Sarvapali (Gopal) Ramchurn is a Professor of Artificial Intelligence, Turing Fellow, and Fellow of the Institution of Engineering and Technology. He is the Director of the UKRI Trustworthy Autonomous Systems hub and Co-Director of the Shell-Southampton Centre for Maritime Futures. He is also a Co-CEO of Empati Ltd, an AI startup working on decentralised green hydrogen technologies. His research is about the design of Responsible Artificial Intelligence for socio-technical applications including energy systems and disaster management. Ferdinando Rodriguez y Baena is Professor of Medical Robotics in the Department of Mechanical Engineering at Imperial College, where he leads the Mechatronics in Medicine Laboratory and the Applied Mechanics Division. He has been the Engineering Co-Director of the Hamlyn Centre, which is part of the Institute of Global Health Innovation, since July 2020.

COVID-19 and its latest omicron strains continue to cause infections across the country as well as globally. Serology (blood) and molecular tests are the two most commonly used methods for rapid COVID-19 testing. Because COVID-19 tests use different mechanisms, they vary significantly. Molecular tests measure the presence of viral SARS-CoV-2 RNA while serology tests detect the presence of antibodies triggered by the SARS-CoV-2 virus. Currently, there is no existing study on the correlation between serology and molecular tests and which COVID-19 symptoms play a key role in producing a positive test result.

Is it possible for artificial intelligence to be conscious? This topic always sparks controversy when academics and professionals debate whether, how, and when AI can regard itself as a person. We, humans, tend to anthropomorphize everything, projecting consciousness onto everything. And, in the case of AI, because of its ability to influence things that are normally human, such as vision and language, society is often driven to assign meaning to the entire experience. In an article for the Economist, cognitive scientist Douglas Hofstadter believes that existing AI is far from comprehending -- and provides numerous examples.

New algorithms allow for a greater level of control in operating rooms and medical centres around the globe. Similarly, self-driving vehicles and city infrastructure will benefit immensely from advanced AI algorithms and machine learning frameworks. AI is now able to understand human emotions to some extent and has the capability to predict human behaviour. For example, some forms of AI can now tell if someone is lying or not. AI can now also be used for social good and in the future maybe even save lives and prevent crimes. Second, they allow us to predict what will happen in the future by using AI to create forecasting models that can tell us about future events or changes in trends. And finally, they help us understand how people behave and react so that we can improve our own behaviour and reactions as well as develop better customer service based on what people want and need. As AI forays into every aspect of human life, it is time for intervention by responsible actions by policymakers as well as industry stakeholders to counter its possible misuse.

Nellore: The conference on Futuristic Nursing being held at Narayana Nursing College here has discussed at length aspects of patient safety as also use of artificial intelligence and tele-medicine, apart from mobile health and sensor-based technologies (smartphones, smartphone apps and wearable technologies). More than 800 nurses are participating in the meet and around 40 eminent nursing leaders across the globe discussing the latest in nursing practices during the 3-day conference from Saturday. In a paper on'Artificial Intelligence in Nursing' presented jointly by Dr Ramesh M.Sc Phd, HoD Medical Surgical Nursing, St Paul's Hospital Millennium Medical College, Ethiopia, and Dr S. Indira, Dean of Narayana Nursing College, said AI offers three advantages over traditional methods -- the ability to quickly consider large volumes of data in risk prediction, increased intervention specificity (accurately flagging patients most at-risk) and automated adjustments in variable selection and calculation. "AI can help detect which patient features are most important in public health applications, allowing for more focused preventive interventions. Robots may aid nursing care tasks in hazardous clinical environments and they have the potential to automate some tasks."

Applications are invited for a research associate position in the Department of Mathematics at Imperial College London to work in the area of statistical machine learning with applications in population health. The overall theme of the research is to develop methods in statistical machine learning to study worldwide phenotypes and transitions in multiple health outcomes. The position is funded through an UKRI Medical Research Council grant which involves collaborative research among statisticians and health researchers at Imperial College as well as with a network of scientists from most of the world's countries, which will give the work significant scientific and policy impact and visibility. The post-holder will be based in the vibrant Statistics section of the Department of Mathematics, which is consistently ranked as one of the top in the country for research and has world-class expertise in statistical machine learning, and will collaborate with the Environment and Global Health Research Group (www.globalenvhealth.org) at Imperial School of Public Health. The project will involve the development of Bayesian hierarchical models to identify multimorbidity clusters and investigate the variation in both magnitude and characteristics of these clusters across and within regions of the world.

In the age of big data, companies track and analyze our buying habits, hobbies and social media accounts to make business decisions. But the impact of big data could have an even greater potential – improving human health. That was the focus of a recent Wellness Education, AI Lifestyle and Health (WEALTH) Symposium in Lake Nona, organized by Dexter Hadley, a College of Medicine physician and big data expert who lead's UCF's Division of Artificial Intelligence. "The UCF College of Medicine is a young school with lots of opportunities and forward thinking," Hadley says. "I want to see the bridging between engineering, AI and medicine."

"Luke, I am your father" are five of the most famous words ever spoken on screen. When Darth Vader shattered Luke Skywalker's world in "The Empire Strikes Back," he sent shivers down the spines of audiences everywhere--in large part because of actor James Earl Jones' famous baritone. Now, Jones, 91, has announced he is hanging up the mask and retiring as the voice of one of the most infamous cinematic villains. But don't despair: Although Jones will no longer record new lines for Star Wars projects, the character--and Jones' voice--will live on thanks to artificial intelligence. As first reported by Vanity Fair, Respeecher, a Ukrainian voice synthesis company, will use a combination of archival recordings, voice acting and AI technology to continue bringing Darth Vader to the screen.

A team of LSU researchers has developed a way to determine which drug therapies work best against an individual's unique type of cancer, possibly providing a way to find cures more quickly and make treatment more affordable. The interdisciplinary team includes researchers from the School of Veterinary Medicine, College of Science, College of Engineering and the Center for Computation & Technology. It created CancerOmicsNet, a new drug discovery engine run by artificial intelligence. Using algorithms originally designed to map complex social networks, like those utilized by Facebook, researchers generated three-dimensional graphs of molecular datasets that include cancer cell lines, drug compounds and interactions among proteins inside the human body. The graphs are then analyzed and interconnected by AI, forming a much clearer picture of how a specific cancer would respond to a specific drug.

More young people than old, and more men than women, are open to artificial intelligence-powered machines replacing people in a variety of jobs, according to the latest Media & Technology Survey from Boston University's College of Communication and Ipsos. By more than 30 percentage points, Americans ages 18 to 34 surveyed were more receptive than those 55 or older when considering AI replacing people working as journalists, hiring managers, trial judges, spiritual advisers or leaders of religious congregations. Respondents ages 35 to 54 were in-between. Men were more receptive than women to AI replacing workers in those jobs by almost 10 percentage points. Still, three out of four respondents across all ages, genders, ethnicities and income groups say having AI replace people in these jobs "doesn't seem like a good idea" or is "definitely a bad idea."