Apart from the inevitable rise of robots, machines taking over human jobs, and the global dominance of machines, can you really think of any disadvantages of AI? Uhum no. Well, this article is not to entertain the far-fetched horrors of AI, but to discuss some real disadvantages of it in a practical world.

“Alexa, play Jhoom Barabar,” “Google, call Mummy,” “Okay Siri, will it rain today?” are some amazing ways in which AI has seamlessly made its way into our lives. We are experiencing the best that AI has to offer. With the future dreams of automated cars (hello, Tesla?), personalized shopping, and auto-homework completing assistants (please, God!). But, do we face any threats from AI, that we are all unaware of?

Let’s find it out:

First off, What is AI? Artificial Intelligence. It is a subset of computer science applications. What is the main objective of AI-based machines? It is to mimic human activities such that they can be used to augment their natural abilities or ease their lives. Some of the major AI-based software include Google Cloud Machine Learning Engine, TensorFlow, Azure Machine Learning Studio, Cortana, IBM Watson, etc.

All coins have two sides (not talking about Bitcoin here). So, with all the good that AI brings to the table, we must also be cautious of all its flaws. Let’s look at some major disadvantages of AI implementation today:

1. HIGH COST OF IMPLEMENTATION

SSetting up AI-based machines, computers, etc. entails huge costs given the complexity of engineering that goes into building one. Further, the astronomical expenses don’t stop there as repair and maintenance also run into thousands of dollars. Do you know how much Apple shelled out to acquire its virtual assistant SIRI? The acquisition of the software cost somewhere around a whopping $200 million. Further, the high cost of AI implementation is evident from the fact that Amazon acquired Alexa for $26 million in 2013.

These AI-based software programs require frequent upgrades in order to cater to the requirements of the changing environment as the machine needs to become smarter by the day. For eg- think you have smart devices connected to your Alexa, and in an out of pattern habit you forgot to switch off a room’s light, Alexa will do it automatically for you. In case the software suffers a severe breakdown, then the process of recovering lost codes and reinstalling the system can give you nightmares due to the huge time and cost involved.

Data Science tingling all your interested brain cells? Here are the Top 5 reasons to become a Data Scientist that you should consider.

2. CAN’T REPLACE HUMANS

It is beyond any doubt that machines perform more efficiently when compared to human beings, by far. But even then, it is practically impossible to replace humans with AIs, at least in the near future. Because you can’t build human intelligence in a machine, as it is a gift of nature. So, no matter how smart a machine becomes, it can never replace a human.

We might get terrified at the idea of being replaced by machines, but honestly, it is still a far-fetched notion (take that, Black Mirror!). Machines are rational but don’t have any emotions or moral values. They lack the ability to bond with human beings, which is a critical attribute needed to manage a team of humans.

Yes, it is true that they can store a lot of data but the procedure of retrieving information from them is quite a cumbersome process, which is way too difficult when compared to human intelligence.

All this talk of AI, makes you interested in Data Analytics? Check out Proschool’s PG Program in Data Analytics

3. DOESN’T IMPROVE WITH EXPERIENCE

One of the most amazing characteristics of human cognitive power is its ability to develop with age and experience. However, the same can’t be said about AIs as they are machines that can’t improve with experience, rather, it starts to wear and tear with time.

One thing that we must understand is that machines can’t alter their responses to changing environments. That is the basic premise on which AIs are built – the repetitive nature of work where the input doesn’t change. So, whenever there is some change in the input, the AI needs to be re-assessed, re-trained and re-built.

Machines can’t judge what is right or what is wrong because they are incapable of understanding the concept of ethics or legality. They are programmed for certain situations and can’t really make decisions in cases where they encounter an unfamiliar (not programmed for) situation.

Interested in the Data Analytics Course?

Download DA Brochure

 

4. LACKS CREATIVITY

AI is not built for creative pieces of work. Creativity or imagination is not the forte of AI (big shout to all you future Van Goghs, AI is not replacing you anytime soon). Although they can help you in designing and creating something special, they still can’t compete with the human brain. Their creativity is limited to the creative ability of the person who programs and commands them.

Human brains are characterized by immense sensitivity and high emotional quotient. To put it simply, AIs can become skilled machines but they can never acquire the abilities of the human brain. The reason is that skills can be learned and mastered, but abilities come naturally and can only be honed.

5. RISK OF UNEMPLOYMENT

With Coming to the looming question – will AI replace humans? Honestly, I am not sure whether AIs will lead to higher unemployment or not. But AIs are likely to take over the majority of the repetitive tasks, which are largely binary in nature and involve minimum subjectivity.

Want to know about jobs after Data Analytics? 

Talk To Our DA Expert

According to a study conducted by McKinsey Global Institute, intelligent agents and robots could replace ~30% of the world’s current human labour by the year 2030. The study further states that “automation will displace between 400 and 800 million jobs by 2030, requiring as many as 375 million people to switch job categories entirely”.

So, it can’t be ruled out that AIs will result in less human intervention which in turn may cause major disruption to the employment standards. Nowadays, most organizations are implementing automation at some level in order to replace minimally qualified individuals with machines that can do the same work with higher efficiency. It is further evident from the information provided by International Data Corp. which states that worldwide AI spending is expected to hit $35.8 Billion in 2019, which is then likely to more than double to $79.2 Billion by 2022.

Read more: Top 10 Machine Learning Projects For Beginners In India

CONCLUSION

There you have it. Some major disadvantages that AI implementation brings to the table. Like any other invention, AI also comes with its own set of problems. However, it won’t be too optimistic to believe that all these problems will probably be fixed with time, including the issue of unemployment which can be solved with human upskilling.

If you want to upskill and take your career to new heights with Data Science, talk to a Proschool Data Science Expert to get started on the right track. Just fill out this form, and we’ll get in touch: