Will Artificial Intelligence Replace Human Intervention Soon? Expectation vs. Reality

10 Nov. 22

Artificial intelligence (AI) is the programming of machines that mimics human intelligence. A computer or robot can perform operations efficiently, like humans, and has become more powerful and competent for daily jobs. We have seen this in our smartphones, cars, and medical equipment. But what about human intervention? Will we stop using humans altogether because machines do everything better than us? The reality is that humans are becoming more dependent on AI to make decisions for them. Still, at the same time, there will always be some level of human interaction with technology. AI is not a threat to humans and does not replace human jobs; instead, it will help us do our jobs better by making better and correct decisions in the first place. In this article, we will discuss the expectations that AI has created in this digital world and the realities that give us the reasons why human intervention is still necessary.


Artificial Intelligence Is Getting More Powerful & Innovative, But Human Intervention Will Always Be There


Artificial intelligence can do things that humans can’t and vice versa, but each has strengths and weaknesses. AI is based on a neural network-like algorithm designed to mimic our brain functions and can do tasks previously reserved for human beings. Yet, human intervention is necessary all the time. For example, robots can manage factories, yet accidents happen even when robots are involved in dangerous environments inherent in factories where they are exposed to chemicals or machinery that could malfunction at any moment. The bottom line is no matter how smart an algorithm gets, there always needs to be someone who ultimately makes decisions.


Humans Are Still Better Than Artificial Intelligence, As Artificial Intelligence Cannot Learn From Mistakes


While AI is good at doing one specific task, humans are still better as they can only design a machine to do one specific job. It is the reason we cannot replace humans that easily. A computer cannot adapt to a new environment and learn from its mistakes as humans can. For example, if you have an accident with your car and it damages your bumper or windshield, you may need to get another vehicle so that you don’t get into another accident again. It shows how humans are better than machines as they can learn from experience and adjust accordingly. A human will not repeat those mistakes later down the road when they want something else done similarly, but we cannot expect similar behavior from artificial intelligence. We must recognize our collective abilities and realize that the choice is not between people and AI but how to create a joint future in which human intelligence and artificial intelligence coexist and work together.


Artificial Intelligence Is Only Partially Trustworthy & Prone To Attacks


The danger lies in the fact that humans are becoming too dependent on AI and trusting it completely without verifying the information they give us. AI systems can be hacked by malicious people who want to gain access to other people’s data or use your personal information against you. AI systems are also prone to making mistakes and biases that may cause harm when used by humans. For example, an algorithm that predicts health risks based on measurements could easily be wrong about some people if trained for only one group of patients with different diseases than others (e.g., smokers vs. non-smokers). Another disadvantage of the AI system is it might not do what we want them to because it has been programmed with certain beliefs from its creators. Even if those beliefs were unconscious when built into the machine-learning models, they pose certain risks when put to use.


A Slight Mistake With Artificial Intelligence Can Cost A Human Life


The cost of making a mistake using artificial intelligence is very high, especially concerning human life issues. Artificial intelligence has been around for quite some time, but it still needs improvement in accuracy and efficiency. There are many cases where people have seen AI fail because they need to understand how these machines work or what they do. It can be due to either lack of education on the subject matter or poor coding requirements from developers when building an app with machine learning capabilities into its framework codebase. This is one reason companies like Google prefer using APIs over building their solutions.


Artificial Intelligence Will Not Be Able To Fully Replace Humans As The Cost Of AI Technology Is Increasing


The increasing cost of AI is the main reason that it might only be able to replace humans later partially. The development process of this technology is expensive and requires more time than creating simple programs like those used by the Google search engine, which only requires primary data inputs but still gets the job done. After all, they use machine learning algorithms to make predictions based on past experiences rather than having designers develop everything from scratch every time. Humans are still a cheaper and widely available resource than artificial intelligence. While some people are thrilled to see what AI is capable of, others have issued warnings about its development costs and adverse social effects. 


Artificial Intelligence is an exciting new technology, but it can also be a scary one. Contrary to the zero-sum projections of what artificial intelligence would do to our society and organizations, the possibility we envision is enrichment and collaboration. Instead, we see increased productivity and the automation of cognitively mundane tasks as an advantage rather than a danger. 


After all, when new technology is first implemented and developed, it always has disruptive impacts and typically shows its actual value much later. It is critical to know that AI still has many problems before becoming completely reliable. However, it is clear from our discussion above that the future of AI lies in its ability to do things more efficiently than humans—and that means making decisions based on what we know rather than just guessing what might happen. 

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