"Cognitive science is the interdisciplinary study of mind and intelligence, embracing philosophy, psychology, artificial intelligence, neuroscience, linguistics, and anthropology. Its intellectual origins are in the mid-1950s when researchers in several fields began to develop theories of mind based on complex representations and computational procedures."
– Paul Thagard. Cognitive Science , in The Stanford Encyclopedia of Philosophy.
The global affective computing market is envisioned to create high growth prospects on the back of the rising deployment of machine and human interaction technologies. With enabling technologies already making a mark with their adoption in a range of industry verticals, it could be said that the market has started to evolve. Facial feature extraction software collecting a handsome demand in the recent years is expected to augur well for the growth of the deployment of cameras in affective computing systems. Detection of psychological disorders, facial expression recognition for dyslexia, autism, and other disorders in specially-abled children, and various other applications could increase the use of affective computing technology. Life sciences and healthcare are prognosticated to showcase a promising rise in the demand for affective computing.
Over the past few decades, technology-based innovations have added a new meaning to business conversations, thus changing the way we live and work in the digital age. With increased focus on improving business agility and performance, to sail through the challenging age of digital transformation, it is in the interest of modern businesses to leverage these cutting-edge technologies to maximize operational efficiencies and sustain profitability. The journey so far and how new technologies will impact key verticals in the coming years. The age of transformation will witness the emergence of varied possibilities and use-cases with the intermingling of new age technologies like Artificial Intelligence, IoT, automation and analytics. While Artificial Intelligence has many use cases, practically in every field, we would see that the best end-to-end application of Artificial Intelligence will happen in conjunction with automation.
Speaking on Computational Semiotics and Artificial Intelligence at conference on Semantics, Semiotics and Truth Function organized by Department of Philosophy, Loyola College and Chennai Philosophical Forum ...on how knowledge representation inspired by cognitive sciences can enrich the field of AI by synthesizing data driven AI, 'connectionist' deep learning and symbolic AI to improve explainability and transparency. I drew inspiration from multiple sources of research already conducted on the confluence of cognitive sciences, semiotics and Artificial Intelligence: 1.
And one such unknown today is artificial intelligence. Is it right to be afraid of AI? Or is this just an irrational fear of the unknown? To make artificial intelligence more understandable to its workforce, the Air Force Research Laboratory Materials and Manufacturing Directorate recently invited Dr. Erick Brethenoux to explain how it all works and how we all can expect to benefit from it in the future. Brethenoux specializes in machine learning, artificial intelligence and applied cognitive computing on the AI team at Gartner Inc., a consulting firm AFRL information technology uses for help with its mission-critical priorities. To begin his talk, Brethenoux reassured his audience that artificial intelligence doesn't really exist.
In the early 1980s, the psychologist Harry Heft put a 16 mm camera in the back of a sports car and made a movie. It consisted of a continuous shot of a residential neighborhood in Granville, Ohio, where Heft was a professor at Denison University. It didn't have a plot or actors, but it did have a simple narrative: The car started moving at 5 miles per hour and made nine turns from one street to another and then came to a stop after traveling just under a mile. One showed just the vistas along the route, the expansive layout of environmental features, such as a group of houses or trees seen from a distance. The second film showed the transitions of the route, the parts between each vista where the view is occluded by, say, a turn in the road or the crest of a hill.
In its annual report, the AI Now Institute, an interdisciplinary research center studying the societal implications of artificial intelligence, called for a ban on technology designed to recognize people's emotions in certain cases. Specifically, the researchers said affect recognition technology, also called emotion recognition technology, should not be used in decisions that "impact people's lives and access to opportunities," such as hiring decisions or pain assessments, because it is not sufficiently accurate and can lead to biased decisions. What is this technology, which is already being used and marketed, and why is it raising concerns? Researchers have been actively working on computer vision algorithms that can determine the emotions and intent of humans, along with making other inferences, for at least a decade. Facial expression analysis has been around since at least 2003.
Transformation is defined by a change in state over a period of time. This is often an ongoing, natural process. For example, as humans we spend our entire lives constantly transforming, both physically and mentally, whether that's growing taller and stronger, or developing emotional intelligence. But sometimes transformation is a necessity, often resulting from the need to adapt to new circumstances. However, regardless of circumstance, transformation can never be instantaneous, and digital transformation for businesses is no exception.
Credit: Jana Dünnhaupt/University of Magdeburg Computer scientists at Otto von Guericke University Magdeburg are aiming to use the findings and established methods of brain research to better understand the way in which artificial intelligence works. As part of a research project, the scientists led by Professor Dr.-Ing. Sebastian Stober from the Artificial Intelligence Lab at the University of Magdeburg will apply methods from cognitive neuroscience to analyze artificial neural networks and better understand the way they work.
When it comes to digital transformation, humans--believe it or not--play an integral role. In fact, companies that make strong use of the combined human/machine workforce have a far greater chance of success in digital transformation. Accenture calls these combined people/bot workspaces "future systems" – systems that seamlessly integrate humans and robots to create business goals that are limitless, agile, and "radically human." I consider the companies that harness the power of humans and machines will be the ultimate winners of the future of work. The good news: these systems are already happening.