Artificial intelligence and human work is a hot topic for many people nowadays, and most of the discussion focuses on whether artificial intelligence will take our jobs in the future. Babak Hodjat, co-founder and CEO of ARTIFICIAL intelligence startup Sentient Technologies, says those worried about AI taking their jobs need not be so nervous because AI will also create new ones.
The word “artificial intelligence” often evokes fear and apprehension, fear of the unknown possibilities it opens up, the dystopian scenarios depicted in movies like Terminator, and fear that AI could one day take our jobs. Such fears are not new, nor are they entirely unfounded. Artificial intelligence is like any other disruptive technological invention, and the resulting faster and more efficient machines are bound to displace some human workers. But those who worry that AI will take their jobs need not be so nervous, because AI will also create new jobs, and they can at least work toward those new jobs.
According to a new Gartner report, while AI will replace 1.8 million jobs, it will also create 2.3 million new ones. Gartner principal researcher Peter Sondergaard predicts that AI will empower employees and could be a “net job creator” by 2020. I believe THAT AI, like all other disruptive technologies in the past, will create many new jobs for us.
Here are five industries that will show significant growth thanks to the rise of AI technology:
Data scientist
Data scientists are a new category of analytical data experts who analyze data to understand complex behaviors, trends, and inferences, uncovering hidden insights that can help companies make smarter business decisions. As SAS, which specialises in business analytics and business intelligence software, puts it, data scientists are “part mathematician, part computer scientist and part trend scientist”.
Here are some examples of data science applications:
Netflix uses data to mine movie viewing patterns to learn about users’ interests and then uses that data to make Netflix original series production decisions.
Target uses consumer data to identify key customers and analyze their unique shopping behaviors to guide messages to different audiences.
P&g can use the time series model to better understand the future product demand, so as to help the company to plan the appropriate production volume.
As AI drives the trend toward creating and collecting data, we can expect to see an increasing demand for data scientists in the future. According to IBM, the demand for data scientists will grow 28% by 2020, with 700,000 data scientists, data developers and data engineers expected to be in demand annually. The average AI expert, including a PhD student fresh out of school and a less educated professional with a few years of experience, can expect to earn between $300,000 and $500,000 a year plus company stock.
AI/ machine learning engineer
For the most part, machine learning engineers collaborate with data scientists to synchronize their work. As a result, machine learning engineers are likely to see similar growth in demand as data scientists. Data scientists have stronger skills in statistics and analysis, while machine learning engineers should have expertise in computer science, often requiring stronger coding skills.
If you entered machine learning a decade ago, it was hard to find a job outside of academia. But now that every industry wants to apply AI to their field, the demand for machine learning expertise is everywhere, so AI will continue to drive the trend of high demand for machine learning engineers. In addition, companies in different AI verticals, including image recognition, speech recognition, medicine and cyber security, are also challenged by a lack of a workforce with the right skills and knowledge. According to a Gartner report, one CIO wanted to hire AI technology professionals in New York, only to find a talent pool of 32, only 16 of whom met the criteria for potential candidates. Of those 16, only eight are actively looking for new employment.
3. Data label professionals
As data collection becomes ubiquitous in almost every vertical, the demand for data tagging professionals will increase dramatically in the coming years. In fact, in the age of AI, data tagging may become a blue-collar job.
“Data tagging becomes the management of data,” says Guru Banavar, head of the IBM Watson team. “You need to take raw data, clean it up, and use machines to collect it.” Tags allow AI scientists to train machines for new tasks.
“Let’s say you want to train a machine to recognize airplanes,” Banavar explains. “You have a million photos, and some of them have airplanes in them, and some of them don’t. You need someone to teach the computer which images have planes and which don’t.” That’s where the tag comes in.
AI hardware expert
Another growing blue-collar job in AI is the industrial operations that create AI hardware, such as GPU chips. Big tech companies are already taking steps to build their own specialized chips.
Intel is building a chip specifically for machine learning. IBM and Qualcomm, meanwhile, are creating a hardware architecture that reflects neural network design and can act like one. Facebook is also helping Qualcomm develop machine learning-related technology, according to Yann LeCun, Director of AI research at Facebook. As the demand for AI chips and hardware continues to grow, the demand for industrial manufacturing jobs dedicated to producing these specialized products will grow.
5. Data protection experts
As valuable data, machine learning models, and code continue to grow, there will also be a need for data protection, and therefore a need for database protection IT specialists.
Many layers and types of information security control apply to databases, including: access control, auditing, authentication, encryption, consolidation control, backup, application security and database security application statistics methods.
Databases are largely protected against hacker attacks by network security measures such as firewalls and network-based intrusion detection systems. The job of securing database systems and their programs, functions, and data will become more and more important as network openers become more and more accessible.
There will always be human judgment
While AI can be used to speed up the pace of everyday work, and may replace some workers in the future, it is creating more jobs than it destroys. Whether it’s analyzing, organizing, or reaching workable conclusions based on data, the human role is still essential. And because of this, the role of humans in creating, implementing and protecting AI will become even more important.
As Andrew Milroy, senior vice president of Frost&Sullivan, said, “the lack of human resources needed to make the transition will slow down the pace of technology adoption and automation. AI will create jobs. As new, disruptive technologies emerge, so will new, highly skilled jobs. Implementation of these technologies is impossible without human workers.”
Artificial intelligence is a step towards the goal of continuous unity of humanity in the future. The jobs created by AI technology could make life easier, freeing human workers from mundane tasks. While the current speed and popularity of AI technology is creating more jobs for us, it also means we face a new challenge, and we need to train people to move into these new positions.
Via: Community for ai enthusiasts