⬇️ Inside this issue:

• Thania on what Indigenous recognition systems can teach us about learning

• Could bias be hiding in your badges? Trevor and Cami share 5 ways to check

• What a 165% jump in AI skills demand tells us about where hiring is headed

INTERESTING READS

🎯 Removing degree requirements is one thing, but building a skills based system is another.

🤖 Workers want to move forward, but access to training and AI support could determine who gets to.

🎓 HBCUs are turning AI disruption into real workforce preparation.

🏅 Digital credentials are ready to scale, so what will it take to get there?

CREDENTIALING

What we can learn from Indigenous Recognition Systems

Long before anyone printed a diploma, communities were recognizing what people knew.

That's the idea behind Indigenous Recognition Systems, a concept presented by Simone Ravaioli at Badge Summit that got me pondering.

He gave it a memorable acronym, IRS, as a play on IKS, or Indigenous Knowledge Systems. IKS refers to the ways of knowing that traditional cultures have developed and passed down for thousands of years. Simone's point was that these cultures also built sophisticated systems for recognizing that knowledge. Those systems are governed by the communities themselves and work independently of any formal institution.

As we approach Indigenous People’s Day, I wanted to share how the discussion fundamentally shifted within me with a question I still can't shake: what do we accept as proof that someone knows something, and who decided?

The currency we trust

In Western culture, learning pays out in paper: a degree, a certificate, a transcript, and now a digital badge. We treat these like currency. They're tangible and portable, and we exchange them for jobs.

Like any currency, they can be counterfeited. Someone signs off on a badge they shouldn't. Someone cheats their way through a course. They land the job and can't do the work, yet on paper they excelled.

I've felt the limits of this system firsthand, and it's why I've disliked pedigree for so long, especially in higher education.

(Franklyyyyy, my Chapman University classmates and I got a better marketing education than a lot of Ivy League grads 😝 We studied public relations and advertising in niche, granular detail. Plenty of people I've worked alongside came into marketing as a result of their prestigious economics degrees and learned the craft on the job. But I watched my Chapman peers lead with their skills and land their first roles already fluent in things others took years to pick up.)

Because really, a diploma's brand name tells you where someone studied. Their work tells you what they learned.

A different kind of proof, and it's worked for millennia

Indigenous recognition runs on a different currency. There's no single "Indigenous system." There are thousands, each rooted in its own place and people. A few ideas from them changed how I see our own system.

Evidence can live in a community. In some Aboriginal Australian traditions, knowledge is passed down orally and can't be shared outside the community, so it can never be documented the way our systems expect. The evidence is the community itself: we know who you are, we know the role you hold, and we know your journey. Your standing is the credential, and you earn it in front of people who have watched you practice for years.

Learning builds over a lifetime. Our assessments assume an authority can declare, at a single moment, that you've mastered something. Through an Indigenous lens, learning keeps accumulating, and a test only captures one afternoon of it.

Our "traditional" is recent. What we call traditional Western assessment is mostly a 20th-century invention. For most of human history, nobody needed a certificate to be recognized as capable. Like duh, the system I've always treated as the default is actually the newer one.

Skills don't disappear in translation

Picture a leader in a tribal nation here in the US. They might govern a community, manage land and resources, run operations, resolve disputes, and carry oral history forward to the next generation. By any standard, that's pure demonstration of leadership, operations, communication, and knowledge management.

But if you put that person through a Western hiring process with no diploma, no badge, and no certificate. Do they lack those skills? Of course not. What's missing is the paperwork. And the value system attached to that paperwork.

Veterans know a version of this. They spend years building real expertise, then have to translate it into language civilian employers recognize. Being unable to convert your skills into someone else's currency says nothing about whether you have them.

I think American education is individualistic: here's what I did, look at my diplomas. Many Indigenous cultures think in terms of the collective: here's what we did.

Maybe what we need is something like a currency exchange. Pesos and dollars are both real money, but they only hold value in certain context. You just need a rate to transfer or translate the value.

Simone gave a more precise version of the same idea. He has studied policy in South Africa, where national qualifications frameworks exist alongside separate Indigenous knowledge policies. He warned that folding Indigenous knowledge into formal frameworks risks assimilation and appropriation. Instead, he proposes interfacing the two, so the systems connect while each keeps its own logic. His example was traditional health practitioners. Their practices feed a booming wellness industry, and as Simone put it, none of that money flows back to them. Part of the reason is that they aren't on the official registries that control access to jobs and grants.

I believe there's a huge untapped talent pool out there. This is where it's hiding: behind an exchange rate nobody has built yet.

What this means for those of us building the system

Most of us reading this don't work directly with Indigenous communities, but the ideas can still apply to everything we're building.

Take open recognition. For years, advocates of self-attestation, peer recognition, and community recognition got pushback from mainstream credentialing. Simone realized that Indigenous communities have practiced all three for millennia. The idea that sounds radical is the oldest one we have.

Or take endorsements. When someone respected vouches for you, it carries weight. In an Indigenous context, that might be an elder saying, "Yes, Thania is really good at communicating." In ours, it might be a LinkedIn recommendation from the CEO of a well-known Fortune 500 company advocating for my marketing skills. Either one holds more value to me than a certificate in “Introduction to Marketing”. That's the community-as-evidence model, and our tools could lean into it much more than they do.

Then there are micro-credential frameworks. Simone pointed out that many are being built on the same patterns as old qualification frameworks, which could limit what micro-credentials become. We have to balance our need for verifiable proof of skills with respect for prior learning, community vouching, and lived experience.

Simone isn't rushing to resolve these tensions, and I'm not either. As he put it, "The resilience comes from being able to hold space in the tension."

What I can say is that my Western lens doesn't set the value of anyone's learning. Recognition starts long before a certificate and continues long after it. So I challenge you to ponder this: where does recognition begin, who decides it and where does it end?

COMPLIANCE

DIVERSITY

5 ways to make sure you’re not accidentally building bias into your badge

As micro-credential developers with a focus on increasing employment outcomes for all Oklahomans, my colleague Cami and I spend a lot of time in front of employers and classrooms discussing equity, diversity and inclusion.

Most recently we had an ethnic affiliated association trying to match candidates to employers based on their skills and relevant job titles.

Unfortunately, the system was being run on a poorly designed LLM and generated what some might perceive as racist or stereotyped results.

Whose fault is that? Is it the program director? Is the bias of AI? Was it just a simple mistake?

These are the types of questions you want to consider when creating badges at your organization.

Being an ally is a design problem

Now, let me preface by saying that we're two white people who have benefited from privilege. Our learners run into barriers we’ve never encountered, and there are questions we’d never think to ask with only ourselves in the room.

Which is why we encourage self-awareness and discourse around this topic.  We want all members of the diverse collective ecosystem to ask the question: Where could bias be hiding as we design new credentials?

None of us can declare ourselves unbiased. We can build a process that accounts for checking bias and give our targeted learners a voice during credential construction. For us, that’s most of what being an ally requires. Here’s 5 takeaways designed to help you see  where bias can show up in digital badge design.

1. Check what your technology is deciding for you

Algorithms make decisions look objective.

Somebody wrote the algorithm, though, and their assumptions were written in, too.

Say your platform recommends occupations from a learner’s profile -- has anybody checked how those recommendations get made? Are two learners with the same skills getting steered toward different jobs? Do identity markers in the badge affect the recommended jobs?

Digital credentials also assume a device, a reliable connection, and somewhere useful to share the thing. That requires a level of presumed privilege for all learners, which is unlikely to be reflective of reality.

Try this tomorrow: Using only a smartphone, go through the whole earning and sharing experience on nothing but a smartphone. Note every place it breaks, and anywhere bias hides.

2. Look at your badge through someone else’s eyes

Design choices are equity choices. The accessibility basics come first: color contrast, readable type, alt text that says what the badge is for, and a platform that meets the Web Content Accessibility Guidelines.

Representation is easier to miss. If everybody pictured on the credential page and in the marketing looks alike, we’re sending a message about who the credential is for, whether we mean to or not.

Try this tomorrow: Show a credential’s page to somebody who had nothing to do with building it and ask who they think the program is for. Then let them answer without steering.

3. Ask whether employers will treat it as evidence

One of our stronger opinions: asking somebody to spend time and money earning a credential employers don’t value is unethical.

The learner carries all of the risk. They pay, in hours taken off a second shift or away from their kids, sometimes in tuition, and they absorb the cost of being wrong about the credential’s value. We absorb none of it, and we get the completion numbers whether or not a single earner gets hired.

Any time the person with the least room for error is the only one exposed, we’ve designed it wrong. Employer recognition belongs at the front, where it decides whether the badge gets built in the first place.

Try this tomorrow: Name an employer who recognizes the skill you’re credentialing and can identify what earning it gets the learner.

If you can’t name one, start doing some outreach to increase the value of the credential for the learner, or consider not charging for it at all.

4. Question what counts as proof

Who decided what competency looks like, and how would we know if they got it wrong? A learner understands the concept and struggles with the format we chose. Did the learner fail to demonstrate the skill, or did the assessment fail to give them a reasonable way to show it?

Try this tomorrow: Before you approve your next assessment, ask whether it measures the skill or measures somebody’s ability to succeed in your preferred format.

5. Pay attention to who decides which badges exist

Gatekeeping is the hardest to see, because it happens before a learner ever encounters a badge. Somebody decides which credentials get funded, which skills deserve recognition, and which learners a program is built to serve. Those decisions determine whose skills become visible.

Look around the room where the deciding happens. Who’s there, and who isn’t?

Try this tomorrow: List the last five credentials your organization approved and, next to each one, the people who were in the room. Look at the pattern.

We’re not going to design a bias-free badge

Micro-credentials get built by humans, inside systems with inequities already baked in. The realistic goal is a habit of looking for bias before it becomes another barrier.

If you do one thing after reading this, pull up a credential you already offer and ask:

• Technology: Who could struggle to access this?

• Design: Who might not see themselves here?

• Employer recognition: What does earning this get a learner?

• Assessment: Are we measuring the skill we say we’re measuring?

• Gatekeeping: Who had a voice in deciding this credential should exist?

We’ve run the five on our own work and haven’t liked every answer.  But that’s the honest and genuine work required to design equitably.

The checking falls hardest on those of us who have done well inside these systems, and in our view that’s part of being an ally.

BY THE NUMBERS

AI skills demand has more than doubled

165% more job postings include AI skills than they did a year ago, and demand grew another 27% between April and August alone, showing just how quickly AI skills are moving from a nice-to-have to something employers are actively looking for.

Source: Navigating Skills Trends: Data Dashboard Analysis

KNOWLEDGE

What to read, watch, and listen to this weekend

📚 Read: How New Visa Limits Are Already Affecting Colleges by Johanna Alonso for Inside Higher Ed

The new four-year limit for international students hasn’t even taken effect yet, and colleges say they’re already feeling it. Students are withdrawing, applications are dropping, and programs designed to take five or more years face new uncertainty. This one is especially interesting through a learner-mobility lens: what happens when policy suddenly makes an established education pathway harder to navigate?

📺 Watch: Why Is the Reskilling Revolution Needed? by the World Economic Forum

The jobs people have and the skills employers need are changing fast. This short video looks at why millions of workers will need opportunities to learn new skills throughout their careers and what it will take for employers, educators, and governments to make reskilling actually work at scale.

🎧 Listen: Is AI a Performance-Enhancing Drug for Entrepreneurs? from Thoughts on Tech & Things with Jason Michael Perry

AI as a performance-enhancing drug is quite the analogy, but hear them out. Host Jason Michael Perry sits down with Technical.ly cofounder and CEO Chris Wink to explore how AI is changing what founders can accomplish and what that shift could mean for workers, entrepreneurs, and the cities trying to build ecosystems around both.

FOR FUN’SIES

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