I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing ...
I write columns on news related to bots, specially in the categories of Artificial Intelligence, bot startup, bot funding.I am also interested in recent developments in the fields of data science, machine learning and natural language processing
The words artificial intelligence often conjure up a sense of fear and apprehension. Fear for the unknown possibilities of AI, fear for the AI-fueled dystopian images brought about by movies like The Terminator, and most practically, fear for the possibility that AI will someday take our jobs. This fear is neither new nor totally unfounded. As with any disruptive technological invention, faster, more efficient machines are bound to replace human workers. However, those who fear AI will take their jobs can rest a little easier knowing they will at least have the potential to find a new job.
A new report by Gartner states that although AI will eliminate 1.8 million jobs, it will create 2.3 million jobs. Peter Sondergaard, head researcher at Gartner, predicted AI will augment workers' abilities and could be a "net job creator" starting in 2020. I believe, like all other disruptive technologies of the past, AI will bring about many opportunities for new jobs.
Here are five of the professions that stand to see significant growth with the rise of AI.
1. Data scientists
Data scientists are a new breed of analytical data expert. They analyze data to understand complex behaviors, trends, and inferences, discovering hidden insights that help companies make smarter business decisions. Data scientists are, as SAS put it, "part mathematician, part computer scientist, and part trendspotter."
Here are some examples of how data science is used:
Netflix data-mines movie viewing patterns to understand what drives user interest. The company uses that data to make decisions surrounding the production of Netflix originals.
Target uses consumer data to identify major customer segments within its base. It also analyzes the unique shopping behaviors within those segments to guide messaging to different audiences.
Procter & Gamble utilizes time-series models to more clearly understand future demand, which helps the company plan optimal production levels.
With AI fueling the trend of creating and collecting more data, we could see an increased need for data scientists in the future. IBM predicts the demand for data scientists will soar 28 percent by 2020, with the annual demand for data scientists, data developers, and data engineers reaching 700,000. Typical AI specialists, including both PhDs fresh out of school and professionals with less education and just a few years of experience, can be paid from $300,000 to $500,000 a year or more in salary and company stock.
2. AI/Machine learning engineers
In most cases, a machine learning engineer partners with a data scientist to synchronize their work. Therefore, demand for machine learning engineers could see an increase similar to data scientists'. While data scientists are expected to have stronger skills in statistics and analytics, ML engineers are expected to have expertise in computer science, and they generally need much stronger coding abilities.
If you were getting into the machine learning field a decade ago, it was hard to find work outside of academia. Now, with every industry looking to apply AI to their domain, demand for machine learning expertise is everywhere. AI will continue to fuel the high demand for machine learning engineers. Moreover, companies that are operating in different verticals - such as image recognition, voice recognition, medicine, or cybersecurity - already face the challenge of acquiring a workforce with the right set of skills and knowledge. According to Gartner, a CIO attempting to hire talent with AI skills in New York City taps into a talent pool of only 32 experts. Of those, just 16 are potential candidates, and only eight are actively looking for new opportunities.
3. Data labeling professionals
With the increased prevalence of data collection in almost every vertical, the demand for data labeling professionals could surge in the future. In fact, data labeling could become a blue-collar job in the AI era.
According to Guru Banavar, head of the team at IBM responsible for Watson, "Data labeling will be the curation of data, where you take raw data, clean it up, and organize it for machines to ingest." Labeling enables AI scientists to train machines in new tasks.
Banavar said, "Let's say you want to train a machine to recognize planes, and you have a million pictures, some of which have planes, some of which don't have planes. You need somebody to first teach the computer which pictures have planes and which pictures don't have planes." This is where labelers will come into play.
4. AI hardware specialists
Another growing blue-collar job in the world of AI is the industrial job responsible for creating 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. Meanwhile, IBM and Qualcomm are creating hardware architecture that mirrors the design of neural networks and can execute like them as well. Facebook is also helping Qualcomm develop technologies related to machine learning, according to Yann LeCun, director of AI research at Facebook. With the increasing need for AI chips and hardware, there will be a growth in industrial manufacturing jobs dedicated to creating these specialized products.
5. Data protection specialists
The increase of valuable data, machine learning models, and code will bring a need for future protection of that data, and therefore database protection IT specialists.
Many layers and types of information security control are appropriate to databases, including:
Database security applying statistical method
Databases are largely secured against hackers through network security measures such as firewalls and network-based intrusion detection systems. Securing database systems and the programs, functions, and data within them will become more critical as networks increasingly open to wider access, particularly from the internet.
Organizations will always need human judgment
Although AI can be used to speed up routine processes and is likely to displace some workers in the future, it will create more jobs than it will destroy. Humans are still necessary for the process of analyzing, organizing, and drawing actionable conclusions from data. This is why the role of humans in the creation, implementation, and protection of AI will become significantly more important.
As Andrew Milroy, senior VP of Frost & Sullivan, said, "The lack of manpower needed to enable the transformations will slow down technology adoption and automation. AI will create jobs. New higher skilled jobs will emerge together with the use of new, disruptive technology. The implementation of this technology is impossible without them."
AI is a step in the continuum of humanity. The technology is building tools to make life easier and reduce the need for humans to perform menial tasks. The speed and prevalence of the spread of AI mean that the responsibility for training the workforce to transition to these new jobs is one that we should take seriously - and an opportunity for yet more job growth, of course.