Higher-ed plays a crucial role in filling AI engineering needs (2024)

Key points:

• Integrating AI capabilities with engineering principles can unlock unprecedented innovation across sectors
• AI, edtech can improve equity in college admissions
• Defining higher-ed policy for AI in teaching and learning
• For more news on AI in education, visit eCN’s hub

To take advantage of the generational opportunity of AI engineering, the industry must address a number of challenges–and higher education plays a pivotal role in meeting the needs of what is poised to be a critical discipline.

A new report released by theEngineering Research Visioning Alliance (ERVA), an initiative funded by the U.S. National Science Foundation (NSF), defines AI engineering as the accelerating convergence of the artificial intelligence and engineering fields to deliver benefits to society.

A late 2023 poll showed thatthe U.S. public is more concerned than excitedabout the progress of AI. At this critical turning point in its development, it is crucial that AI systems adopt the engineering discipline’s commitment to safety and systems to serve the greater good. Engineers are uniquely positioned to lead the charge in harnessing AI’s potential and shaping its future direction, according to the new report,AI Engineering | A Strategic Research Framework to Benefit Society.

At the same time, AI holds the potential to enable greater, more efficient engineering feats, provided engineers are equipped with the skillsets needed to apply AI to processes and tasks.

“This emerging fusion of the AI and engineering fields represents a profound opportunity to make breakthrough research advances as well as to address some of the most pressing challenges facing society today,” saidPramod Khargonekar, professor of electrical engineering and computer science and vice chancellor for research at the University of California, Irvine,and chair of the visioning event. “By leveraging AI to enhance engineering research and innovation and vice versa, we can achieve unparalleled progress and create a brighter future for all.”

For AI engineering to thrive, it’s essential to create new education and training programs at all levels: undergraduate, graduate, and professional education.

“Significant work is needed to determine how to expand educational efforts to meet the growing demand for people who can not only create AI but also manage it, especially in safety-critical settings. Current education efforts do not address the bold initiatives required to advance engineering education at all levels with a view to AI engineering education for the coming decade. To make a major impact on AI for engineering, we need an engineering-focused consortium across government, universities, industry, civil society, and nonprofits with a clear set of goals,” according to the report.

Engineering schools and colleges are ideally positioned to collaborate with industry and government to create programs that can build on existing strengths in data science, machine learning, and related topics. Elements of these courses and programs can be useful to current faculty and research staff.

Actions to infuse education programs with AI engineering elements include:

• At a minimum, undergraduate students in all engineering fields will require a basic course in AI fundamentals
• As generative AI-based tools proliferate across various knowledge domains, engineering educators need to confront the core issue of how to teach engineering fundamentals
• Companies could provide summer internships employing methods taught the previous semester
• For graduate education, each engineering field should devise courses for both master’s and doctoral students
• A substantial opportunity exists to develop optimized short courses and certificate programs for industry professionals to rapidly learn the aspects of AI engineering relevant to their work

AI engineering is based on the firm commitment of engineering processes and culture to ethics of safety, health, and public welfare. According to the report, AI and engineering practitioners, enabled by collaboration among government, industry and academia, can work to address 14 “grand challenges” of AI engineering that fall under three categories of action:

• Design, manufacturing, and operations: Creating secure, reliable and trustworthy AI systems, which can then allow engineers to transform manufacturing quality and efficiency, build AI-engineered systems with cradle-to-grave awareness and scale engineering as never before
• AI engineering and society:Constructing systems for safe and productive human-AI collaboration, mitigating mishaps, and ensuring ethical foundations for the technology
• National initiatives for AI engineering:Overcoming information barriers and sector and discipline silos to enable national collaboration between engineers and AI practitioners in government, industry, and academia, and also training the new AI Engineering workforce through new institutes of higher education and academic courses

In an era marked by rapid technological advancement and societal transformation, AI engineering is a pivotal discipline poised to transform the future of our world. By seamlessly integrating AI capabilities with established engineering principles, practitioners can unlock unprecedented innovation across various sectors.

AI Engineering | A Strategic Research Framework to Benefit Societyis the eighth report released by ERVA, an initiative funded by the NSF to help identify future engineering research directions. The executive summary and full report, based on a visioning event convening 28 engineering researchers from academia, industry, and government agencies, can be found on ERVA’s websitehere. Visit ERVA’s website to see the previous reports:Engineering Materials for a Sustainable Future,Engineering the Future of Distributed Manufacturing,Engineered Systems for Water Security,Sustainable Transportation Networks Engineering,R&D Solutions for Unhackable Infrastructure,Leveraging Biology to Power Engineering Impact,andThe Role of Engineering to Address Climate Change.

ERVA is funded bythe National Science Foundation.