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The Summer of 2019 was historic for open standards and digital credentials. Learning Machine is taking the following highlights with us into the Fall: 

After years of work, the W3C Credentials Community Group, which Learning Machine co-chaired, released the first specification (v1.0) of a global framework for forming verifiable digital credentials. The new Verifiable Credentials open standard has already garnered significant international support in the United States, Europe, and Canada. International agreement around a single, open approach for verifiable credentials is critical for the long-term interoperability and usability of important records.

In the healthcare industry, the US Federation of State Medical Boards has taken the lead by emphasizing the importance of transitioning to open standards for self-attesting, recipient-owned practitioner credentials in a Report co-authored with Learning Machine. The US Congress was briefed on the Report in July.  

After the W3C release, Learning Machine received a grant from the Department of Homeland Security's Science & Technology Directorate to prevent forgery and counterfeiting of official documents used in immigration, travel, and other use cases pertaining to citizen and national security. The grant's purpose is being fulfilled by bringing the Blockcerts open standard and the Learning Machine Issuing System into full alignment with the new W3C specification. These upgrades will be made seamlessly available to all Learning Machine customers.

Finally, this September we announced the arrival of blockchain-secured digital transcripts. These are complex, multi-page digital records that can be issued to a learner once, then shared and verified instantly anytime they are needed.

"As we move from a world of discrete paper repositories to a world of interconnected digital systems, we need academic records that are natively digital and self-verifying to reap the full benefits of electronic exchange."

- Chris Jagers, Learning Machine CEO, Remaking Credentials
Copyright © 2019 Learning Machine, All rights reserved.

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