Penn State researchers report that users respond differently when AIs either offer to help the user, or ask for help from the user. Developers may want.
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UNIVERSITY PARK, Pa. As the use of artificial intelligence (AI) in health applications grows, health providers are looking for ways to improve patients experience with their machine doctors.
Researchers from Penn State and University of California, Santa Barbara (UCSB) found that people may be less likely to take health advice from an AI doctor when the robot knows their name and medical history. On the other hand, patients want to be on a first-name basis with their human doctors.
When the AI doctor used the first name of the patients and referred to their medical history in the conversation, study participants were more likely to consider an AI health chatbot intrusive and also less likely to heed the AI s medical advice, the researchers added. However, they expected human doctors to differentiate them from other patients and were less likely to comply when a human doctor failed to remember their information.
Consumers decision to buy a product is based on its recommendation online: Study
Penn State University researchers suggested that it s not just what is recommended, but how and why it s recommended, that helps to shape consumers opinions.
As more people go online for shopping, understanding how they rely on e-commerce recommendation systems to make purchases is increasingly important. Penn State University researchers suggested that it s not just what is recommended, but how and why it s recommended, that helps to shape consumers opinions.
Through the study published in the Journal of Advertising, the researchers investigated how people reacted to two product recommendation systems. The first system generated recommendations based on the user s earlier purchases often referred to as content-based recommendation systems.
A new research center at Penn State, the Center for Artificial Intelligence Foundations and Scientific Applications, or CENSAI, will unite Penn State researchers to explore the use of artificial intelligence (AI) as a tool to investigate key steps in the scientific process. CENSAI is part of Penn State’s Institute for Computational and Data Sciences, and it includes faculty from across Penn State.
Penn State Institute for Computational and Data Sciences
“The emergence of big data and advances in machine learning have dramatically accelerated some of the key steps in science. However, many key elements of the scientific process remain largely untouched and untamed by artificial intelligence,” said Honavar. “We believe that we can dramatically accelerate scientific progress, potentially by several orders of magnitude, in some disciplines, by effectively addressing these bottlenecks.”
Consumers buy product based on its recommendations
ANI
04 May 2021, 14:55 GMT+10
Washington [US], May 4 (ANI): As more people go online for shopping, understanding how they rely on e-commerce recommendation systems to make purchases is increasingly important. Penn State University researchers suggested that it s not just what is recommended, but how and why it s recommended, that helps to shape consumers opinions.
Through the study published in the Journal of Advertising, the researchers investigated how people reacted to two product recommendation systems. The first system generated recommendations based on the user s earlier purchases often referred to as content-based recommendation systems.
The second provided recommendations based on what other people bought called collaborative recommendation systems.