Can Data Scientists Be Replaced By Automation?

The advent of AI, automation and smart bots triggers the question: Is it possible that data scientists will become redundant in the future? Are they indispensable? The ideal approach appears to be automation complementing the work data scientists do. This would better utilise the tremendous data being generated throughout the world every day.

Data scientists are currently very much in demand. But there is the question about whether they can automate themselves out of their jobs. Can artificial intelligence replace data scientists? If so, up to what extent can their tasks be automated? Gartner recently reported that 40 per cent of data science tasks will be automated by 2020. So what kind of skills can be efficiently handled by automation? All this speculation adds fuel to the ongoing ‘Man vs Machine’ debate.

Data scientists need a strong mathematical mind, quantitative skills, computer programming skills and business acumen to make decisions. They need to gather large unstructured data and transform it into results and insights, which can be understood by laymen or business executives. The whole process is highly customised, depending on the type of application domain. Some degree of human interaction will always be needed due to the subjective nature of the process, and what percentage of the task is automated depends in the specific use case and is open to debate. To understand how much or what parts can be automated, we need to have a deep understanding of the process.

Data scientists are expensive to hire and there is a shortage of this skill in the industry as it’s a relatively new field. Many companies try to look for alternative solutions. Several AI algorithms have now been developed, which can analyse data and provide insights similar to a data scientist. The algorithm has to provide the data output and make accurate predictions, which can be done by using Natural Language Processing (NLP).