I’m excited to join the Decentralized Identity Foundation (DIF) steering committee on behalf of Learning Machine. To introduce myself and Learning Machine to the DIF community, I wanted to describe Learning Machine’s background/interest in decentralized identity (or, more specifically, self-sovereign identity) for ensuring an individual’s control over their data. I’ll highlight the initiatives Learning Machine is especially eager to champion at DIF, lending our experience and use cases from educational/occupational credentialing.
Learning Machine is deeply committed to recipient-centric credentialing. We incubated Blockcerts with MIT Media Lab in 2016 as an open source, open standard for creating, issuing, and verifying digital records. Learning Machine has a natural kinship and aligned purpose with the broader self-sovereign identity community, and from our leadership roles in the W3C Credential Community Group and Rebooting Web of Trust, we have advocated for recipient control of digital records and contributed standards and prototypes of the SSI stack.
We’ve become particularly interested in initiatives occurring at DIF, which has carved out a crucial role in the SSI community advancing protocol development; interoperability; and self-sovereign approaches to identity data storage/access. Efforts such as the Universal Resolver and DID Auth have been crucial for vetting the emerging DID data model (the base layer of the SSI tech stack) and helped inform how we develop DID methods. Identity Hubs introduce a new approach to how we access our data, unlocking options besides the traditional data silos. DIF has worked in tandem with standards bodies and communities and is well positioned to encourage the advancement of prototypes in the next phase of standards development.
As the SSI technical stack and standards advance, vetting against a range of use cases becomes critical. We must ensure our frameworks appropriately handle the privacy, security, longevity, and lifecycle concerns that arise in the many applications we envision (educational and occupational credentials, identity cards, medical records, etc). While SSI standards have robust frameworks for these concerns, it is important that the implementations and ecosystem preserve the principles as they transform into real systems.
DIF has already done great work in this area, and I look forward to helping advance these efforts over a broadening set of use cases to ensure an open, standards-based ecosystem, without vendor silos.