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Tuesday, April 28, 2026

CredX2026: Making Recognition a Verb

Voices from CredX2026 - Word Cloud by Taruna Goel

Over the last two weeks, I have been reflecting on my experience at CredX2026 and trying to make sense of it all in terms of what was said, what I heard, what we discussed, and what needs to be done next.

A core part of my work sits at the intersection of systems that do not always speak the same language, yet are all working toward shared outcomes around competence, credentials, and workforce mobility. I am talking about industry, post-secondary, and government. CredX2026 brought all of these systems and people into the same room. 

As we intermingled, it made me realize how the challenge is not just about translating across these systems. It is about building trust between them

As Chad Doerksen from the Ministry of Post-Secondary Education and Future Skills shared at our table, “credentials are a proxy for trust.” If that is true, then Recognition of Prior Learning (RPL) is not simply an assessment mechanism or an alternative pathway to credentials. It is a way of making trust visible, portable, defensible, and valuable. 

Which is why Julie Klein’s framing of “recognition as a verb” stayed with me. It shifts RPL from being a static system or policy into something active, relational, and ongoing, It is something we do constantly and intentionally, not something we design once and implement.

As I listened across sessions and conversations, I was struck by how much innovation already exists in the system. Jako Olivier from the Commonwealth of Learning presented the microcredential framework already working across the commonwealth but also reminded us that "while we call them microcredentials, there is nothing micro about the work", especially when situated within a broader lifelong learning context. Robert Luke from eCampus Ontario pointed to the growing importance of making skills visible through tools like Skills Finder and LMI-enabled curriculum stacks. Susan Forseille from Thompson Rivers University highlighted both the scale of PLAR in practice and future-facing ideas such as a provincial credit bank, along with important work on decolonizing and Indigenizing assessment methodologies. Sonia Hall from the Ministry of Social Development and Poverty Reduction shared BC’s current initiatives, policies, and regional innovations in credentialing. 

And yet, alongside all this progress, there was a quiet but persistent tension. Jackie Pichette from RBC Thought Leadership captured it well: “Change often starts at the margins. The problem is when it stays there.” RPL, microcredentials, and work-integrated learning are no longer fringe ideas, and yet they are still not fully embedded in how systems operate. As Jeremy McQuigge noted, it is time we reclaim these invisible systems. Because the challenge now is less about innovation and more about integration.

That tension becomes even sharper when viewed through current labour market realities. Tricia Williams, Future Skills framed the challenge within the realities of mid‑career disruption due to automation. Jeff Griffiths, leading the Alberta Talent Pipeline Management Initiative, noted that the system itself has changed, that the lack of entry-level jobs is a structural issue and how "we cannot credential our way out of it". At the same time, Rob Goehring from AI in BC observed, how skills are decaying faster than degrees are being updated. Nan Travers from Credential As You Go added another layer, reminding us that the quality and value of a credential are experienced differently by learners and institutions, and that while "AI may help us achieve efficiencies, we must remain intentional about effectiveness". 

In that context, RPL begins to look less like an alternative pathway and more like essential infrastructure. A big part of that infrastructure is the "language of competencies" and the value of  engaging industry extensively, not peripherally as highlighted by Dan McFaull. Margo Griffiths spoke about how behind every trusted credential is the data standard, governance and interoperability infrastructure. But the infrastructure here is not just technical; it is deeply relational. Jennifer Beale and Katie Fitzmaurice from Invest Vancouver spoke about the importance of “relational infrastructure” and the role of "neutral conveners in connecting systems". Joanna Jagger from WORTH Association emphasized “community over credentials,” while Darion from Teqare and Lynn White from ACCESS highlighted the value of empowering communities through training, achievement and self-sufficiency. Jodi Tavares from MyCreds Network reminded us that a "healthy ecosystem is connected, not competitive, and must remain focused on the mobility of the credential holder". 

These are not just ideas; they are conditions required for trust to exist and scale.

Throughout the two days, I found myself returning to the book, Thinking, Fast and Slow. Much of the world around us is pushing us into fast, reactive thinking. We are reacting to AI, economic shifts, and global uncertainty. But CredX2026 created space for something different. It provide space to think about and share ideas for a slower, more deliberate, and more collaborative response rather than simply another reaction. And that shift in pace felt important, because systems change does not happen at the speed of reaction; it happens at the speed of alignment.

Which brings me to what feels like the most important takeaway. If recognition is truly a verb, if it is about continuously validating and translating learning across contexts, then we need to normalize it. David Porter’s call to “make RPL normal” may sound simple, but it carries tremendous weight. It challenges us to move beyond pilots and pockets of innovation toward something more embedded and systemic. We need to understand that RPL is not an exception or a shortcut. Recognition is simply about creating pathways that meet people where they are, not where the system expects them to start. 

In a system where skills are changing faster than credentials, and where industry, post-secondary, and government are all working toward shared outcomes, RPL is no longer an “alternative pathway."

This feels like a real opportunity particularly here in British Columbia for us to move from conversation to coordination. We are doing important work across sectors, but too often in parallel.  Gregory W. Stone from BC Colleges noted how opportunities exist to re-vision and re-purpose what we have and how the most important question  is "What is going to happen next?"

Here's my call to action that I want to advocate for, support and be a part of:
The good? Industry, post-secondary, and government are all solving the same problem.
The what can be better? We just are not solving it together yet.

There is space for a cross-system RPL Community of Practice that brings together employers, post-secondary institutions, government, and other intermediaries (neutral conveners) for ongoing dialogue grounded in practice. So, not just to participate in conferences to share ideas, but to work together to build a shared language, toolkits and guidelines, competency frameworks and recognition-based credentialing models. 

I am imagining a kind of a living network of practitioners and partners, of people and institutions, who are actively engaged in this work so that the connections transcend beyond LinkedIn and conferences like CredX into real work, pilots, shared projects and cross-system collaboration. That is what will help move credentials, recognition and validation from the margins to the centre. 

Thanks to all the speakers, and to Tannis Morgan Adrian Lipsett, Erin, Hal and team, BCcampus Tracy Roberts Britt Dzioba, M.Ed. Helena Prins Gwen Nguyen Kelsey Kilbey, Future Skills Centre and the rest of the #CredX2026 team.

CredX2026 helped frame this important work and I hope we can move beyond episodic conversations and toward something more sustained.

I went into CredX2026 thinking about credentials. I left thinking about recognition and trust. 
Recognition is not just a process. Not just a noun. It is a verb. Recognition is how trust moves across systems.

Monday, April 27, 2026

Lifelong Unlearning

I was talking to a colleague the other day and we were discussing how our formal systems always assume that learning is additive. We are always talking about more courses, more skills, more knowledge. But in practice, growth also comes from subtracting. Anyone who has worked hard to drop a bad habit knows how tough it is to let go. Whether it is a habit, our assumptions and biases, or even poor work practices and ways of working, "unlearning" is hard to do but has nothing to show. There is no concrete evidence of unlearning or any artifacts or portfolio to show what and how much we have unlearned. We don't give out certificates for what people have stopped doing!

Unlearning is subtle, but it is powerful. After unlearning my fair share, I know that it has made space for better judgment, greater adaptability, and more thoughtful practice.


I wrote about this previously, in 2012, in my blog post titled:
Emptying Your Cup: Unlearning to Learn.

The point I am making is that not all growth comes from learning something new. Sometimes, it comes from letting something go. And we have to be intentional about it.

What did you let go of recently that contributed to your growth? How do you encourage others to unlearn? How do we design "learning" systems that also enable and support unlearning?

Thoughts?

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Additional reading:

  • Chapter 15: Learning, relearning and unlearning

    November 2024 Open Books and Proceedings
    DOI:10.38140/obp1-2024-15
    License CC BY 4.0
    Authors:
    Rosemary Akinyi Menya-Olendo
    Lucy Mawang
    Kenyatta University


In this chapter, the authors describe the following key terms:

Learning is contextualised as the continuous ability to acquire competencies relevant for the 21st century. This form of learning enables people to continuously improve their performance, expand their horizons, and equip themselves for the future. It further allows individuals to grow and develop personally and professionally throughout their lifespan. Turk (2023) observes that this type of learning occurs in various contexts, such as formal education, informal learning, and experiential learning. 

Unlearning means leaving behind old, outdated, and obsolete knowledge that is deemed inefficient in ad-dressing current challenges. It therefore entails questioning one’s assumptions and beliefs, and opening up to new perspectives that can help solve present problems. No wonder Turk (2023) postulates that the unlearning process may be challenging, as it necessitates confronting personal biases and preconceptions.

Relearning is the process of learning something again, often in a new or different way. It involves building on previous knowledge and experiences to gain a deeper understanding of a subject or skill. Relearning is important because it allows individuals to update their knowledge and skills in response to new information and changing circumstances (Turk, 2023).



"Multimodal large language models (MLLMs) are trained on massive multimodal data, making data unlearning increasingly important as data owners may request the removal of specific content. In practice, these requests often arrive sequentially over time, creating the problem of MLLM Lifelong Unlearning."


Tuesday, April 14, 2026

Lessons from the Far Side of the Moon

“human in the loop”

I am sure you have seen and heard this phrase that has become almost a default in conversations about AI and work. I have been thinking about it for months. It is supposed to be a reassuring phrase. That, in everything that AI is taking over, humans are still somewhere in the system overseeing, validating, and intervening when needed. But in the last few weeks, the more I have mulled over this phrase, the less reassured I have felt.

But something shifted last week.

Image credit: NASA
Seen during Artemis II’s lunar flyby on April 6, 2026, the Moon and Earth align in the same frame, each partially illuminated by the Sun.

On April 10, 2026, four astronauts completed a mission to fly around the far side of the Moon. They went further from Earth than any humans in over 50 years. On their way back, for about 40 minutes, they were completely cut off from NASA mission control. 

There was no signal and no loop; it was all human

While I am not a 100% sure, I bet the team at NASA focused a lot on how to build and nurture the competencies of the four astronauts for this 40-minute blackout when the Orion module would be cut off entirely. All these efforts would be in preparing the humans to respond to unknown and unpredictable situations and trusting that the humans inside the spacecraft will know what to do. 

Image credit: NASA
The Artemis II crew – (clockwise from left) Mission Specialist Christina Koch, Mission Specialist Jeremy Hansen, Commander Reid Wiseman, and Pilot Victor Glover – pause for a group photo inside the Orion spacecraft on their way home.

NASA did not send AI to the Moon, they sent humans because fundamentally, there are many things where humans are not just meant to be in the loop, they are meant to be in the lead. I was reassured by such a mission where humans were not just a checkpoint or validation point in the system, instead they were the ones leading the design and the decisions. And if you have seen all the pictures and the beautiful, poetic expressions of the astronauts trying to reflect on what they were seeing and feeling and learning, you will agree that humans are not just validators; we are value creators. 

It was Accenture CEO Julie Sweet who said, "AI future should be human in the lead", and I love this reframing. This difference between loop and lead is not a subtle one. It is a powerful way to think about how organizations must use AI, but not at the expense of losing their own ability to think, learn, grow, and become more intelligent.

When an organization like NASA sends humans to space through missions like Artemis II, it is not because machines are incapable. It is because, in environments where there is ambiguity and uncertainty and the consequences are as real as it gets, we can't afford to outsource our judgement.

So, as AI is reshaping our work and our world, instead of thinking about whether or not we keep humans in the loop, we have to think more intentionally about how to keep humans in the lead! This means thinking about how we design roles, systems, training and work so that humans continue to build their capability and thinking and they continue to feel and express and to question and engage with each other. 

I have said this before. I don't think the real risk of AI is replacement. I think it is the erasure of our unique fingerprints. It is the things that each of us leaves behind as breadcrumbs that highlight the mix of who we are through our choices, decisions, and connections with other humans.

In the race to AGI, if we focus only on making AI more intelligent, we may end up designing systems and organizations that make us less intelligent. Which also means that perhaps the real work ahead is not just building smarter AI, but redefining human intelligence itself.