Artificial intelligence (AI) has come to define society today in ways we never anticipated. AI makes it possible for us to unlock our smartphones with our faces, ask our virtual assistants questions and receive vocalized answers, and have our unwanted emails filtered to a spam folder without ever having to address them.
These kinds of functions have become so commonplace in our daily lives that it’s often easy to forget that, just a decade ago, few of them existed. Yet while artificial intelligence and machine learning may have been the topic of conversation among science fiction enthusiasts since the ’80s, it wasn’t until much more recently that computer scientists acquired the advanced technology and the extensive amount of data needed to create the products we use today.
The impact of machine learning and AI doesn’t stop at the ability to make the lives of individuals easier, however. These programs have been developed to positively impact almost every industry through the streamlining of business processes, the improving of consumer experiences, and the carrying out of tasks that have never before been possible.
This impact of AI across industries is only expected to increase as technology continues to advance and computer scientists uncover the exciting possibilities of this specialization in their field. Below, we explore what exactly artificial intelligence entails, what careers are currently defining the industry, and how you can set yourself up for success in the AI sector.
What is Artificial Intelligence?
The term “artificial intelligence” has many connotations, depending on the specific industry it is used in. Most often, however, “when people say ‘artificial intelligence,’ what they actually mean is machine learning,” says Bethany Edmunds, associate dean and lead faculty in the computer science master’s program within the Khoury College of Computer Science. “[Although AI] is a large umbrella term that incorporates a lot of statistical methods, historically, what it actually means is a computer acting like a human.”
The ability for a computer to replicate human-like behavior is at the core of all AI functions. Machine learning software allows computers to “witness” human behavior through the intake of data. These systems then undergo advanced processes to analyze that data and identify patterns within it, using those findings to apply the discovered knowledge and replicate the behavior.
Edmunds identifies that, while advanced technology is important in this process, the key to the operation is actually the data. In fact, the astounding increase in the quantity of data collected over the last decade has had a significant impact on the advancement of the AI industry today.
“What’s happening right now is that the technology has finally caught up to what people have been predicting [about AI] for a long time,” she says. “We finally have the right amount of data and the advanced machines that can process that data, which is why, right now, [AI] is being applied in so many sectors.”
Despite the exciting opportunities that these advances are bringing to light, some individuals are still quite skeptical about the use of AI. Edmunds believes that this is due, in large part, to a lack of understanding about exactly how these processes work and the fear that comes with that.
“I like to equate [the introduction of AI] to cloud computing; while people don’t necessarily know how Google Drive works, they understand the concept and are faster to participate in…putting their information in cloud storage,” she says. “AI is not like that. People don’t understand the statistics behind it…so it all just seems very magical.”
Those who have a complex understanding of computer science and statistics, however, recognize that the potential impact of this function is endless. “AI is doing amazing things today and allowing for developments across industries that we’ve never seen before,” Edmunds says.
5 Top Careers in Artificial Intelligence
As the possible applications of AI continue to increase, so does the positive career potential for those with the skills needed to thrive in this industry. The World Economic Forum’s “The Future of Jobs 2018“ report predicts that there will be 58 million new jobs in artificial intelligence by 2022.
However, those with the necessary combination of skills are often hard to come by, Edmunds explains. “The job market is really huge in [AI], but a lot of people aren’t trained for it,” she says, resulting in an above-average job outlook for those who do have the skills needed to work in this niche area.
Read on to explore some of these top careers defining the industry today.
1. Data Analytics
With data at the heart of AI and machine learning functions, those who have been trained to properly manage that data have many opportunities for success in the industry. Though data science is a broad field, Edmunds emphasizes the role that data analysts play in these AI processes as one of the most significant.
Responsibilities: Data analysts need to have a solid understanding of the data itself—including the practices of managing, analyzing, and storing it—as well as the skills needed to effectively communicate findings through visualization. “It’s one thing to just have the data, but to be able to actually report on it to other people is vital,” Edmunds says.
Education & Training: Those looking to excel in the field of analytics as it relates to AI and machine learning should consider either a master’s degree in analytics or a master’s degree in computer science with a specialization in data science.
2. User Experience
User experience (UX) roles involve working with products—including those which incorporate AI—to ensure that consumers understand their function and can easily use them. Although Edmunds emphasizes that these roles do exist outside of the artificial intelligence sector, the increased use of AI in technology today has led to a growing need for UX specialists that are trained in this particular area.
Responsibilities: In general, user experience specialists are in charge of understanding how humans use equipment, and thus how computer scientists can apply that understanding to the production of more advanced software. In terms of AI, a UX specialist’s responsibilities may include understanding how humans are interacting with these tools in order to develop functionality that better fits those humans’ needs down the line.
Did You Know: One of the most prominent examples of how user experience influenced technology we know today is Apple. The invention of Mac operating software—compared to Windows—came from the need for a product that was more user-friendly and which didn’t require an advanced technical understanding to operate. Apple approached the development of the iPhone in the same way. “The iPhone was all about user experience,” Edmunds says. “That was a [user experience expert] understanding how people interact [with their phones], including what’s intuitive and what’s not. Then they designed the best possible phone to fit those needs.”
Job Outlook: The job outlook for user experience designers is quite positive. The average salary for UX designers is $73,971 per year (though those at the top of their field make over $100,000 annually). Job growth in this industry is expected to increase by 22.1 percent by 2022, effectively increasing opportunities for those with the right training and experience.
Education & Training: Earning a master’s degree in computer science can be beneficial for those looking to pursue a career in user experience for technology.
3. Natural Language Processing
Many of the most popular consumer applications of AI today revolve around language. From chatbots to virtual assistants to predictive texting on smartphones, AI tools have been used to replicate human speech in a variety of formats. To do this effectively, developers call upon the knowledge of natural language processers—individuals who have both the language and technology skills needed to assist in the creation of these tools. “Natural language processing is applying machine learning to language,” Edmunds says. “It’s a really big field.”
Responsibilities: As there are many applications of natural language processing, the responsibilities of the experts in this field will vary. However, in general, individuals in these roles will use their complex understanding of both language and technology to develop systems through which computers can successfully communicate with humans.
Career Outlook: “There’s a real shortage of people in these roles [today],” Edmunds says. “There are a bunch of [products] where we’re trying to interact with a machine through language, but language is really hard.” For this reason, those with the proper skill sets can expect an above-average salary and job outlook for the foreseeable future. The average annual salary for those with natural language processing skills is $107,000 per year.
Education & Training: Those hoping to pursue a career in natural language processing should consider a master’s degree in computer science with a specialization in human-computer interface.
4. Computer Science & Artificial Intelligence Research
Although many of these top careers explore the application or function of AI technology, computer science and artificial intelligence research is more about discovering ways to advance the technology itself. “There will always be somebody developing a faster machine,” Edmunds says. “There’s always going to be somebody pushing the edge, and that [person] will be a computer scientist.”
Responsibilities: A computer science and artificial intelligence researcher’s responsibilities will vary greatly depending on their specialization or their particular role in the research field. Some may be in charge of advancing the data systems related to AI. Others might oversee the development of new software that can uncover new potential in the field. Others still may be responsible for overseeing the ethics and accountability that comes with the creation of such tools. No matter their specialization, however, individuals in these roles will work to uncover the possibilities of these technologies and then help implement changes in existing tools to reach that potential.
Career Outlook: As these individuals are at the crux of advancement in AI, their job outlook is very positive. The New York Times estimates that high-level AI researchers at top companies make more than $1,000,000 per year as of 2018, with lower-level employees making between $300,000 and $500,000 per year in both salary and stock. Individuals in base-level AI research roles are likely to make an average salary of $83,490 annually.
Education & Training: Due to the extensive need for a background in not only applied statistics but also mathematical theory, many of these research roles require a master’s or P.h.D in computer science.
5. Software Engineering
The AI field also relies on traditional computer science roles such as software engineers to develop the programs on which artificial intelligence tools function.
Responsibilities: Software engineers are part of the overall design and development process of digital programs or systems. In the scope of AI, individuals in these roles are responsible for developing the technical functionality of the products which utilize machine learning to carry out a variety of tasks.
Career Outlook: The Bureau of Labor Statistics predicts a growth rate of 21 percent—much faster than average—by 2028 for software developers, including the addition of 284,100 jobs. Software engineers also make an average salary of $84,336 per year, with potential increases for those with a specialty in AI.
Education & Training: Individuals hoping to achieve a successful career in software engineering should have a master’s degree in computer science. Those looking to then design software specifically for AI should also consider programs with a concentration in artificial intelligence.
Establishing a Career in AI
Artificial intelligence is a lucrative field with above-average job growth, but the industry remains competitive. Roles in this discipline are very niche, requiring both an advanced technical background and extensive hands-on experience. Those with this rare balance of skills and real-world exposure will be able to land any number of roles in AI and continue shaping the landscape of this constantly evolving field for years to come.
Hone Your Skills
Artificial intelligence professionals share an array of practical skills and theoretical knowledge in mathematics and statistics, alongside a working understanding of role-specific tools and processes. Some AI-focused computer scientists may also pursue an understanding of the ethics and philosophy that go into giving a computer the capability to “think” and draw conclusions.
However, Edmunds emphasizes that, while quite advanced, these common abilities alone do not always set an individual up for a successful career in artificial intelligence. Instead, she explains, it’s the personal backgrounds and unique interdisciplinary skills each computer scientist brings to the table that allow them to thrive.
“One of the most important factors of AI is an understanding of the application,” she says. “Somebody needs to look at the data [these tools use] and understand what that actually means for their specific sector.”
In healthcare, for instance, an ideal AI specialist would have an understanding of data and machine learning, as well as a working knowledge of the human body. In this scenario, the specialist’s background in both areas allows them not only to interpret the conclusions of these AI tools, but also understand how they fit into the broader context of health.
Edmunds has also observed that, while a computer scientist with a dual background is ideal for the new kinds of applications of AI across industries, very few currently exist. “If you had a dual background, you would be able to write your own check,” Edmunds jokes. “I can assure you, you wouldn’t be looking for a job right now.”
Instead of this ideal candidate, those in AI often see machine learning experts with high-level computer science and statistics abilities but without a further grasp in any particular domain. This, Edmunds identifies, is the missing piece needed for further sector-specific AI advancement.
To bridge this gap, computer science programs like those at Northeastern look to embrace students’ personal backgrounds or prior career paths and develop artificial intelligence specialists with the ability to make a real difference across industries.
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Earn an Advanced Degree
Those looking to either break into or advance their careers in computer science can benefit from obtaining a master’s degree at a top university like Northeastern.
Both Northeastern’s general master’s in computer science program and Align program aim to develop professionals that have a well-rounded understanding of their field alongside an in-depth knowledge of a specific area such as AI.
The Align Master of Science in Computer Science Program offers students with a bachelor’s degree in a field other than computer science the unique opportunity to pursue an advanced computer science education while bringing with them a set of interdisciplinary abilities from their undergraduate career. These types of students, Edmunds explains, are the key to bridging that gap between AI technology and disciplines like healthcare, marketing, biology, and more.
“Khoury [College of Computer Science] is specifically good at recognizing that people can have different backgrounds and skills,” Edmunds says. “They look at the application of computer science in different ways to allow you to weave [your past experience in] with your future career.”
Those hoping to work in AI who already have a bachelor’s in computer science or technology should instead consider a master’s in computer science degree with a specialization in artificial intelligence or a Master of Science in Artificial Intelligence degree, both of which are offered at Northeastern. Either degree will allow students to hone their skills, learn from top industry leaders, and obtain the real-world experience they need to properly develop their career.
These practices allow Northeastern’s students to prepare for their future in the changing field of artificial intelligence while always keeping the real-world aspect of their work in mind. “Through experiential learning and interdisciplinary integration, [Northeastern’s] master’s programs are focused on developing the professional,” Edmunds says. “All the course work is centered around real-world problems or application domains, and we do our best to get industry practitioners in the classroom to make sure what we’re doing is cutting edge.”
While Northeastern emphasizes the benefits of experiential learning across all of its graduate and undergraduate programs, these opportunities allow computer science students specifically to practice what they’re learning in the classroom at some of the top companies in the world.
Did You Know: Northeastern has developed an array of regional campuses in locations across North America that are known for their top tech talent, including Seattle, the San Francisco Bay Area, Toronto, Charlotte, and Vancouver. These regional locations have allowed unique partnerships to develop between the university and local organizations, which happen to be among the top companies in the world. Popular co-op locations for computer science students in these areas include Amazon, Facebook, Microsoft, Nordstrom, and Google, alongside many other leading organizations.
Northeastern’s computer science programs provide the rare opportunity to learn from top industry leaders, work with some of the most famous companies in the world, and develop not only relevant computer science skills but those which align with your preferred specialization all before you graduate. Consider enrolling in one of our top programs in your location today and take the first step toward a fulfilling career in the exciting artificial intelligence field.