AI Use Case Scoping: Discussion Resources

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Scoping AI Use Cases for Scaling Competency Data

The AOC (formerly RWSC) interspersed AI scoping in multiple meetings and held two meetings focused on use cases for scaling competency data. The following resources were used for discussions.

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
  • validating data-justified specificity of statements, e.g. determining if competencies within a task are defined at a measurable level or left to too much human interpretation and if sufficiently contextualized. I.e. finding the poorly defined statements.

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