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Forward-thinking technology companies are advocating for science, technology, engineering, and mathematics (STEM) curricula in the United States, according to Facebook artificial intelligence (AI) experts Yann LeCun and Joaquin Quinonero. The duo cites algebra, calculus, probabilities and statistics courses as important training for tomorrow’s workforce. For newer sciences such as machine learning, report the pair, a firm grasp of differential equations and statistics is vitally important. In fact, the AI specialists believe that statistics play an important role in nearly all areas of life.
The pair also remarks that computer science, economics, math engineering and neuroscience are important learning paths for tomorrow’s professionals. To round off these skills, the AI leaders suggest that students pursue training in philosophy to gain a better understanding of the human learning process. In this regard, the two scientists state that philosophy is important, because behind every machine lies a human operator.
After advancement, AI graduates will face the challenge of finding gainful employment. According to LeCun and Quinonero, the smartest move for graduates will be to work with a professor or doctoral student in finding an industry specific internship to learn how to use artificial intelligence for real world applications.
Make It Happen: Getting Started With AI
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The artificial intelligence field is rapidly changing and maturing. Today’s computer science majors have an exciting future waiting for them. The field is well-suited for candidates that are interested in computers, think analytically and enjoy reading and learning about the latest technological developments.
Artificial intelligence specialists work with massive amounts of information, so analytical thinking is especially important for success in the field. To thrive in the field, specialists must devise creative ways to use information for discovering practical solutions that help organizations to meet objectives.
Artificial Intelligence in Action
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In the AI and machine learning disciplines, there exists a conundrum where scientists understand that the technology works but not exactly how, a phenomenon call the black box problem. In the most basic sense, artificial intelligence is a tool, requiring skill and expertise for effective implementation. In the work setting, AI experts are responsible for choosing specific machine learning programs based on whether the tool will deliver the needed outcome. Additionally, effective specialists ensure that enterprises don’t blindly fall into the trap of relying on artificial intelligence reports, remembering to always maintain a balance between computer-aided decision-making and human intervention.
Tomorrow’s AI leaders will man the helm of change initiatives designed to make better use of existing enterprise benchmarks, metrics and data stores. In addition to their advanced technological expertise, computer scientists must possess exemplary communications skills to lead their respective organizations forward into a marketplace empowered by AI. An example of this kind of innovation in the CompStat data-driven policing management system introduced in 1994. A year after its launch, the crime rate in the United States dropped 12-percent. Since then, municipalities across the United States have enjoyed a 49-percent decrease in violent crime and a 51-percent drop in property crime.
Organizations will task the computer science leaders of tomorrow with engineering programs for exactly this kind of real world innovation. In this field, successful AI specialists will hire and lead team members who have an intimate knowledge of how a given organization collects and uses information. While policing agencies may never develop the awe-inspiring predictive capabilities displayed in Steven Spielberg’s rendition of the future called Minority Report, the marriage of artificial intelligence, machine learning and criminal justice may make America much safer.
Taking the Reigns
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In the modern marketplace, organizations implement artificial intelligence technology for customer service management and to alleviate workers of mundane, repetitive tasks. The information technology leaders of the future, however, are up for a bigger challenge in finding ways to do more work faster, and with less waste.
The experts will have to dive deep to discover how AI technology can help enterprises implement vital decision-making language at a higher level to maximize the potential of the tool. Chatbots that ask basic questions and then wait for human intervention do not fully exploit the ability of this bold and relatively novel technology. In the future, artificial intelligence specialists will automate not only minute task, but entire business processes.
Computer science is the ideal learning track for prospective students who want to tap into the full potential of their curiosity. Whether it’s for a career change or a career launch, potential learners make a wise choice when deciding to take the first step toward earning a high demand computer science skill.
References:
Maryville University – Going Back to School for Computer Science
O’Reily – 4 Tips to Stop Reading About AI & Start Doing AI
Tech Crunch – Facebook’s Advice to Students Interested in AI
University of Cincinnati – The Future of Policing With Compstat
