How Should Data Scientists Evolve with the Rise of AI?

Artificial Intelligence (AI) is the talk of the technology town, with everyone becoming excited over it lately. Though AI is still in the exploratory mode, there have been various areas where it has established itself as a vital component and has brought revolutionary changes in some industries. The best example is that of ‘automation in the IT industry, which some say is the cause of massive layoffs seen in various organizations.

In order to achieve better profitability and revenue growth, some of the prominent IT companies in India have started automating low-skilled jobs. Wipro became the first Indian IT firm to launch an artificial intelligence platform, Holmes, last year. After that, TCS launched its artificial intelligence platform, Ignio, and Infosys rolled out its artificial intelligence platform – Mano.

This article will cover:

What is Artificial Intelligence?

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Some of the activities computers with artificial intelligence are designed to include:

• Speech recognition
• Learning
• Planning
• Problem-solving

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Machine learning is the connection between data science and AI. It is the process of learning from data over a period of time. AIs require a huge pool of data to do even the simple of things. Hence the connection between data science, machine learning, and artificial intelligence.

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How is AI becoming a threat to data scientists?

Just 4 years ago Harvard Business Review dubbed ‘Data Scientist’ as “the sexiest job in the 21st century” and it became one of the most lucrative job titles. Due to the shortages of good data science professionals, a lot of companies pay attractive packages to hire an expert.

Fast-forward to the current scenario in the technology space, AI has suddenly created deep impacts on various areas. It appears to be a threat to the jobs of data scientists; as shown by MIT’s “Data Science Machine”. It offers the capability to build predictive computer models by identifying relevant features in the raw data. However, according to an expert, “some humans can beat the machine and it would be naïve to say that data scientists do not have any value.”

The convergence of big data with AI has also led to the belief that it will replace the pool of data scientists who are limited to working on sample sets of data.

Data Science and Artificial Intelligence

For any Data Scientist, Artificial Intelligence is a procedure that lies on top of other methodologies for analyzing the data. This is analogized via Maslow’s Hierarchy of needs in which each component in the pyramid represents a data operation which is performed by a Data Scientist.

Why and How should data scientists evolve?

Data scientists need to evolve in order to survive along with the world of AI. The role of data scientists will assume a different level of importance and they should, instead, take the help of AI to create better predictive models. The young generation of data scientists should be prepared for the AI revolution and get trained in more advanced deep learning approaches. The same path as software development has been followed by data scientists, automating the lower level tasks and moving up to the abstraction level. They should start focussing on the higher level and complex tasks.

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AI and other technologies can bring revolutionary changes in the future. However, professionals should always be ready to keep their skills at the highest level. Advanced level data science courses developed by experts in the industry and will help you to keep up-to-date with the latest skills and techniques.

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