Two New Jobs That AI is Creating Now

Two New Jobs That AI is Creating Now
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We are all aware millions of jobs will be lost to AI, but did you know that the technology is also creating new jobs?

According to The Future of Jobs 2018 report by the World Economic Forum (WEF), 75 million jobs will be displaced by 2022, but at the same time, 133 million new jobs will be created by 2022. This is already happening in the field of Big Data.

We are drowning in data

The world has become data mad. In fact, we are drowning in data. The volume of data in the world has increased to such an extent that we have had to develop a new vocabulary to describe these magnitudes. So there are such measures as terabytes, petabytes, exabytes, and zettabytes. Just in case you’re interested, a terabyte is 1,000 gigabytes; a petabyte is 1,000 terabytes; an exabyte is 1,000 petabytes…. You get the picture.

It’s estimated that by 2025 the world will create 463 exabytes of data per day – that’s the equivalent of 212,765,957 DVDs per day!

All this data is only useful to draw insights from if there are enough data scientists to do the job.

We are facing a shortage of data scientists

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Image by Gerd Altmann from Pixabay

 

The LinkedIn Workforce Report 2018 noted that in the U.S. there’s a shortage of 151,717 data scientists. The Harvey Nash/KPMG CIO Survey 2019 found that skills shortages are at an all-time high with skills in big data/analytics, cybersecurity and AI at the top of the list.

Organizations need the expert skills of data scientists to benefit from advanced predictive and prescriptive analytics. But these skills, as we have seen, are scarce.

Enter the citizen data scientist

What is a citizen data scientist, apart from a person with an awkward-sounding handle?

Gartner defines a citizen data scientist as a person who creates or generates models that use advanced diagnostic analytics or predictive and prescriptive capabilities, but whose primary job function is outside the field of statistics and analytics. Citizen data scientists can bridge the gap between mainstream self-service analytics by business users and the advanced analytics techniques of data scientists.

The main point is that they can perform sophisticated analysis without having to be experts in statistics and analytics like data scientists.

This fairly recent development means that organizations don’t have to employ data scientists to benefit from the data they generate; they can just make use of the skills of citizen data scientists. In fact, the number of citizen data scientist is expected to grow at five times the rate of traditional data scientists by 2020.

The birth of this new class of data scientist is made possible by a new range of data and analytics software platforms aimed at enabling big data analytics.

Companies are retraining existing staff to become citizen data scientists by training them to become proficient at using business intelligence software. For example, retail giant, Sears, deployed Platfora’s big-data analytics platform for Hadoop to empower more than 300 business intelligence staff to become citizen data scientists. These newly-minted citizen data scientists are now able to generate their own data-analysis reports without the help of a data scientist.

These reskilling and upskilling initiatives hold many benefits for both companies and their employees. Companies benefit from greater efficiency and increased competitive advantage; employees can develop advanced skills and take on new roles more in line with an AI-enhanced work environment.

These developments don’t mean that data scientists will become obsolete. On the contrary, they will be able to do more complex and specialized work.

In the meantime, big analytic platforms like Platofora are enabling a wider range of employees within an organization to be exposed to and work with artificial intelligence.

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Image via Pixabay

How do I become a citizen data scientist?

First of all, you don’t need a degree in data science; you need reskilling and upskilling and access to data. Let’s look at some logical steps to take if you’re thinking of reskilling as a citizen data scientist.

1. Get access to more data

This is the first, logical step on your road to becoming a citizen data scientist. Ask for access to a wide range of documents that are data-rich.

2. Learn to use the right software programs

Next, you need proficiency in business intelligence software powered with big data analytics capabilities. These tools will enable you do data analytics even though you don’t have a post- graduate degree in data science or statistics.

Platfora has a big data discovery software solution that you can try out or you can explore the Alteryx platform to help you fulfill your new data science and analytics role.

Another new role created by AI: “guardian”

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Image by Stefan Keller from Pixabay

The greater the number of employees accessing a wider range of data sets, the more care must be taken that the data is treated with due sensitivity by everyone involved.

According to the software vendor, Capterra, Gartner suggests that companies appoint “guardians” to monitor how data is used. A guardian is there to make sure that citizen data scientists use data responsibly. They oversee data security and bridge the gap between traditional data management roles and the citizen data scientists using data in new ways.

This is what Joao Tapadinhas, research director at Gartner said in a press release about citizen data scientists: “Equipped with the proper tools, they can perform intricate diagnostic analysis and create models that leverage predictive or prescriptive analytics. This enables them to go beyond the analytics reach of regular business users into analytics processes with greater depth and breadth,”

Conclusion

AI may be taking jobs away, but the technology is already creating jobs that didn’t exist even five years ago and this trend will continue. The creation of these fairly new roles solves a big problem for organizations with limited data scientists available. Thanks to advanced business intelligence software, they can now empower their skilled information analysts and other staff to take on the role of citizen data scientists and yet others to become “guardians” of this new process.

 

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