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Pros And Cons Of Artificial Intelligence

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Artificial Intelligence Artificial Intelligence (AI) is a topic of major controversy in today’s world. When people first hear about this, they may quickly jump to conclusions that can be either positive or negative. On one end of the spectrum, some may think that it could mean the end of humanity. That AI systems might surpass human intelligence, and come to the conclusion that humans are inferior to them, which has several implications on its own. On the other end, some may think that it could be the pinnacle of human innovation. AI can make our lives much easier with everyday tasks such as planning out schedules, or even by just driving people to work. AI can go one of two ways, which is why it is, understandably, a topic of major …show more content…

According to Futurism, there are various applications such as decision support systems, laboratory information systems, robotic surgical systems, therapy, reduction of human error in diagnosis, and medical education—a major one being the reduction of human error. A study by John Hopkins Medicine brings to light how dangerous human error is today. Their study, which was published in May of 2016 and conducted over an eight-year period, shows that human error accounts for 250,000 deaths per year in the U.S. alone. This makes human error in diagnosis the third leading cause of death in the United States. Researchers attribute this to systematic errors, rather than inherently bad doctors (John Hopkins Medicine). With the implementation of AI, these flaws can essentially be eradicated. A more realistic con to the implementation of AI, includes the costs that go into developing and maintaining AI. A large amount of resources are required to develop artificial intelligence. Jennifer McCarron, technology program manager at Cisco, describes the different costs, such as licensing and purchasing solutions, startup costs, and maintenance costs. Not only would companies have to shell out a lot of money to get AI systems developed and started up, they would have to hire new employees to maintain and teach the systems. She says, “For large-scale projects with unstructured data, it’s going to require a little bit more complexity. You’re [talking] half a million dollars and

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