The past few years have seen significant advancements in information technologies such as artificial intelligence, and the adaptation of such technologies were only further necessitated and accelerated as a result of the coronavirus pandemic. Applications for artificial intelligence technology are no longer exclusive to the tech industry, and today there are an increasing number of new products and use cases that allow businesses to leverage the wealth of digital insights the technology can provide. The insurance industry is no exception to this. Those developing the technology have identified solutions to some of the most common pain points, and by embracing artificial intelligence, insurance providers large and small have the ability to create new efficiencies in their operations. From automating form-filling processes to assessing vehicle damage, artificial intelligence has the ability to help organizations dramatically reduce costs and time.

Data security is currently more essential than any other time in recent memory. The present cybersecurity threats are unimaginably smart and advanced. Security experts face an every day fight to identify and assess new dangers, identify possible mitigation measures, and find some solution for the residual risk. This upcoming age of cybersecurity threats requires agile and smart projects that can quickly adjust to new and unexpected attacks. AI and machine learning's ability to address this difficulty is perceived by cybersecurity experts, most of whom trust it is a key to the eventual future of cybersecurity The utilization of AI systems, in the realm of cybersecurity, can have three kinds of impact, it is constantly expressed in the work: «AI can: grow cyber threats (amount); change the run of the mill character of these dangers (quality); and present new and obscure dangers (quantity and quality).

The FDA tells Axios it is working on developing a framework to handle advances in AI and medicine, as pointed out by Commissioner Scott Gottlieb last year. Meanwhile, Ravi B. Parikh, co-author of the paper and a fellow at University of Pennsylvania's School of Medicine, tells Axios that the FDA needs to set standards to evaluate the "staggering" pace of AI development. Why it matters: Advanced algorithms present both opportunities and challenges, says Amol S. Navathe, co-author and assistant professor at Penn's School of Medicine. Details: The authors list the following as recommended standards... Outside comment: Eric Topol, founder and director of Scripps Research Translational Institute, who was not part of this paper, says the timing of these proposed standards is "very smart" before advanced algorithms are placed into too many devices. What's next: The scientists hope the FDA considers integrating the proposed standards alongside its current pre-certification program under the Digital Health Innovation Act to study clinical outcomes of AI-based tools, Ravi says.