In 2012, Tom Davenport and DJ Patil declared in the Harvard Business Review that data scientists are "the sexiest jobs of the 21st century." Since then, universities have been ramping up data science education. While there is still a shortage of data scientists graduating from college, the coming AI revolution will require a fundamental shift in education — not just for the data scientists who build AI applications, but for those of us who live with them.
According to the Data Science Project website, more than 500 universities across the United States offer data science degree programs. In total, there are more than 980 disciplines, of which the Master of Data Science is the most popular. According to past data shared by the site, this number has increased significantly in recent years.
Martial Hebert, dean of the School of Computer Science at CMU-Carnegie Mellon University, said that while the supply of data scientists from universities has increased, strong business demand for them still outweighs supply.
By expanding its data science degree program, CMU has been at the forefront of data scientists and AI experts. Carnegie Mellon University was the first university in the United States to offer a bachelor's degree in artificial intelligence and remains the only school in the country to offer such a program, said Herbert, who joined Carnegie Mellon University in 1984 as a researcher in computer vision and autonomous systems.
Finance is no longer just finance, but finance and artificial intelligence. Political science is no longer just political science, it is political science and artificial intelligence. From healthcare to agriculture, from the military to mining, many academic and humanities disciplines are somehow reinventing AI.
Herbert said: "The prospect in this field is that we will see more and more developments in artificial intelligence and other new disciplines." "For example, there's been a lot of development in automated science and AI for scientific discovery, and it's not just about applying the AI tools out there to some scientist stuff here." It's really about bringing them together and creating a whole new discipline. ”
These new disciplines are beginning to take root. CMU has a new graduate program that allows students to apply AI extensively, called the Master of Science in Artificial Intelligence and Innovation. Herbert said the company is also working on a new degree program at the Heinz School of Public Policy that will explore the use of AI in public policy, including topics around bias and equity. Students entering these graduate programs will be required to have a solid technical understanding of data science, just like students pursuing a traditional data science degree, typically taught in the computer science department. These courses will go beyond the core understanding of data science to enter the field of artificial intelligence, creating an environment for students to create new tools and techniques for specific disciplines.
Of course, not all courses can benefit from ARTIFICIAL intelligence. For example, it's hard to see how the study of literature or Renaissance art would benefit from AI. But AI also seems to have clear applications in other aspects of the humanities, such as journalism or music.
But Herbert's vision goes beyond creating degree programs that combine traditional curriculum and artificial intelligence. He hopes to teach AI topics widely in schools at all levels, including K-12. As AI plays an increasing role in society, having a mass that understands how it adapts and can work with AI will benefit future societies.
It is important for students to understand the capabilities and limitations of AI so that they can address these issues. "If you don't have a technical background, if you don't know the details of this system, at least you know how to evaluate them, how to compare them, how to predict where these problems will be encountered, and so on," he said.
The collective proliferation of computer vision, natural language processing (NLP), traditional machine learning, and advanced analytics capabilities is setting off a wave of data-based automation and innovation around the world.
Three years ago, McKinsey predicted that the impact of AI would reach $13 trillion by 2030. After witnessing the accelerated digital transformation due to COVID-19, this number may actually be underestimated. This makes it all the more important to understand the fundamental limitations of AI technology, as it will have a greater impact on the world and affect more people at the same time.