Tuesday November 19, 2019
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Social Robots Can Now be Conflict Mediators: Study

The study also found that the teams did respond socially to the virtual agent during the planning of the mission they were assigned (nodding, smiling and recognising the virtual agent's input by thanking it) but the longer the exercise progressed, their engagement with the virtual agent decreased

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Artificial Intelligence Bot
Artificial Intelligence Bot. Pixabay

We may listen to facts from Siri or Alexa, or directions from Google Maps, but would we let a virtual agent enabled by artificial intelligence help mediate conflict among team members? A new study says they might help.

The study was presented at the 28th IEEE International Conference on Robot & Human Interactive Communication in the national capital on Tuesday.

“Our results show that virtual agents and potentially social robots might be a good conflict mediator in all kinds of teams. It will be very interesting to find out the interventions and social responses to ultimately seamlessly integrate virtual agents in human teams to make them perform better,” said study lead author Kerstin Haring, Assistant Professor at the University of Denver.

Researchers from the University of Southern California (USC) and the University of Denver created a simulation in which a three-person team was supported by a virtual agent ‘Avatar’ on screen in a mission that was designed to ensure failure and elicit conflict.

The study was designed to look at virtual agents as potential mediators to improve team collaboration during conflict mediation.

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“We’re beginning to see the first instances of artificial intelligence operating as a mediator between humans, but it’s a question of: ‘Do people want that?” Pixabay

While some of the researchers had previously found that one-on-one human interactions with a virtual agent therapist yielded more confessions, in this study, team members were less likely to engage with a male virtual agent named ‘Chris’ when conflict arose.

Participating members of the team did not physically accost the device, but rather were less engaged and less likely to listen to the virtual agent’s input once failure ensued among team members.

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The study was conducted in a military academy environment in which 27 scenarios were engineered to test how the team that included a virtual agent would react to failure and the ensuing conflict.

The virtual agent was not ignored by any means.

The study also found that the teams did respond socially to the virtual agent during the planning of the mission they were assigned (nodding, smiling and recognising the virtual agent’s input by thanking it) but the longer the exercise progressed, their engagement with the virtual agent decreased. (IANS)

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This AI Tool Can Predict Mortality Of Heart Failure Patients

Researchers develop a tool that can predict mortality of heart failure patients

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This artificial intelligence (AI) tool can predict life expectancy in heart failure patients. Pixabay

Researchers have developed an artificial intelligence (AI) tool to predict life expectancy in heart failure patients.

The machine learning algorithm based on de-identified electronic health, records data of 5,822 hospitalised or ambulatory patients with heart failure at UC San Diego Health in the US.

“We wanted to develop a tool that predicted life expectancy in heart failure patients, there are apps where algorithms are finding out all kinds of things, like products you want to purchase,” said Avi Yagil, Professor at University of California.

“We needed a similar tool to make medical decisions. Predicting mortality is important in patients with heart failure. Current strategies for predicting risk, however, are only modestly successful and can be subjective,” Yagil added.

From this model, a risk score was derived that determined low and high risk of death by identifying eight readily available variables collected for the majority of patients with heart failure:Diastolic blood pressure, Creatinine, Blood urea nitrogen, White blood cell count, Platelets, Albumin and Red blood cell distribution.

Yagil said the newly developed model was able to accurately predict life expectancy 88 per cent of the time and performed substantially better than other popular published models.

“This tool gives us insight, for example, on the probability that a given patient will die from heart failure in the next three months or a year,” said researcher Eric Adler.

Heart failure patients
The mortality of a heart failure patient can be predicted. Pixabay

“This is incredibly valuable. It allows us to make informed decisions based on a proven methodology and not have to look into a crystal ball,” he added.

The tool was additionally tested using de-identified patient data from the University of California San Francisco and a data base derived from 11 European medical centers.

“It was successful in those cohorts as well,” said Yagil.

“Being able to repurpose our findings in independent populations is of utmost importance, thus validating our methodology and its results,” Yagil added.

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Researchers said the partnership between physicists and cardiologists was critical to developing a reliable tool and extensive knowledge and experiences from both sides proved synergetic.

The study was published in the European Journal of Heart Failure. (IANS)