AI Use Case Scoping: Discussion Resources

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Scoping AI Use Cases for Scaling Competency Data

• T3 Phase 2 landscape analysis for skill and competency data published in 2020
  • AI Use Cases pulled directly from the Phase 2 landscape analysis for skill and competency data report
• AI Discussion Guiding Questions

Themes From Discussions

AI will play a vital role in scaling competency data that is important to all T3 Networks.  Each T3 network need reliable sources for competency data for numerous use cases and actors.

Scaling Competency Alignments and Mapping

• generating semantically-based competency alignments between competencies and other resources (e.g., credentials, assessments, learning opportunities, jobs, work roles, tasks, etc..)

Scaling Competency Analysis

• accelerating currency of competency trends
• drilling down to micro or up to macro details such as geographic significance
• protecting identity (companies and individuals)
• providing measures of competency alignment
• removing bias and increasing equity

Scaling Competency Data Search Sources

• extracting competencies with context from documents (e.g., competencies from job postings and job descriptions with the context of the job specialty)
• improving cross-competency searching (e.g., automating alignment for competency disambiguation)
• living representations of competencies (rather than static one-time information)
• providing curated data for research and benchmarking

Additional Resources

• May 4, 2022 RWSC Meeting: Guest Presentation on skillsync AI services by Robby Robson, Elaine Kelsey, and Elliot Robson with Eduworks
  • Presentation (slides 9-12) and starts at about 8:18 mins in the Video
    • skillsync Resources:
      • AI Magazine Spring Issue Vol. 43, Issue 1:  Intelligent Links: AI-Supported Connections between Employers and Colleges (pages 75-82 )
      • Supporting Companies and Colleges As They Reskill the Workforce of the Future, October 18, 2021
      • SkillSync Website
• April 20, 2022 RWSC Meeting: Guest facilitation by Matt Gee, Co-Founder & CEO at BrightHive / Senior Researcher at the University of Chicago
  • Two themes came from the discussion: (1) improving cross-competency framework search (automating alignment) and (2) providing curated data for research and benchmarking.
  • Presentation (slides 8-12), Video, Audio
• There is some similar work happing in Europe in projects related to the European Skills, Competences, Qualifications and Occupations Initiative (ESCO) that reinforces the message about how AI and machine learning can help in building frameworks of competences around which education and employment related services can cohere. Here are three reports from ESCO that are worth a look, one relatively recent and narrow, the other two a year old and broader (all PDFs):
  • The role of contextual information when connecting data to the ESCO Occupations Pillar using Artificial Intelligence
  • Leveraging Artificial Intelligence To Maintain The ESCO Occupations Pillar
  • Leveraging Artificial Intelligence To Update The ESCO Occupations Pillar
  • Slide deck from a presentation about this work given a couple of months ago at the ESCO 1.1 launch, for which there is a video at https://www.youtube.com/watch?v=YPECXVRagu8