A Howard University-led consortium is working to investigate the current state of artificial intelligence jobs by developing a multi-disciplinary national network with a goal of predicting future trends in the AI job market. 

Howard mathematics professor Dr. Talitha Washington is the principal investigator of the project, “Research Coordination Network on Assessing and Predicting Job Outcomes in AI,” a new initiative aimed at analyzing the evolving AI job landscape. The two-year project, which is funded by a nearly $500,000 grant from the National Science Foundation, will involve establishing a national Research Coordination Network (RCN) that brings together key stakeholders across varying sectors, disciplines, and organizations to better classify trends in the AI job market. According to Washington, the main purpose of the network is to better understand what AI jobs are with a goal of predicting future trends in the sector to build a stronger AI workforce. Current AI-related job roles include AI research scientists, robotics and machine learning engineers, AI ethics specialists, and UX designers. 

The RCN will focus on answering three core questions: What defines an AI or AI-adjacent job, what AI skills are needed, and how do we build AI credentials and curricula? Washington, who is the executive director of Howard’s Center for Applied Data Science and Analytics, said that the network will work to “create some grounding documents for people across multiple sectors to know what AI jobs are. This is not a traditional research project.”  

Preparing the Workforce for AI 

The RCN will be comprised of a collection of members and collaborative partners who are guided by a steering committee to generate insights from a series of convenings and workshops focused on AI jobs. Drawing on input from educators, industry leaders, government agencies, workforce innovators, and the broader public, the RCN will accelerate the development of strategies to strengthen the nation’s ability to respond to emerging AI workforce needs through public-private partnerships. The network will produce synthesis reports, workshop proceedings, curated labor data dashboards, and a public-facing knowledge base website. 

The project is part of Howard’s ongoing AI initiative, which includes academic scholarship that aims to advance the frontiers of AI through cutting-edge research and innovation. This also includes the university's recent outreach efforts to educate emerging college students on industry careers in tech and other AI-related jobs. Washington is the co-chair of the university’s AI Advisory Council and noted that this new research initiative will help better equip students for an AI-driven job market.  

“In our council meetings and various collaborations, the ideas that kept coming up included what students need to know about AI jobs,” Washington explained. “What does AI look like on the job and what does that really mean? Carving out a space where we can [explain these things] through this national network will be helpful.” 

The project is a collaborative effort with co-principal investigators Enrico Pontelli of New Mexico State University, Siobahn Grady of North Carolina Central University, and George Brown of Houston Community College. At the end of the two-year RCN project, Washington’s team will develop a synthesis capstone workshop that will consolidate the group’s findings  

In addition to this project, Washington is convening a virtual workshop for Howard faculty and staff on “AI and the Future of Higher Education” Sept. 17.