Learning Machine and GC Talent Cloud Issue Blockchain Credentials to Canada's Free Agents

OTTAWA, Ontario, June 24, 2019 (Newswire.com) - ​​​​​​As part of a one-year talent mobility project being conducted by Talent Cloud at the Treasury Board Secretariat of Canada (TBS) in partnership with Learning Machine, Government of Canada 'Free Agents' have been issued Blockcerts, blockchain-anchored credentials, as a permanent and self-owned record of the skills they demonstrated to be selected into the program. This is a first-of-its-kind project for skill validation in the Government of Canada.

View and verify an example Blockcert, courtesy of Free Agent Brian Double, here (shared with permission).

Free Agents are government employees who have been recruited based on attributes valuable to problem-solving in the public sector. Members of the program are free to move about the federal government, choosing deployments in other departments based on their own skills and interest. Free Agents have skills assessed by their Talent Managers upon entry into the program, but the record of these assessments are difficult to access and share.

To test the concept that digital credentials issued by the Government of Canada may be owned by the recipient, and verified by anyone in the world for free, Free Agents have been issued an official Blockcert credential that captures all of the data and criteria related to their acceptance into the Free Agent program. This includes the date of acceptance, the attributes that were assessed, the names of the Free Agent Talent Managers who accepted them into the program along with other relevant metadata. Free Agents now have a way to easily demonstrate a trusted record of their skills as they move about the federal government doing project-based work.

Trusted digital credentials are a big part of the future of work. Blockcerts are a step towards a global ecosystem for open and dynamic digital credentials. This proof of concept demonstrates that fully portable, trusted digital credentials are not a distant vision, but a reality today.

"Thankfully, proving yourself with paper or checking a database is now in the past. Using Blockcerts with your own digital credentials, you can prove your identity and your qualifications in an independent, secure, privacy-respecting way," says Alex Benay, Chief Information Officer of Canada.

"Government of Canada's Free Agents now have Blockcert credentials as official records of their skills in a format that is secure, shareable, and easily verifiable. The Blockcerts pilot program, being led by Talent Cloud, empowers Free Agents by enabling them to own and easily share their official and secure credentials that can be instantaneously verified by anyone, thereby enhancing workforce mobility and marketability," says Kausar N. Samli, Learning Machine Senior Vice President of Global Services.

About Talent Cloud

Talent Cloud is an experimental staffing platform within the Government of Canada testing the viability of a new model for recognizing and mobilizing talent for the Public Service.

To learn more about the proof-of-concept, please contact:

[email protected]

Valerie Thomas / Lead, Talent Mobility Strategy, Talent Cloud

About Learning Machine Technologies, Inc.

Learning Machine provides Enterprise Credentialing Systems that issue verifiable credentials using the Blockcerts open standard. Blockcerts, developed by the MIT Media Lab and Learning Machine, is the leading international open standard for issuing recipient-owned credentials to any blockchain. Learning Machine's global customer base includes governments, companies, and school systems that need to issue verifiable, portable, and secure credentials at scale. To ensure the longevity and interoperability of these credentials, the company is an active contributor to international standards communities, including the W3C, Blockcerts, DIF, IMS Global, and Rebooting Web of Trust.

For more information about Learning Machine, visit: https://www.learningmachine.com or follow on Twitter @LearningMach1.

Source: Learning Machine