With the rate at which data science has slowly become a part of practically every industry, there are very few people who remain unaware of it. And while the evolution continues to take place, there are some specialists who raise the question pertaining to longevity. More precisely, they are questioning if data science is just a short-term trend that will soon become obsolete.
With the rate of technological change in modern culture, many college students are asking, “Will data scientists become obsolete?” Data science is one of the fastest-growing industries in the economy, so it will be at least a few decades before it becomes obsolete. The debate over how disruptive artificial intelligence will be for human society is still ongoing. In the extreme case that data science becomes obsolete, most human jobs will be performed by computers, and the loss of data science employment will be just one among many social problems humanity has to deal with.
What Role Will Data Scientists Play in the Future?
According to the U.S. Bureau of Labor Statistics, data science jobs are projected to grow by 15 percent over the next decade. The average pace of growth for all jobs in the U.S. economy is around 4 percent, so data science is much more indispensable than the typical profession. In the future, data scientists will solve problems of practical and logistical importance. They will identify trends in human society and look for new uses of technology to serve basic needs.
Employment for data scientists will be spread out across many sectors of the economy. From cyber security to agriculture and entertainment, industries will hire data scientists to analyze an ever-increasing amount of information. These professionals will look for smarter ways to defend proprietary knowledge and deliver goods to consumers.
The need for data scientists will extend to the research and development of artificial intelligence for just about every digital tool or service available now or in the future. As long as computers use machine learning algorithms to interact with humans, data scientists will be needed to analyze the algorithms and come up with bug fixes and other solutions to problems not yet on the horizon. Data science is simply a branch of science that intersects with mathematics, statistics and computer science. It will be studied in universities and used in laboratories as long as modern civilization holds up.
Are Data Science Jobs Endangered by Machine Learning?
Machine learning algorithms are self-teaching programs that iterate millions of times through a problem until all the possible mistakes have been made. They use brute-force learning techniques to identify all the potentially wrong ways to do a task, and then they perform a side-by-side analysis of all the working solutions to decide which one works best.
The bottleneck in a brute-force algorithm is the processing speed of the computer. Even if a processor performs a trillion operations per second, it could take thousands of years to solve some of the currently unsolvable problems in computer science and other domains.
The likelihood that artificial intelligence will one day become actually intelligent is a hotly debated topic. For the foreseeable future, data scientists will work with computer scientists and other professionals to program machine learning algorithms and make sense of the findings. At present, machine learning technology creates jobs for data scientists who have the skills to write these programs and interpret their results.
Will Data Scientists Be Replaced by Future Technology?
No one can say whether some future technology will one day make data science obsolete. From the perspective of modern science, it is perhaps equally likely that an ecological catastrophe will make all modern jobs obsolete. Barring some unforeseen calamity, human progress will likely continue apace for the remainder of the 21st century.
As digital technology evolves over the coming decades, new jobs will emerge from the transformation of old jobs. Digital technology is still in its infancy, however, and it’s not yet mature enough to be self-sustaining.
Even if computers become as clever as people in the near future, artificial intelligence won’t be as good as humans at many types of analysis. Modern culture will have to make several major breakthroughs in understanding before computers are as good as people at thinking in holistic and emotional terms, for example. Of course, data scientists aren’t paid to be holistic and emotional. They are paid to be totally impartial data analysts, just like their unpaid artificial counterparts.
Are Data Scientists Designing Their Own A.I. Replacements?
The types of jobs scheduled for A.I. replacement in the future are knowledge-based jobs that require complete separation from emotion. While data science jobs more or less fit that description, they probably won’t be replaced any time soon. The more likely outcome is that most lower-skilled data science jobs will be taken over by machine learning technology and higher-skilled jobs will require human attention.
At the moment, a typical data science job requires at least a master’s degree. If A.I. causes a major transformation of the economy, the typical data science job of the future could require a Ph.D. along with some specialized scientific expertise. The data scientists currently designing advanced A.I. technology are themselves specialized experts in their fields, so their jobs will be safe.
In the worst-case scenario, some data scientists will invest thousands of dollars and many years of their lives into earning a master’s degree only to lose their jobs to A.I. These people could choose to extend their education to the Ph.D. level with just a few more years of study. However, this possibility is still many years in the future, and people currently enrolled in data science master’s programs have absolutely nothing to worry about. On the contrary, the outlook for graduates of data science master’s programs is excellent.
Best Degrees for Data Science Careers
According to the BLS, job growth in this field will be concentrated in industries currently experiencing rapid expansion, such as biomedical technology, cyber security and software design. A growing number of universities offer graduate programs specifically in data science, but a degree in a related field could make more sense for some people. For example, a cyber security degree might be a better choice for someone who plans to do data mining research in cyber security. A computer science or computer engineering degree could be a better choice for someone who wants to research algorithms or software technology. The current job market is very good for people with these types of interests and skills.
Employment experience will help job seekers find work that matches their training and abilities. Most accredited universities offer job placement assistance for graduates, and large firms often recruit new employees from the natural science and mathematics departments at local colleges.
When enrolling in a data science program, choosing a degree focus is an important first step. Colleges that offer data science master’s degrees typically give students a choice of concentration for their studies. As the field of data science continues to mature over the years, these specialized degrees will become the norm. In this case, a master’s degree in data science with a concentration in biomedical technology would be the best choice for a student who wants to go into data mining for biomedical research and development. In the current job market, most employers would see this degree favorably and consider hiring this job candidate.
How Much Money Will Data Scientists Earn in the Future?
For the foreseeable future, data scientists can expect to earn around $120,000 to $200,000 per year, depending on their level of experience and professional expertise. The median annual salary for all occupations is a little under $40,000 while the median for computer-related jobs is just under $90,000.
Data scientists take home significantly more money than other professionals in computer-related industries and over three times as much as the average worker in the U.S. As data science jobs become more specialized and focused, the pay will increase proportionally. During the same span of time, the economy overall will experience inflation and other fiscal changes that cause the average salary to increase. The spending power of data scientists will increase during this time, and their jobs will become more complex and demanding.
In a generation or two, the economy could look much different than it does today, especially in computer-related industries. The people needed in the future to design and implement data analysis and data mining algorithms will be more highly educated, and they will earn more money than industry professionals currently earn.
What Are the Best States for Data Science Jobs?
In the coming decades, the best states for data science jobs will be California, Virginia, Maryland, Washington and Texas, according to the BLS. Other good places for data scientists to find employment will be Utah, Florida and New York. Southern and Midwestern states such as Louisiana, Arkansas, Michigan and Indiana will be the worst places for data scientists to seek work. Professionals in these regions can still find jobs in universities and research laboratories, but the majority of hiring will take place in the Silicon Valley region as well as in large firms based in cities such as Seattle, Dallas and Houston.
Students expecting to graduate from a data science program in the near future can prepare for employment by speaking with an advisor in their college department. The mood among data scientists and A.I. researchers is generally upbeat, and fears about mass unemployment in these industries are low.
Major Threat to Data Science
One of the major threats that data science is facing is the rise of Artificial Intelligence (AI). In simple terms, AI stands for computerized machines who automate processes by being able to learn and exhibit human-like understanding. For instance, Apple’s talking software, Siri, is a perfect example of one of the relatively early forms of AI. Some industries that currently rely on this type of technology include healthcare, business, and government sectors.
Well, due to the fact that AI automates tasks, many people are wondering if further development of automation will facilitate a lack of need for manual data analysis. That would mean that the data science as we know today would certainly become obsolete and those who specialize in this area would find it difficult to land a job. Obviously, that is an extreme scenario that is unlikely to happen anyway. The more realistic way of approaching the topic is to question the degree of displacement that the data science will experience with AI’s forthcoming growth.
Although both data science and AI are based on analysis of various inputs, they do not have the same objectives. The analysis of data simply aims to understand the information in a manner that is useful to some particular person. For example, when an investor analyzes a corporation’s financial statements, they are often looking for signs of profitability. If an auditor looks at those same financial statements, they are more focused on signs of fraud. Nonetheless, they can apply versatile data analyses to derive results that help them make useful conclusions.
With AI, the main goal is to simply automate a process and help reduce the number of manual tasks. For example, according to Forbes, a lot of financial institutions are leveraging this technology for easier customer communication. That includes the ever-growing chatbots that have become an essential part of almost every large brand’s website. While AI certainly uses a lot of data science to properly answer to inquiries, its goal is not to derive the same type of results.
The Likely Outcome
Given that there is a clear disconnect between what AI and data science achieve, saying that either of them will ever become obsolete is a far-reaching statement. Not to mention that data science is responsible for the proper functioning of AI as well as all subsequent inventions. Even though specialists may have to work on their skillsets as the industry progresses, there are countless signs that show how information analysis is here to stay.
One thing that must be mentioned as a caveat here, however, is the unpredictability of the inventions in the field of technology. Even with AI lacking the power to replace information analysis, we could see something brand new come to life next year and completely revamp the market. Regardless, there is nothing that currently carries the power to uproot data science.
Data science is currently one of the most important industries of the economy. The possibility that data scientists will become obsolete is small, but that doesn’t mean that concerns about this possibility are unfounded. Projections about the future economy are tentative, and no one can say for sure what will happen. The question “Will data scientists become obsolete” may loom over the tech industry for years to come.
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