Machine Learning Engineer, Data Scientist, Artificial Intelligence Developer, AI Software Engineer, Deep Learning Engineer, AI Systems Engineer, Cognitive Computing Engineer, Robotic Process Automation Engineer, Natural Language Processing Engineer, Computer Vision Engineer, AI Research Engineer
The notion of human-like intelligence existing within machines has been around for nearly 150 years. As you might expect, the idea was introduced in a fictional context (in the 1872 novel Erewhon). However, artificial intelligence, or AI, has been a reality for some time now. We can thank the visionary mind of Alan Turing, the famous World War II codebreaker, for the modern exploration of machine intelligence and the push to discover its limits.
Artificial Intelligence Specialists are at the forefront of this computer science movement aimed at teaching computers to think and engage with people in a human-y manner. Today, our devices use AI for speech recognition and to communicate with us as virtual assistants. AI recognizes our faces, voices, and fingerprints. It predicts and suggests, filters online search results, scans our emails for spam, translates languages, and operates machines. Most of us engage with this wondrous tech every day without thinking about it, or in some cases even realizing it.
There are, of course, credible concerns about AI and its rapid advancement. Indeed, AI Specialists are now faced with the real problem of AI ethics. One potential ethical dilemma being researched is, how do we protect ourselves from “AI bias” as we build technology that is faster and smarter than its own creators? A scary consequence of building AI that is more advanced than us is the loss of control over intelligent systems...and undesirable consequences afterward!
- Working on cutting-edge, world-changing technologies
- Making everyday life easier for millions of AI users (via devices, etc.)
- Helping businesses become more competitive
- Creating new connections between AI and the Internet of Things (IoT)
- Augmenting medical practice, potentially saving lives and improving health
- Building AI solutions for unmanned vehicle operation
Artificial Intelligence Specialists work full-time, usually indoors but some work involves outdoor activities. When a program or system malfunctions, the employer may contact workers for assistance to get things running correctly again.
- AI Specialists work in a broad field, so individual duties depend on the employer and the role the worker was hired for specifically
- Some specialists work on spam blockers and plagiarism checkers
- Others might build language translation services such as Google Translate
- Other role-dependent typical duties can include:
- Cognitive simulation modeling
- Create applied AI programs to identify and track persons based on recognition of facial features, voice, fingerprints, gait detection, heartbeat, and other factors
- Build programs to gather and interpret data and information, spot patterns, use results to determine solutions to problems and make decisions
- Work on software to help medical professionals diagnose patients
- Enhance advice-giving chatbots
- Advance technology for finding undiscovered natural resources
- Write programs to control (auto-pilot) unmanned vehicles for numerous purposes
- Push the envelope on creating smarter AI systems that can reason and learn and even program themselves and other AI
- Improve programs that simulate human vocal patterns
- Work on AI to assist in legal and financial sectors
- Collaborate with external clients and stakeholders
- Keep up with developments; attend professional organization events and conferences
- Attention to detail
- Highly organized
- Investigative and inquisitive
- Problem-solving skills
- Strong communications skills
- Able to explain complex issues in simpler terms
- Knowledge of many computer programming languages
- Systems analysis
- Natural Language Processing
- Neural networks
- Strong math skills, including calculus, linear algebra, and statistics
- Computer science background
- Strong familiarity with cognitive science
- Familiarity with anthropology, philosophy, and psychology
- Corporations/private-sector companies
- Governmental/Military agencies
- Healthcare industry
- Higher education institutions
- Research and development centers
- Scientific organizations
- Vehicle and transportation industry
Before humanity turns over the keys of society to AI, we should ensure it works the way we intend for it to work. Above, we mentioned a few concerns related to AI ethics. But there are many more expectations that AI Specialists are held liable to meet. They’re tasked with creating programs to think like humans, however the fact is that AI operates incalculably faster than us for many functions, and can be unpredictable at times.
What happens when an AI makes a mistake (or what humans consider a mistake, but is logical to the AI?). That very problem was perhaps best portrayed in 2001: A Space Odyssey, when a space vessel’s onboard AI decided the only way it could complete its programmed mission was to terminate the humans trying to abort the mission.
Luckily, Artificial Intelligence Specialists have figured that one out already. These scenarios may seem like science fiction but the hypothetical problems are taken very seriously. If evil AI does take over the Earth to destroy all humans, AI Specialists will get the blame (though not for long, obviously)!
Seriously, some of the hottest current trends are AI ethical issues. The often-mentioned Singularity is a major challenge being studied by experts who want to ensure we approach such an event very cautiously. For those who haven’t heard of it, the Singularity is a hypothetical future event at which point AI becomes so advanced we can’t control it or predict what it’ll do next. In other words, The Terminator franchise covered this topic with the fictional rise of Skynet, a military defense AI system networked into our weapons systems. It’s “self-awareness” became a Singularity event as it took control of our nuclear missiles and other machines to become an unstoppable adversary.
Aside from preventing a dystopian future, other AI industry trends include increasing cybersecurity so that humans cannot hack into AI systems, the advent of AI-enabled chips, growing the connections between AI and the Internet of Things, automated machine learning, and AI in the world of cloud computing.
This likely goes without saying, but AI Specialists were probably sci-fi fans as kids. Science fiction has exposed generations to the seemingly endless possibilities of what computer programs are capable of. Although most AI doesn’t operate within a robotic host (yet), it has reached the point that many writers predicted years ago (Eugene Goostman, an AI chatbot created by three programmers in Saint Petersburg, Russia in 2001 is widely regarded to have passed the fabled Turing Test, meaning the AI could fool humans communicating with it).
But AI enthusiasts must also have outstanding hard technical skills to go along with those creative, dream-filled minds. Workers in this field probably studied hard in school, did their research, formatted their papers properly, and paid attention to details. They were likely very logical and objective, results-oriented, and independent. Indeed, like many IT professionals in their youths, AI Specialists are often quite content to work alone and indoors for long periods, focused on the tasks at hand or perhaps lost in a world of code.
- Entry-level AI Specialists should have at least a bachelor’s, typically in computer science or a related major (or even an interdisciplinary degree like cognitive science)
- Many workers either complete a graduate degree before starting work, or they finish one while employed in the industry
- Advanced degree majors can include anthropology, philosophy, psychology, or psycholinguistics
- AI is a broad field, but typical coursework can include:
- Algebra, algorithms, calculus, logic, probability, and statistics
- Bayesian networks
- Cognitive science theory
- Computer programming languages/coding
- Graphical modeling (neural nets)
- Natural Language Processing
- Systems analysis
- AI-specific programs are the best bet if you can find them. Otherwise, look for programs that offer courses in the above-listed areas
- Cost is always a consideration. The university name on your diploma is something employers will look at, but in the end, it’s your qualifications that will land you a job
- Look for programs that list stats on student retention, or try to find student reviews of the program and/or faculty
- What’s the student-to-faculty ratio? AI is a complicated field of study, so you’ll want sufficient attention from your teachers, when you need help or have questions
- Funding and research facilities are a huge consideration. Working with Artificial Intelligence requires a ton of practice!
- The best schools typically rake in the most external funding but make sure it’s being used to benefit student learning
- Read faculty biographies! Often a handful of teachers will make up the bulk of your AI-learning experiences, so don’t just focus on the school but also on the people
- Speaking of people, what sort of AI clubs and student organizations are on campus? How active are they? Do they have any nationally recognized achievements?
- If enrolling in an IT degree, check if the program is ABET-accredited
- Consider online programs, if feasible, but remember that in-person attendance can greatly enhance the learning experience for many courses. Sometimes a hybrid program is a perfect compromise!
Great Values Colleges’ 40 Best Colleges in the U.S. for Artificial Intelligence has a strong list of schools for undergrad programs. Also, check out U.S. News’ Best Computer Science Schools and Best Artificial Intelligence Programs. As mentioned, not all AI Specialists complete degrees in AI or computer science, but these lists should get you started!
- High school students should learn everything they can prior to college, to lay a solid foundation for the hard work ahead
- Taking advanced math, programming, and other related courses is important to be prepared for that college freshman year
- Get a head start by doing short online courses (or longer certification programs), such as those offered by edX, Coursera, Udemy, Pluralsight, and more. You can also complete online coding classes or bootcamps
- In college, use electives wisely. Take classes to move you forward in your AI career
- Participate in school projects, or start your own if there aren’t any!
- Speak with your university program about ways to assist in their research centers
- Look for internships or any opportunities to get work and research experience
- Partner with peers to share knowledge and potentially find students able to guide you
- Watch tutorial videos, read books and online content, and participate in discussions
- Check out Lionbridge’s Top 18 AI and Machine Learning Subreddits for suggestions
- The best way to get the job is to be fully qualified and to demonstrate your academic and work experiences on your applications
- Take the TripleByte Quiz and they will connect you with employers if you pass the screening test
- Only apply for positions you’re a solid match for. Read the job postings carefully and make sure you can check off all the boxes
- You can find job postings on Indeed, ZipRecruiter, Glassdoor, and several other portals
- Ask your university’s department or career center about ways they can help
- If you haven’t done an internship, why not try that? It can get you in the door and help you gain work experience. Even if they don’t hire you permanently, it’s a start!
- Tell your friends and teachers, and put the word out on LinkedIn. These days, most jobs are found through networking (added to which, make sure you have a strong network!)
- Check out articles that recruiters read, to gain insights. TOPBOTS has a good one on hiring AI and Machine Learning experts
- Attend university-hosted industry fairs and other events. Ask questions, make connections, and pass out resumes!
- Speaking of resumes, make sure yours is error-free and well-written. Snag some AI resume templates to get ideas
- Read Springboard’s Artificial Intelligence interview prep questions
- Get in there and show your employer what you’re made of. Impress them early and continually with your dedication to the field and devotion to the organization
- Turn yourself into an invaluable subject matter expert able to fix things!
- Don’t stop learning. This is a constantly evolving field, with breakthroughs happening around the world. Keep tabs on international AI news, take courses, and finish your graduate degree(s)
- Be a consummate professional, on the job and when “off duty.” In today’s online world, one questionable deed can come back to haunt you, so keep your digital footprint clean
- Show the boss that you can be a boss, too. Demonstrate leadership potential and take the lead on team projects when you can
- Often there are work suspenses to meet, so make your deadlines but don’t take shortcuts. Quality counts and tiny errors can lead to a ripple effect of consequences
- AI Specialists are there to solve problems but also to push boundaries. In other words, part of the job is to propose new problems (aka challenges!) to overcome. Don’t be afraid to throw out some “what if…?” questions for brainstorming
- American Association for the Advancement of Science
- American Mathematical Society
- American Society for Engineering Education
- Association for Computing Machinery
- Association for the Advancement of Artificial Intelligence
- Center of Excellence for Information and Computing Technology
- Computing Research Association
- European Association for Theoretical Computer Science
- The Association for Uncertainty in Artificial Intelligence
- International AI associations
- 2084: Artificial Intelligence and the Future of Humanity, by John C. Lennox
- AI Crash Course: A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python, by Hadelin de Ponteves
- Artificial Intelligence: A Modern Approach (4th Edition) (Pearson Series in Artificial Intelligence), by Stuart Russell and Peter Norvig
- Artificial Intelligence Basics: A Non-Technical Introduction, by Tom Taulli
- Artificial Intelligence For Dummies, by John Mueller and Luca Massaron
- You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It's Making the World a Weirder Place, by Janelle Shane
The concept of working as an Artificial Intelligence Specialist can seem inspiring, but the reality is sometimes not as exciting as the idea itself. This career field is unlike virtually any other because workers are in many ways literally creating it as they go. They’re exploring uncharted territories, and don’t always know what they’re even looking for! That’s why many students opt to consider other job possibilities, such as:
- Computer Science Teachers
- Computer Systems Analysts
- Computer Systems Engineers/Architects
- Remote Sensing Scientists and Technologists
- Software Developers, Systems Software