Are Schools Collecting Too Much Data? | Dr. Kelly Page

In this episode, Getting Smart host Mason Pashia chats with Dr. Kelly Page, a social design ethnographer and the CEO of Live What You Love (LWYL Studio). They tackle the hype surrounding ‘digital credentials’ and verifiable learning records. Drawing on her recent book, When Credentials Cause Harm, Dr. Page breaks down the risks of surveillance and inequity built into many of these systems, offering a better path forward that prioritizes learner agency and consent.

Listeners will walk away with a clearer picture of the power dynamics in edtech procurement and why true ‘recognition’ should be about more than just top-down grading. Dr. Page challenges leaders to think beyond simple tech adoption and instead build systems that respect human storytelling, ethical design, and true data ownership.

Transcript

Mason: You’re listening to the Getting Smart podcast. I’m Mason Pashia. With great power comes great responsibility. This, of course, is a line from Spider-Man, but it’s also something product designers have to contend with, especially when designing for the education sector, FERPA and other privacy standards, accountability for big technology companies.

If not checked, a great idea can run amok and potentially do more harm than good. In the education sector, we have no shortage of professed silver bullets, but few of them loom as large as badging and credentialing for solving the perennial challenge of signaling and communicating what a learner knows and is able to do.

Over the last few years at Getting Smart, we’ve been conducting research, commentary, and hypotheses on what it would look like if innovations in transcripts, learner employment records, and high-fidelity signaling systems were designed to actually serve learners. So today I’m super excited to continue this conversation.

I’m going to unpack what’s at stake and what’s essential to get this powerful technology to break in an equitable and accessible way. I’m thrilled to be joined by Dr. Kelly Page, the author of a book called “When Credentials Cause Harm: Unpacking the Risks of Verifiable Learning and Work Records.”

She’s a social design ethnographer and inclusive usability researcher who specializes in developing accessible, inclusive, and consent-driven technologies. Dr. Page currently serves as founder and CEO of Live What You Love, LWYL Studio. Kelly, thanks so much for being here. Good to see you.

Kelly: Thank you so much for having me. It’s a pleasure.

Mason: We got the chance to hang out in Boulder recently at the Digital Badging Summit, so it’s always great to continue those conversations. It’s easy to go a whole three days with someone and not really figure out what they do day to day, but you just have interesting conversations and are in interesting rooms. So I’m excited to continue this with you today.

Kelly: Thank you so much. Yeah, Digital Badge Summit in Boulder is always a wonderful space to meet folks who really care about recognition, really care about centering learners, and elevating the skills and experience they have in any conversation. At the same time, it brings together vendors, all sorts of different people from different backgrounds. So it was wonderful to meet you and start that conversation around this work we’re doing at Live What You Love.

Mason: For sure. It feels like a family reunion with family you haven’t met yet, a really interesting and cool space. I’m excited to dig in. I’m really curious to start with kind of a softball question: what made you start looking at the harm of this thing that a lot of people are celebrating? Credentials and badges have sort of been this unfulfilled promise for a number of years. There’s been a ton of credentials, and a lot of people are like, “Can we trust these? What does this mean?” But where did you start to really put yourself into this harm framing of the conversation?

Where the Harm Framing Comes From

Kelly: I’ve always been on the journey of inclusive design. If we’re promising something’s going to impact people, those people need to be at the table, whether it’s the design table, testing table, or what have you. Over the years, my work has always been around recognizing learners, helping learners tell their stories. Especially when it comes to digital technologies, from the early days of Web 1.0, I remember the early conversations on how websites were being developed, right through to today, where we’re seeing a plethora of different digital credentialing vendors, formats, standards, things in the marketplace.

The promise, that’s what the very first chapter of the book is about, the promise and the peril. On the one hand, we’re promising something, but then what might be that other side of it we might not be talking about? I started documenting the harms many years ago. I started working in digital badges during the early days, when Mozilla and the MacArthur Foundation contracted and commissioned a group of people when they started on this journey, and I was one of the first researchers. I’ll give a shout-out to Dr. Cheryl Grant, who’s very much elevating learner perspective and learner impact in this space.

Over the years, on multiple projects, I started noticing that whether it was learners or faculty and students, they were raising concerns or questions that weren’t necessarily being elevated or included in the case study or the report. It started to feel uncomfortable, like there was a thread here. As we know, our medical professions have an ethical responsibility to do no harm. So I’m like, well, what does that look like in edtech? There are thousands of tools and technologies that promise learner impact, yet we have to also ask, well, do they, and how do they?

I started documenting the harms, and it can be anything from vendor lock-in, which I know we’ll probably talk about, and a number of things the book covers. I try to turn it around and ask, “How can this harm be a design challenge?” If there’s evidence of harm, so it started for me in the research, in the field, hanging out with people, and also myself not feeling heard at design tables when raising concerns, because there’s such a positive feeling, “this is amazing, this is going to impact lives.” I think that positivity can sometimes cloud out the concerns people raise.

Mason: Yeah, I think that’s super smart. Just for the listeners, this book is a really great overview of where credentialing systems have been and where they’re going, as well as doing this really useful chapter-by-chapter breakdown of some of these potential harms and offering a solution. We’re going to spend some time with some of those today, but the format really lends itself well to sitting with these questions, knowing where they’ve been and where they’re going. You can find the link in the show notes, and we’ll plug it again. It’s really great, and you can tell you’ve been in this work for a while.

Kelly: As innovators, as entrepreneurs, as technologists, we’re always interested in where we can go, relative to being able to look at the history of credentialing. Recognition systems have been around for a very long time, and they have different formats, they were developed for different reasons. Understanding that history helps us understand the shoulders we’re standing on, and that’s really important.

Mason: It’s critical, yeah. It goes back pretty far anthropologically as well. I’m kind of a paper nerd, and I was reading a book on the origins of the notebook a few years ago, and there was so much interesting stuff on the idea of having a technology with which you could write something, primarily for merchants, so the numbers could not be altered afterwards. That was such a huge innovation, to have a piece of paper where you could write something and see if somebody tampered with it. Today we’re still kind of having that conversation, how can you give something verified that has meaning, ensure it’s not altered, but also ensure it’s an honest representation of what was there. I think it’s really interesting.

Who Controls the Record

Kelly: When you look at that chapter on history, you see who had control over creating the records and creating the credentials, and often it wasn’t the worker or the learner, it was something done to them by a group of individuals trying to optimize the system. They wanted apprenticeship systems, and this goes back to before even the guilds, we’re talking Ancient Greece, Mesopotamia, where things were documented to try to optimize the system, and at the same time we were applying labels to people. That’s an important power dynamic we need to recognize that we live in.

Mason: Yeah, I think about this a lot, and hopefully we’ll spend a bit more time with this later. I think health records and criminal records are the two most publicly visible record types in the United States. A health record in a lot of ways serves the individual for having it, for knowing where they are, and also the medical professionals. But a criminal record is one that’s sort of about you, it’s like a shadow self that follows you, and it’s really hard to change, really hard to have it not signal something about you. It’s a really interesting analog, obviously an extreme example in some ways, but we have to make sure that as we’re building records, the learner or the, I know “earner” is not my favorite word and not yours either.

Kelly: No.

Mason: But whoever is in this picture has ownership and can actually control that data and who is seeing what, and that it helps them navigate.

Kelly: And also what’s written about them. It’s interesting, I’ve been part of many of these projects building these systems, and there’s one project I obviously won’t name, that’s a core thing with me, ethics, we don’t out groups in the book, just like we don’t out individuals. Because it’s about building with care and understanding what that looks like. Yet if you have a system with over 300 data fields on identity about children, you have to start asking, are we building this the right way? The book gets into that too, a big thing around data equity is the data needed, and what is it needed for?

We’re also in this world right now of, because there is data, well, let’s collect all of it, without realizing what impact that data could have on the individual. Records are created, and health records are an interesting one, I hear in the education space a lot of people referring to health records as the example you can create interoperable learner records from. I’m often like, “Okay, they don’t always work.” There are real examples of how health records work, especially for those who are disabled, who don’t have digital access.

Mason: We have to be mindful of, let’s learn from different systems and how we can actually make them better for the individual, not just the institution or organization, but most importantly the person it’s about. That’s super important.

Surveillance Versus Empowerment

Mason: I want to sit with this inclusion idea for a second, because there’s this really tricky chicken-and-egg thing around surveillance and verification. Part of this conversation is about providing access to credentialable experiences, like providing access to industry-recognized credentials, providing access to already-recognized credentialing systems. Then there’s a part of providing evidence that something you’ve done is valuable, maybe that’s a video of you doing something in the world, and it’s like, “Oh, this person can clearly do that.”

The challenge becomes, and you talk about this eloquently in the book, that oftentimes some of the communities we’re talking about, the most marginalized or excluded, are also the most rightly wary of video documentation, of things that feel more like surveillance. So much of their skills and what they know how to do goes undocumented. It becomes a thing you actually cannot demonstrate because you’re nervous, because you don’t know who’s watching it, who controls it. So how do we start to pull at that knot and actually do this without surveillance? How can you document the magnitude of what someone knows without this kind of ever-present eye capturing the demonstrations?

Kelly: That’s the line between empowerment and surveillance, which we touched on a little at Badge Summit. It’s interesting, because sometimes things that might look like control, well, it doesn’t always look like control, it’s optimization. What’s interesting when it comes to surveillance and empowerment is, do people have the choice to opt out and not be penalized? If someone doesn’t have the opportunity to opt out, you have to first question, well, who is the system for?

Then there’s the notion of surveillance, the more data and information we’re collecting on people and codifying, how much control do they have over it? Can they export it from the system? Can they remove it? I often see the movement between the language of data control versus data management versus data access. Can I self-assert my skills? I know more about my experiences, then can I seek endorsement from, say, Mason, who I’ve worked with? It’s really interesting to look at the design of the system and what role a learner or worker has in how the system’s designed and what they can do with it.

I think the myth we kind of live under is that we need more data to be able to prove or evidence something, when actually we might not need more data, we just might need the right data. Does that make sense? Unfortunately, there are actors interested in building profiling systems designed to exclude, and we have to be very mindful of that. The surveillance thing is, by collecting the data, you are surveilling.

Building the Right Data, Not More Data

Mason: We’re in this weird AI moment where you can just submit all of your data and say, “What’s valuable from this?” But that pretty much violates all the data principles, because you’re just saying, “Here’s all of it, tell me what to use.” How do you think about actually building a complex portrait of the right data, rather than just flattening into, “Here’s a project I did, you can go to the website and look at it”?

Kelly: Tell me a little more about that.

Mason: I think there’s a benefit, specifically if you’re looking at durable or transferable skills, to showing a wide variety of experience, whether it’s a portfolio about one specific thing or otherwise, and people can start to extrapolate from it, “Oh, I bet you could probably do this in this context.” However, if you’re doing more of a curatorial role of evidence, you might not think to include this unique moment where you demonstrated critical thinking in a unique way. How can we, as the learner, the person with the record about us, actually curate and author that in a way that’s high-fidelity and represents us and our complexity, rather than being this flattened, token version of ourselves?

Kelly: Well, firstly, I think any data, any credential, any record that’s about you, you should have a say about it, because most data, most credential information, is super flat. The way you use it when applying for a job is very different than when you might be applying for a scholarship, or seeking an opportunity locally with a local business. It’s really interesting to think about how the individual wants to use their data, and what story is around it for them. I think we haven’t necessarily built the tools from that perspective.

To really center the learner and worker means giving them the right to reply to any data about them, the right to change it, the right to marry data together to tell their own story. At the same time, it takes training and development in digital literacies, data literacies, to help someone do that, because not everyone has those skill sets. We flatten experiences down to checkboxes, meta tags, certain data that’s in a credential, and then a five-year experience of something becomes this credential on a portfolio. The only way to give it meaning is if someone can speak to it.

I did a study with California State University on learner utility, what was really interesting was around learner utility of digital credentials, especially digital micro-credentials, they used them as a conversation starter. It was how they spoke about them and shared them, more than the credential itself. That’s what gives more meaning and scope to pieces of data, the story it’s embedded within. That’s why I find it interesting when people talk about how “the resume is dead,” and I’m like, but the resume was only ever meant to be a conversation starter, it was never meant to be the conversation.

Mason: Right. I think at best, yeah, I think we’ve moved into a place where the resume is kind of the conversation for the stack of 5,000 applicants for one role, it narrows it down to like 20, and then it’s, “Now we can have a conversation.” But that’s a huge conversation about equity and access.

I’m totally with you though. I think you can almost think of them like, if you were to ask a learner about their day at the classic dinner table, and you’re nervous about the word “fine” coming up, a credential or micro-credential could almost serve as the PowerPoint example of how they could talk about what they did. If they were to give a five-minute TED Talk about this thing, consider the micro-credential a PowerPoint, and they’re going to voice over it. It becomes an occasion to know when you’ve done something and how to talk about it, and I think that’s really important, because a lot of the time it’s really hard to notice the moments of learning. That’s not something we’re good at as a species, and not super good at teaching in schools, recognizing when you know something, or recognizing when you’ve changed.

Kelly: Imagine a portfolio of records, because I believe in the plurality of it, there’s so many. As an ethnographer, we’re collectors, collectors of experiences, of people, of all sorts of different assets throughout our life, and we leave trails as well. That’s why for an ethnographer, we like to hang out and get a sense of things.

One of the harms I find is that organizations, whether schools or universities, look at engagement indicators and say, “No one’s claiming it, no one’s using it.” Imagine a driver’s license, you only use it when you need to, same with a passport, it’s seasonal. A lot of this data we’re collecting or repurposing, so long as a learner has access to it and can go back to it, it’s a prompt for a memory of something they did when they have to apply for something. We need to be mindful of what the data is for, what it was collected for, and how a learner could use it when they need it, not just when the district needs it, or the vendor needs it.

I did a lot of work in early childhood in Chicago, in a couple of schools, and saw young people telling the stories of their projects and what was meaningful for them in different environments. I think it’s stepping back to the actual human experience of storytelling, and when you need to tell your story for a transition. In another project, we asked learners and workers for their own definition of a credential, what did they think a credential was, and which ones were most important when they were in transition. It’s getting back to the notion of, yes, let’s collect the information and the data, let’s issue it in formats that mean people can take it with them, yet let’s also build the tools so they can do cool stuff with it in their storytelling.

Toward Self-Sovereign Data

Mason: Totally. I keep pushing on the idea that whatever version of this exists, I also think there’s some amount of plurality in this, and it has to be interoperable to the level where there’s a collection of everything. Maybe, just for the sake of visualization, we’ll call it a wallet, but I’m agnostic as to what that actually looks like. I think whatever that thing is should be an incremental, real-time tool for helping a learner understand more about themselves, first and foremost. It should not necessarily be about signaling and communicating, that can come second, because it’s a great source for that.

But it should be more like a journal, or more like a Strava-type health app, where it’s like, “Oh, this is telling me about me, that I’m looking at this, or that I’m entering that I read a book, or that I did this thing.” It’s almost like constellating your life in a way that’s really powerful. I’d love to see that conversation happen more, where the user is the user in a self-contained loop, and see how the technology actually changes, because it doesn’t feel like that’s where the conversation is right now.

Kelly: I really concur and agree with you. I’m also not attached to what we call it, I believe in digital assets, and it’s super interesting, if you think about digital financial assets and the picture you can get of your finances through your financial institution, what you do with your credit card, compared to what you can get on your child in a school district. Or with any kind of app or technology, often the dashboards are built for the user, but “the user” means the superintendent or the district, or the faculty at the university. They’re not built for the learner or the parent to really understand what’s happening in their learning environment.

We’re seeing some change in some applications, and that’s where I think there’s a really important breaking of the third wall between the user, the learner, the worker, and their parents if they’re under 16, and the actual vendor and institution collecting this data, and having a relationship. If my teacher can see this, then my parent should be able to see this. If my professor sees this at university, and these are the skills I’ve demonstrated, then I should see this as a student too. I think that would go a long way to educating people about their data and how valuable it is, and therefore how they could use it. That’s the empowerment piece for me, that literacy doesn’t live with learners, workers, and everyday people, even though it’s our data, it’s about us.

Mason: Right. Have you seen a version of this done well, whether educational or otherwise? The kind of full, inclusive design process that actually took one of these specific challenges, whether that’s articulation and the language and how we talk about something, or something more about opt-in, opt-out, and really flipped it on its head so it’s pro-learner?

Kelly: I’ve seen pockets of it in different communities and projects. I’m yet to see one solution that really embodies the learner’s needs and the individual’s needs and leads with that in its design. There have been a number of projects that start out really well, really well-intentioned, and then the funding mechanism gets in place, and it’s like, well, how is this being funded, who’s funding this, and it changes the dynamic of what’s going on in a project. So I’ve definitely seen components of it. I think we have a long journey to go, especially around consent, what that means, and how you actually implement it in an easy and accessible way, given the complexity of what we’re talking about, the amount of data. It also requires a very honest conversation about who are the parties at the table and what are their interests in what we’re building. I’m yet to see one system that does this really, really well and truly centers learner needs.

Mason: Yeah. We’re both like early stages and also not, it feels like the technology’s been here for a long time, but actually adopting it at a system level is slow and tricky. I’m curious how you would advise a school leader on adoption of one of these tools, whether that’s just digitizing their pre-existing records, or actually adopting something that looks more like a credentialing tool for maybe a competency-based progression. How would you advise them on auditing the technology when they take it in, or just things to look for that are good?

Advice for School Leaders: Data Governance First

Kelly: I always start with data and data governance. It’s really important, before you even think of a technology or a solution, to understand your district’s approach to data and data governance with existing technologies you already probably have, because of the granularity, I love that word, when we start to get into learner data, the amount of data that’s collected through different systems, it’s really important to start thinking, well, what do we believe as a district, what do our schools believe we should be collecting?

That’s when you get into what’s the purpose of whatever this is, and whose values align with you as a district or a college relative to what you’re building. Writing down what the data is for, who’s involved in the decision-making around it. There’s so much around data governance to unpack, especially when this requires multiple organizations to touch the data. As a district, you have a responsibility to your constituents, your children, your teachers, your parents. What does that actually mean in terms of data rights? And also, what data should not be included, or not shared, or if it is going to be shared, these are the requirements.

When collecting and using data, there needs to be a retention date, it can’t be forever. We talk about lifelong learning, but imagine being a child in middle school who got a record issued to you, and then 10 years later that’s still on your record. There has to be an end date, and that has to be in collaboration with the learner.

I’d also be looking at vendor lock-in, that’s always a big one for me. If you’re interviewing vendors, ask them, “What happens if you go away? What happens if you disappear? What happens to the data?” Their response will tell you everything. One project I sat on, at the end of the project, the educational institution decided not to move forward with the vendor, and we were like, “Well, okay, what happens now with the data that’s in the system?” Interesting conversation, and when people start saying, “Oh, we need to talk to our legal team,” that’s when I go, “Oh, okay.” So a few very honest conversations around what’s the data for, who’s collecting it, is there a retention policy, and most importantly, what happens if the vendor disappears?

Mason: Yeah, that’s a really tricky one. Do you think, if you extend this out, say 10 years from now, and this works, is your vision for this something that looks more like a state-issued digital driver’s license, where it’s all mapped and it’s not a technological provider to a district, there’s no procurement, it’s just a really centralized database? Or do you think about it differently?

Kelly: I think for this to truly work, it has to be learner-centered, so the learner is at the center of the technology, something they’ve opted into, because any solution that comes from a district, a state, or whatever, they’re going to have governance over it. The future I see is total decentralized, self-sovereign data, institutions having to ask us for permission for access to our data to do certain things with it.

It’s existing, but not in learning. There’s a lot of innovation happening in what self-sovereignty actually means around data. Have you heard of the MyData project?

Mason: I have, yeah, but tell our listeners more about it.

Kelly: MyData is a group of individuals and organizations coming together to actually build protocols, systems, and policies around really ensuring individuals’ rights around their data. What I find interesting about the approach of MyData, and others similar to it, is that instead of starting with the technology solution, it starts with the thing we should have more rights over, the kind of data we have.

The difficulty we have now is, if you go back to the early days of the web and the internet, it was more decentralized, more individual control, and we’ve seen more centralized control since. So how can we build systems that truly enable individuals to take their data with them? When you graduate high school, does your high school actually require all that learning information about you in your LMS, your student information system? Or do they just need a record that you met the requirements for graduation, and that’s the only record they get to keep, and you take the rest with you?

It’s taking the principles around MyData and saying, “If this is truly my data, developed in collaboration with my teachers and my school district, at some point that data should be passed on to me for my sovereignty over it.” I kind of feel like we have more sovereignty over some things and not others. I know more about what my electric car is doing than I do about my child in school, and that doesn’t sit very well.

Mason: Yeah, that makes a lot of sense. I was looking into some of the AI data collection stuff recently, because I was using chatbots and thinking, “How much of this are you retaining and using to train models?” Even the ways that’s structured, like a company account that’s paid, they don’t keep any of it, but if you’re a free user, they collect it. I think those are the kinds of conversations we’re just going to keep having going forward, and really going to have to hold people accountable, “That’s actually an equity issue.” If you’re collecting all this data about free users, people who are probably not under a corporate account, that will be a self-perpetuating cycle of harm to the people who tend to get harmed the most.

Kelly: And the people who have a responsibility are our school districts, our publicly funded educational institutions. If you’re funded through public money, you have a governance responsibility to your learners and your families. We start to think, well, what is the accountability and the responsibility, and who’s involved in those kinds of decisions? Data equity for me always starts with not just how data might be used about me, but how much is collected on me. Do people really need that kind of data?

When I work with clients and we start to build data models, one of the projects had over 300 data points on a child in school, including GPS coordinates if they’re using the app. And I’m like, “They’re in school, do we need to know the GPS coordinates?” But that was considered an identity field. This is where I start to go, how much is too much, and what do you actually need to make the business decisions you’re making as a school district, or as a teacher, whatever your role might be, versus “oh, we can collect it, so let’s collect it.” This is actually one of the chapters in the book, where we dig into this.

That’s where I think we’re starting to see how we build consent mechanisms and the ability for people to truly consent to how their data is being used, and also to withdraw that data if they don’t want to participate. We’ve not figured that out.

Mason: No, we have not figured that out. We’ve been using a lot of tools for a long time that we thought were free, that are not really free. That’s kind of the dark side of the information age we’ve all been through.

What a Real Credential Looks Like

Mason: Maybe a second-to-last question here. I’m curious, and if you don’t have an answer, that’s fine, because I’m throwing this at you on the spot. But if you were to go apply for a job right now, in maybe something adjacent to what you’re doing, what’s an example of an artifact or micro-credential or something you would bring along with you to demonstrate knowing something, and what’s the story you would tell about it?

Kelly: Ooh, wow, okay, that’s a thing. I’ll actually give you one that’s very recent. I’ve worked in education and workforce development for many years, specifically in tech innovation and adoption, and really learning from learners and workers. I was fortunate to get certified with the National Association of Workforce Development Professionals, with their certification.

The interesting thing about that certification, as I said, is it’s just a conversation starter. It might be listed on something, usually nowadays we have to complete applicant tracking systems, there are so many things we have to fill in, and it would be a line item. Yet if someone asked me about my workforce development experience, I could speak to these stories of things I’ve done. The way data is being treated is it’s being used to filter you in or filter you out, you don’t get a chance to tell the story.

One of the promises of verifiable learning and employment records is that evidence link. What’s interesting is sometimes you have the ability to withhold the evidence if you wish, depending on how the credential is designed, and sometimes you don’t, and the evidence has been added by somebody else. That’s a prime example, in my opinion, it’s less about the credential and more about the evidence it speaks to, and how are we helping people collect and build profiles of verifiable evidence, verifiable credentials, or verifiable stories. A story could have 10 different actual verifiable credentials added to it. That, to me, is more powerful.

Mason: Totally agree. I think that’s a really helpful demonstration of what we’ve been talking about. One other thing I was curious about, whether it would come up in that answer, we both sat in on a session at Badge Summit led by Simone on indigenous recognition systems, his term, rooted in indigenous knowledge systems. So much of that work, and so much of the work of the workforce, is about who you know, a social capital component. That’s really missing from the credentialing conversation, how do you recognize networks of people? How do you get beyond the sort of cheap LinkedIn endorsement, or the LinkedIn connection that’s a friend of a friend of a friend you met once, and actually make it people who will vouch for you, reciprocally, who will be that living testimony or story of evidence. Because once you have a witness, that really starts to verify your experience in a way.

Kelly: One thing I don’t think we do enough of in the record and credentialing space is, what do peer-to-peer endorsements look like, feel like, and how are they verifiable? When I talk about recognition, I talk about it as a triangle. That triangle has self-recognition, I can recognize certain things I do or don’t do with certain experiences, but my peers also recognize things about me that I don’t see, because I have blind spots, and so might an institution.

With the CWDP certification, what I loved about their team and what they’re doing with it, is it’s not just me saying, “I’ve got X amount of years experience doing this.” There were also peer endorsements that collected stories about what I had done, as well as an institution evaluating and assessing me on what I had done. If you really want verifiable, it can’t just be top-down, the teacher telling me whether I passed. The students I’m working with at school, they can also give evidence, and let’s trust that, and let’s also trust self-assessments.

I don’t have an answer for this, Mason, so I’m not giving you an answer, but the fear-mongering around the use of AI to build resumes and apply for jobs, the people it’s doing the most damage to are everyday learners and workers who spend hours putting their resumes together and then get told they used AI when they might not have. We know the validation systems, the science that’s been looked at, even people can’t really recognize whether it’s AI or not. We need to be mindful of where care and trust live in these systems we’re building, and the real lived experience of their use. I spend a lot of my time rolling out a technology, let’s sit with people, let’s hang out, let’s show it to them, let’s have them use it. They’ll tell you whether it works for them or not, and that’s the most important part.

I’d love to get into that triangular model of recognition, it’s about peers, it’s about institutions, it’s about self, and it might manifest itself in a credential, or it might manifest itself in something else. That’s really important, to recognize those social networks. Our indigenous communities do it really, really well, in how they recognize people’s skills, their cultural impact, their value, and I think we can learn a lot from them, as opposed to trying to imprint our way of recognition and credentialing onto indigenous knowledge systems. They’ve been doing it for thousands of years.

Mason: Absolutely.

Kelly: Thousands of years. Let’s learn from them.

Closing

Mason: I totally agree. All right, final question, where can our listeners go to learn more about what you’re up to?

Kelly: To learn more about what we’re up to, you can go to lwylstudio.com. For the book, bookshop.org, I’m a big believer in our independent bookstores, love to support them, you can search “When Credentials Cause Harm.” You can also search our other book, “By Co-Design,” how to truly build better innovations together. Those are really the best places to go, or just Google our name, get out there, connect with me on LinkedIn, happy to have a chat.

Mason: Fantastic, awesome. Well, Dr. Kelly Page, thank you so much for being here today. It’s great to see you.

Kelly: My pleasure. Great to see you too, Mason. Thank you so much, everyone.

Guest Resources

• When Credentials Cause Harm
• LinkedIn Profile: Dr. Kelly Page LinkedIn
• Organization Website: LWYL Studio
• Past Interviews and Resources: Dr. Kelly Page Website