Today’s data volumes are mind-boggling. It’s why corporations and governments alike are looking to machine learning (ML), natural-language processing (NLP), neural networks and other forms of artificial intelligence (AI) to understand, analyze and act on our oceans of information.
Trouble is, there aren’t enough AI-educated people to fill the skyrocketing demand for AI expertise. And it’s not just PhDs in data science who are needed. Organizations require skills and experience in many capacities to realize the full promise of AI.
In response, IT providers are investing in AI education. In particular, they’re supporting AI course programs at technical and community colleges – to equip the workers of today and tomorrow with the knowledge and skills that will underlie the AI capabilities of the future.
Growing demand for AI skills and education
Right now, the fastest-growing jobs are data analysts and scientists, AI and ML specialists, and big data specialists, according to the World Economic Forum Future of Jobs Report 2020. AI is also among the top 20 “cross-cutting specialized” skills, along with competencies such as digital marketing, software development, and human-computer interaction.
Educators are aware of these trends, suggests a survey of community colleges, vocational colleges, and four-year colleges and universities conducted by FedScoop.
More than one-half of educators say AI is the area of study that will see the highest increase in demand in the next three years. And well over two-thirds sense increasing demand from employers for graduates with AI skills.
Yet 52 percent said the biggest obstacle to adding AI programs to their curriculums is lack of instructors with subject-matter expertise. And 59 percent said they needed help with professional development from industry.
Better diversity for better AI
Many four-year computer science programs cover AI – but often not till the third or fourth year. For students who can’t afford or choose not to pursue a four-year degree, AI education has remained largely out of reach.
That’s not a good situation for many current and future workers, nor is it ideal for the companies that want to employ them. After all, AI is a team sport. You can’t do effective AI with just one employee or just one type of employee. AI requires the contribution of people from diverse communities and experiences.
Here’s an example of why. In 2018, Joy Buolamwini, then a researcher at MIT Media Lab, led a study finding that facial-analysis programs offered by major IT companies were biased based on gender and skin color. For instance, error rates were 0.8 percent for light-skinned men but 34.7 percent for dark-skinned women. That kind of bias can be introduced unintentionally based on the datasets used to train ML algorithms. The more diverse perspectives we bring to AI, the more likely we’ll be effective in rooting out built-in bias to make AI more accurate, equitable and useful.
But working in AI requires foundational knowledge and skills. Not every AI professional needs to know how to program in Python or load a panda library into Jupyter Notebook. But they do need to know what that means. They need to understand the difference between a linear regression and a convolutional neural network regression. Just as important, they need to know how to ask the right data-analytics questions to get to the best AI answers.
Hitting an AI education sweet spot
Those are among the reasons that AI education programs are so necessary at universities – especially programs designed specifically for technical and community colleges. The schools should incorporate AI education to augment existing courses or develop AI certificate or associate degree programs.
Ocean County College, a community college in New Jersey, offers both a certificate in AI and a two-year associate in applied science degree. While students must have a degree in computer science or equivalent industry experience to enter the certificate program, no background knowledge is needed to enroll in the applied science degree program.
Students in either program can pick and choose the courses that are the most interesting or relevant to them, but often progress from intro to AI – available across majors – to more in-depth courses focused on ML, NLP, and other AI topics.
Graduates of the certificate and two-year associate programs are prepared to enter the workforce and immediately work in AI – graduates of the program have gone on to work in industries including tech, healthcare, automotive, manufacturing and aerospace. They often obtain roles such as AI/ML specialist, data scientist, process automation specialist, or computer systems analyst, among others.
Some graduates choose to not enter the workforce immediately, as the program also provides a path to pursuing a four-year degree in computer science or related fields. Overall, the program enables students to gain technical confidence in AI, increases employability and teaches students how to apply their AI education to address challenges in whatever industry field or career path they pursue.
But it won’t just be those in technical roles who harness the power of AI. Professionals in marketing, finance, manufacturing, healthcare, and other industries and lines of business will also use AI. They’ll apply AI to do everything from identifying the best candidate for a job, to adjusting traffic lights to improve safety, to finding cures for diseases like COVID-19.
By providing AI knowledge and skills to a diversity of students, technical and community colleges can democratize AI education – and advance the democratization of AI solutions that will drive the future of business and society.
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