Can Artificial Intelligence Replace Data Scientists? – Know The Truth

Since we did not refer to data scientists by that name in the 1990s, Steve Urkel from the renowned ABC sitcom Family Matters was not a data scientist. However, the geeky adolescent Urkel is undeniably the model Data Scientist. Urkel created a robot whose IQ quadrupled every 2 minutes in one of the episodes. Although it was impressive, this was a poor idea. Urkelbot quickly toppled its master and imprisoned him in the cellar.

According to McKinsey, automation can save 64-69% of the time used for data collection and processing. Many people wonder if artificial intelligence (AI) will ever be able to operate more quickly and efficiently than data professionals as technology develops.

Data professionals can be divided into two categories:

• Data engineers gather data from many sources, extract it, put it together, clean it up, and then load it into a repository in a predetermined manner.

• Data scientists use the information in the repository to create advanced models using machine learning methods and test them.

Overview of Artificial Intelligence

Artificial Intelligence (AI) includes machine learning by definition. AI can also automate much of data scientists and engineers' work. AI can be used to perform the following tasks that data engineers generally carry out, to start:

• Data preparation, cleansing, accuracy verification, detection of outliers, and empty record detection

• Self-service systems to provide teams with data

• Deployment of models into production via automation

Additionally, AI can automate some of the following tasks performed by data scientists:

• Finding and expressing relevant prediction features

• Create tens of millions of various model variations (for different segments and markets)

• Creating simple models with user-friendly interfaces

• Identifying outdated models

So let’s come to the main question. Can AI replace data scientists? 

As discussed, data scientists can develop hundreds or thousands of variations of models with various prediction features with the assistance of artificial intelligence, then run iterative simulations to select the optimal variation ultimately. AI and data scientists work together to build the finest iterations. No matter how sophisticated an algorithm is, a dynamic, multi-faceted decision process gained through automation will surpass it because it can automatically test, iterate, and monitor data quality, incorporate new data points as they become available, and react wisely to events in real-time.

• AI can also help Data Engineers prepare raw data, tidy it up, and verify its accuracy. AI still needs to be fully capable of handling this. However, human judgment is still required to transform unprocessed data into insights that make sense for a complicated organization. AI cannot fully understand the implications of specific data for a company, its operations, and the broader industry. AI can assist in automating lower-level data preparation and visualization stages, freeing up data scientists to explain the implications of the findings to decision-makers.
  
  

• AI will first impact lower-level jobs, which Data Engineers typically perform. 

For instance, the need for lower-level programmers declined in the 1980s as computer programming languages evolved. However, as businesses adapted to these new languages, demand for developers soared. Analytics is going through the same process, with AI automating lower-level jobs. As a result, increasingly complex problem-solving duties are transferred to people. As a result, rather than endangering Data Scientists' careers, the mix of AI and human problem-solving has strengthened them.

• However, data engineers and scientists must adjust. Data engineers must transition to data science as AI automates lower-level data processing. Only the newest Data Scientists have received training in the more sophisticated deep learning techniques. In a few years, the skill set of data scientists will be obsolete due to technological advancements. However, it will not harm them. Hence, data professionals must become proficient with new AI tools or risk falling behind.

• Also, AI is more likely to become knowledgeable assistants to data scientists, enabling them to run more complex data simulations than ever before rather than posing a danger to their careers. Many more conventional occupations may soon require analytical abilities. A new class of data scientists, known as citizen data scientists that bridges the gap between business and solely analytical roles is predicted to be created due to this change.

Fortunately, after being imprisoned in the basement for 22 comedy minutes, our friend Steve Urkel could ultimately overthrow the oppressive Urkelbot, whose intelligence quadrupled every two minutes. When AI surpasses human intellect, rather than becoming a threat to humanity, data scientists are likely to continue working with AI or creating newer AI systems.

You don’t have to worry about being a data scientist. All you need to do is learn the latest data science and AI tools with data science courses in India, to stay ahead of others and be an expert at it.