AI Engineering: A Strategic Research Framework to Benefit Society

Abstract

The strategic convergence of artificial intelligence (AI) and engineering, envisioned as AI Engineering, represents a generational opportunity to supercharge engineering for the benefit of society through enhancements to national competitiveness, national security, and overall economic growth. AI Engineering is a nascent field arising from this convergence and synthesis that will advance our nation’s interests by leveraging the traditional strengths of engineering disciplines with breakthrough developments in the field. AI Engineering will be bidirectional and reciprocal: it evokes a future vision in which an engineering approach makes for better AI while AI makes for better-engineered systems. AI Engineering is based on the firm commitment of engineering processes and culture to ethics of safety, health, and public welfare and is a principal term used throughout this report.

Engineering for AI. Engineering disciplines will bring their domain knowledge, techniques, tools, and culture to the creation of new forms of explainable, trustworthy, and reliable AI-enabled cyber-physical systems. Knowledge, tools, and techniques from engineering will revolutionize the hardware on which AI is realized. Building on existing connections between AI and engineering fields such as signal processing, information theory, and control theory, the next generations of AI methods, models, and algorithms will be created. The most important benefits of these interdisciplinary fusions will come via the increased assurances of safety, reliability, and trustworthiness, as well as energy efficiency and environmental sustainability of AI-enabled cyber-physical systems.

AI for engineering. Increasingly capable AI tools can transform fundamental disciplines of engineering science. They will also transform major engineering endeavors of design, manufacturing, and infrastructure. These changes will impact the cost, performance, efficiency, customizability, and sustainability of engineered products and systems. They will also significantly enhance the productivity and capabilities of engineers across the full spectrum of the discipline: practicing engineers, engineering researchers, engineering educators, and engineering students.

The U.S. engineering enterprise is positioned to lead in the research and education necessary for the creation and development of AI Engineering, thereby enhancing U.S. leadership in AI and engineering technologies. Engineering researchers must assist with defining future AI systems through the evolution of existing and new systems, even as they employ existing AI systems to help drive the future of engineering.

AI Engineering has the potential to impact each of the 14 grand challenges articulated by the National Academy of Engineering. To define AI Engineering, develop key strategies and initiatives, and identify innovative lines of research, a group of researchers, industry leaders, policymakers, and other stakeholders were brought together on Nov. 7- 8, 2023, at a visioning event convened by the Engineering Research Visioning Alliance (ERVA). During the two-day event, 28 participants generated and refined critical grand challenges at the intersection of engineering and AI that face engineering researchers now and in the next decade. Grand challenges were identified in three thematic areas: Design, Manufacturing, and Operations; AI Engineering for Humans and Society, and National Initiatives for AI Engineering. The full report discusses a dozen specific engineering research directions to catalyze the AI Engineering landscape.

Keywords: Artificial Intelligence, AI, AI Engineering, Engineering AI, AI Education, AI Human interface

JEL Classification: Z10, I23, I28, L52