I’ve been online long enough to know that you should copy to the clipboard text you’re about to post as a comment. That way you don’t lose it. Don Presant’s blog ate my comment on this post, so I’m posting it here.
For context, Brian Mulligan wondered about the burden that employers/institutions face when an application that contains a large number of digital credentials. He wondered whether anyone is working on tools to ease the burden of validating and evaludating the credential.
My response:
Brian, you make good points here – and ones that have been made before. The problem is that both hiring and Higher Education are broken. And by ‘broken’ (as someone has been through the entire system and has a terminal degree) I mean broken.
So we’re now in a situation where people ask a series of questions to candidates before they look at their CV. This is ostensibly for diversity and unconscious bias (which I fully support) but also because CVs do a terrible job at differentiating between candidates.
Given that many microcredentials simply take existing ‘chunky’ credentials such as degrees and diplomas, and break them down into smaller parts, they’re not solving the problem. They’re just allowing universities to make more money by prolonging it.
Instead, we need full-spectrum recognition of individuals. We’ve been at this ever since the start of my career – first with eportfolios, then with badges, then with blockchain, and now with Verifiable Credentials. The issue is that people mistakenly think it’s the credential, badge, or portfolio that needs to be validated. It’s not, it the identity of the individual.
We’re not going to live in a world where everyone has their own domain, sadly, so we need verification systems that allow people to claim and controlled identifiers either publicly or anonymously identify them. If you think about it, you shouldn’t have to apply for jobs, because jobs should come looking for you. I think the systems that are being built now, coupled with some of the AI that Don was talking about, so I think we’re getting closer to solving all of this.
For those dissatisfied with the false dawn of microcredentialing, I’m working on a ‘Reframing Recognition’ email course which I’m hoping to have ready after I get back from holiday. It’ll help people understand why Open Recognition is a much better approach. Come join badges.community to find out why.
I boiled snow for the first time this morning. Last night, I wild camped somewhere in The Cheviots as the clocks ‘sprang’ forward. Waking up before dawn, I put my iPod on shuffle, skipped one track and listened to Surprise Ice by Kings of Convenience. The song couldn’t have been more apt, given that my tent was covered in snow and ice!
The overnight camp was in preparation for walking at least half of The Pennine Way in a few weeks’ time. I’ve got all the kit I need, so I was just testing the new stuff out and making sure the existing stuff was still in good working order. The good news is that it’s very unlikely to get colder during my walk than it did last night, and I was warm enough to sleep!
This week, I’ve been helping WAO finish off our work (for now) with Passbolt and Sport England, continuing some digital strategy stuff for the Wellbeing Economy Alliance, doing some work around Greenpeace and KBW. I updated a resource I’d drafted on open working for Catalyst, and put together a proposal for some badges work under the auspices of Dynamic Skillset.
We had a co-op half day on Tuesday in which we ran, and eventually passed, a proposal about experimenting with a ‘drip release’ model for our content. Essentially, this would mean that we would have patrons (platform TBD) who would get our stuff first, and then everything would be open a few weeks later. This emerged from an activity of us individually coming up with a roadmap for WAO for the next few years. We were amazingly well-aligned, as you’d hope and expect!
I also helped a little with this post from Laura, and she helped me with one that I’ve written but has yet to be published. I’ve also drafted another couple of posts and an email-based course. I also (with a little help) created a weather app using the OpenWeatherMap API. Which brings us onto…
I’ve continued to find ChatGPT 4 really useful in my work this week. It’s like having a willing assistant always ready. And just like an assistant, it sometimes gets things wrong, makes things up, and a lot of the time you have domain expertise that they don’t. AI-related stuff is all over the place at the moment, especially LinkedIn, and I share the following links mainly for future me looking back.
While I got access to Google Bard a few days ago, the experience Google currently provides feels light years behind OpenAI’s offering. This week there were almost too many AI announcements to keep up with, so I’ll just note that ChatGPT was connected to internet this week. Previously it just relied on a training model that cut off in 2021. Also, OpenAI have announced plugins which look useful, although I don’t seem to have access to them yet.
There are lots of ways to be productive with ChatGPT, and this Hacker News thread gives some examples. I notice that there’s quite a few people giving very personal information to it, with a few using it as a therapist. As Tristan Harris and Aza Raskin point out in the most recent episode of their podcast Your Undivided Attention, AI companies encourage this level of intimacy, as it means more data. However, what are we unleashing? Where are the checks and balances?
It’s interesting that we talk about jobs being “at risk” of being automated. Under a socialist economic system, automating many jobs would be a good thing: another step down the road to a world in which robots do the hard work and everyone enjoys abundance. We should be able to be excited if legal documents can be written by a computer. Who wants to spend all day writing legal documents? But we can’t be excited about it, because we live under capitalism, and we know that if paralegal work is automated, that’s over three hundred thousand people who face the prospect of trying to find work knowing their years of experience and training are economically useless.
We shouldn’t have to fear AI. Frankly, I’d love it if a machine could edit magazine articles for me and I could sit on the beach. But I’m afraid of it, because I make a living editing magazine articles and need to keep a roof over my head. If someone could make and sell an equally good rival magazine for close to free, I wouldn’t be able to support myself through what I do. The same is true of everyone who works for a living in the present economic system. They have to be terrified by automation, because the value of labor matters a lot, and huge fluctuations in its value put all of one’s hopes and dreams in peril.
Next week is my last before taking three weeks off. I’m very much looking forward to a family holiday and am psyching myself up for my long walk. Ideally, I’d like to do the whole 268 miles in one go over a two-week period. But I don’t think my family (or my body!) would be up for that…
In a previous blog post, I discussed how microcredentials have deviated from Mozilla’s original Open Badges vision. This post explores some ways in which microcredentials can be realigned with those initial goals and better empower individuals and communities.
Firstly, it’s essential to emphasise the importance of informal and non-formal learning. Experiences such as volunteer work, self-directed online learning, and engaging in communities of practice have immense value. Microcredential issuers should think more widely to recognise a broad range of learning, allowing individuals to showcase not only their knowledge, skills, and understanding, but also their behaviours, relationships, and experiences.
Interoperability and decentralisation are crucial for a thriving microcredential ecosystem. Open standards and protocols can enable seamless sharing and displaying of badges across platforms. Microcredential providers need to think not only about their own issuing, but that of others. How can learners showcase learning that has taken place elsewhere? In addition, how can we use approaches such as Creative Commons licensing to encourage the reuse and remix of badge metadata? The move to Verifiable Credentials will allow badges without images, which will make collaboration around taxonomies even more important.
Thirdly, accessibility and reducing barriers to entry are vital in countering the commercialisation of microcredentials. Universities and other microcredential providers are no doubt feeling the squeeze in the current economy, but free or low-cost learning opportunities make for a more inclusive learning ecosystem. After all, the original vision for Open Badges was to widen participation and recognise different kinds of learning.
Open Recognition plays a key role in realigning microcredentials with the initial Mozilla Open Badges white paper. Along with approaches such as ungrading and Recognition of Prior Learning (RPL), we can focus on formative aspects such as learner growth and development, rather than solely on traditional summative evaluation methods. This approach can help build trust and ensure microcredentials are meaningful to employers, educators, and learners alike.
Finally, building a diverse ecosystem is essential. At the moment, microcredentialing seems to be almost entirely about the formal education to employment pipeline. However, wider collaboration can ensure the relevance, sustainability, and utility of microcredentials. Community-driven initiatives and partnerships can foster innovation, create new opportunities, and encourage widespread adoption of the original Open Badges vision.
So, in conclusion, realigning microcredentials with the original Open Badges vision has the potential to empower learners, recognise diverse skills, and foster a more accessible recognition ecosystem. By implementing the strategies discussed in this post, we can contribute to the revitalisation of the Open Badges movement and create a better future for learners worldwide.
