18th and 19th centuries, housing and care moved away from families and towards an asylum model. People were placed by, or removed from, their families (usually in infancy) and housed in large professional institutions, many of which were self-sufficient through the labor of the residents. Some of these institutions provided a very basic level of education (such as differentiation between colors and basic word recognition and numeracy), but most continued to focus solely on the provision of basic needs of food, clothing, and shelter. Conditions in such institutions varied widely, but the support provided was generally non-individualized, with aberrant behavior and low levels of economic productivity regarded as a burden to society. Individuals of higher wealth were often able to afford higher degrees of care such as home care or private asylums. Heavy tranquilization and assembly-line methods of support were the norm, and the medical model of disability prevailed. Services were provided based on the relative ease to the provider, not based on the needs of the individual. A survey taken in 1891 in Cape Town, South Africa shows the distribution between different facilities. Out of 2046 persons surveyed, 1,281 were in private dwellings, 120 in jails, and 645 in asylums, with men representing nearly two-thirds of the number surveyed. In situations of scarcity of accommodation, preference was given to white men and Black men (whose insanity threatened white society by disrupting employment relations and the taboo sexual contact with white women).

In the late 19th century, in response to Charles Darwin's On the Origin of Species, Francis Galton proposed selective breeding of humans to reduce intellectual disability. Early in the 20th century, the eugenics movement became popular throughout the world. This led to forced sterilization and prohibition of marriage in most of the developed world and was later used by Adolf Hitler as a rationale for the mass murder of people with intellectual disability during the Holocaust. Eugenics was later abandoned as an violation of human rights, and the practice of forced sterilization and prohibition from marriage was discontinued by most of the developed world by the mid-20th century.

In 1905, Alfred Binet produced the first standardized test for measuring intelligence in children.

Although ancient Roman law had declared people with intellectual disability to be incapable of the deliberate intent to harm that was necessary for a person to commit a crime, during the 1920s, Western society believed they were morally degenerate.

Ignoring the prevailing attitude, Civitans adopted service to people with developmental disabilities as a major organizational emphasis in 1952. Their earliest efforts included workshops for special education teachers and daycamps for children with disabilities, all at a time when such training and programs were almost nonexistent. The segregation of people with developmental disabilities was not widely questioned by academics or policy-makers until the 1969 publication of Wolf Wolfensberger's seminal work "The Origin and Nature of Our Institutional Models", drawing on some of the ideas proposed by S. G. Howe 100 years earlier. This book posited that society characterizes people with disabilities as deviant, sub-human and burdens of charity, resulting in the adoption of that "deviant" role. Wolfensberger argued that this dehumanization, and the segregated institutions that result from it, ignored the potential productive contributions that all people can make to society. He pushed for a shift in policy and practice that recognized the human needs of those with intellectual disability and provided the same basic human rights as for the rest of the population.

The publication of this book may be regarded as the first move towards the widespread adoption of the social model of disability in regard to these types of disabilities, and was the impetus for the development of government strategies for desegregation. Successful lawsuits against governments and increasing awareness of human rights and self-advocacy also contributed to this process, resulting in the passing in the U.S. of the Civil Rights of Institutionalized Persons Act in 1980.

From the 1960s to the present, most states have moved towards the elimination of segregated institutions. Normalization and deinstitutionalization are dominant. Along with the work of Wolfensberger and others including Gunnar and Rosemary Dybwad, a number of scandalous revelations around the horrific conditions within state institutions created public outrage that led to change to a more community-based method of providing services.

By the mid-1970s, most governments had committed to de-institutionalization and had started preparing for the wholesale movement of people into the general community, in line with the principles of normalization. In most countries, this was essentially complete by the late 1990s, although the debate over whether or not to close institutions persists in some states, including Massachusetts.

In the past, lead poisoning and infectious diseases were significant causes of intellectual disability. Some causes of intellectual disability are decreasing, as medical advances, such as vaccination, increase. Other causes are increasing as a proportion of cases, perhaps due to rising maternal age, which is associated with several syndromic forms of intellectual disability.

Along with the changes in terminology, and the downward drift in acceptability of the old terms, institutions of all kinds have had to repeatedly change their names. This affects the names of schools, hospitals, societies, government departments, and academic journals. For example, the Midlands Institute of Mental Sub-normality became the British Institute of Mental Handicap and is now the British Institute of Learning Disability. This phenomenon is shared with mental health and motor disabilities, and seen to a lesser degree in sensory disabilities.

Terminology

Over the past two decades, the term intellectual disability has become preferred by most advocates and researchers in most English-speaking countries. In a 2012 survey of 101 Canadian healthcare professionals, 78% said they would use the term developmental delay with parents over intellectual disability (8%). Expressions like developmentally disabled, special, special needs, or challenged are sometimes used, but have been criticized for "reinforc[ing] the idea that people cannot deal honestly with their disabilities".

The term mental retardation, which stemmed from the understanding that such conditions arose as a result of delays or retardation of a child's natural development, was used in the American Psychiatric Association's DSM-IV (1994) and in the World Health Organization's ICD-10 (codes F70–F79). In the next revision, ICD-11, it was replaced by the term "disorders of intellectual development" (codes 6A00–6A04; 6A00.Z for the "unspecified" diagnosis code). The term "intellectual disability (intellectual developmental disorder)" is used in the DSM-5 (2013). The term "mental retardation" is still used in some professional settings such as governmental aid programs or health insurance paperwork, where "mental retardation" is specifically covered but "intellectual disability" is not.

Historical terms for intellectual disability eventually become perceived as an insult, in a process commonly known as the euphemism treadmill. The terms mental retardation and mentally retarded became popular in the middle of the 20th century to replace the previous set of terms, which included "imbecile", "idiot", "feeble-minded", and "moron", among others, and are now considered offensive. By the end of the 20th century, retardation and retard become widely seen as disparaging, politically incorrect, and in need of replacement.

Usage has changed over the years and differed from country to country. For example, mental retardation in some contexts covers the whole field, but it previously applied to people with milder impairments. Feeble-minded used to mean mild impairments in the UK, and once applied in the US to the whole field. "Borderline intellectual functioning" is not currently defined, but the term may be used to apply to people with IQs in the 70s. People with IQs of 70 to 85 used to be eligible for special consideration in the US public education system on grounds of intellectual disability.

United States

Special Olympics USA team in July 2019
  • In North America, intellectual disability is subsumed into the broader term developmental disability, which also includes epilepsy, autism, cerebral palsy, and other disorders that develop during the developmental period (birth to age 18). Because service provision is tied to the designation "developmental disability", it is used by many parents, direct support professionals, and physicians. In the United States, however, in school-based settings, the more specific term mental retardation or, more recently (and preferably), intellectual disability, is still typically used, and is one of 13 categories of disability under which children may be identified for special education services under Public Law 108–446.
  • The phrase intellectual disability is increasingly being used as a synonym for people with significantly below-average cognitive ability. These terms are sometimes used as a means of separating general intellectual limitations from specific, limited deficits as well as indicating that it is not an emotional or psychological disability. It is not specific to congenital disorders such as Down syndrome.

The American Association on Mental Retardation changed its name to the American Association on Intellectual and Developmental Disabilities (AAIDD) in 2007, and soon thereafter changed the names of its scholarly journals to reflect the term "intellectual disability". In 2010, the AAIDD released its 11th edition of its terminology and classification manual, which also used the term intellectual disability.

United Kingdom

In the UK, mental handicap had become the common medical term, replacing mental subnormality in Scotland and mental deficiency in England and Wales, until Stephen Dorrell, Secretary of State for Health for the United Kingdom from 1995 to 1997, changed the NHS's designation to learning disability. The new term is not yet widely understood, and is often taken to refer to problems affecting schoolwork (the American usage), which are known in the UK as "learning difficulties". British social workers may use "learning difficulty" to refer to both people with intellectual disability and those with conditions such as dyslexia. In education, "learning difficulties" is applied to a wide range of conditions: "specific learning difficulty" may refer to dyslexia, dyscalculia or developmental coordination disorder, while "moderate learning difficulties", "severe learning difficulties" and "profound learning difficulties" refer to more significant impairments.

In England and Wales between 1983 and 2008, the Mental Health Act 1983 defined "mental impairment" and "severe mental impairment" as "a state of arrested or incomplete development of mind which includes significant/severe impairment of intelligence and social functioning and is associated with abnormally aggressive or seriously irresponsible conduct on the part of the person concerned." As behavior was involved, these were not necessarily permanent conditions: they were defined for the purpose of authorizing detention in hospital or guardianship. The term mental impairment was removed from the Act in November 2008, but the grounds for detention remained. However, English statute law uses mental impairment elsewhere in a less well-defined manner—e.g. to allow exemption from taxes—implying that intellectual disability without any behavioral problems is what is meant.

A BBC poll conducted in the United Kingdom came to the conclusion that 'retard' was the most offensive disability-related word. On the reverse side of that, when a contestant on Celebrity Big Brother live used the phrase "walking like a retard", despite complaints from the public and the charity Mencap, the communications regulator Ofcom did not uphold the complaint saying "it was not used in an offensive context [...] and had been used light-heartedly". It was, however, noted that two previous similar complaints from other shows were upheld.

Australia

In the past, Australia has used British and American terms interchangeably, including "mental retardation" and "mental handicap". Today, "intellectual disability" is the preferred and more commonly used descriptor.

Society and culture

Severely disabled girl in Bhutan

People with intellectual disabilities are often not seen as full citizens of society. Person-centered planning and approaches are seen as methods of addressing the continued labeling and exclusion of socially devalued people, such as people with disabilities, encouraging a focus on the person as someone with capacities and gifts as well as support needs. The self-advocacy movement promotes the right of self-determination and self-direction by people with intellectual disabilities, which means allowing them to make decisions about their own lives.

Until the middle of the 20th century, people with intellectual disabilities were routinely excluded from public education, or educated away from other typically developing children. Compared to peers who were segregated in special schools, students who are mainstreamed or included in regular classrooms report similar levels of stigma and social self-conception, but more ambitious plans for employment. As adults, they may live independently, with family members, or in different types of institutions organized to support people with disabilities. About 8% currently live in an institution or a group home.

In the United States, the average lifetime cost of a person with an intellectual disability amounts to $223,000 per person, in 2003 US dollars, for direct costs such as medical and educational expenses. The indirect costs were estimated at $771,000, due to shorter lifespans and lower than average economic productivity. The total direct and indirect costs, which amount to a little more than a million dollars, are slightly more than the economic costs associated with cerebral palsy, and double that associated with serious vision or hearing impairments. Of the costs, about 14% is due to increased medical expenses (not including what is normally incurred by the typical person), and 10% is due to direct non-medical expenses, such as the excess cost of special education compared to standard schooling. The largest amount, 76%, is indirect costs accounting for reduced productivity and shortened lifespans. Some expenses, such as ongoing costs to family caregivers or the extra costs associated with living in a group home, were excluded from this calculation.

Human rights and legal status

The law treats person with intellectual disabilities differently than those without intellectual disabilities. Their human rights and freedoms, including the right to vote, the right to conduct business, enter into a contract, enter into marriage, right to education, are often limited. The courts have upheld some of these limitations and found discrimination in others. The UN Convention on the Rights of Persons with Disabilities, which sets minimum standards for the rights of persons with disabilities, has been ratified by more than 180 countries. In several U.S. states, and several European Union states, persons with intellectual disabilities are disenfranchised. The European Court of Human Rights ruled in Alajos Kiss v. Hungary (2010) that Hungary cannot restrict voting rights only on the basis of guardianship due to a psychosocial disability.

Health disparities

People with intellectual disabilities are usually at a higher risk of living with complex health conditions such as epilepsy and neurological disorders, gastrointestinal disorders, and behavioral and psychiatric problems compared to people without disabilities. Adults also have a higher prevalence of poor social determinants of health, behavioral risk factors, depression, diabetes, and poor or fair health status than adults without intellectual disability.

In the United Kingdom people with intellectual disability live on average 16 years less than the general population. Some of the barriers that exist for people with ID accessing quality healthcare include: communication challenges, service eligibility, lack of training for healthcare providers, diagnostic overshadowing, and absence of targeted health promotion services. Key recommendations from the CDC for improving the health status for people with intellectual disabilities include: improve access to health care, improve data collection, strengthen the workforce, include people with ID in public health programs, and prepare for emergencies with people with disabilities in mind.

Uncrewed spacecraft

From Wikipedia, the free encyclopedia
 
The uncrewed resupply vessel Progress M-06M
Galileo space probe, prior to departure from Earth orbit in 1989
Uncrewed spacecraft Buran launched, orbited Earth, and landed as an uncrewed spacecraft in 1988 (shown here at an airshow)
Model of James Webb Space Telescope

Robotic spacecraft or uncrewed spacecraft are spacecraft without people on board. Uncrewed spacecraft may have varying levels of autonomy from human input; they may be remote controlled, remote guided or autonomous: they have a pre-programmed list of operations, which they will execute unless otherwise instructed. A robotic spacecraft for scientific measurements is often called a space probe or space observatory.

Many space missions are more suited to telerobotic rather than crewed operation, due to lower cost and risk factors. In addition, some planetary destinations such as Venus or the vicinity of Jupiter are too hostile for human survival, given current technology. Outer planets such as Saturn, Uranus, and Neptune are too distant to reach with current crewed spaceflight technology, so telerobotic probes are the only way to explore them. Telerobotics also allows exploration of regions that are vulnerable to contamination by Earth micro-organisms since spacecraft can be sterilized. Humans can not be sterilized in the same way as a spaceship, as they coexist with numerous micro-organisms, and these micro-organisms are also hard to contain within a spaceship or spacesuit.

The first uncrewed space mission was Sputnik, launched October 4, 1957 to orbit the Earth. Nearly all satellites, landers and rovers are robotic spacecraft. Not every uncrewed spacecraft is a robotic spacecraft; for example, a reflector ball is a non-robotic uncrewed spacecraft. Space missions where other animals but no humans are on-board are called uncrewed missions.

Many habitable spacecraft also have varying levels of robotic features. For example, the space stations Salyut 7 and Mir, and the International Space Station module Zarya, were capable of remote guided station-keeping and docking maneuvers with both resupply craft and new modules. Uncrewed resupply spacecraft are increasingly used for crewed space stations.

History

A replica of Sputnik 1 at the U.S. National Air and Space Museum
A replica of Explorer 1

The first robotic spacecraft was launched by the Soviet Union (USSR) on 22 July 1951, a suborbital flight carrying two dogs Dezik and Tsygan. Four other such flights were made through the fall of 1951.

The first artificial satellite, Sputnik 1, was put into a 215-by-939-kilometer (116 by 507 nmi) Earth orbit by the USSR on 4 October 1957. On 3 November 1957, the USSR orbited Sputnik 2. Weighing 113 kilograms (249 lb), Sputnik 2 carried the first animal into orbit, the dog Laika. Since the satellite was not designed to detach from its launch vehicle's upper stage, the total mass in orbit was 508.3 kilograms (1,121 lb).

In a close race with the Soviets, the United States launched its first artificial satellite, Explorer 1, into a 357-by-2,543-kilometre (193 by 1,373 nmi) orbit on 31 January 1958. Explorer I was an 205-centimetre (80.75 in) long by 15.2-centimetre (6.00 in) diameter cylinder weighing 14.0 kilograms (30.8 lb), compared to Sputnik 1, a 58-centimeter (23 in) sphere which weighed 83.6 kilograms (184 lb). Explorer 1 carried sensors which confirmed the existence of the Van Allen belts, a major scientific discovery at the time, while Sputnik 1 carried no scientific sensors. On 17 March 1958, the US orbited its second satellite, Vanguard 1, which was about the size of a grapefruit, and remains in a 670-by-3,850-kilometre (360 by 2,080 nmi) orbit as of 2016.

The first attempted lunar probe was the Luna E-1 No.1, launched on 23 September 1958. The goal of a lunar probe repeatedly failed until 4 January 1959 when Luna 1 orbited around the Moon and then the Sun.

The success of these early missions began a race between the US and the USSR to outdo each other with increasingly ambitious probes. Mariner 2 was the first probe to study another planet, revealing Venus' extremely hot temperature to scientists in 1962, while the Soviet Venera 4 was the first atmospheric probe to study Venus. Mariner 4's 1965 Mars flyby snapped the first images of its cratered surface, which the Soviets responded to a few months later with images from on its surface from Luna 9. In 1967, America's Surveyor 3 gathered information about the Moon's surface that would prove crucial to the Apollo 11 mission that landed humans on the Moon two years later.

The first interstellar probe was Voyager 1, launched 5 September 1977. It entered interstellar space on 25 August 2012, followed by its twin Voyager 2 on 5 November 2018.

Nine other countries have successfully launched satellites using their own launch vehicles: France (1965), Japan and China (1970), the United Kingdom (1971), India (1980), Israel (1988), Iran (2009), North Korea (2012), and South Korea (2022).

Telepresence

Telerobotics becomes telepresence when the time delay is short enough to permit control of the spacecraft in close to real time by humans. Even the two seconds light speed delay for the Moon is too far away for telepresence exploration from Earth. The L1 and L2 positions permit 400-millisecond round trip delays, which is just close enough for telepresence operation. Telepresence has also been suggested as a way to repair satellites in Earth orbit from Earth. The Exploration Telerobotics Symposium in 2012 explored this and other topics.

Design

In spacecraft design, the United States Air Force considers a vehicle to consist of the mission payload and the bus (or platform). The bus provides physical structure, thermal control, electrical power, attitude control and telemetry, tracking and commanding.

JPL divides the "flight system" of a spacecraft into subsystems. These include:

Structure

An illustration's of NASA's planned Orion spacecraft approaching a robotic asteroid capture vehicle

This is the physical backbone structure. It:

  • provides overall mechanical integrity of the spacecraft
  • ensures spacecraft components are supported and can withstand launch loads

Data handling

This is sometimes referred to as the command and data subsystem. It is often responsible for:

  • command sequence storage
  • maintaining the spacecraft clock
  • collecting and reporting spacecraft telemetry data (e.g. spacecraft health)
  • collecting and reporting mission data (e.g. photographic images)

Attitude determination and control

This system is mainly responsible for the correct spacecraft's orientation in space (attitude) despite external disturbance-gravity gradient effects, magnetic-field torques, solar radiation and aerodynamic drag; in addition it may be required to reposition movable parts, such as antennas and solar arrays.

Landing on hazardous terrain

In planetary exploration missions involving robotic spacecraft, there are three key parts in the processes of landing on the surface of the planet to ensure a safe and successful landing. This process includes an entry into the planetary gravity field and atmosphere, a descent through that atmosphere towards an intended/targeted region of scientific value, and a safe landing that guarantees the integrity of the instrumentation on the craft is preserved. While the robotic spacecraft is going through those parts, it must also be capable of estimating its position compared to the surface in order to ensure reliable control of itself and its ability to maneuver well. The robotic spacecraft must also efficiently perform hazard assessment and trajectory adjustments in real time to avoid hazards. To achieve this, the robotic spacecraft requires accurate knowledge of where the spacecraft is located relative to the surface (localization), what may pose as hazards from the terrain (hazard assessment), and where the spacecraft should presently be headed (hazard avoidance). Without the capability for operations for localization, hazard assessment, and avoidance, the robotic spacecraft becomes unsafe and can easily enter dangerous situations such as surface collisions, undesirable fuel consumption levels, and/or unsafe maneuvers.

Entry, descent, and landing

Integrated sensing incorporates an image transformation algorithm to interpret the immediate imagery land data, perform a real-time detection and avoidance of terrain hazards that may impede safe landing, and increase the accuracy of landing at a desired site of interest using landmark localization techniques. Integrated sensing completes these tasks by relying on pre-recorded information and cameras to understand its location and determine its position and whether it is correct or needs to make any corrections (localization). The cameras are also used to detect any possible hazards whether it is increased fuel consumption or it is a physical hazard such as a poor landing spot in a crater or cliff side that would make landing very not ideal (hazard assessment).

Telecommunications

Components in the telecommunications subsystem include radio antennas, transmitters and receivers. These may be used to communicate with ground stations on Earth, or with other spacecraft.

Electrical power

The supply of electric power on spacecraft generally come from photovoltaic (solar) cells or from a radioisotope thermoelectric generator. Other components of the subsystem include batteries for storing power and distribution circuitry that connects components to the power sources.

Temperature control and protection from the environment

Spacecraft are often protected from temperature fluctuations with insulation. Some spacecraft use mirrors and sunshades for additional protection from solar heating. They also often need shielding from micrometeoroids and orbital debris.

Propulsion

Spacecraft propulsion is a method that allows a spacecraft to travel through space by generating thrust to push it forward. However, there is not one universally used propulsion system: monopropellant, bipropellant, ion propulsion, etc. Each propulsion system generates thrust in slightly different ways with each system having its own advantages and disadvantages. But, most spacecraft propulsion today is based on rocket engines. The general idea behind rocket engines is that when an oxidizer meets the fuel source, there is explosive release of energy and heat at high speeds, which propels the spacecraft forward. This happens due to one basic principle known as Newton's Third Law. According to Newton, "to every action there is an equal and opposite reaction." As the energy and heat is being released from the back of the spacecraft, gas particles are being pushed around to allow the spacecraft to propel forward. The main reason behind the usage of rocket engine today is because rockets are the most powerful form of propulsion there is.

Monopropellant

For a propulsion system to work, there is usually an oxidizer line and a fuel line. This way, the spacecraft propulsion is controlled. But in a monopropellant propulsion, there is no need for an oxidizer line and only requires the fuel line. This works due to the oxidizer being chemically bonded into the fuel molecule itself. But for the propulsion system to be controlled, the combustion of the fuel can only occur due to a presence of a catalyst. This is quite advantageous due to making the rocket engine lighter and cheaper, easy to control, and more reliable. But, the downfall is that the chemical is very dangerous to manufacture, store, and transport.

Bipropellant

A bipropellant propulsion system is a rocket engine that uses a liquid propellent. This means both the oxidizer and fuel line are in liquid states. This system is unique because it requires no ignition system, the two liquids would spontaneously combust as soon as they come into contact with each other and produces the propulsion to push the spacecraft forward. The main benefit for having this technology is because that these kinds of liquids have relatively high density, which allows the volume of the propellent tank to be small, therefore increasing space efficacy. The downside is the same as that of monopropellant propulsion system: very dangerous to manufacture, store, and transport.

Ion

An ion propulsion system is a type of engine that generates thrust by the means of electron bombardment or the acceleration of ions. By shooting high-energy electrons to a propellant atom (neutrally charge), it removes electrons from the propellant atom and this results the propellant atom becoming a positively charged atom. The positively charged ions are guided to pass through positively charged grids that contains thousands of precise aligned holes are running at high voltages. Then, the aligned positively charged ions accelerates through a negative charged accelerator grid that further increases the speed of the ions up to 40 kilometres per second (90,000 mph). The momentum of these positively charged ions provides the thrust to propel the spacecraft forward. The advantage of having this kind of propulsion is that it is incredibly efficient in maintaining constant velocity, which is needed for deep-space travel. However, the amount of thrust produced is extremely low and that it needs a lot of electrical power to operate.

Mechanical devices

Mechanical components often need to be moved for deployment after launch or prior to landing. In addition to the use of motors, many one-time movements are controlled by pyrotechnic devices.

Robotic vs. uncrewed spacecraft

Robotic spacecraft are specifically designed system for a specific hostile environment. Due to their specification for a particular environment, it varies greatly in complexity and capabilities. While an uncrewed spacecraft is a spacecraft without personnel or crew and is operated by automatic (proceeds with an action without human intervention) or remote control (with human intervention). The term 'uncrewed spacecraft' does not imply that the spacecraft is robotic.

Control

Robotic spacecraft use telemetry to radio back to Earth acquired data and vehicle status information. Although generally referred to as "remotely controlled" or "telerobotic", the earliest orbital spacecraft – such as Sputnik 1 and Explorer 1 – did not receive control signals from Earth. Soon after these first spacecraft, command systems were developed to allow remote control from the ground. Increased autonomy is important for distant probes where the light travel time prevents rapid decision and control from Earth. Newer probes such as Cassini–Huygens and the Mars Exploration Rovers are highly autonomous and use on-board computers to operate independently for extended periods of time.

Space probes and observatories

A space probe is a robotic spacecraft that does not orbit Earth, but instead, explores further into outer space. Space probes have different sets of scientific instruments onboard. A space probe may approach the Moon; travel through interplanetary space; flyby, orbit, or land on other planetary bodies; or enter interstellar space. Space probes send collected data to Earth. Space probes can be orbiters, landers, and rovers. Space probes can also gather materials from its target and return it to Earth.

Once a probe has left the vicinity of Earth, its trajectory will likely take it along an orbit around the Sun similar to the Earth's orbit. To reach another planet, the simplest practical method is a Hohmann transfer orbit. More complex techniques, such as gravitational slingshots, can be more fuel-efficient, though they may require the probe to spend more time in transit. Some high Delta-V missions (such as those with high inclination changes) can only be performed, within the limits of modern propulsion, using gravitational slingshots. A technique using very little propulsion, but requiring a considerable amount of time, is to follow a trajectory on the Interplanetary Transport Network.

A space telescope or space observatory is a telescope in outer space used to observe astronomical objects. Space telescopes avoid the filtering and distortion of electromagnetic radiation which they observe, and avoid light pollution which ground-based observatories encounter. They are divided into two types: satellites which map the entire sky (astronomical survey), and satellites which focus on selected astronomical objects or parts of the sky and beyond. Space telescopes are distinct from Earth imaging satellites, which point toward Earth for satellite imaging, applied for weather analysis, espionage, and other types of information gathering.

Cargo spacecraft

A collage of automated cargo spacecraft used in the past or present to resupply the International Space Station

Cargo or resupply spacecraft are robotic spacecraft that are designed specifically to carry cargo, possibly to support space stations' operation by transporting food, propellant and other supplies. This is different from a space probe, whose missions are to conduct scientific investigations.

Automated cargo spacecraft have been used since 1978 and have serviced Salyut 6, Salyut 7, Mir, the International Space Station and Tiangong space station.

As of 2023, three different cargo spacecraft are used to supply the International Space Station: Russian Progress, American SpaceX Dragon 2 and Cygnus. Chinese Tianzhou is used to supply Tiangong space station.

Virtual assistant

From Wikipedia, the free encyclopedia
https://en.wikipedia.org/wiki/Virtual_assistant
Google Assistant running on a Pixel XL smartphone

A virtual assistant (VA) is a software agent that can perform a range of tasks or services for a user based on user input such as commands or questions, including verbal ones. Such technologies often incorporate chatbot capabilities to simulate human conversation, such as via online chat, to facilitate interaction with their users. The interaction may be via text, graphical interface, or voice - as some virtual assistants are able to interpret human speech and respond via synthesized voices.

In many cases users can ask their virtual assistants questions, control home automation devices and media playback, and manage other basic tasks such as email, to-do lists, and calendars - all with verbal commands. In recent years, prominent virtual assistants for direct consumer use have included Amazon's Alexa, Apple's Siri, Microsoft's Cortana, and Google Assistant. Also, companies in various industries often incorporate some kind of virtual assistant technology into their customer service or support.

Recently, the emergence of recent artificial intelligence based chatbots, such as ChatGPT, has brought increased capability and interest to the field of virtual assistant products and services.

History

Experimental decades: 1910s–1980s

Radio Rex was the first voice activated toy, patented in 1916 and released in 1922. It was a wooden toy in the shape of a dog that would come out of its house when its name is called.

In 1952, Bell Labs presented "Audrey", the Automatic Digit Recognition machine. It occupied a six- foot-high relay rack, consumed substantial power, had streams of cables and exhibited the myriad maintenance problems associated with complex vacuum-tube circuitry. It could recognize the fundamental units of speech, phonemes. It was limited to accurate recognition of digits spoken by designated talkers. It could therefore be used for voice dialing, but in most cases push-button dialing was cheaper and faster, rather than speaking the consecutive digits.

Another early tool which was enabled to perform digital speech recognition was the IBM Shoebox voice-activated calculator, presented to the general public during the 1962 Seattle World's Fair after its initial market launch in 1961. This early computer, developed almost 20 years before the introduction of the first IBM Personal Computer in 1981, was able to recognize 16 spoken words and the digits 0 to 9.

The first natural language processing computer program or the chatbot ELIZA was developed by MIT professor Joseph Weizenbaum in the 1960s. It was created to "demonstrate that the communication between man and machine was superficial". ELIZA used pattern matching and substitution methodology into scripted responses to simulate conversation, which gave an illusion of understanding on the part of the program.

Weizenbaum's own secretary reportedly asked Weizenbaum to leave the room so that she and ELIZA could have a real conversation. Weizenbaum was surprised by this, later writing: "I had not realized ... that extremely short exposures to a relatively simple computer program could induce powerful delusional thinking in quite normal people.

This gave name to the ELIZA effect, the tendency to unconsciously assume computer behaviors are analogous to human behaviors; that is, anthropomorphisation, a phenomenon present in human interactions with virtual assistants.

The next milestone in the development of voice recognition technology was achieved in the 1970s at the Carnegie Mellon University in Pittsburgh, Pennsylvania with substantial support of the United States Department of Defense and its DARPA agency, funded five years of a Speech Understanding Research program, aiming to reach a minimum vocabulary of 1,000 words. Companies and academia including IBM, Carnegie Mellon University (CMU) and Stanford Research Institute took part in the program.

The result was "Harpy", it mastered about 1000 words, the vocabulary of a three-year-old and it could understand sentences. It could process speech that followed pre-programmed vocabulary, pronunciation, and grammar structures to determine which sequences of words made sense together, and thus reducing speech recognition errors.

In 1986 Tangora was an upgrade of the Shoebox, it was a voice recognizing typewriter. Named after the world's fastest typist at the time, it had a vocabulary of 20,000 words and used prediction to decide the most likely result based on what was said in the past. IBM's approach was based on a hidden Markov model, which adds statistics to digital signal processing techniques. The method makes it possible to predict the most likely phonemes to follow a given phoneme. Still each speaker had to individually train the typewriter to recognize his or her voice, and pause between each word.

Birth of smart virtual assistants: 1990s–2010s

In the 1990s, digital speech recognition technology became a feature of the personal computer with IBM, Philips and Lernout & Hauspie fighting for customers. Much later the market launch of the first smartphone IBM Simon in 1994 laid the foundation for smart virtual assistants as we know them today.

In 1997, Dragon's Naturally Speaking software could recognize and transcribe natural human speech without pauses between each word into a document at a rate of 100 words per minute. A version of Naturally Speaking is still available for download and it is still used today, for instance, by many doctors in the US and the UK to document their medical records.

In 2001 Colloquis publicly launched SmarterChild, on platforms like AIM and MSN Messenger. While entirely text-based SmarterChild was able to play games, check the weather, look up facts, and converse with users to an extent.

The first modern digital virtual assistant installed on a smartphone was Siri, which was introduced as a feature of the iPhone 4S on 4 October 2011. Apple Inc. developed Siri following the 2010 acquisition of Siri Inc., a spin-off of SRI International, which is a research institute financed by DARPA and the United States Department of Defense. Its aim was to aid in tasks such as sending a text message, making phone calls, checking the weather or setting up an alarm. Over time, it has developed to provide restaurant recommendations, search the internet, and provide driving directions.

In November 2014, Amazon announced Alexa alongside the Echo.

In April 2017 Amazon released a service for building conversational interfaces for any type of virtual assistant or interface.

Artificial intelligence and language models: 2020s-present

In the 2020s, artificial intelligence (AI) systems like ChatGPT have gained popularity for their ability to generate human-like responses to text-based conversations. In February 2020, Microsoft introduced its Turing Natural Language Generation (T-NLG), which was then the "largest language model ever published at 17 billion parameters." On November 30, 2022, ChatGPT was launched as a prototype and quickly garnered attention for its detailed responses and articulate answers across many domains of knowledge. The advent of ChatGPT and its introduction to the wider public increased interest and competition in the space. In February 2023, Google began introducing an experimental service called "Bard" which is based on its LaMDA AI program to generate text responses to questions asked based on information gathered from the web.

While ChatGPT and other generalized chatbots based on the latest generative AI are capable of performing various tasks associated with virtual assistants, there are also more specialized forms of such technology that are designed to target more specific situations or needs.

Method of interaction

Amazon Echo Dot smart speaker running the Alexa virtual assistant

Virtual assistants work via:

Some virtual assistants are accessible via multiple methods, such as Google Assistant via chat on the Google Allo and Google Messages app and via voice on Google Home smart speakers.

Virtual assistants use natural language processing (NLP) to match user text or voice input to executable commands. Many continually learn using artificial intelligence techniques including machine learning and ambient intelligence. Some of these assistants like Google Assistant (which contains Google Lens) and Samsung Bixby also have the added ability to do image processing to recognize objects in the image to help the users get better results from the clicked images.

To activate a virtual assistant using the voice, a wake word might be used. This is a word or groups of words such as "Hey Siri", "OK Google" or "Hey Google", "Alexa", and "Hey Microsoft". As virtual assistants become more popular, there are increasing legal risks involved.

Devices and objects where found

Apple TV remote control, with which users can ask Siri the virtual assistant to find content to watch

Virtual assistants may be integrated into many types of platforms or, like Amazon Alexa, across several of them:

Services

Virtual assistants can provide a wide variety of services. These include:

  • Provide information such as weather, facts from e.g. Wikipedia or IMDb, set an alarm, make to-do lists and shopping lists
  • Play music from streaming services such as Spotify and Pandora; play radio stations; read audiobooks
  • Play videos, TV shows or movies on televisions, streaming from e.g. Netflix
  • Conversational commerce (see below)
  • Assist public interactions with government (see Artificial intelligence in government)
  • Complement and/or replace human customer service specialists in domains like healthcare, sales, and banking. One report estimated that an automated online assistant produced a 30% decrease in the work-load for a human-provided call centre.
  • In-Car Voice Assistants Interaction with virtual assistants like Siri and Alexa has become common today. It allows people to get more comfortable and have an exceptional driving experience.

Conversational commerce

Conversational commerce is e-commerce via various means of messaging, including via voice assistants but also live chat on e-commerce Web sites, live chat on messaging applications such as WeChat, Facebook Messenger and WhatsApp and chatbots on messaging applications or Web sites.

Customer support

A virtual assistant can work with customer support team of a business to provide 24x7 support to customers. It provides quick responses, which enhances a customer's experience.

Third-party services

Amazon enables Alexa "Skills" and Google "Actions", essentially applications that run on the assistant platforms.

Virtual assistant privacy

Virtual assistants have a variety of privacy concerns associated with them. Features such as activation by voice pose a threat, as such features requires the device to always be listening. Modes of privacy such as the virtual security button have been proposed to create a multilayer authentication for virtual assistants.

Privacy policy of prominent virtual assistants

Google Assistant

The privacy policy of Google Assistant states that it does not store the audio data without the user's permission, but may store the conversation transcripts to personalise its experience. Personalisation can be turned off in settings. If a user wants Google Assistant to store audio data, they can go to Voice & Audio Activity (VAA) and turn on this feature. Audio files are sent to the cloud and used by Google to improve the performance of Google Assistant, but only if the VAA feature is turned on.

Amazon's Alexa

The privacy policy of Amazon's virtual assistant, Alexa, states that it only listens to conversations when its wake word (like Alexa, Amazon, Echo) is used. It starts recording the conversation after the call of a wake word, and stops recording after 8 seconds of silence. It sends the recorded conversation to the cloud. It is possible to delete the recording from the cloud by visiting 'Alexa Privacy' in 'Alexa'.

Apple's Siri

Apple states that it does not record audio to improve Siri. Instead, it uses transcripts. Transcript data is only sent if it is deemed important for analysis. Users can opt out anytime if they don't want Siri to send the transcripts in the cloud.

Presumed and observed interest for the consumer

Presumed added value as allowing a new way of interactions

Added value of the virtual assistants can come among others from the following:

  1. It is convenient: there are some sectors where voice is the only way of possible communication, and more generally, it allows to free-up both hands and vision potentially for doing another activity in parallel, or helps also disabled people.
  2. It is faster: Voice is more efficient than writing on a keyboard: we can speak up to 200 words per minute opposed to 60 in case of writing on a keyboard. It is also more natural thus requiring less effort (reading a text however can reach 700 words per minute).
  • Virtual assistants save a lot of time by automation: they can take appointments, or read the news while the consumer does something else. It is also possible to ask the virtual assistant to schedule meetings, hence helping to organize time. The designers of new digital schedulers explained the ambition they had that these calendars schedule lives to make the consumer use his time more efficiently, through machine learning processes, and complete organization of work time and free time. As an example when the consumer expresses the desire of scheduling a break, the VA will schedule it at an optimal moment for this purpose (for example at a time of the week where they are less productive), with the additional long-term objective of being able to schedule and organize the free time of the consumer, to assure them optimal work efficiency.

Perceived interest

Graphical sum up of the study capturing reasons of interest of virtual assistants for consumers
  • According to a recent study (2019), the two reasons for using virtual assistants for consumers are perceived usefulness and perceived enjoyment. The first result of this study is that both perceived usefulness and perceived enjoyment have an equivalent very strong influence for the consumer willingness to use a virtual assistant.
  • The second result of this study is that:
  1. Provided content quality has a very strong influence on perceived usefulness and a strong influence on perceived enjoyment.
  2. Visual attractiveness has a very strong influence on perceived enjoyment.
  3. Automation has a strong influence on perceived usefulness.

Controversies

Artificial intelligence controversies

  • Virtual assistants spur the filter bubble: As for social media, virtual assistants' algorithms are trained to show pertinent data and discard others based on previous activities of the consumer: The pertinent data is the one which will interest or please the consumer. As a result, they become isolated from data that disagrees with their viewpoints, effectively isolating them into their own intellectual bubble, and reinforcing their opinions. This phenomenon was known to reinforce fake news and echo chambers.
  • Virtual assistants are also sometimes criticized for being overrated. In particular, A. Casilli points out that the AI of virtual assistants are neither intelligent nor artificial for two reasons:
  1. Not intelligent because all they do is being the assistant of the human, and only by doing tasks that a human could do easily, and in a very limited specter of actions: find, class, and present information, offers or documents. Also, virtual assistants are neither able to make decisions on their own nor to anticipate things.
  2. And not artificial because they would be impossible without human labelization through micro working.

Ethics implications

In 2019 Antonio A. Casilli, a French sociologist, criticized artificial intelligence and virtual assistants in particular in the following way:

At a first level the fact that the consumer provides free data for the training and improvement of the virtual assistant, often without knowing it, is ethically disturbing.

But at a second level, it might be even more ethically disturbing to know how these AIs are trained with this data.

This artificial intelligence is trained via neural networks, which require a huge amount of labelled data. However, this data needs to be labelled through a human process, which explains the rise of microwork in the last decade. That is, remotely using some people worldwide doing some repetitive and very simple tasks for a few cents, such as listening to virtual assistant speech data, and writing down what was said. Microwork has been criticized for the job insecurity it causes, and for the total lack of regulation: The average salary was 1,38 dollar/hour in 2010, and it provides neither healthcare nor retirement benefits, sick pay, minimum wage. Hence, virtual assistants and their designers are controversial for spurring job insecurity, and the AIs they propose are still human in the way that they would be impossible without the microwork of millions of human workers.

Privacy concerns are raised by the fact that voice commands are available to the providers of virtual assistants in unencrypted form, and can thus be shared with third parties and be processed in an unauthorized or unexpected manner. Additionally to the linguistic content of recorded speech, a user's manner of expression and voice characteristics can implicitly contain information about his or her biometric identity, personality traits, body shape, physical and mental health condition, sex, gender, moods and emotions, socioeconomic status and geographical origin.

Developer platforms

Notable developer platforms for virtual assistants include:

  • Amazon Lex was opened to developers in April 2017. It involves natural language understanding technology combined with automatic speech recognition and had been introduced in November 2016.
  • Google provides the Actions on Google and Dialogflow platforms for developers to create "Actions" for Google Assistant
  • Apple provides SiriKit for developers to create extensions for Siri
  • IBM's Watson, while sometimes spoken of as a virtual assistant is in fact an entire artificial intelligence platform and community powering some virtual assistants, chatbots. and many other types of solutions.

Previous generations

In previous generations of text chat-based virtual assistants, the assistant was often represented by an avatar (a.k.a. interactive online character or automated character) — this was known as an embodied agent.

Economic relevance

For individuals

Digital experiences enabled by virtual assistants are considered to be among the major recent technological advances and most promising consumer trends. Experts claim that digital experiences will achieve a status-weight comparable to 'real' experiences, if not become more sought-after and prized. The trend is verified by a high number of frequent users and the substantial growth of worldwide user numbers of virtual digital assistants. In mid-2017, the number of frequent users of digital virtual assistants is estimated to be around 1 bn worldwide. In addition, it can be observed that virtual digital assistant technology is no longer restricted to smartphone applications, but present across many industry sectors (incl. automotive, telecommunications, retail, healthcare and education). In response to the significant R&D expenses of firms across all sectors and an increasing implementation of mobile devices, the market for speech recognition technology is predicted to grow at a CAGR of 34.9% globally over the period of 2016 to 2024 and thereby surpass a global market size of US$7.5 billion by 2024. According to an Ovum study, the "native digital assistant installed base" is projected to exceed the world's population by 2021, with 7.5 billion active voice AI–capable devices. According to Ovum, by that time "Google Assistant will dominate the voice AI–capable device market with 23.3% market share, followed by Samsung's Bixby (14.5%), Apple's Siri (13.1%), Amazon's Alexa (3.9%), and Microsoft's Cortana (2.3%)."

Taking into consideration the regional distribution of market leaders, North American companies (e.g. Nuance Communications, IBM, eGain) are expected to dominate the industry over the next years, due to the significant impact of BYOD (Bring Your Own Device) and enterprise mobility business models. Furthermore, the increasing demand for smartphone-assisted platforms are expected to further boost the North American intelligent virtual assistant (IVA) industry growth. Despite its smaller size in comparison to the North American market, the intelligent virtual assistant industry from the Asia-Pacific region, with its main players located in India and China is predicted to grow at an annual growth rate of 40% (above global average) over the 2016–2024 period.

Economic opportunity for enterprises

Virtual assistants should not be only seen as a gadget for individuals, as they could have a real economic utility for enterprises. As an example, a virtual assistant can take the role of an always available assistant with an encyclopedic knowledge. And which can organize meetings, check inventories, verify informations. Virtual assistants are all the more important that their integration in small and middle-sized enterprises often consists in an easy first step through the more global adaptation and use of Internet of Things (IoT). Indeed, IoT technologies are first perceived by small and medium-sized enterprises as technologies of critical importance, but too complicated, risky or costly to be used.

Security

In May 2018, researchers from the University of California, Berkeley, published a paper that showed audio commands undetectable for the human ear could be directly embedded into music or spoken text, thereby manipulating virtual assistants into performing certain actions without the user taking note of it. The researchers made small changes to audio files, which cancelled out the sound patterns that speech recognition systems are meant to detect. These were replaced with sounds that would be interpreted differently by the system and command it to dial phone numbers, open websites or even transfer money. The possibility of this has been known since 2016, and affects devices from Apple, Amazon and Google.

In addition to unintentional actions and voice recording, another security and privacy risk associated with intelligent virtual assistants is malicious voice commands: An attacker who impersonates a user and issues malicious voice commands to, for example, unlock a smart door to gain unauthorized entry to a home or garage or order items online without the user's knowledge. Although some IVAs provide a voice-training feature to prevent such impersonation, it can be difficult for the system to distinguish between similar voices. Thus, a malicious person who is able to access an IVA-enabled device might be able to fool the system into thinking that they are the real owner and carry out criminal or mischievous acts.

Emic and etic

From Wikipedia, the free encyclopedia https://en.wikipedia.org/wiki/Emic_and_etic In anthropology , folk...