Open Learning Talks: Digital Credentials and the Last Mile to Employment
Welcome, everyone to Open Learning Talks. It's great to be here. My name is Philipp Schmidt.
I'm a research scientist at MIT, and the Director of the Digital Credentials Consortium. And I will be moderating a discussion today about the work of the Digital Credentials Consortium, and some of our recent research, and specifically a report we authored called, The Last Mile: Barriers to Adoption of Digital Credentials. A couple of quick housekeeping notes before we get started.
So first, this talk is being recorded. And we will post the video on the Open Learning YouTube channel as soon as it has been captured. And then secondly, we welcome all of your thoughts, and questions, and input. And so feel free to post any questions you have, at any time actually, throughout the discussion in the chat. And some of our team members will be monitoring the chat, and pulling out questions that you're asking, and then we'll bring those back into the discussion. So at any time if you feel like you'd we'd like to ask a question, just put it in the chat, and we will pay attention to that.
So to start off, I would like to just ask my incredible panelists to say a couple of sentences about who they are. So we have Sharon Liu, Sean Murphy, and Brandon Muramatsu on the session today, and maybe we will just go in that order. Hi, everyone.
My name is Sharon Liu and I'm an Executive in Residence at Jobs For The Future. I'm excited to be here, especially on Sean's birthday. So Sean, happy birthday. You are right about everything. Thank you, Sharon. I think right about only thing-- only today, I guess.
No, I appreciate the opportunity to join you all today. I'm a director here at Walmart, so we're located just down the street from campus in Bentonville, Arkansas, home of Walmart. And while I'm representing the entire company, I sit within the team that really focuses on opportunity for all, especially as we think about upward mobility within careers. And so everything that's being talked about today really aligns with that, and look forward to further conversation. And I'm Brandon Muramatsu from MIT Open Learning. I am actually pleased to be in the MIT Open Learning today.
It's a novel concept that many of you will give me a hard time about. I'm pleased to be here with these panelists talking about The Last Mile report. Great. Thank you for joining me and thank you for giving away our little secret, Sharon.
It is Sean's birthday. It's amazing to see the birthday wishes come through the chat. So this work is so interesting that Sean chooses to spend his birthday discussing with us.
We-- that's high praise. So in terms of the run of show, I'll say just a few things about the DCC, and why we're doing this work, and kind of high-level. Then Brandon will jump in and give an overview of the report, some of the things some of the insights we've pulled together, and some of the recommendations.
And then the four of us-- I'll ask the questions, but occasionally jump in-- the four of us are going to discuss some of the things that are in the report and any other kind of related themes that we want to tackle here together. And as I said, feel free to post questions in the chat. We'll make sure to weave some of those into the discussion, as well. All right, let me just give you a little bit of a background on the Digital Credentials Consortium to position this work.
The DCC is a group of originally 12 universities from North America and Europe that set out to work together to build an infrastructure for digital academic credentials that can support the education systems of the future. And if you think about it, why would universities do this? Well, credentials are pretty important to our mission and what we provide to our students. They're maybe not the most important thing-- I think some people would argue the learning is really the most important thing, and the research-- but the credentials are how our graduates communicate some of the things that they've learned to potential employers, and they really help them open up opportunities throughout their careers. And so for universities to think about what those systems look like is very essential, and especially as we're starting to issue many different kinds of credentials. Not just traditionally diplomas, and degrees, and transcripts, but micro credentials, online courses, boot camps.
So there's such a plethora of credentials now, the thinking about digital systems to support that is becoming important, even more important. And so our vision, though, is not just to serve the needs of these 12 institutions and our students, but really to think about what an educational landscape looks like where learners have a higher degree of agency over how they represent what they've learned to a potential employer, and that is designed to promote more equitable learning outcomes and career pathways. Because one of the big challenges is that people learn things in all kinds of settings, not just at universities.
They learn on the job. They learn it when they pursue their hobbies. They learn from their friends. They take additional training programs. And finding ways to really reflect all those skills and competencies so that you can find the job that you're looking for, it's actually quite complicated right now. And so our hope is that, through this work, we can build an infrastructure that's trusted, and distributed, and shared, and then lets people issue, store, display, and verify these digital credentials in a way that serves these equitable outcomes.
And I'll just end by a little bit of terminology, because there are a lot of terms flying around. And the most-- the way we think about digital credentials is often through this metaphor of the envelope and the document that's inside the envelope. And so you want to be able to protect what's written on the document. But the university should be able to put on the document what they want to put on this document. And so the term learning and employment records is becoming, I would say, the more generally accepted term for all of these types of credentials.
And so learning and employment record is a system that contains verifiable information about a person's achievements spanning an inclusive range of contexts, whether education or training processes, formal or informal, classroom-based or workplace-based. And LERs can seamlessly record, verify, transmit, and interpret information about these learning achievements between learning institutions, businesses, and individuals. That's a mouthful, but I just wanted to make sure that we have that terminology somewhat shared and we all kind of use the terms in similar ways to avoid confusion later on. And with that, that's it from my side for now.
I will hand over to Brandon, who's going to walk us through some of the key findings from the report. Thank you, Philipp. So this is the report that we published at the end of September, beginning of October, Credentials To Employment: The Last Mile. It was a report primarily authored by Anthony Camilleri and a team he had put together, where Phillip and I served as editors, and we worked quite a bit with Anthony and his team to refine the report to what we published to the website.
So if you go to bit.ly/dcclastmile, you'll be able to get a copy of the report. Jeanine's dropped a copy into chat. And as Philipp was describing about this with the complex nature of the landscape, with some support from Sean at Walmart, we undertook to do this report to start to map and understand the space between digital credentials that can represent skills, competencies, abilities, and what's the relationship to adoption.
Why and how might employers be adopting them? What are some barriers to that? And then, taking a look at the recommendations that we could put forward to various constituencies to break down some of those barriers and to advance the use of digital credentials in employment? I'm just going to do very high-level of the key findings and then talk about some of the recommendations before we get into the panel discussion. Employers want to be able to match skills held by applicants to jobs. So being able to understand that, if I'm applying for a job and I want to share a set of skills I have-- whether they be in project management, or budgeting, or communications-- that there's some way of understanding what those skills are, and understanding where and how I got those skills. But there's currently a disconnect between wanting to be able to hire based off that, or promote based off that, and the information available in a way that is meaningful to employers. Resumes, both paper and PDF are still the lingua franca of application processes. You might have to fill out a whole bunch of information into-- when you apply for a job into a set of fields, but you still end up sending a PDF of your resume with it.
Or if you're applying in person, you hand over a resume. Ultimately to move forward with better understanding skills and abilities, we need some way of expressing that information in a detailed way. So that's the granular information.
There are things that universities can do. There are things that are-- employers might expect. There are things that various players in the ecosystem can do to help that. But ultimately moving from, I have a single piece of paper, right, a piece of paper that is my diploma, to a set of expressions about the skills and competencies I might have, is sort of the path forward.
These details on skills and credentials, more generally, are not integrated into human resource management systems. Much of the-- many of the large employers, as well as governments and other private organizations, use human resource management systems. They use technology to help mediate this process of individuals applying for jobs, and then also sort of managing their careers at the universities. They don't currently support verifiable credentials or digital credentials.
And the research found that it's unlikely that they'll be added by the vendors of these systems until there's demand, so the employers need to ask for this. Everyone says that this is an important thing to have, but it doesn't seem to be showing up in the processes and the supporting technology to get a job. And then in general, there's a lack of coordination across all of the different players in the ecosystem.
Some groups at ecosystem might be talking with one another, but there are all of these clumps of ecosystems. And I think maybe, Philipp, you'll talk about that a little bit at the end. Or maybe Sean, you will, with some of the LER mapping efforts. Those are sort of the findings at a high level. I encourage everyone to take a look at the report.
Take a look in more detail. Some of the recommendations, there are recommendations for a different-- each different set of organization. So issuers, universities, like MIT, we could accelerate issuing at scale. So MIT, for example, already provides a digital version of our diploma.
We could do so across all of the other programs and learning opportunities at MIT. We could start to include more skills and competencies in those digital diplomas or program certificates, and also supporting interoperability. The other members of the DCC consortium could start to do the same thing. Some of them do.
A couple of them do. Others are exploring. Recommendations for employers, they could-- employers, when a person's on-the-job they develop a set of skills, and the employers could issue credentials for those skills. So when I go into the proverbial Starbucks as a barista, I learn a set of skills, or use a set of skills there, that Starbucks, for example, could say that Brandon has the skills in making lattes, and that's something I could take with me to another job to share it. Or I have great skills talking with customers.
That's maybe a better example of a skill you might want to carry forward. They could also participate, and/or be invited to participate, in the development of competency frameworks. So many of the frameworks that exist now have been developed maybe with employers on the side, but also as activities with other non-employment partners-- whether they be academic researchers or nonprofit organizations-- participating in those, the development of those frameworks, as a way of expressing competencies at skills.
And frankly, buying into that is an important activity. Governments could support innovation. They could remove barriers to being able to use digital credentials as part of a job process.
They could use digital credentials in their own hiring processes. They can-- Department of Education as an example, the US Department of Education, could promote them as a requirement for some of the federal funding. There are things that governments could do to help accelerate the adoption of the digital credentials. And one of the themes here is getting more credentials out there-- more importantly, getting more credentials that identify skills and competencies at a granular level-- for the system as a whole to start to recognize that they exist, and start to be able to use them. One more set of recommendations around trust providers. Trust providers are those like perhaps accreditation agencies, licensing bodies, ministries of education, professional societies like in the United States, perhaps.
These could be regional accreditors, or they could be somebody like, say, Educause, or they could be a consortium of colleges and universities. They can publish their information about who they trust, what organizations they recognize, as a set of data. Something that can be looked up, and can be expected to be accurate and maintained.
So we can start to do some of the things that are possible technology-wise to draw relationships between credentials and who issued them to understand whether we should trust the credential. So I can say that I graduated from UC Berkeley. You can call up UC Berkeley's registrar, ask if I attended, ask if I got a degree.
That's kind of a high-touch process. Computers make those kinds of things really easy, really quick. Trust providers can do quality guidelines to talk about the processes by which they are recognizing or trusting institutions. And then some things for joint action, developing a map of the skills ecosystem, enhancing evidence base of research. Why does this work? What organizations are doing this? What has been the impact on their businesses because of using skills and competencies as part of their job hiring process and promotion process? And then, a set of tools to help with validation to help demonstrate that the skill I claim, and the skill that you have said I have, is indeed the skill I have.
That you can validate that that's a skill. That was a really quick, possibly too quick, overview of The Last Mile report. But, hopefully, that gives you a little bit of a background.
And I will turn it back to you, Philipp. Thank you, Brandon. I thought that was an excellent overview, but I am biased, probably. So let's jump into the discussion with the rest of our panel. And they've already introduced themselves very briefly, but the question I would like to start off with is, maybe for each of you to say a little bit more about who you are in terms of the organization you represent, and the work that you're doing related to this field. And then also, why you think this is important.
Or what drives you, both personally-- why are you personally, kind of, invested in this-- and also then the perspective of your organization, like what's the particular angle that your organization has, and interest has, in this area. So we'll start with Sharon, maybe over to you first. So maybe just give a little bit more background on your work at JFF, and why you think this is important, and what the opportunities are.
Yeah, thank you. And thank you for the good overview, Brandon. It was-- actually, I agree with Jeanine, Brandon-tastic.
So let me tell you a little bit more about JFF, the who we are, and the kinds of work that we traditionally do, and our interest now in digital credentials and LERs. JFF is a national not-for-profit organization. We have been first located in the Boston area, but now national for about 40 years.
And our vision is, I guess, a society where workforce and education systems allow individuals to accelerate their own economic advancement. We know that there are individuals who are traditionally and systematic excluded, excluded from participation, and so a lot of the work that we do is to support inclusion of those populations. And in that context, one of the things-- so traditionally then, what a lot of our work is in supporting institutions, training providers, workforce development organizations to think about the different ways that learning can be provided, so that job seekers, workers who are interested in advancement, can obtain the skills that they need and then progress to the next level. At the same time, one of the other things that we do is we support employers who are constantly learning how to thrive in just a changing economy, changing demand for different kinds of skills, helping them to think about, are there different ways that they can engage with a broader diversity of talent to see more people? So that's actually why digital credentials, we think, is a critical part of the strategy. I think both you and Brandon both mentioned, credentials are a very important communication tool.
And traditionally-- and I think this is also in the report, as well-- the diploma says, I know something about something. But for a lot of Americans-- I think the last number from the Student Clearinghouse is that there are 33 million adults in the United States who have attended college in some capacity, but don't have their degree. So it's a language of deficit in a lot of cases for job applications.
Do you have a college degree? Yes or no. And the answer is no, so then they're automatically excluded from participation. But these credentials, LERs, allow people to say, actually these are other things that I can do.
Maybe I'm close to a Bachelor's degree. Maybe I'm close to an Associate's degree. Maybe I have job experience, or military, or community service experience. I'm going to capture these skills that I have, and communicate them to you in a way that you understand. So we're very interested in this. I think-- we think that the answer isn't, should we use digital credentials, but how? Is there something about the way that credentials are constructed so that individual learners and workers can control the information about themselves? Is part of that using open standards to allow portability across different vendor platforms? Is it to allow the sort of transparency into the different skills that are described by these credentials? So that's a little bit of why JFF is interested, and we look forward to having conversations with many people here about how to do that better.
Great. And actually, you've already hit on a few really big important themes now in your opening statement. So there are some things you mentioned, interoperability, equity, I definitely want to circle back to. So let's move on and hear from Sean.
Maybe a little bit more background on your work, and Walmart's work, and also, why you personally are invested in this space. Yeah, Philipp, thank you. And just real quick before I forget, just thank you to MIT for hosting this today, and all the work that's gone into making this a possibility. Diving in, Walmart, for those that may not know, really we've been engaged in this work of opportunity for the last eight years.
It's really been the last couple of years now that we have been more focused specifically on this whole idea of signaling your skills, right? And so why is that important to us? Why are we focused on that? For me personally, it's about truly giving everyone an opportunity to be successful. Recognizing that we all come from different means, and different places, and that means different things. And yet, we don't necessarily, in our economy, value all of the different types of learning that we all do, some of which you all have mentioned already in your comments. But as we think about this, if we really want to meet the economic opportunities of now in the future, right-- there's been all this conversation of future of work-- well, I think we all know the future is now, and it's only going to continue to evolve as we move forward. But if we're going to meet those opportunities, we really need the talent in the right places at the right time. We need a talent pool that is continually learning and growing.
It can't just be, did I get a four year degree right out of college? It means you need to learn throughout your lifetime and, hopefully, have those skills in a way that can be validated, right? As we know in our society, part of the reason that degree brings so much value is because it is validated by an institution that has all of the processes in place to make sure that has value, and that's important. But what if we could really not diminish in any way the value of a degree, but instead be able to gain the ability to understand what we're gaining through all of the other ways. Really raise the profile of all of the different ways you can learn and grow. And additionally-- and Phillip, you started going down this.
And Sharon, you did as well, right-- if we're going to really drive future growth, the future economic opportunity needs to be for all. It needs to really be a talent pool that is diverse in a lot of different ways. And in our current systems, we're not necessarily seeing that. And we can see that through the data, and I'm not going to rehash all of that. And this is where-- is the work that I get the privilege of working on on behalf of Walmart, but really our entire team, and the organization representing the company.
Really, we think to make this all a reality. We need to recognize that diverse talent pool requires a recognition that we all live within a world that provides different life circumstances, many of which that require different modalities and learning styles. Which is why we think that we need to really move to this idea of normalizing and validating learning through multiple pathways, ones that offer on ramps and off ramps to learning in a lot of different ways, recognizing that people have different circumstances, as I said. So to make this possible, this is where we really think you ultimately need a language that crosses all forms of learning, employment, and service.
Highlights service in there, right? We have a lot of service members that come out with immense levels of talent and skills they gained from the military, or through nonprofits, or other ways. Philipp, you started going down that path earlier, right? But really that this language, or language is, will be the idea that it's skills. It is skills, is that language, is that communication tool. And so to use this language to really enable it, we have to recognize right away that you're going to exponentially grow the amount of data that now must be maintained by end users, as well as all of the system partners. And it's not just manage, it's what do you do with this information. So this is really why we have believed, and continue to invest in, to support this work, is to really think we need that interoperable learning and employment record system that can do all of those things.
And emphasize again, that ability to share that data across systems. I'll go into a little bit more in a later comment here, but-- you know, and so for me, I'm just honored to be able to be here today to help amplify this and really influence the need for removing these barriers, many of which you all called out in the report, and more importantly presented some paths forward. So with that, I'll pass it back to you, Philipp.
Thank you. And I feel like we're starting to see some themes emerging here from the discussion. And so, let's go over to Brandon. And Brandon, kind of similar to the other two, maybe spend a little more time just talking a little bit about your personal background and why you're interest in this space. And then talking from the DCC perspective and maybe the MIT perspective, why do you think this is important work? Sure. Thank you, Philipp.
I don't think my comments are going to be nearly as good as Sean and Sharon's, but I'll take a shot at it. Philipp introduced the DCC and what are the overall mission of the 12 universities are. And I think that dovetails and ties into, sort of, my background and experience.
Over much of my work, or almost all of my work, is focused on helping others do the thing that they want to do-- whether it's learning a particular topic, whether it's finding educational resources on the web, whether it's sharing those resources openly through OpenCourseWares and open educational resources-- but it's providing the underpinnings of that opportunity. So Sean talked a lot about opportunity, and Sharon did as well. And I think what the DCC is doing is a couple fold. It has a focus on its members, helping its members achieve their vision of what they'd like to do with digital credentials. So in some cases that's issuing digital credentials, writ large, for all of the degrees issued by the University. For some it's transitioning between technologies, so technologies that-- previous versions of technologies to, sort of, current modern ones.
And in order to do those things, the DCC sort of centrally does a couple of things. We are active participants in the standards community. That we work very closely with the bodies that write and develop the standard, the technical underpinning standards for this. We do things like working with Sharon. So I was just with Sharon a couple of days ago where she and JFF had hosted a Plugfest. So how do we get to interoperability between systems? How do we ensure that there's an option for learners to take their credentials with them on their mobile phone, and to not be locked into a single mobile phone? So I've got an Apple device in my backpack.
I've got an Android device. What if I want to be able to move between the two? But as we focus on what universities need, or want to make available for their learners or their graduates, we keep finding that we need to keep expanding out our view. That it ends up-- it is an ecosystem challenge. It is an ecosystem problem to solve. And while we focus on some of the underlying technologies, we focus on some of the underlying process, we work from a support perspective to help registrars and other administrators understand what it might mean to put all of your digital diplomas online, we also find that in order to make sure that each of those have-- there's value to doing that, that ecosystem at large is supported. So our ties to employers, our ties to community colleges, and working with them.
So Sean was talking a lot about a degree as a terminal thing. And if you didn't get a degree-- and Sharon mentioned this-- then we don't recognize you. You can't go further in our job application process. But there's a lot of skills that people acquire before that, right? And so instead of waiting for the end, what if we are issuing credentials along the way? What if colleges and universities are issuing those credentials along the way to provide that opportunity, to send that signal, and send that in a verifiable way? I think I'll close there, Sean, and let you take it from there.
Great. Thank you. I think actually the three contributions, if we had no questions already articulated, we would be fine to just continue on those threads for the next half hour and probably longer. So thank you, thank you for that additional context. I'm going to kind of pick a question for each of you, and ask you to go a little deeper in a specific area. But feel free if you want to chime in or add to what someone else has already said, and I didn't ask you specifically, to just unmute your mic and come in and join the discussion.
So let me start with you, Sharon. You talked a little bit about JFF, and how JFF works with a lot of organizations. And so I wonder if you could give us a few examples of how LERs affect the organizations, and the people that are affiliated with these organizations, in the work that you do. Just to try to make this fairly abstract topic and field a little bit more concrete, like how are people really engaging with this? What are some of the barriers that you're bumping into? And then see if there are certain opportunities, or certain issues that you've encountered in that work, that you want to share.
So this is what's really exciting is that it is, I think, theoretically interesting to talk about this topic, but the number and diversity of projects that we work on is also, I think, an interesting data point. Just a context over the last I think three-- I guess I would say three to four years, the number of projects that people have wanted to partner with JFF on related to career pathways and digital credentials has just exploded. And I think this gets to all of the things that we are talking about, and I'll give you a very concrete example. So one of the things that we talk a lot about is, can you capture all of the learning regardless of where you obtained these experiences? And one of the kinds of learning that consistently is where individuals have difficulty translating is their military experience.
And there's a lot of reasons for this. First, the military is an example of another organization that is a trust organization, the government entity, but they speak an entirely different language than even the employers, or the educational institutions, or training providers. They have their own way of saying how far you've progressed in the level of skills you have based on your rank and your category.
And I'm going to also get this wrong, because I forget these things sometimes. But then also there's the secret, not secret, parts about what they want to tell the university about the skills that you have. So over the last several years, a lot of people have been working on how to transition military servicemen and service members as they're leaving the military into civilian jobs.
There have been a lot of projects around creating taxonomies that map the skills. But the project that JFF is currently working on right now that's pretty interesting, it's called MilGears. And it's essentially, how do you help transitioning service members describe the skills that they have achieved and their accomplishments during the military into language to hold those records, but also have a transition layer for those skills and achievements that ties into any civilian experience that they might have, so that they can compete for civilian jobs at the appropriate level. And I think I identified a number of the challenges around language, but it's also around formats of the digital credentials.
And can we create enough visibility into the skills contained in the credential packages, so that there can be a smooth transition? And then, how can we work then separately with employer networks to say, if you are going to try to make an effort to hire service members, here is a different way that you can engage them, so that they don't automatically get screened out in your engagement process? So this goes to a separate set of projects that JFF is engaged in around our Impact Employer network. And again, we have separate groups that do these projects because there is a separate way of working. Every kind of group has a different community culture and language set.
And so the groups that support employers think about, well, can you engage talent by committing to pathway programs internally? How do companies internally document the skills of their existing workers, and then, help them create training programs that allow their existing employees to advance to management levels, or other roles within their organization? And then, digital credentials is sort of the fabric that is underneath all of that. It is a way of translating across these two different languages and meeting in the middle, where individuals then can control their next steps. So I don't know if those are two-- I tried to be broad in how I provided the examples, but I think those are just two quick projects that we work on.
Yeah. No, I thought those were great. Because I think sometimes for all of us working in the field, we throw around some jargon, and we make grand statements. And sometimes, it's hard to forget that this has to be articulated in ways that actually make sense to people, to organizations, to businesses that are trying to do very different things. It's not their core interest to do digital credentials. And so I feel like those were great examples of both the opportunity, but also like, how would you actually start thinking about this in a particular context? So let me shift and-- there's a great question in the chat that I'm hoping to come back to, actually, which is about the employer perspective.
But we'll do that after our, kind of, first round of questions. So let me shift to Sean. Sean, you've already-- in your earlier remarks, you've already mentioned a whole range of different stakeholders, and how it's important that we understand all of their different perspectives. And so I wonder if you could speak a little bit more about that, this range of perspectives, and how they might connect to each other? And then also, I heard you say the future is now, which I liked.
And I wonder if you could say a little bit about, is there a certain urgency? Is there an opportunity about this right now? Or why would this be something that maybe we need to focus on now, rather than five years ago, or five years in the future? Yeah. No, great question Philipp. I think as we think about all of the stakeholders engaged, whether directly engaged-- I like my joke of, we got to teach everyone to spell LER, right-- there's a lot of change that has to come in the coming years from a narrative change perspective, right? What does all this mean? What are we doing? And each of those stakeholder groups have to hear it slightly different, because how it impacts their work. And so while we need some standardization across some of this work, we also need to recognize stakeholders, especially those that represent different organizations or individuals across this ecosystem. Need to be able to recognize how this plays into their world, and see the value and why they're engaging.
And recognize why it needs to be, not some sort of separate part of their work, but really needs to be aligned with what they're doing if we're really going to see the kind of change we'd like to see in the future. And that's where I think it's so important about some of-- as you looked, and did the research, and the report of, how do we bring this all together? And somewhat shifting to your second question is that, what's the urgency in this? You know, the concept of skill-based system has left the station. And while it's still evolving ecosystem, it's really moving with or without clear uniformity, even in places that are obviously needed, such as interoperability. And as I previously mentioned, skills will drive expanded use requirements for data, which must incorporate the needs of users, and especially workers, and employers.
But really all of the stakeholders, as I started going down the path of, need to figure out how their worlds play with this. How does this underlying utility support their work, and how do they better support their constituencies? Or how do they better use that data? You know, as I think-- as we think about bringing this system together, and why this is so urgent to do this now, is that we can either replicate the mistakes of our current health care record system-- no offense to anybody that plays in that space-- but we can either replicate the challenges in that system where all of our data is locked away within vendors used by providers, or we can get out in front of this evolving workforce system by bringing stakeholders together to build a shared vision to really map the ecosystem. Brandon started talking about that earlier, and I know that's in the report. And to really work towards answering unanswered questions that will get us-- get us in a way to, that this, all of this what we're talking about, can be sustainable, can be accessible, can be interoperable, and really meet the other necessary system components. You know if we do this right, there will be plenty of room for vendors, there will be plenty of room for providers and other distinguished folks to really distinguish themselves as a part of this overall body of work, while assuring we build a more equitable system that meets the needs of all involved in our economy, versus just those that might have access to a system like this. And so you know again, I think the key thing on-- for example in the health care records piece that I mentioned, is there's all the work now trying to make those things interoperable.
But how do we do that in advance of this workforce system, this LER system, this skill-based system, versus trying to fix it later? Yeah, I think the theme of interoperability resonates very strongly with me. I sometimes think about the early days of the internet, where people had to agree on certain protocols to share information. Things like email. Like if we had one company decide what email looks like, we'd now all be using some name of the company email.
But the early designers of that infrastructure designed a protocol that was open, that anyone could implement. And so we saw this amazing level of innovation happening, not just email of course, but all across the web, right? Those underlying protocols were interoperable, and that really was the secret. And so I feel like in this space that is maybe even more important to never forget that that's ultimately what we're all working towards. So Brandon, I was going to ask you a question more specifically about what could universities do, because you and I work in that space.
But there is that question about employers in the chat. So I wonder-- feel free to take this, maybe, whichever direction you want to go in-- focus on the universities, focus a littler more on the employers, or both-- but I think the question is more, what are some things that people can concretely do if they want to get started with this technology? OK, sure. They-- people, organizations-- can issue digital credentials, and more importantly verifiable ones. Ones that have a digital signature for which we can trust that things-- that the credential hasn't been altered. That we can trust the organization that issued it, so we can trace that back to an organization that we can then evaluate for trust. And companies can start to do it in a couple of things.
One, accept them as job applicants share them. Change and rethink their processes to, I'm not just going to look to see if you have a degree from one of 10 universities before I look at for this job. I'm going to think about the skills I actually need to see. The skills you'll actually need to use. The competencies that I've found over the course of running the business are important for people in your role with our business. And start to look for individuals with those-- that match those requirements.
So the requirement of a four-year degree is, well maybe, could you stick with something long enough to get a four-year degree? How well does that translate to the business needs of, you need to be able to speak to customers coming up to you and ordering things, being angry and upset, asking you for help while you're trying to do something else, right? So how much does a four-year degree really show that? I'm not so sure. But can we get to the sense of skills that you might have learned from another job, and being able to express those. Going back to Sharon and Sean's talking about the military, or even prior employers, being able to take the skills I have there and express those in a way that the new employer wants to see them. So I want to see which skills you have. I want to see where they've come from.
I want to see, perhaps, who validates these skills. Is that sort of along the lines of what you're hoping I'd chat about, Philipp? Yeah, I think that was good. I think just-- in the report, we say that-- we talk about these two levels. One is, let's just take all the things that people are-- that issuers are already issuing credentials for, and make-- and use an open standard for those diplomas, credits, transcripts. And then the other one is, I think, what you talked about. It's like, there are probably much better ways of representing skills and competencies than what we're doing today.
And so how can we start innovating in that space more with micro credentials, and open badges, and so. I think that's the university side. And maybe we can come back to the employer side also, because others-- go for it, Brandon.
One addition is, it might be worth drawing a distinction between universities and some of the activities that go on at universities. So some of them are probably very good at talking about micro credentials, or very granular skills and competencies. But as a whole, as a university, we're giving you a diploma-- a Bachelor of Science degree, or a Master of Science degree, or Master of Arts degree-- and we're expecting that to be sufficient to explain all of the richness of your experiences at the university, and whether it be in coursework or everything else. And so I think there are different players within the college and university ecosystem that do this ultimately better or more usefully than others.
Great, yeah. So I want to shift to a topic that I would call equity, kind of, as the headline. But it's really about, I think, all of us in some way or other have said that we are trying to design a system that works for everyone, that increases opportunities for people who may not have those opportunities today, for whatever reason. And that we believe that that's one of the benefits of the system, and that's why we're excited about it.
And so what are some of the-- you know, the history of education technology is long, and often new innovations have not been able to overcome existing inequities, or sometimes even exacerbated them. So how do we need to think about the risks related to equitable outcomes, and how are some of the ways that we could mitigate them? And I want to start with Sharon, but this is really a question to all of us. And also I want to highlight Naveen and Noah asked questions in the chat that kind of touched on this a little bit, so I'm trying to weave those questions into this bigger topic of equity and equitable outcomes. Over to you.
OK. Yeah, I'm just looking. Those are great questions, and thanks for combining them. So I feel like there are a number of-- I'll take this on, I think, three different levels, right? So on the most fundamental level, is there a way that the design of the technology stack itself presents inequities? And then about the utility of the credentials, and then how this plays in the ecosystem, right? So in the design of credentialing systems, absolutely it can potentially reflect all of the same inequities that, not just educational technology but technology in general, present for dividing between people who are in different categories per the census, right? So for example, credentialing systems that are mobile only or are web only present challenges to different populations.
People who don't have storage or broadband access may be prevented from engaging if your talent engagement platform is only online, or can't be used or accessed from a public library. So this is a challenge to people who are designing technology to be thinking about this. And I think that's a very long conversation for a whole different topic about, how can we design any technology to incorporate what is necessary to make sure that more people can use it? The second, I think, is a question about the utility of the credential by humans, like the credential itself. And I think this is even trickier because I think that, if you look at the literature and if you look at a lot of the projects that are ongoing, the question about digital credentials is mostly a set of hypotheses, or hopes and dreams, that we have for the future. I said earlier, and I think you also had said earlier, these are communication tools. We want people to be able to express their skills, but we want them to do it in a way that other people can understand in the language, so we work on those.
But ultimately, do we have research that using digital credentials actually leads to better social economic outcomes? And the answer is we don't yet, because I think we're just at a point where there's a critical number of digital credentials in the ecosystem. In addition to, I think, adopting the technology that will allow digital credentials to be used, there's an entire change management process around if I'm no longer screening based on, yes or no, do you have a Bachelor's degree, how does that change the way that I engage talent? Do I passively screen, or can it help me to actually be proactive in searching for a particular talent profile that I want, or I need to fill a particular role? I think that's really exciting. We just don't have a lot of implementations believe that-- that have those characteristics, and we don't know then how to measure the outcome. So I think this is a challenge for all of us as we continue to build to work together, because some of us will be technologists, some of us will be implementers, some of us will be researchers.
I think if we all approach this at the same time together, then as we design our deployments, as we design our technology, we can be asking these critical questions. And I also want to say one final thing-- about which, maybe Brandon we'll talk about in a second, too-- is the design of some of these credentials can help with this. So Brandon keeps mentioning digital signatures on credentials, but there are other elements of how digital credentials can be packaged and used so that it can ensure the privacy of individuals. So for example if you hate your job and you want a job search, how do you prove that you have a job without them calling your employer? Or if you don't want them to know that you are a certain racial or ethnic background, can you hide information that's not critically necessary to a decision about whether you are a talent match? And can employers mitigate any concerns that-- any of their practices by saying, no, we won't look at any of those data.
We'll only look at profiles. I think that the technology provides this potential, but I think that all of us as implementers need to be intentional and vigilant to make sure that this happens the way we want. Yeah, so let me just open it up to Sean and Brandon also to chime in.
How do we make sure that the system that we're all building really serves the needs of everyone? Yeah, I think building off of that, and also building off a little bit of some of what I was talking about earlier, is that data is king these days. And so data drives so much of what we do, whether we're at university making decisions around enrollments or other types of things, or we're Walmart making decisions on inventory and other types of things, right? Data drives so much of what we do, and often those with the right data at the right time are the ones winning most often. Now we could go into a whole conversation about sports, and how data is used in sports, but we'll spare that for another webinar, another day.
You know but what we have to recognize is, not everyone has access to that data. And so how do we make sure, as we think about what we're doing here, we give people access to their own data, and we bring them value in that, right? Give them the appropriate level of value for that data. And a lot of that comes with validation and other mechanisms that will bring value to those different forms of learning. But beyond just making sure people have access to their data, and then can share that interoperably across systems, we also have to recognize that a lot of the systems we're building will need us to remove the bias on the front end, right? Some of that's going to be by real engagement by workers and learners in the process of developing these systems, right? I think too often we build systems and hope they will come, whether-- no matter what the customer looks like. And in this, I think we really have to be deliberate in making sure those worker learners are engaged on the front end, and throughout the process, and that can show up in a lot of different ways.
But then also as we think about that removing of bias from the systems that will ultimately make a more equitable system, is that right now-- I talked earlier about the fact that this whole idea of skills has kind of left the barn, right? It's happening. And a lot of what's being used now is AI and skill inferencing, and building lots of cool tools that are doing that. But if we want to get out in front of removing a lot of that bias in those systems, is we need to make sure that the data that is informing that AI, that is informing the skill inferencing, is verifiable whenever possible, right? So instead of me having experience as an individual where big data is being used to tell my personal story, we're now feeding both big data and all kinds of different data sets into the AI and skill inferencing tools, along with my personalized data that I own that really tells my story, whether that is earned through a career pathway working at a Walmart store-- where 75% of our frontline or of our managers have started as hourly associates, right-- those folks are moving through. They're gaining lots of skills. And how do they, ultimately, have value for that as they move forward? And ultimately, make sure we're removing the bias and providing an equitable system across the board? Thanks, Sean. Over to you, Brandon.
Maybe just a couple of quick reflections on, how do we bake equity into the design of these systems? I think it's a tough challenge. I think we end up doing a lot of things by proxy, and that we need more direct contact with users. And so some of that comes, like for the DCC, with our work with Jobs For The Future and the various other colleges and universities we're working with. And it's going to sound kind of hokey, but taking a principled stance.
So the DCC, one of our core principals is learner agency. Another one is privacy. Another one is open software, open processes, and transparency. And the things we do as DCC, I think, in this space are meaningful because of that. That we're always looking out to make sure that the tools and technologies that we're promoting and we're implementing are ones that are as privacy-preserving as we can make them. That we're not baking in additional surveillance into these processes, and to give individuals an opportunity to fully control all of those credentials on their phone.
So I made a point in chat of, we've got iOS and Android implementations to allow individuals to carry their credentials with them that we don't do any analytics on. We don't know who you are. We don't know who's using it, what you're doing with it. But that's not the case in the rest of the industry. But we can make a case for why it's important.
All right, let me jump in here. We're almost at the top of the hour, and I just want to thank the panelists for joining me today and for this engaging discussion. I want to invite all of you to thank them as well, and to wish Sean a happy birthday.
And just say a couple of sentences about what's next. Because one of the recommendations from this report was to better coordinate the community, bring stakeholders together, develop a shared vision that people really buy into. And that can guide a little bit of our work over the next three to five years, and also inspire other people who want to get involved in this space, who maybe want to come in as funders, or as collaborators, or as tech companies, to give them a roadmap or an ecosystem map where they can find themselves. They can see what the challenges are. And they can see, also, how they might be able to address some of them.
And to Noah's question from the chat, he asked about HRMS systems. Like how are we going to get these systems to adopt this technology? And the answer is really that it has to be an ecosystem approach, because no individual stakeholder alone has enough incentive to invest in making this happen. It's like everyone kind of has to move it-- has to jump at the same moment, almost.
Like we have to kind of all agree that this is important, and then we all jump together, and then this will get momentum. And so I'm excited that we're continuing to do this work with Sean and a group of other organizations, including JFF. And thank you, Brandon, Sharon, and Sean for joining me today. Great discussion. I look forward to chatting with you soon again.