The role of uncertainty and affect in decision-making on the adoption of AI-based contact-tracing technology during the COVID-19 pandemic

Transformative Potential of AI in Healthcare: Definitions, Applications, and Navigating the Ethical Landscape and Public Perspectives

Artificial intelligence (AI) has emerged as a crucial tool in healthcare with the primary aim of improving patient outcomes and optimizing healthcare delivery. By harnessing machine learning algorithms, natural language processing, and computer vision, AI enables the analysis of complex medical data. The integration of AI into healthcare systems aims to support clinicians, personalize patient care, and enhance population health, all while addressing the challenges posed by rising costs and limited resources. As a subdivision of computer science, AI focuses on the development of advanced algorithms capable of performing complex tasks that were once reliant on human intelligence. The ultimate goal is to achieve human-level performance with improved efficiency and accuracy in problem-solving and task execution, thereby reducing the need for human intervention. Various industries, including engineering, media/entertainment, finance, and education, have already reaped significant benefits by incorporating AI systems into their operations. Notably, the healthcare sector has witnessed rapid growth in the utilization of AI technology. Nevertheless, there remains untapped potential for AI to truly revolutionize the industry. It is important to note that despite concerns about job displacement, AI in healthcare should not be viewed as a threat to human workers. Instead, AI systems are designed to augment and support healthcare professionals, freeing up their time to focus on more complex and critical tasks. By automating routine and repetitive tasks, AI can alleviate the burden on healthcare professionals, allowing them to dedicate more attention to patient care and meaningful interactions. However, legal and ethical challenges must be addressed when embracing AI technology in medicine, alongside comprehensive public education to ensure widespread acceptance.

Prospective mixed-methods study evaluating the potential of a voicebot (CovBot) to relieve German health authorities during the COVID-19 infodemic

Background

During the COVID-19 pandemic, telephone hotlines of local health authorities in Germany were overloaded due to information requests by the public.

Objective

Evaluating the use of a COVID-19-specific voicebot (CovBot) in local health authorities in Germany during the COVID-19 pandemic. This study investigates the performance of the CovBot by assessing a perceptible relief of staff in the hotline service.

Methods

This prospective mixed-methods study enrolled local health authorities in Germany from 01 February 2021 to 11 February 2022 to deploy the CovBot, which was mainly designed to answer frequently asked questions. To capture the user perspective and acceptance, we performed semistructured interviews and online surveys with their staff, conducted an online survey among callers, and analyzed the performance metrics of the CovBot.

Results

The CovBot was implemented in 20 local health authorities serving 6.1 million German citizens and processed almost 1.2 million calls during the study period. The overall assessment was that the CovBot contributed to a perceived relief of the hotline service. In a survey among callers, 79% indicated that a voicebot could not replace a human. The analyzed anonymous metadata revealed that 15% of calls hung up immediately, 32% after hearing an FAQ answer, and 51% of calls were forwarded to the local health authority offices.

Conclusions

A voicebot primarily answering FAQs can provide additional support to relieve the hotline service of local health authorities in Germany during the COVID-19 pandemic. For complex concerns, a forwarding option to a human proved to be an essential functionality.