Reviewed by James Ives, M.Psych. (Editor)Apr 22 2019The U.S. Food and Drug Administration today permitted marketing of the first medical device to treat attention deficit hyperactivity disorder (ADHD). The prescription-only device, called the Monarch external Trigeminal Nerve Stimulation (eTNS) System, is indicated for patients ages 7 to12 years old who are not currently taking prescription ADHD medication and is the first non-drug treatment for ADHD granted marketing authorization by the FDA.”This new device offers a safe, non-drug option for treatment of ADHD in pediatric patients through the use of mild nerve stimulation, a first of its kind,” said Carlos Peña, Ph.D., director of the Division of Neurological and Physical Medicine Devices in the FDA’s Center for Devices and Radiological Health. “Today’s action reflects our deep commitment to working with device manufacturers to advance the development of pediatric medical devices so that children have access to innovative, safe and effective medical devices that meet their unique needs.”ADHD is a common disorder that begins in childhood. Symptoms include difficulty staying focused and paying attention, difficulty controlling behavior and very high levels of activity. The diagnosis of ADHD requires a comprehensive evaluation by a health care professional. For a person to receive a diagnosis of ADHD, the symptoms of inattention and/or hyperactivity-impulsivity must be chronic or long-lasting, impair the person’s functioning and cause the person to fall behind normal development for his or her age.The Monarch eTNS System is intended to be used in the home under the supervision of a caregiver. The cell-phone sized device generates a low-level electrical pulse and connects via a wire to a small patch that adheres to a patient’s forehead, just above the eyebrows, and should feel like a tingling sensation on the skin. The system delivers the low-level electrical stimulation to the branches of the trigeminal nerve, which sends therapeutic signals to the parts of the brain thought to be involved in ADHD. While the exact mechanism of eTNS is not yet known, neuroimaging studies have shown that eTNS increases activity in the brain regions that are known to be important in regulating attention, emotion and behavior.The stimulation should feel like a tingling sensation on the skin, and the device should be used in the home under the supervision of a caregiver during periods of sleep. Clinical trials suggest that a response to eTNS may take up to 4 weeks to become evident. Patients should consult with their health care professional after four weeks of use to assess treatment effects.Related StoriesNew study reveals ‘clutch’ proteins responsible for putting T cell activation ‘into gear’New therapy shows promise in preventing brain damage after traumatic brain injuryNew network for children and youth with special health care needs seeks to improve systems of careThe Monarch eTNS System’s efficacy in treating ADHD was shown in a clinical trial that compared eTNS as the sole treatment, or monotherapy, to a placebo device. A total of 62 children with moderate to severe ADHD were enrolled in the trial and used either the eTNS therapy each night or a placebo device at home for four weeks. The trial’s primary endpoint was improvement on a clinician-administered ADHD Rating Scale, ADHD-RS. ADHD-RS scales are used to monitor severity and frequency of ADHD symptoms. A higher score is indicative of worsening symptoms. The ADHD-RS uses questions about the patient’s behavior, such as whether they have difficulty paying attention or regularly interrupt others. The trial showed that subjects using the eTNS device had statistically significant improvement in their ADHD symptoms compared with the placebo group. At the end of week four, the average ADHD-RS score in the active group decreased from 34.1 points at baseline to 23.4 points, versus a decrease from 33.7 to 27.5 points in the placebo group.The most common side effects observed with eTNS use are: drowsiness, an increase in appetite, trouble sleeping, teeth clenching, headache and fatigue. No serious adverse events were associated with use of the device.The Monarch eTNS System should not be used in children under seven years of age. It should not be used in patients with an active implantable pacemaker or with active implantable neurostimulators. Patients with body-worn devices such as insulin pumps should not use this device. The eTNS System should not be used in the presence of radio frequency energy such as magnetic resonance imaging (MRI), because it has not been tested in an MRI machine, or cell phones, because the phone’s low levels of electromagnetic energy may interrupt the therapy.The FDA reviewed the Monarch eTNS System through the de novo premarket review pathway, a regulatory pathway for low- to moderate-risk devices of a new type. This action creates a new regulatory classification, which means that subsequent devices of the same type with the same intended use may go through the FDA’s 510(k) premarket process, whereby devices can obtain marketing authorization by demonstrating substantial equivalence to a predicate device.The FDA granted marketing authorization of the Monarch eTNS System to NeuroSigma. Source:https://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm636379.htm
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This article was originally published on The Conversation. Read the original article. “Whatever your job is the chances are that one of these machines can do it faster or better than you can.” Explore further Artificial intelligence is growing up fast—what’s next for thinking machines? Hype cycle for emerging technologies. Credit: Gartner Research Human-machine cognitive partnerships can amplify what each partner does best: humans are great at making intuitive and creative decisions based on knowledge while computers are good at sifting through large amounts of data to produce information that will feed into human knowledge and decision making. We use this combination of narrow AI and human unique cognitive and motor skills every day, often without realising it. A few examples:Using Internet search engines to find content (videos, images, articles) that will be helpful in preparing for a school assignment. Then combining them in creative ways in a multimedia slide presentation. Using a translation algorithm to produce a first draft of a document in a different language, then manually improving the style and grammar of the final document.Driving a car to an unknown destination using a smartphone GPS application to navigate through alternative routes based on real-time traffic information;Relying on a movie-streaming platform to shortlist films you are going to appreciate based on your recent history; making the final choice based on mood, social context, serendipity.Netflix is a great example of this collaboration at its best. By using machine-learning algorithms to analyse how often and how long people watch their content, they can determine how engaging each story component is to certain audiences. This information is used by screenwriters, producers and directors to better understand what and how to create new content. Virtual-reality technology allows content creators to experiment with different storytelling perspectives before they ever shoot a single scene. Likewise, architects can rely on computers to adjust the functional aspects of their work. Software engineers can focus on the overall systems structure while machines provide ready-to-use code snippets and libraries to speed up the process. Marketers rely on big data and visualisation tools to determine how to better understand customer needs and develop better products and services. None of these tasks could be accomplished by AI without human guidance. Conversely, human creativity and productivity have been enormously leveraged by this AI support, allowing to achieve better quality solutions at lower costs.Losses and gainsAs innovation accelerates, thousands of jobs will disappear, just as it has happened in the previous cycles of industrial revolutions. Machines powered by narrow AI algorithms can already perform certain 3-D tasks (“dull, dirty and dangerous”) much better than humans. This may create enormous pain for those who are losing their jobs over the next few years, particularly if they don’t acquire the computer-related skills that would enable them to find more creative opportunities. We must learn from the previous waves of creative destruction if we are to mitigate human suffering and increasing inequality. For example, some statistics indicate that as much as 3% of the population in developed countries work as drivers. When automated cars become a reality in the next 15 to 25 years, we must offer people who will be “structurally unemployed” some sort of compensation income, training and re-positioning opportunities.Fortunately, the Schumpeterian waves of destructive innovation also create jobs. History has shown that disruptive innovations are not always a zero-sum game. On the long run, the loss of low-added-value jobs to machines can have a positive impact in the overall quality of life of most workers. The ATM paradox is a good example of this. As the use of automatic teller machines spread in the 1980s and ’90s, many predicted massive unemployment in the banking sector. Instead, ATMs created more jobs as the cost of opening new agencies decreased. The number of agencies multiplied, as did the portfolio of banking products. Thanks to automation, going to the bank offers a much better customer experience than in previous decades. And the jobs in the industry became better paid and were of better quality. A similar phenomenon happened with the textile industry in the 19th century. Better human-machine coordination leveraged productivity and created customer value, increasing the overall market size and creating new employment opportunities. Likewise, we may predict that as low-quality jobs continue to disappear, AI-assisted jobs will emerge to fulfil the increasing demand for more productive, ecological and creative products. More productivity may mean shorter work weeks and more time for family and entertainment, which may lead to more sustainable forms of value creation and, ultimately, more jobs. Adapting to the futureThis optimist scenario assumes, however, that education systems will do a better job of preparing our children to become good at what humans do best: creative and critical thinking. Less learning-by-heart (after all, most information is one Google search away) and more learning-by-doing. Fewer clerical skills and more philosophical insights about human nature and how to cater to its infinite needs for art and culture. As Apple founder and CEO Steve Jobs famously said, “What made the Macintosh great was that the people working on it were musicians and poets and artists and zoologists and historians who also happened to be the best computer scientists in the world.” To become creative and critical thinkers, our children will need knowledge and wisdom more than raw data points. They need to ask “why?”, “how?” and “what if?” more often than “what?”, who?” and “when?” And they must construct this knowledge by relying on databases as cognitive partners as soon as they learn how to read and write. Constructivist methods such as the “flipped classroom” approach are a good step in that direction. In flipped classrooms, students are told to search for specific contents on the web at home and to come to class ready to apply what they learned in a collaborative project supervised by the teacher. Thus they do their “homework” (exercise) in class and they have web “lectures” at home, optimising class time to do what computers cannot help them to do: create, develop and apply complex ideas collaboratively with their peers.Thus, the future of human-machine collaboration looks less like the scenario in the Terminator movies and more like a Minority Report-style of “augmented intelligence”. There will be jobs if we adapt the education system to equip our children to do what humans are good at: to think critically and creatively, to develop knowledge and wisdom, to appreciate and create beautiful works of art. That does not mean it will be a painless transition. Machines and automation will likely take away millions of low-quality jobs as it has happened in the past. But better-quality jobs will likely replace them, requiring less physical effort and shorter hours to deliver better results. At least until artificial general intelligence becomes a reality – then all bets are off. But this will likely be our great-grandchildren’s problem. Provided by The Conversation Citation: No, artificial intelligence won’t steal your children’s jobs—it will make them more creative and productive (2018, February 14) retrieved 18 July 2019 from https://phys.org/news/2018-02-artificial-intelligence-wont-children-jobsitwill.html This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only. No, this is not a 2018 headline about self-driving cars or one of IBM’s new supercomputers. Instead, it was published by the Daily Mirror in 1955, when a computer took as much space as a large kitchen and had less power than a pocket calculator. They were called “electronic brains” back then, and evoked both hope and fear. And more than 20 years later, little had changed: In a 1978 BBC documentary about silicon chips, one commentator argued that “They are the reason why Japan is abandoning its shipbuilding and why our children will grow up without jobs to go to”.Artificial intelligence hype is not newIf one types “artificial intelligence” (AI) on Google Books’ Ngram Viewer – a tool that allows us to check how often a term was printed in a book between 1800 and 2008 – we can clearly see that our modern-day hype, optimism and deep concern about AI are by no means a novelty.The history of AI is a long series of booms and busts. The first “AI spring” took place between 1956 and 1974, with pioneers such as the young Marvin Minsky. This was followed by the “first AI winter” (1974-1980), when disillusion with the gap between machine learning and human cognitive capacities first led to disinvestment and disinterest in the topic. A second boom (1980-1987) was followed by another “winter” (1987-2001). Since the 2000s we’ve been surfing the third “AI spring”.There’s plenty of reasons to believe this latest wave of interest for AI is going to be more durable. According to Gartner Research, technologies typically go from a “peak of inflated expectations” through a “trough of disillusionment” until they finally reach a “plateau of productivity”. AI-intensive technologies such as virtual assistants, the Internet of Things, smart robots and augmented data discovery are about to reach the peak. Deep learning, machine learning and cognitive expert advisors are expected to reach the plateau of mainstream applications in two to five years. We finally seem to have enough computing power to credibly develop what is called “narrow AI”, of which all the aforementioned technologies are an example. These are not to be confused with “artificial general intelligence” (AGI), which scientist and futurologist Ray Kurzweil called “strong AI”. Some of the most advanced AI systems to date, such as IBM’s Watson supercomputer or Google’s AlphaGo, are examples of narrow AI. They can be trained to perform complex tasks such as identifying cancerous skin patterns or playing the ancient Chinese strategy game of Go. They are very far, however, from being capable to do everyday general intelligence tasks such as gardening, arguing or inventing a children’s story. The cautionary prophecies of visionaries like Elon Musk, Bill Gates and Stephen Hawking against AI really are meant as an early warning against the dangers of AGI, but that is not something our children will be confronted with. Their immediate partners will be of the narrow AI kind. The future of labour depends on how well we equip them to use computers as cognitive partners .Better togetherGarry Kasparov – the chess grandmaster who was defeated by IBM’s Deep Blue computer in 1997 – calls this human-machine cooperation “augmented intelligence”. He compares this “augmentation” to the mythic image of a centaur: combine a quadruped’s horsepower with the intuition of a human mind. To illustrate the potential of centaurs, he describes a freestyle chess tournament in 2005 in which any combination of human-machine teams was possible. In his words:”The winner was revealed to be not a grandmaster with a state-of-the-art PC but a pair of amateur American chess players using three computers at the same time. Their skill at manipulating and ‘coaching’ their computers to look very deeply into positions effectively counteracted the superior chess understanding of their grand-master opponents and the greater computational power of other participants. Weak human + machine + better process was superior to a strong computer alone and, more remarkably, superior to a strong human + machine + inferior process. Human strategic guidance combined with the tactical acuity of a computer was overwhelming.” Searches for the term ‘artificial intelligence’ on Google Books’ Ngram viewer.
Citation: Tech giants vow to double number of women managers by 2022 (2019, May 15) retrieved 17 July 2019 from https://phys.org/news/2019-05-tech-giants-vow-women.html Forty-five tech giants committed Wednesday to doubling the number of women on their management boards to 30 percent by 2022, the French presidency said. © 2019 AFP Explore further High-profile global companies including IBM pledged to boost the number of female executives from 15 percent to 30 percent Macron presses tech giants on taxes, working conditions Alibaba, BNP Paribas, Booking.com, IBM, L’Oreal and Uber were some of the high-profile companies to sign a pledge at the second “Tech for good” summit taking place in Paris.Businesses that reach the goal are then to pursue complete parity including on executive committees, the Elysee palace said in a statement.A recent tech-sector study by the consulting firm McKinsey & Company showed that women occupied just 15 percent of management posts at present, it added.The “Tech for good” summit aims to encourage global tech leaders to think about how new technologies can contribute to the common good, in areas such as education and health.The initiative is the brainchild of French President Emmanuel Macron who was scheduled to dine with 180 leaders of digital companies including Jack Ma of Alibaba, and Ken Hu of Huawei on Wednesday evening.He was also due to individual meetings with IBM boss Virginia Rometty and Dara Khosrowshahi of Uber. This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.