A recording of a cough, the noise of a person’s breathing or even the sound of their voice could be used to help diagnose patients with Covid-19 in the future, according to Professor Cecilia Mascolo, co-director of the centre for mobile, wearable systems and augmented intelligence at the University of Cambridge, UK.
Prof. Mascolo has developed a sound-collecting app to help train machine learning algorithms to detect the tell-tale sounds of coronavirus infection. Created as part of a project called EAR, she hopes it might eventually lead to new ways of diagnosing respiratory diseases and help in the global fight against coronavirus.
Why should robots have artificial social intelligence? According to Heather Knight, assistant professor of computer science, if robots are going to help in hospitals or work with people in factories, they will need to be adapted to our social conventions.
In work presented at AAAI-20 researchers from National University of Singapore, Carnegie Mellon University, and KAIST described their approach for anomaly detection in time-evolving graphs. In this interview Siddharth Bhatia tells us about their methodology, why research into anomaly detection is crucial, and plans for future studies.
It will take many different approaches to repair these systems. Given my area of expertise and my research focus, I am interested in the role that Artificial Intelligence (AI) might play in bolstering the continent’s health systems.
A major international consultancy firm identified ‘AI ethicist’ as an essential position for companies wanting to successfully integrate artificial intelligence into their business. It declared that AI ethicists are needed to help companies navigate the ethical and social issues raised by the use of AI .
Can we trust artificial intelligence to make good decisions? The answer is a resounding, maybe. More and more, society and individuals are entrusting AI to make potentially life-changing decisions. Rather than putting blind trust in the judgement of these remarkable systems, Professor Alan Fern and a team of computer scientists want to reveal their reasoning processes.
The AIhub coffee corner captures the musings of AI experts over a 30-minute conversation. This edition focusses on the state of the AI research landscape amid claims from some quarters that we are on the cusp of another “AI winter”. Our seven experts discuss the historical context to these claims, their feelings about the position of AI research now, and their expectations for the near future.
The outbreak of COVID-19 has seen disruption and cancellation of a number of scientific conferences. One of the biggest casualties was the APS March meeting, the world’s largest physics conference, with organisers making the difficult decision to call the event off less than 36 hours before the scientific sessions were due to start. Elsewhere, the ICLR (International Conference on Learning Representations), scheduled for April, has made the decision to go fully virtual. Could the trial of online solutions, albeit under unfortunate circumstances, herald the start of a new conference era?