Transparency is an equity issue. Adding common language and richer data on skills and competencies to credentials means: * More data about courses/module * Learning outcomes from those modules * Connect to evidence of achievement * Refer to occupational standards/competency frameworks

Clearly, the LinkedIn recommendations use case is an example of one of these initiatives. It has not succeeded in creating strong social signals anchored in trust models. We are wise to consider what's missing from efforts like this. An even greater concern however, and one that I believe is an essential if we are to realize the transformative potential of digital credentials, is how to design social signals built on trust models that help all people. In a world long-governed by "it's not what you know, it's who you know," the social signals and trust models are overweighted in favor of people with connections to other people, organizations and brands that are all to some degree legacies of exclusionary and inequitable systems. We are likely to build new systems that perpetuate the same problems if we do not intentionally design them to function otherwise. For people (especially those from historically underserved populations) worthy of the recommendations but lacking in social connections, how do they access social recommendations built on trust models?

Helping earners appropriately articulate their own skills is an equity issue.