AI and Existential Risks

In the last decade, several companies have implemented new technologies to enhance their products and services. These technologies have allowed companies to innovate and create solutions that years ago were unthinkable.

However, new technologies have had several adverse effects around the world, including a massive job disruption and isolation as users prefer to spend more time using electronic devices rather than meeting people. With this in mind, a big question comes up. Are people concerned about the effects of new technologies?

Most people don’t care about the effects new technologies can have on the human race. However, for the common good, organizations and users must be aware of the effects of these technologies.

Artificial Intelligence (AI) and machine learning have allowed organizations to develop more personalized products. As a result, customers feel engaged because they feel their expectations have been met.

Systems can learn from experience and improve, but what about the potential risks? Many people believe AI will replace humans in the future. In this article we consider the existential risks of AI.

What is Artificial Intelligence?

AI is a field in computer science concerned with building smart machines. Using mathematical algorithms provides systems the ability to learn. Machine learning is a subset of AI.

When systems or machines use machine learning algorithms, they can perform human tasks exceptionally well. But, before that, user input is required so systems can learn how to do a specific job.

Nowadays, companies use AI and machine learning in almost every product. These technologies allow organizations to reduce costs and increase productivity. Robots and smart chatbots rely on machine learning. 

Automation has been beneficial for companies as they have increased their profits. But, several employees have lost their jobs because their skills are no longer needed. For example, smart robots have been used in the automotive industry to build more cars in less time while reducing occupational accidents. As a result, many manufacturing production operators have lost their jobs. 

What are Existential Risks? 

As long as we are alive, risks are everywhere. However, there are different types of hazards. With this in mind, it’s important to define what’s an existential risk. Because of technological improvements, humankind may be approaching a crucial phase in its evolution. An existential risk is where the human race is prone to disappear because of an adverse outcome.

Human inventions or natural disasters can cause adverse outcomes. On the other hand, when experts talk about existential risk caused by AI, they refer to the human extinction probably caused by robots.

To put it another way, it’s argued that humans dominate other species because of their brain capabilities. Humans are more intelligent than any other living creature. Given that, as smart machines are able to learn from humans, there is a big concern that they could surpass humanity. 

For example, let’s think about smart machines. They become better and better in specific tasks as they keep learning from input. If there’s a time when intelligent machines no longer need users’ contributions to improve, it’s probable that they could replace humans.

What is Superintelligence?

Superintelligence can be defined as the ability of smart machines or systems to surpass humankind’s intelligence. It can be achieved as AI systems become more powerful and more ubiquitous.

The superintelligence concept also refers to the machine’s performance superiority. It may sound like science fiction, but many experts believe it’s possible. For example, a machine that can beat humans in nearly all domains.

Whether possible or not, it can lead to positive developments but can also pose terrible risks. We have to realize that accidents can happen, and the more powerful systems are, the more catastrophic accidents can be.

On the other hand, superintelligent machines can also be used as a military asset. In that case, as world leaders know military weapons can generate money, superintelligent machines can be misused. Imagine a super machine in the wrong hands; it can destroy the whole world if everything’s out of control.

Is it Possible for Machines to Replace Humans?

As can be seen, AI can be used for good and bad purposes. However, there is a big question we must answer. Can machines replace humans in the future?

In the present day, smart systems and machines can’t replace humans. They are not that sophisticated, and they still need humans to improve. In the same way, most machine learning algorithms allow machines to become better in only one task. 

With this in mind, multitasking is a challenge machines still need to overcome. In the same way, nowadays, systems use logical thinking to operate. But, having an artistic approach is like a dream for machines. 

For example, UX/UI designers need creativity to build visually appealing websites. In that case, humans would beat machines as they are not able to feel inspired and provide artistic results to the real world.

Apart from that, experts are concerned that digital products are vulnerable as threats like viruses and hackers can take control of systems. For that reason, most companies hire professionals with cybersecurity skills that can keep their information safe.

Finally, to answer the question, it’s essential to say that machines are becoming better as days go by. But, as long as they need humans to operate and improve, they won’t replace humanity in the future.

Conclusion

As can be seen, AI is helping humanity take significant strides. They have helped companies to create products that years ago were unimaginable. In the same way, the right use of new technologies will help humanity go to the next level. For example, living among robots was also a science fiction thing, but nowadays people can work among them.

Smarter machines can bring the world and the human race several benefits. On the other hand, powerful machines in the wrong hands can cause unpredictable and harmful outcomes. 

Source: Artur Meyster


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