The great race in Artificial Intelligence (AI) is now a global reality and Canada is intensifying its commitment and investment with the Pan-Canadian Artificial Intelligence Strategy, with over 100 million Canadian dollars destined for the new generation of technology and computer skills... At the end of 2018, the representatives of the Canadian government gathered in Montreal together with the other G7 leaders and 150 participants selected from experts and "opinion leaders" from the economic, academic, institutional and research world, to explore the potential and possible impact of machine learning on the global economy. According to a 2018 report from the McKinsey Global Institute, machine learning will have a huge influence on the future global economy, bringing the potential annual GDP growth to over 1%, with the forecast of an increase of 13 trillion dollars in the volume of global economic activity by 2030. Both the government and industry are investing significant amounts in companies and research centres that are paving the way for the development of new talent and pioneering studies in the field of artificial intelligence. Manulife has donated nearly half a million dollars to the University of Waterloo for its cutting-edge artificial intelligence research, while Samsung has partnered with the University of Montreal and McGill, to set up an artificial intelligence centre in Montreal, the fourth of its kind in North America. According to Peter van Beek, Co-director of the Waterloo AI Institute at the University of Waterloo, "There is a huge global interest in artificial intelligence and many countries are making major financial investments, including Canada. It is a necessary step to safeguard our talents and our intellectual property".
The opening of the Samsung Electronics Artificial Intelligence Center in Montreal (news.samsung.com)
The social benefits of Artificial Intelligence
Peter van Beek, who has worked in the AI field for thirty years, recognises that ensuring Artificial Intelligence is socially responsible poses challenges. At the same time, he also thinks that Artificial Intelligence could be an great source of benefit for society. For example, researchers at the University of Waterloo were able to use the potential of machine learning to help experts share data and information on fires. Change is also taking place in the pharmaceutical research sector, where Artificial Intelligence is contributing to testing new drugs. "When testing different combinations of drugs, many of them fail and Artificial Intelligence is a way to speed up this process, because it can help predict which of these approaches will be most likely to succeed” says van Beek. In addition to scientific committees and university campuses, machine learning is increasingly also being applied in primary and secondary schools. Chinese schools have begun to use robots to automate assessment processes, while Harlem children can learn to programme thanks to Code Next, the result of a collaboration between the MIT Media Lab and Google to spread computing to disadvantaged communities.
MIT and Google introduce students to Coding and Maker Technologies (media.mit.edu)
Robots and autism
According to data from the World Health Organization (WHO) about one child in 60 has an autism spectrum disorder (ASD) and males are four times more likely to be diagnosed than females. Therapies, specialised learning and other educational resources are all expensive. An interesting solution from RoboKind, the company that created Milo, is a humanoid robot. Robotherapy is useful for therapists and teachers in helping autistic children on their learning journey to understanding emotions and social interaction. Milo speaks more slowly than humans and is able to work with therapists to help autistic children through a series of learning modules, accompanied by videos and visual aids on the robot's chest. According to Gregory Firn, RoboKind Operations Manager, "We estimate that up to 50% of students working with Milo experience positive changes during their first three months, especially in relation to self-control and learning how to manage their own behaviour”. By helping to chart a new route for assisting autistic children, Milo demonstrates the extraordinary potential of artificial intelligence in education. Robotherapy, used in 35 US states and four Canadian provinces, is helping to assist thousands of students in North America.
Milo never gets tired and is always consistent, important when teaching through repetition.
The fight against illiteracy
Artificial Intelligence is also paving the way for new forms of support for child literacy problems. The National Assessment of Adult Literacy reports that nearly 100 million Americans have literacy difficulties. Adults with literacy problems are more likely to earn less and suffer from low self-esteem and, above all, are more likely to have children with literacy problems. Costs related to unemployment and health due to low literacy levels total more than 400 billion dollars. Learning Ovations aims to change this. It is a detailed computer software that assesses students' reading ability and develops a personalised assistance programmes for children. By helping teachers in the analysis and assessment phase, Learning Ovations provides useful educational information to promote literacy in the classroom through the computerised collection of intelligent data.
The results of special education with A2i.
They cannot replace the importance of human interaction
According to Firn, "Robots can guide, facilitate and ultimately assess learning, but they cannot replace the role, judgement and importance of human interaction. Creating and constructing meanings are exclusively human activities". Machine Learning and new information technologies are demonstrating how Artificial Intelligence's numerous application opportunities have a huge impact on economics. A potential that is limited solely by our level of competence and the opportunities we are able to create to extend the boundaries of what we can do with technology.
The Intelligence that "reads us"
By rapidly detecting eye movement, Artificial Intelligence can now determine an individual’s personality. In a study, published by the Frontiers in Human Neuroscience journal, researchers traced the eye movement of 42 people engaged in daily activities. Using Artificial Intelligence, scientists were able to identify the main personality traits such as neuroticism, extroversion, pleasantness and conscientiousness. Fascinating research that show that in recent years the interest of research for the use of automatic learning, in order to distinguish personality traits and anticipate behaviours, has increased considerably. In another study, published in Vision Research in 2015, scientists were able to determine the degree of an individual's curiosity from answers to a series of general culture questions, using instruments to trace eye movements. However, this and other similar studies have been conducted exclusively in the laboratory and there is a narrow field of application in real life. To manage that possible limitation, the same subjects were asked to perform simple activities outside the laboratory. Participants were equipped with special devices, capable of tracking eye movements, and were asked to walk around the campus for around 10 minutes and purchase something in the campus shop. The scientists assessed the individual’s personality by giving them basic psychological questionnaires. From this investigative activity, it was possible to work out which personality traits were linked to specific eye movements, based on information such as blinking duration and frequency. Artificial Intelligence was then able to correctly predict the personality traits of subjects simply by looking them in the eye. According to the study carried out, further research will be needed to establish whether the results obtained can be replicated on other sample populations and to see if the ability to predict personality traits through Artificial Intelligence is influenced in any way by factors such as mood or fatigue.
Following the wearer's eye movements and identifying what they are looking at.
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