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This article presents the background and vision of the Skills-based Talent Ecosystem for Upskilling (STEP UP) project. STEP UP is a collaboration among teams participating in the US National Science Foundation (NSF) Convergence Accelerator program, which supports translational use-inspired research. This article details the context for this work, describes the individual projects and the roles of AI in these projects, and explains how these projects are working synergistically towards the ambitious goals of increasing equity and efficiency in the US talent pipeline through skills-based training. The technologies that support this vision range in maturity from laboratory technologies to field-tested prototypes to production software and include applications of Natural Language Understanding and Machine Learning that have only become feasible over the past two to three years. 

We describe a human-centered and design-based stance towards generating explanations in AI agents. We collect questions about the working of an AI agent through participatory design by fo- cus groups. We capture an agent’s design through a Task-Method-Knowledge model that explicitly specifies the agent’s tasks and goals, as well as the mechanisms, knowledge and vocabulary it uses for accomplishing the tasks. We illustrate our approach through the generation of explanations in Skillsync, an AI agent that links companies and colleges for worker upskilling and reskilling. In particular, we embed a question-answering agent called AskJill in Skillsync, where AskJill contains a TMK model of Skillsync’s design. AskJill presently answers human-generated questions about Skillsync’s tasks and vocabulary, and thereby helps explain how it produces its recommendations. 

Motivated by the need to rapidly and equitably upskill workers in response to technological advances and social change, a team funded by the US National Science Foundation Convergence Accelerator program has developed and piloted an application called SkillSync that (i) helps employers identify and communicate the skills their workers require; (ii) connects employers to non-degree college programs that can provide relevant training; (iii) helps those programs align their offerings with employer requirements; and (iv) facilitates the exchange of proposals to offer training. This paper describes SkillSync and explains how Artificial Intelligence (AI) is used to automate skills extraction and align training resources with training requests. This paper then discusses the steps taken to ameliorate possible biases and an intelligent agent that is included in SkillSync to increase transparency and trust in the application. The methods discussed in this paper are applicable to many classes of applications that use AI in training, education, and talent management