The Future of AI: Careers in Machine Learning

If you're considering a career in machine learning or artificial intelligence, some of the job titles you might look into include data scientist, artificial intelligence engineer, big data engineer, robotics scientist, machine learning engineer and computer and information research scientist.
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Three professionals working with a robot in a machine learning career with the text The Future of Machine Learning

The robots are coming. If there is one thing we learned from the COVID-19 pandemic, it’s that when humans are sent home, machines keep working. 

This doesn’t mean that robots will take over the world. It does, however,  mean that our technical landscape is changing. 

Human history has a long and favorable track record of technological advancements, particularly when it comes to ideas that seem ludicrous at the time (Wright brothers, anyone?). The printing press, assembly line and personal computer have all helped move civilization forward by leaps and bounds over the last few centuries. 

Imagine being one of the first people to replace glasses with contact lenses – by putting them directly on their eyes, no less. Henry Ford replaced horses with the automobile as our main mode of transportation. The process of pasteurization changed the way we eat. Examples like these are endless, because throughout human history, there has been innovation and change. 

Even as recently as the 1980s, there was no internet in people’s homes. The very means by which you are reading this article did not exist. Online school did not exist, at least not in the way we take college classes online now. 

And while each technological advancement may have its detractors, it’s hard to argue with the benefits of technology as a whole. After all, thinking big got us to the moon, and gave us television, 3-D printing and a host of incredible advances in modern medicine. 

So, are you wondering what’s next? The future of technology lies squarely with machine learning and with artificial intelligence, known as AI. 

What is Artificial Intelligence? 

Artificial intelligence is part of the field of data science. People who work in data science are skilled in developing mathematical algorithms to answer complex questions. When, for example, a company like Netflix wants to predict what movies a customer might want to watch next, a data scientist will create an algorithm based on that customer’s viewing history. Then, they will use that algorithm to offer a list of suggestions. 

Ben Tasker with the text Ben TaskerMachine learning is a branch of data science which involves using “data science programs that can adapt based on experience,” said Ben Tasker, technical program facilitator of data science and data analytics at Southern New Hampshire University. “Take a weather predictor, for example. The more weather inputs there are, the better the prediction for what will come next.” 

While machine learning is useful, it’s important to note that there is no artificial intelligence involved in its functions. Machine learning involves rote mathematical or mechanical processes only. 

Artificial intelligence then advances data science and machine learning even further. 

Whereas machine learning can make predictions, artificial intelligence can make adjustments to its computations. In other words, “AI can adjust a program to execute tasks smartly,” Tasker said. For example, a fully autonomous, self-driving car is an example of something that would use full artificial intelligence. 

These days, the idea of such a self-driving car is no longer science fiction. As the fields of science and engineering continue to advance, artificial intelligence is becoming “a lot less artificial and a lot more intelligent,” Tasker said. 

What are Some Careers in Machine Learning and AI? 

Because so much about the field of data science in general and AI in particular is new, there are many opportunities to “make your own niche, especially now that many companies have started to invest in the idea of artificial intelligence,” Tasker said. This creates a wealth of career opportunities for those who thrive on charting their own path. The future of AI is great.

Careers for computer information and research scientists are predicted to grow 15% between now and 2029, according to the U.S. Bureau of Labor Statistics (BLS). That is much faster than the national average for career growth. The median pay is a healthy $122,840 per year, BLS reported. 

Some other top career options for machine learning and artificial intelligence include: 

  • Data Scientist: In this role, one might use data, computer modeling and statistics to solve problems. A foundation in computer science and sound programming skills will allow this person to help businesses of all sizes make sound business decisions based on data.
  • AI Engineer: In this role, one may be involved in the different facets of designing, developing and building artificial intelligence models using machine learning algorithms. This role requires a strong aptitude for innovation in addition to superior math skills. 
  • Big Data Engineer: Overlapping with the role of a data scientist, the person in this role analyzes a company’s volume of data known as “big data,” and then uses the analyses to mine useful information in support of the company and its business model.
  • Robotics Scientist: A person in this role may design machines and mechanical models to complete tasks that humans could do, but won’t or can’t. This role combines electronics, mechanics, math and engineering and spans many industries, including prosthetics and automotive.
  • Machine Learning Engineer: This role could be a good fit if careers in machine learning are of interest. A person in this role may design software that automates predictive models. Strong math and analytical skills are needed to thrive in this role, as creating algorithms is a key job function. Exceptional data management skills are necessary. 
  • Computer and Information Research Scientists: The person in this role may use data to design new technological solutions for businesses, as well as seek to find and develop innovative uses for existing technology. In this position, one may work with robotics and programming as well as algorithms and cloud computing.

What About Those Robots? 

So, will robots replace humans moving forward? For some jobs or tasks, quite possibly. For all jobs or tasks? Not likely. 

Of course, “robots are already in the workplace,” Tasker said. “They are not intelligent, but they perform basic tasks.” Car manufacturers use robots on assembly lines already and have for years. 

Whether a company actively uses artificial intelligence or not, “all industries will be impacted by it, whether intentionally or unintentionally,” Tasker said. “I do think that some industries will have a ‘higher barrier of entry,’ so to speak, such as medicine,” he said. Patients still prefer a human touch for things like receiving a diagnosis or test results. 

As artificial technology continues to develop, “humans will need to have an ethical debate about what robots can and cannot do, but yes, we will see more robots,” said Tasker.

And as use of robots grows, without a doubt, “ethics is going to play a much larger role as AI grows,” said Tasker, “or at least it should.”

Is AI a Good Career?

Careers in machine learning and artificial intelligence are still being defined, which creates generous opportunities to innovate and carve your own career path. If you like math, computer programming, coding, and technology in general, a career in data science, machine learning, or AI is definitely one to consider. 

Having a strong foundation in math and STEM can help prepare you for a career in AI. Knowledge of psychology will be particularly helpful, too.

Also important: a large threshold for change. “Data science [and AI with it] changes every year,” Tasker said, “so the people working in data science will need to change with it. You will always be learning new technologies, algorithms, and coding languages.”

What are Some Key Skills Needed for a Career in AI?

The more math, programming, and experience with cloud computing that you can get under your belt, the better. 

And, as more and more adoption of artificial intelligence technologies occur, “we will begin to see an ethical debate emerge about what AI should and should not be doing,” Tasker said. That makes courses in ethics critical, because "as the field of AI grows, more ethical considerations will need to be applied."

Keep in mind that while a bachelor’s degree is a great foundation on which to build a career in artificial intelligence, an advanced degree is likely necessary to advance to the highest levels in the field.

“Most jobs in the field of artificial intelligence require a graduate degree, such as a master of science or even doctorate, so be ready to continually learn,” said Tasker. 

Is a Career in AI Future-Proof?

While no career is truly future-proof given the ever-changing technology landscape, there are some ways you can be best prepared to weather the change. By grounding yourself with a strong science, math, and engineering background and then being ready to drive change, you may enjoy a long and prosperous career in the field of artificial intelligence. 

Of course, while having a strong academic background is important, being good at math and programming is not enough. To really thrive in this career-field, you also need good, old-fashioned grit. In fact, “curiosity, grit, and being humble” are key traits toward having a successful, long-term career in data science, and especially in artificial intelligence, said Tasker. “These are traits that you cannot necessarily learn in the classroom, but are helpful to being successful in this field long-term.” 

How Will AI be Used in the Future?

We have actually been using AI for some time, and not just in factories and on assembly lines, or to design futuristic cars. 

Have you ever filled out a job application and included key words so that the artificial job screening tool doesn’t filter you out of contention? That’s artificial intelligence. 

Some artificial intelligence programs can even “scan how a resume is drafted to see personality traits of an applicant,” said Tasker. “Other programs use facial recognition, which scans your facial expressions in an interview to create personality profiles of applicants.”

Likewise, if you have ever used a website and a “chat bot” popped up, saying “How can I help you today?” that is also artificial intelligence. If you’ve ever thought you were chatting with a real, live human only to be informed that you’re chatting with a “bot,” you already know just how realistic artificial intelligence tools already are in the business and retail world. 

Chat bots and virtual assistants are being routinely used to “respond to easy emails, schedule appointments, and even take meeting notes for users,” Tasker said. While at times, being on the receiving end of using a “bot” can be frustrating, many businesses use them because they “can perform repetitive tasks that have some known outcomes,” such as which department your query needs to be routed to when you contact customer service for a company. 

There are limitations currently, though. While chat bots can accomplish a surprisingly large number of tasks, “they cannot operate your Tesla, for example,” said Tasker. 

What’s Next for AI?

With high return-on-investment to using chat bots and interview bots, the use of artificial intelligence in commerce is not likely to go away anytime soon. If anything, the use of AI will continue to grow in new and innovative ways. 

With an increased use in artificial intelligence comes an increase in the conversation about how it should be implemented. This is where a background in psychology could be helpful for people working in this field. "Psychology is important because it teaches a student how the human brain works, which is complicated," said Tasker. "To really learn to program AI, learning how the brain works at some basic level would help as well."

Just because a chat-bot can attend a meeting for an employee, does that mean that we should also make a bot that can perform medical exams? Where is the line? “What about facilitating a classroom and teaching our children?” Tasker asked. "What about fully autonomous truck driving?" 

Is there a line between what we need versus what we can do? And where does focusing on the bottom line financially begin to cost us when it comes to our humanity? 

These are big questions for which there are no easy answers. Yet by studying data science, math and STEM, and by embracing the change inherent in the field of machine learning and artificial intelligence, you just might be the next Wilbur or Orville Wright.

Marie Morganelli, PhD, is a freelance content writer and editor.

STEM

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