Wayne Skipper, CEO of Concentric Sky: Future-Proofing with Digital Badges

Van Ton-Quinlivan: Welcome to WorkforceRx with Futuro Health, where future-focused leaders in education, workforce development, and health care explore new innovations and approaches. I’m your host Van Ton-Quinlivan, CEO of Futuro Health.

Regular listeners to this podcast know that online learning is booming as people seek new skills and credentials as a quicker, cheaper alternative to degree programs. We’ve also heard guests talk about the need for credible ways to capture all of the hard and soft skills people acquire through various virtual and in-person learning, work, and life experiences. Today’s guest is going to help us understand one approach to meeting the need: digital badging.

Wayne Skipper is the founder and CEO of Concentric Sky, a software development firm that’s launched hundreds of products including a platform for digital badging and micro-credentials called Badgr http://www.badgr.com which we’ll be learning about in detail. He also co-founded Open Skills Network, a group of more than 400 employers, education organizations and technology providers dedicated to accelerating the adoption of skills-based education and workforce opportunities. Thank you so much for joining us today, Wayne.

Wayne Skipper: My pleasure. Thanks for having me on, Van.

Van Ton-Quinlivan: Wayne, before we dive into the world of digital badging and micro-credentials, can you help our listeners understand more about your background and Concentric Sky?

Wayne Skipper: Certainly. So, my background is engineering. I spent over a decade in the world of hardware engineering, silicon chips, computer systems, networking systems, etc. I founded Concentric Sky in 2005 as my own personal consultancy in the world of education technology, and I’ve since grown it to be nearly a hundred people who are based in Eugene, Oregon. So, our work tends to be on the high end of the consulting spectrum — a lot of machine learning work these days, analytics systems handling trillions of records — and our work has been featured broadly over the years, including by Apple who included it in the launch of the iPad.

Van Ton-Quinlivan: I was so glad to have met you at the Institute for the Future. What brought you to the Institute by the way, Wayne?

Wayne Skipper: I was invited by some other thought leaders that thought that it would be beneficial for an exchange of ideas, and I have to say that my conversation with you was perhaps the most valuable thing to come out of that entire event. It has been impactful on the lives of millions of people. So, serendipity for sure.

Van Ton-Quinlivan: You’re absolutely right. As I think back to that moment in time, our conversation actually opened my mind to the concept of digital badging. Most people got their initial exposure to the concept of badges in Girl Scouts or Boy Scouts…you learn a skill, you get a physical badge that you can put onto your ribbon. Now you’re translating that into the digital world and you’re actually also advocating to badge everything. So, what is a digital badge and why badge everything?

Wayne Skipper: Great questions. When Mozilla and the MacArthur Foundation first came up with a concept of digital badges back in 2011, their goal was to create exactly what you stated — a digital version of a merit badge. It was a way that a user could convey some sort of achievement online –typically a light, low-stakes sort of achievement — for use in various purposes. They weren’t really aspiring at that point in time to high-stakes credentials such as degrees. We entered into the conversation when Mozilla and MacArthur approached us in 2015 to write what is known as Open Badges 2.0, which is the second version of the technology standard which underlies the digital badging world. Part of our work there was to really increase the security of digital badges and to make them more suitable for use in a higher-stakes learning environment. That was really the moment when they started to catch on for use in what we think of as traditional credentials that are typically higher stakes. People use them to get jobs, people use them to get promotions, etc.

There are a number of trends that are working together to create a demand for this technology. In education, you see a shift from measuring seat time to measuring proficiencies, sometimes also called competencies or skills. In the workforce, you see a shift towards skills-based hiring, upskilling and re-skilling. Digital badges give us a way to speak to employers in a language that they understand, creating better outcomes for learners at all levels. Institutions, who are now measuring student success through the lens of job placement, are able to do a better job of helping employers understand what is meant by a credential and what proficiencies a learner who goes through their program can demonstrate.

The primary value of digital badges as a mechanism for this exchange of information is that a digital badge is not just a digital sticker. It’s not just an image that appears on a social media feed. A digital badge actually contains embedded metadata which allows the claims that are made about the credential by the issuer of the credential to be independently verified by third parties. So, you can think about it not just as an image but as a vehicle by which a little mini-transcript with supporting evidence can be conveyed from place to place. That’s the real key innovation of digital badges and what makes them so interesting.

Van Ton-Quinlivan: One of the provocations you chose when we were there in Silicon Valley was…your children are toddlers, and we don’t know what kind of jobs they will have in their future because some of those jobs don’t exist yet. That was the importance of digital badging everything.

Wayne Skipper: Absolutely. Preparing for the unknown is really one of the primary goals of education. If you look at the practices of antiquity and what is known as the liberal arts approach to education, the goal of that is not necessarily to train someone for a job. The goal of that is to produce a whole person. You teach dance, you teach math, you teach history, you teach philosophy because you don’t know what the future holds for people. It’s important that people can deal with the unknown and as we shift more towards job training, some of that is lost. We’re not really trying to endeavor to create whole people anymore. We’re trying to create people that have skill profiles that match what employers want, but it’s very difficult to know what that’s going to be over time because what employers want is determined by market forces which are complex and really beyond anyone’s control. The challenge with education is to continue to adapt to this quantification of learning while also helping to prepare students for the unknown.

I have a stance on badging which isn’t as popular with some, but I say ‘badge everything.’ Give people badges for tying their shoes. I know it sounds absurd, but it tells you something about that individual. The key thing to understand about digital badges is that they don’t all have to represent the same grain size of learning. In education and traditional credentialing, you have associate’s degrees, baccalaureate degrees, master’s degrees, Ph.Ds. — those all represent different grain sizes of accomplishment. Well, you can go even smaller. You can get down to skills. You can get down to small proficiencies and you can get as small as you need to get a really good picture of what somebody is doing and quantifying things to their benefit.

I’ll give an example. Say I’m a kid in high school and I like to play flight simulator games and I get open badges for achievements inside of a video game. I also like to go to air shows and I get digital badges for going to those things and activities that I might do there. Now, you look at that through the traditional education lens and you say, “Well those are worthless pieces of information because there is no assessment and there’s no pedagogy, so who cares about that stuff?” But then you put your guidance counselor hat on and you realize, “Whoa…this student has identified an interest in a STEM career and I can use that to motivate them towards a career trajectory that’s going to line up their passions and their knowledge with something that’s going to be beneficial to them throughout their career.”

For this reason, I say badge everything. Quantify it all. This is how we can benefit learners as we move into the unknown because we don’t know what will be valuable in the future. Maybe the top skill in the next century is hand-eye coordination because we all live in a VR world and all the kids that played video games are the ones that are in highest demand because they can navigate that world better than so many other people. We just don’t know.

Van Ton-Quinlivan: That’s what we all hope, Wayne…that all of our children who are playing video games are going to have the hand-eye coordination to become the future surgeon or drone pilot.

Wayne Skipper: (laughs) Exactly. Exactly.

Van Ton-Quinlivan: What’s your assessment of the future of digital badging? Is it catching on and do you think it will be commonplace in the future?

Wayne Skipper: I would say, at this point, it’s a runaway freight train. When I first got into this space in 2014 working with Mozilla and MacArthur the questions were, what is a digital badge and why should I care? “We don’t need no stinking badges”– I heard that joke about a million times. But at this point, I would estimate between my company and some of our near competitors, close to 100 million digital badges have been issued in the world, give or take, and so they’re everywhere. You see them all over the place. Lots of companies are using them. The utility of these tools and these trends that I mentioned, in addition to some other trends around AI and machine learning, are really just going to keep driving the adoption of this technology.

Van Ton-Quinlivan: You mentioned 100 million badges. Now, to make sense of 100 million badges don’t we need AI or machine learning to crunch through that and help us translate what is actually meaningful to the job market, or what is meaningful in my skills that relate to the jobs that are opening?

Wayne Skipper: Absolutely. We’re just awash in data. The internet expands daily. There’s just too much data, really, for the human mind to process and to work with. But at the same time, we don’t want the internet to be smaller just because it’s full of garbage. There’s a lot of data that is not useful or it’s not useful beyond a certain amount of time. What we want to do is we want to sort that data, and machine learning is an excellent tool for sorting that data. But there are challenges that come along with using machine learning and AI for these things.

When you start to think about applying AI and machine learning to skills and learning, there’s really two ways to think about developing a skills framework or some sort of “graph of knowledge.” One of those is to have the machine learning process all of the information and decide for itself what concept relates to which other concepts, and what knowledge is associated with what ability, etc. But the challenge with this is that it doesn’t allow us to inspect the resulting models. Those models tend to be multi-dimensional, they’re very complex, they’re hard to visualize and so it’s challenging to assess them for something that I think is a very important consideration in this technology, which is implicit bias.

And so, it’s really important that we can inspect the AI models because that allows us to address that sort of bias. The way we do that is with the second technique which I like to call human-curated structured data which is really having a subject matter expert define the skills framework to say which concept leads to which concept, and what knowledge is associated with what ability and then use that as the beginning framework for which you can build AI learning models. This gives us the ability to interject, at the point of skills definition, the idea of more equitable use of language. I think this is just essential. It was the need that I saw to create this that led to me founding the Open Skills Network.

Van Ton-Quinlivan: Tell us more about the Open Skills Network and why skills open taxonomy matters in getting that done?

Wayne Skipper: I started thinking about this back in 2019 and I created something called the Open Taxonomy Project. The idea was to have a Rosetta Stone for skills so that we would have open taxonomies that we could use to understand the meaning of a skill as it traveled from context to context. What I saw was that a lot of organizations were using machine learning to derive sets of keywords from the bodies of information that they had. We’ve already talked about the challenges of the biases there, but there are more concrete and very challenging issues with deriving keyword lists from sets of knowledge. For example, what’s a server? Is a server a member of a wait staff team, or is a server a computer system? When all you have is one word, you really can’t answer that question in any meaningful way. But there are more nuanced challenges. If you start thinking about communication, the communication skill that’s needed for a teacher or a nurse is actually very different than the communication skill needed by an air traffic controller, a graphic designer, or an engineer. So those are related skills, but one word is insufficient to capture the meaning of that skill.

So, I gathered partners of ours at the U.S. Department of Education in early 2020. It was a number of organizations including Western Governors University, Southern New Hampshire University, Arizona State University, major employers such as Walmart, Sales Force, and others. We had a conversation about this topic and I proposed the creation of what is now called the Open Skills Management Toolset, which is an open-source set of tools designed to help organizations design intentional skills frameworks and start to move along that skills journey that all of us are really taking together whether we know it or not.

My goal with the technology was to have it not be in the way. As someone who’s designed a lot of technology, I see technology systems often become impediments and my goal in proposing this, and why I wanted it to be an open-source tool instead of a product, was really to move the ball as fast as possible for organizations that wanted to adopt skills-based practices. The result of that conversation was the founding of what is now known as the Open Skills Network and you can learn more about that at openskillsnetwork.org. The momentum there is just really incredible. From the five or six organizations that were intentional early founders of that, we have now grown to over 400 organizations worldwide and we have a skill summit coming up here at the end of July, where our first 14 pilot consortia are going to be displaying the work that they’ve done using these tools. I would invite those that are really interested in learning more about Open Skills and more about the current work and the momentum there to check out the Skill Summit coming up at the end of July. A video recording of the summit will be available on http://openskillsnetwork.org if you are unable to make it to the event.

Van Ton-Quinlivan: Wayne, we had a prior guest on the podcast from New America Foundation who talked about Learner and Employment Records. Is there a relationship between the open skills taxonomy and this LER record?

Wayne Skipper: Absolutely. So, the LER concept is being addressed in several different directions by different organizations, but the seed of the idea came from the American Workforce Policy Advisory Board which was launched by the prior administration. That resulted in a set of pilots which are available at commerce.gov that describe, conceptually, this idea of a Learning and Employment Record which has been called by several different acronyms. LER is really more of a concept at this point than a specification. In terms of its relationship to skills framework…the skills framework provides the Rosetta Stone so that we can understand the meaning of a skill or proficiency as it moves from setting to setting. So, rather than just saying this badge represents communication, we can say this badge represents communication as defined by Western Governors University for example, or by the military or by a key employer, and this communication skill has a level of proficiency perhaps associated with it.

The badges and the skills and the frameworks — the technology standards — are what make it possible to have something that is a Learning and Employment Record that is not just a blob of text because when you move back towards using blobs of text you end up moving back towards processing those with machine learning language models, which is definitely a step backward. What we really need is the structured data so that I can as an employer understand what is meant by the credential, not just the words that are used to describe the credential, which is a key difference.

Van Ton-Quinlivan: We’re cheering you and everyone on in terms of this frontier of innovation. When we first met, I was with the California Community Colleges. We went on to collaborate on the Program Mapper using this digital badging technology. Tell us the resulting “on path” student outcomes and why the Program Mapper led to those outstanding student success results.

Wayne Skipper: The Program Mapper is one of the things I’m most proud of in my entire career specifically because of those outcomes. The Program Mapper was a way to visualize for prospective community college students what a journey might look like through the course of program structure of the California Community Colleges. You can look at the interest clusters, you can look at the programs, see the learning outcomes, see the expected employment outcomes for holders of the resulting credentials. Then you get a really beautiful map that’s easy to understand for a prospective college student and their family what that journey is going to look like term through term.

It’s not a scheduling tool. It’s really more of a catalog visualization tool, and where it really started to take off was when we started to think through what would it look like if we included both the two-year and the four-year programs together and helped families and prospective students understand what their articulation might look like for them. “I want to go take my two-year general education stuff at a local institution because that’s easy to get that out of the way. Then I want to transfer to UCLA, or I want to transfer to one of the Cal State schools. What does that journey look like for me?” The tool does that. It includes information that crosses all of the public higher education sectors in California and we have it now in over half of the California Community Colleges.

After the application of the Program Mapper tool what we saw was not only a statistically significant increase in the on-path student percentage of about 20% but more importantly than that — and what I’m proudest of — is that across all demographic groups the outcomes were far more equitable. They were within one or two percent of each other rather than being an eight or ten percent difference. A highly impactful tool, and what I’m so proud of is that it’s rare for technology to be able to actually demonstrate efficacy in increasing equitable outcomes. I’m really proud that we have the data to show that it does.

Van Ton-Quinlivan: As executive vice chancellor back then I was so delighted to have championed this experimentation. One of the things that most interested me in our conversation was the approach that you had, which was to make things open standard so that we’re not locking institutions into proprietary processes.

Wayne Skipper: Exactly.

Van Ton-Quinlivan: Can you talk more about this because this helped the adoption of Badgr into countries as well, right?

Wayne Skipper: Absolutely. There are entire countries that base their credentialing systems on our Badgr product and you can learn more about that at badgr.com. The value of open standards…you really nailed it with the lack of vendor lock-in. What it does is allows us to create a system of innovation that is not dependent on key vendors and I would go back to the creation of the internet itself, which you mentioned earlier. The internet functions the way it does because it was never designed to be a product. The internet was designed by engineers for engineers for efficacy. It was designed to work from a technical perspective. No one at the time — Vince Cerf and Tim Berners Lee in particular — were thinking ‘how do I make money with this internet thing.’ They just wanted to build something that was great and build something that would work for society, and look what we have built upon it. We would be nowhere near where we were now if we had some company that was charging us a penny per email that we’ve sent or a penny per packet that moved through the pipes. But in general, open standards allow us to create a level playing field for the exchange of information which benefits everyone.

For example, go to the common power plug. Regardless of where you are in the world there is a standard way of connecting an electrical device into your wiring grid. When you go and buy an appliance you don’t have to think, “How am I going to wire this into my house? Do the voltages match? I don’t know about any of that stuff.” You just plug it in. It’s a no-brainer and that’s what open standards give us…the ability to define these key connection points between technologies that are not dependent on a particular vendor.

For the institutional side of things, this eliminates this idea of vendor lock-in where you have things like education plans and skills progressions and other things represented in data formats that are easily portable from system to system and because they are understandable and inspectable, other people can build stuff that works with it. For example, you have an open standard that represents a transcript. It’s really easy to ingest that and then use that in another system. We don’t have to pay a licensing fee to look at somebody’s transcript, not the data format of it. I would say open standards are essential in the exchange of information and really trying to build the kind of future that we want to live in.

Van Ton-Quinlivan: Thank you for that good explanation of the importance of open standards to innovation. Dr. Soon Joo Gog of Skills Future in Singapore advised us to look at innovation leaders and see how their technology is changing workflows, and when you see how workflows change you can infer how the workforce skills would change. Looking ahead, name one entity whom you regard as an innovation leader who will disrupt workforce skills as they are, and who would you advise us to follow?

Wayne Skipper: I would name several in different verticals. I would say on the employer side, the work that Walmart is doing is particularly inspiring. They have created a skills-based hiring and training system that they’re currently rolling out to all 1.5 million employees. What I like about this program is that it is not just skilled professionals. A lot of focus in this space is on things like industry certifications and things like professional organizations, but that’s a very small segment of the population. Focusing on the frontline workers is something that I think is really imperative and trying to improve outcomes is very admirable. I think Walmart should be commended for their leadership there.

In the education space, the institutions I named previously — Western Governors University, Southern New Hampshire University, and Arizona State University — are all doing really groundbreaking work in the area of skills. In particular, I would call out Western Governors University which is just doing some amazing work in the Open Skills Network and has graciously lent their skills architects to all of the pilot participants there. I think that in education, that’s definitely an organization to watch.

Van Ton-Quinlivan: And what do you see 10 years from now for the future of work, of higher education, of learning. Let’s put on our crystal balls here.

Wayne Skipper: I’ll address each one in turn. In the future of work, what we’re going to see is a shift toward skills-based hiring and practices because it makes sense and it reduces friction. The current systems of credentialing still leave employers with the need to assess. I’m an employer, I hire engineers. Someone having a degree in computer science is lovely but I would like to know how well they can code in Java. How well do they understand JavaScript? What’s their comprehension of a Version Control System? I need detailed information, and to get that I have to assess that person.

In the future, what we’ll have is what I like to call the quantified learner or the quantified worker. You look at all of the data about yourself and use that to design your own systems for your own benefit. I see this in the future of work, where workers will understand what skills they have and what skills they don’t have through the lens of where they want to go. For instance, I want to be a nurse or I want to be a pilot or I want to be a scientist. What skills do I need to get there? What do I have now? What does that journey look like for me? People can start to design those journeys themselves. This is the future, but the flip side of that is a lot more management by an algorithm. You see this in Uber and Lyft in particular, where the drivers there don’t actually report to humans in a traditional management structure. They’re managed by algorithm. We’re going to see a lot more of that as well, as we start to quantify learning and sort of quantify work.

In higher education, there’s a number of challenges happening. In particular, the decreasing market value of the traditional degree. When I was younger, going to college was the thing you did because we had data that showed it would increase earning potential. That’s a key value. In addition, I think that people want to be educated. They want to understand the world, history, philosophy, things like that. What makes the world work? How did we get here? By learning those sorts of things, they can start to think about the future. As part of what’s happened because of the shift in focus towards workforce outcomes you start to see an unfortunate trend, which is higher education becoming a job training system which I think gives short shrift to the value of things like philosophy and history that aren’t as easily quantifiable, but important parts of the human endeavor.

In higher ed, I think what we’re going to see is the use of machine learning and AI systems to try to abstract bodies of knowledge into competency graphs and knowledge graphs against which AI can create assessment information. You can almost think of it as a “university in a box,” which I think is a really terrible thing, but it’s something that technology is going to enable and is going to further increase the pressure on the traditional higher education institutions. When I talk to institutions, I tell them that any STEM field will be automated in the near future via machine learning and the way to create value for learners over the long term is to focus on the humanities — those things that are harder to quantify that people will still want to learn outside of just job training. But the forces that are pushing on higher education are pushing them towards this idea of job training and I think it’s going to be challenging for a lot of institutions to keep pace with that. The momentum behind digital badging and skills-based, competency-based education is a reflection of that pressure on the institutions.

Van Ton-Quinlivan: What about the future of learning?

Wayne Skipper: In the same light, I would say that the future of learning is likely to be construed as the future of training where the idea is that people have skills, jobs require skilled profiles, you have a personal skill profile that matches that or it doesn’t, and if it doesn’t you need to fill gaps A, B, and C. People will start using these defined data structures to curate their own career journeys. But the focus really is on the career and less on learning as a practice. I’m of the opinion that learning as a practice is a noble endeavor in and of itself, regardless of whether the outcomes are measurable in terms of career progression. So, I think that we run the danger of losing some of the value of the less quantifiable parts of learning and shifting more towards just pure training. It’s incumbent on all of us to try to make sure that we don’t lose the value that’s been created throughout history in these less quantifiable practices. But in general, we’re going to see self-curated journeys through these well-defined data structures which are going to reduce a lot of friction in the workforce. For that reason, I think it’s going to be very popular with everyone.

Van Ton-Quinlivan: As Marina Gorbis of the Institute for the Future would say we have in front of us multiple futures and the future is ours to choose.

Wayne Skipper: Absolutely.

Van Ton-Quinlivan: It’s wonderful to be in cahoots with you across some of these endeavors. Thank you very much, Wayne, for being with us today.

Wayne Skipper: Thank you, Van, for having me on. I really enjoyed our conversation

Van Ton-Quinlivan: Likewise. I’m Van Ton-Quinlivan, CEO of Futuro Health. Thanks for checking out this episode of WorkforceRx. I hope you will join us again as we continue to explore how to create a future-focused workforce in America.