Human resources technology probably isn’t something education providers think about much, but HR Tech is undergoing transformational changes that will impact how most people advance their career. At last week’s HR Open Standards annual meeting in Toronto, several HR companies showcased how they are using artificial intelligence (AI) to improve their products. Somen Mondal CEO of Ideal highlighted how most people have a very poor experience applying for jobs and that AI could can be used in several ways to positively engage applicants, such as by contacting applicants more quickly, providing candid feedback, and rediscovery of other positions. IBM presented a Watson-powered chatbot that tripled the historical rate at which website users applied for jobs. Several other speakers directly addressed concerns about AI applications such as cost, privacy, efficacy, governance, and equity; often by highlighting current problems with human-mediated solutions and describing how AI might lead to improvements.
While AI focused attendees’ attention, the most consequential outcome of the week was the announcement of the HR OpenStandard’s approval of the HR-JSON 4.1 data exchange specification by board president Andrew Cunsolo‘s,VP of Product Development at Talemetry. Reaching this goal was no easy feat; organizational volunteers working across ten different projects and committees collaborated to make this specification successful with supporting documentation on specific use cases including descriptions, actors, narrative user stories, steps, diagrams, alternatives, variations, and sample payloads. This detailed work on interoperability is often quite tedious and rarely recognized sufficiently, but interoperability is critically important to many of our most impactful innovations. Today, standardized data exchanges permeate our lives— think about how often you use cell phones, email, web pages, credit cards, or even just book a hotel room. AI applications are particularly dependent on open specifications to access data required for predictive models and to ensure optimization of one use case (such as, recruitment) doesn’t come at the expense of another (such as, retention). As HR products support open data specifications, HR professionals can expect continued innovations that help them be even more effective and valuable to their organizations.
The implications for education providers seem clear; employers will expect educational credential data to connect with their HR technology systems. Meeting this expectation will be a challenge. While there are many encouraging pilots across higher education, the truth is we have a very long way to go. Last week, Credential Engine released its first credential inventory that conservatively estimated over 300,000 credentials in the United States alone, not including the significant number of non-credit certificates, credentials from non-Title IV institutions, non-registered apprenticeships, or badges. With this many credentials, we can’t continue to rely on paper documents. Credential Engine is committed to modernizing educational credentials via an open, linked-data registry. Since recently launching the registry already contains over 1,800 credentials, which is an impressive start but many more are needed and that’s where you can help by publishing your educational credentials. Our technical approach for publishing is flexible to the scale and needs of your institution, with multiple methods supported including a manual editor, bulk upload, API, trusted third-party publishing, and self-publishing via JSON-LD. To get started helping students find relevant offerings and advancing the future talent marketplace, click on this brief overview and then set up an account with the Credential Registry.
About the Author: Jeff Grann is the Credential Solutions Lead at Credential Engine. He can be reached at email@example.com.