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Is It Possible For Automation To Bring An End To Data Science Jobs?

by Paul Petersen

Today, data scientists are very prevalent and in demand. With AI or artificial intelligence development, we can expect that AI will replace data scientists’ jobs and their place in a firm. Gartner gave a statement sometime earlier that about 40% of data science jobs will be automated. This means that with the development of artificial intelligence, nothing can be said. So, this is purely the case of a very controversial ‘man vs. machine’ topic.

Why could this possibly happen, and what could be the consequence?

  • Data scientists are very costly to recruit because they charge a lot of money. A data scientist is a new career that is still buzzing and growing, and there are now many data scientists today. Therefore, it is difficult for companies to hire such personnel. To cut the costs, numerous tech-based companies are looking for alternatives. The point is that these companies have found a solution with artificial intelligence.
  • This means that companies, organizations, and many businesses that required data scientists are now switching to AI, and then by others seeing that, they are thinking about it. Breakthroughs are occurring in the field of AI. This means that there are many algorithms designed to think like a data scientist and perform tasks.
  • Such algorithms analyze given data using inputs and assumptions and make exact forecasts as a data scientist would use Natural Language Processing or NLP. But the point is that this would make data scientists jobless sooner than we think. Companies prefer investing money in AI and become independent, rather than being dependent on costly data scientists.
  • Countless people believe that this algorithm is the future and do not think about the process involved in developing the algorithms. They also don’t think about the intricacies and the details of a data scientist’s job. A data scientist’s job is one with too many difficulties. For example, they have to run predictive solutions to problems that occur in commerce, which is a very tough task to do, even for an artificial intelligence algorithm.

You can’t leave humans out of the equation: 

The automation process will NOT bring to an end to many ambitious young minds. Automation is rather a way to reduce the data scientists’ workload. This means that the system will implement low-level capacities and tasks with not many efforts. Automation has its limits, and can’t automate itself.

The cycle includes the proper involvement of a human mind. This means automation can’t work without our involvement. The AI isn’t stable upon itself. Human discoveries need to be introduced, and logic needs to be explained. So, we can conclude that AI can’t replace a data scientist’s job in any way. It can, however, make it much easier and the process less tiresome. The companies that demand high functioning data scientists and are investing their money in AI have found that a data scientist’s work gets much easier if AI is involved. Therefore, the theory that AI would replace the existence of data scientists is entirely fictitious and bogus. Everyone needs to complete their facts.

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