The Credential Flywheel: How Accredible Is Building Tomorrow’s Workforce with Danny King

Danny King is the CEO and Co-Founder of Accredible, a global digital credentialing platform that serves certificates and badges on behalf of MIT, Harvard, Google, Skillsoft, IEEE, GMAC, McGraw Hill and over 1,000 others. He founded the company in 2012 with Alan Heppenstall, with the vision of becoming the world's first truly verifiable repository of human capital. Over the years he has built a high performing organization fueled by the belief that individuals should be evaluated holistically, and organizations should take advantage of every technology to better identify the most capable team members. Today, Accredible is building the world's backbone infrastructure for credentials, empowering individuals around the globe to choose educational and career pathways that maximize their expected return on investment in terms of time, money and satisfaction.

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Transcript

Alexander Sarlin: 0:04

Welcome to Season Eight of Edtech Insiders where we speak to educators, founders, investors, thought leaders and the industry experts who are shaping the global education technology industry. Every week we bring you the week in edtech. important updates from the Edtech field, including news about core technologies and issues we know will influence the sector like artificial intelligence, extended reality, education, politics, and more. We also conduct in depth interviews with a wide variety of Edtech thought leaders and bring you insights and conversations from Edtech conferences all around the world. Remember to subscribe, follow and tell your Edtech friends about the podcast and to check out the Edtech Insiders substack newsletter. Thanks for being part of the Ed Tech insiders community enjoy the show. Danny King is the CEO and co founder of Accredible a global digital credentialing platform that serves certificates and badges on behalf of MIT, Harvard, Google Skillsoft, i e. G, MMAC, McGraw Hill and over 1000 others, even 2000 others, he founded the company in 2012, with Alan heppenstall, with the vision of becoming the world's first truly verifiable repository of human capital. Over the years, he's built a high performing organization fueled by the belief that individuals should be evaluated holistically, and organizations should take advantage of every technology to better identify the most capable team members. Today, Accredible is building the world's backbone infrastructure for credentials, empowering individuals around the globe to choose educational and career pathways that maximize their expected return on investment in terms of time, money and satisfaction. Danny King, Welcome to Edtech Insiders.

Danny King: 1:58

Hi, thank you so much for having me really delighted to be here.

Alexander Sarlin: 2:00

Yeah, I'm really, really excited to talk to you. I've been very impressed at Accredible I've followed your work for a long, long time. I followed the credentialing movement for a long, long time, and you have been in it for a long, long time. Accredible was founded in 2012. And it's grown like crazy. And you've done amazing things. Can you give us a little bit of a background of what inspired you to found Accredible and how you think about credentialing as well as how you think it's begun to change in the last decade?

Danny King: 2:31

Yeah, absolutely. Well, thank you for the kind words. First of all, it's been Yeah, an 11 or 12 year journey. And it's been a blast and having fun every day as the whole team. And like you said, we've really seen the sort of Dawn of the digital credentialing industry and CNET go from this tiny baby of a thing to what's pretty big now, and what what got us thinking and if it wasn't just me, so I co founded the company with Danny, I'm the CEO and co founder with my CTO, Alan tap INSTALL. And then we met at that university, and also the Genesis story for why on earth we started credentialing company of all things, it's definitely not what you grew up as a little boy dreaming about. Yeah, it's actually the story of my getting into my university of choice. So I went to university in the UK called Durham University. And so it's not Durham, North Carolina, there's another one. I fell in love with this university. It's apparently it's where Hogwarts was partly filmed there. So it's your Harry Potter, it literally is like that you went to gowns is this beautiful Collegiate School. It's one of the best schools in the world for computer science, which is what I really wanted to do. And so the entry requirements are really, really high, it's pretty hard to get in. I had this issue, which was I was kind of struggling with math at the time, you pretty much needed to get straight A's to get into the school. And to be honest, I was actually trending towards a D in mathematics for my sort of entry level exams. That is what I ended up getting. And so it was a tough sell to get into the school. But I basically got a little lucky, I've managed to figure out who the head of admissions was for the School of Computer Science there and convince this person to just sit down with me and hear my pitch and the pitch took me an hour. But basically, it was, hey, I don't think that DMF is a good predictor of will it be a good computer scientist, here's all the other things, other credentials that I think you should look at. And we got very lucky because this person found a way to let me in any way in the UK, the admissions process is a lot more rigid than in other places in the world. Like I live in the US now, for example, but he found this way to let me in. And despite that DMF saying I would be a pretty bad computer scientist, because that was the lead way they predicted if you should be in a computer science degree, I ended up graduating top of the class. And the weaker moment for me and Alan, who like said, I met in this course was, well, I was lucky I was I managed to find this person, this person took a chance on me thank God for them. And how many millions and millions of people every year are denied by an academic or a career pathway because that the resolution of the data we have on you and what you can do and what you're passionate about, we summarize you down to a letter or another. And that's it. So that was the genesis of a credible and we've pivoted a few times and grew from that sort of kernel of an idea and but that was the start of it.

Alexander Sarlin: 4:54

That's a really powerful story. A very personal story about the power of the sometimes people call it alternative Chris essential things other than a grade or a degree, that can be very much more predictive, much more truth, but much more honest about what somebody's skills are what they are capable of, than the sort of somewhat blackbox academic credentials that we all rely on as the major signal. Obviously, that's something you have been paying attention to for many years. I'm sure it's been incredibly transformative for many of your users, just like it was for you to be able to get digital credentials that change the pathways of their lives or education's Can you tell us a little bit about I'm sure you've had so many stories like this over a decade, tell us a little bit about some of your users who have really gotten a totally different lease on life because of this different type of credentialing system?

Danny King: 5:46

Yeah, I'd be happy to. I mean, there are so many stories, and like you said, with the proliferation of all these different types of credential all the way for me to standard degree or towards all sorts of more flexible types of credentials you can do alongside your life. There are many you could point to, but one that's fresh in my mind is we actually just did a webinar yesterday with one of our customers McGraw Hill. And they'd actually brought one of one of their students along to talk about the impact that credentialing had had on his career. It's really great guy, a guy called Michael dewulf. And he also it was really awesome, because he had his Professor Frank Sarcoptes, join him as well. And kind of talking about it from from both sides of the the table there. And Michael is a junior at Penn State University, and each gone the extra mile. So he is studying a formal undergraduate degree, I believe it was in accounting and finance. But he'd gone the extra mile and realized that he wanted to get an internship if you want really wanted to try and do the best job he could. So he went and started doing these online courses in Excel and other sort of similar sort of products like that. And he got certified for that, put it on his resume, put on his LinkedIn, and that did apparently really move the needle in securing him and internship. So that was cool. Because one of the things that we hear from recruiters a lot of the time and they say this with a little bit tongue in cheek, but basically for something like Excel, which obviously isn't a sort of full degree style course. But it's something that we literally all put on a resume, and we're like, Yeah, super Excel proficient. And the recruiters say, they basically can't tell the difference between three people, three types of people, there's people who are genuinely certified in Excel and are like masters, people who claim to be good, but are not claiming to be certified and people who are not good and are claiming to be good, you just can't tell the difference between those three people. And so this McGraw Hill sort of certification, he was able to do it while studying. So it was very flexible. It was bite size, but didn't really move the needle. So stories like that are really powerful. There are other stories, I can talk about single parents who are able to really up level and do things like online master's degrees or alternative career credentialing alongside working, things like that to get pretty excited for but even just the traditional sort of, hey, I'm doing a degree, things like that can still be heavily influenced and modified by taking these sort of extra supplemental credentials. Yeah,

Alexander Sarlin: 7:42

is there such it's such a powerful ecosystem, when you can break down and provide a menu of different types of credentials that are meaningful that come from different providers, it occurs to me that I've been paying attention to this face for a long time, I think it's fascinating, and I'm sure some of our listeners have as well, others may not be as much. And I you are probably best position to explain the entire I use the word to alternative credentials glibly there. But really, there's a very complex and very interesting ecosystem of credentials and what they do and how they work. Maybe we could just take the 10,000 foot view before we even dive deeper and talk a little bit about just just explain to the listeners who may not be familiar with this whole sort of credential movement. What it is why, why the degree or the or grades or certificates that you traditional certificates, what how that sort of proliferation of credentials has happened over the last decade and what it's meant. Yeah,

Danny King: 8:43

happy to gosh, where do I begin? Because like you said, it's very fractionalized, and I don't think there's any one definition of any of the things I'm about to talk about alternative credentials or pathways or micro credential, stack credentials. Nano, you hear all these different phrases. So what do they all mean? But to zoom out to the highest possible view? Basically, over a decade ago, I think there was this movement, a very exciting movement, which was, can we figure out how we can unbundle learning? Can we make it so that in some cases, can we make it easier, more flexible, maybe more cheap, more accessible? Can we lower the barrier to or the friction to people being able to further their education or their careers? That for me, I think is at the kernel of the idea of, I hesitate to call them necessarily alternative credential pathways, because some of them are alternatives. Some of them are more mainstream. Absolutely. But yeah, so you know what, what I do. Right, is, is digital credentialing, which is only one part of this right? This is just the the viewing format of the actual learning. So a credible is kind of interesting, because we get to zoom out and we've got over 2200, you know, active paying customers now. So we see a very, very broad swath of what we're talking about here. So I think we do get to see some of the patterns. And I think some of the patterns we're seeing is or first of all, higher education and how that's evolving and morphing and growing and changing, and that's a fascinating story. And then you've got the proliferation of All these different types of credentials that are either being supplemented to that, or as alternatives. And so there is no one definition of a badge or a certificate or credential, or there are multiple competing ones. But what I've taken away from it is adding credibility to different types of learning, where the learning itself is always valid. But there may have been a bit of a fear, perhaps on the recruitment side, or even on the learning side for Yeah, I'll get the skill. But will I be able to represent myself with credibility? I think that is the major theme that we're seeing of what might be changing over the decade. Yeah,

Alexander Sarlin: 10:31

that's a really terrific synopsis of a very complex space. And you mentioned a couple of things in your last answer that I think we can drill back down on here, which is the use of Excel, the Excel credential is an interesting use case, right? Because Excel is a, you know, an industry wide technical tool created by a massive tech company, it's Microsoft product, of course. And it's basically a requirement in a huge number of different jobs. And but you can't major in excel at a university, right? It's not a thing. And you can put Excel, as you mentioned, on your resume or your LinkedIn, regardless of how much you've used it, or how little or how amazing you are. So this idea of credentials that give a clear signal for a technical skill. Let's talk about exactly that use case. And then I'm gonna talk about the recruiting use case. But what have you seen of your 2200 customers? Do you see others who are trying to credential technical skills in that way? Because it's very hard to know, outside of this type of credential, how good somebody is at any of the leading tools?

Danny King: 11:35

Yeah, we see that a lot. I would say it's actually the fastest growing area of credentialing right now. So I'll give a few examples. And what's interesting is, some of these are, let me say in these sort of smaller, more bite sized things like, hey, I want to show that I'm proficient in Excel. And there's different levels. The way that McGraw Hill do this is actually really interesting. They take an analogy, I think it's from karate of white belt all the way through up to Black Belt. And so you know, it's this linear progression of mastery as well that they try and articulate. So there are areas like that, where it's more about supplementing, it's more about, like you said, No one graduates in Excel, but it is his core skill. There are also other less technical skills, actually, especially around things like soft skills where these credentials may be in one topic or another. But then also, there's this meta data that underpins the credential, which is, well, how helpful were you on the course forums? And were you giving up voted for often helping people with the correct answers, things like that. It's so fascinating to be able to share. But But back to the sort of more technical side, yes, there are all these sort of alternative credentialing pathways. But one, a couple that I highlight first, actually is let's say you're actually interested in being a marketer. And actually, most of the time, it is probably worth going and doing something like a marketing degree in that particular area. The marketing is an interesting example. Because and it's representative many sort of careers, you don't become a marketer anymore, maybe 50 years ago, you would be a marketer. But now you're a I don't know, digital automation marketing specialist, right, or a growth hacker or like, they're like probably 50, or 60 types of some type of marketer. So okay, you go, you get your degree, and you have this really, really, really strong foundation, hopefully, in all the sort of areas that you might need to know like, all the way from sort of thinking through to probably macroeconomics and a few other areas, but then how to actually do my job. And so what we're seeing is one company that that comes to mind is Marketo, a customer of ours, mission, they are a tech company, but they created a really well received super high quality credential is not necessarily mean another sort of Marketo certified engineer opposite or sorry, marketer. But instead of having the foundational sort of concepts around marketing automation, I think that's really smart for marketers point of view. But that credential plus the combination of this more broad foundation, you get hired very quickly. And we've seen that all over the place. Another example that comes to mind is slack. And you might think flex customer realize, you might think, well, what would you get certified in Slack? Do you need a credential to know how to use Slack. And actually, that's not what they're doing, what they're doing. If you're a 1000 company, people company plus, it's usually someone's full time job to be a Slack integrations engineer, and you need to integrate slack with everything. So it's about people finding these niches and these specialties and then being able to not just pay claim that you're really proficient with their API, or you've done a bunch of these integrations, you can actually get certified in that. So we're seeing this really interesting union, I think of it's not just tech companies, but organizations who have owned a technology or sort of a really predominant in a sort of industry, starting to make best practices around the industry certifying that and then marrying that with either a degree or sometimes you don't need a degree. That's been really, really interesting and exciting to watch.

Alexander Sarlin: 14:24

The nuance in which you're taking apart the different use cases, I think is really powerful. Here, you mentioned that there's technical skill credentials, there's soft skill credentials, durable skills, there's a number of different names for this kind of thing like communication or collaboration or support, critical thinking. And then there are these technical areas that may not be tied to a specific tool. You mentioned Marketo has their marketing automation certificates that you could use that whether or not you're using Marketo. You don't have to be using that exact tool, but it's still a skill. So and still a skill set that is hard to parse and understand from people coming out of school with a marketing degree, they may or may not know how to do marketing, automation. But the Marketo certification says that they do. So there's and these are all slightly but meaningfully different use cases using an exact technology like Excel, and knowing a technical skill set like marketing automation, or having the underlying soft skills to be able to use them in different contexts, like collaboration or working with working with a team to help integrate a new technology change management, for example. So, so interesting. And it's so widespread, again, you have an incredible perspective, as you mentioned, 2200 customers, I'm sure you see all different varieties of these. Tell us a little bit more about either of these use cases or even others that you're seeing across your your wide wide use of customers. Yeah, like

Danny King: 15:52

you said to me, we have all sorts of types of issuers. So our customers tend to fall into three or four main buckets, you've got the universities, and they're doing everything for undergraduate, postgraduate PhDs, but also sometimes to get online free courses or supplemental sort of business school add ons, you can do so either within higher education, it's actually incredibly fractionalized. And within that group, I've talked to a number of provost and other folks that are senior in universities, where they're, they're really leaning into this sort of non degree side as well, both for the people who are studying their degrees and outside of that. And so that is an interesting, I think, evolution that we're seeing, that we also work with. And so we work with tons and tons of universities all over the world, from the UK, to the US to Mexico and many, many other places. And so seeing that the fractal nature in that has been interesting as well, Kaplan University, one of our customers has a very different sort of type of demographic and offering and therefore model then say when MIT, also a customer of ours, or UC Berkeley, which is also very different from the University of Monterrey in Mexico. And so seeing again, how they're all adapting to this sort of proliferation of different sort of demands from the consumers. that's been, that's been cool. But then we also see we do a lot of work with professional associations. So if you're a doctor, or a lawyer, and accountant or customers as a CFP Board, so if you're a Certified Financial Planner, you will get a credential through them. But we also have things like the under US road laying Association, right. And there's literally an association for everything. And so we are seeing in every single sector, blue collar, white collar US International, late stage career, early stage career, there's so many ways you can slice and dice this, what we are seeing is a fragmentation of, oh, it's not it's not a one size fits all credential anymore, or a linear career pathway. And that's both good and bad, right? The good of that is, wow, it's way more accessible, way more flexible, easier to get started easier to figure out, not just oh, gosh, I know, I want to be a marketer. But here's the data to help you figure out what type of marketer you want to be that in itself is. But the other side of things is, well, where do I get started? There's so many options. Now, where do I begin? And so that's part of the segue into one of the things I think is really, really important in this proliferation of these credentialing organizations like incredible I think can really help with this is taking the data of which credentials went led to which outcomes, and then being able to show that to people and say, Hey, Alex, I know you've got these credentials in the bank already. And I know that you've got these career ambitions. Great. Well, here are the seven or eight pathways that we've seen people take and actually have a successful outcome over the last few years in your geographic area. And so if you take these four or five credentials, they may be from different organizations, statistically, you should expect this outcome, giving people the data to make an informed decision about what their options are, and then which might be right for them based on their life circumstances or their ambitions. That is something that I think we need to lead into, because otherwise it will get overwhelming that the amount of choice that we

Alexander Sarlin: 18:32

have, yeah, you bring up two really interesting conditions and recognitions of reality in this space that I think are really important to think about. One is, as he said, that proliferation you have, there are so many credentials, there's a project called a credential engine, right? That found that there was over a million different possible credentials that you could get in the world, I believe was the number they came up with, including all the ones you said think universities, personal associations, technical tools, so many options in that kind of space, the kind of initiative you're talking about, which are the actual valuable ones, which have the best return on investment for your time and money. Incredibly important. The other you've also mentioned is the hiring situation is the idea that in this fast moving world, fast changing technology landscape, how can and soft skills are and recognition of the need for soft skills? How can recruiters and hiring managers understand how to differentiate candidates? When when How do they know which certificates are worth while and relevant to their use case? How do they know which ones are blank or umbrella certificates that may or may not actually be so the skills upon their users that hiring use case and that which ones to take use case are both really big issues in the field. Tell us about those issues, as well as any other challenges that you've seen in the sort of understanding of this new digital badge certificate world

Danny King: 20:00

Yeah, well, let's start with from the sort of recipient of the credential their point of view the intellect, because often what will cause very close to my heart, I'm sure it's close to all of the listeners hearts, what are they going through right now? Because Because like I said, it's both very good. And it's also a little bit confusing and complex and learning how to lean into the good of change and lean away from the bad of change. That's how you have successful change. So from their point of view, I mean, well, let's look at the college degree, first of all, because one question I'm often asked is, what's my take on? Is the college degree worth it anymore? I've got a seven year old what what am I advising him to do when he grows up like that? So we can start that. And my take on this, I think it's necessarily really important that is that is nuanced, which is, I'm not one of those people that actually thinks that the degree is worthless, and it's going the way of the dodo, I doubt that very much. Because there are so many careers or even non career life choices that I think a degree is the best foundation to get equally, from, from what I've read something like 40% of college students drop out every year. And something like only 41% of college students graduate on time within four years. And almost all of those are getting very expensive student loans, whether they graduate or not. So there's clearly and that's ignoring the fact that the cost of higher education is growing way, way, way faster than salaries are. So there's clearly economic problems there. But I see that probably more is there's a bit of a matching problem going on where people probably don't know, what was the right choice for them. And it may have been should have gone to college now or later, or it may have been Did I do the right degree? Or it may have been did I specialize in the right subsection of my degree? Or it may have been should I have done this over seven years and worked alongside it, there are all these different options. And unfortunately, I think most advice is basically go to college, figure it out college, or avoid college entirely that those are the two spectrums that advice I think people get. And I think that it's more nuanced. And actually, I'm really grateful and happy to see that it's getting more nuanced. Because, yes, that's a false dichotomy, right? It doesn't have to be those those two outcomes. So for me, it's okay, given your ambitions, which may change and your goals which may change probably even on the short term, they may change, how can you set up yourself with the best foundation assuming that you're at the beginning of your career? And then from there, how can you keep your options as wide as possible, while not having to spend time or money on areas that may or may not help you with your goals? So like, minimize cutting off choices maximize highly efficient learning. And I'm not just talking about educational app, sorry, I mean, financial outcomes, that's one lens to look at in satisfaction or might be flexibility you're looking for in your job, there are different angles you can look through. So that's one area where I think that there's great potential for really dramatically better outcomes, and data, like giving people the data to make informed decisions on their own, which is something that frankly, you know, millennials and under have grown up with, you can't go to a restaurant without knowing that 4000 People that have eaten that in the last two years, or whatever their opinion was, or you don't enter the dating pool anymore without like pretty much perfect knowledge of who's in the market right now for going on a date with me or getting a job. You have companies like Glassdoor we Millennials are very used to getting perfect data, but they don't have that when it comes to essentially education choices. So let's give them that. That's something that we point out. And then I think on the other side of things, which is okay, well, what about as I go throughout my career, how do I because your degree that you graduate with maybe what you end up doing, it probably won't be what you end up doing after four or five jobs, who knows. And you should keep your options open, especially as with things like AI that change things, or AI is just the most recent thing that could disrupt sort of career progression and pathways. But but by no means the first How can you say adaptive and know how to grow in new areas, whether it's doubling down in one area of specialty, and getting deep? Or if it's switching to another area? Or going broad? How can I Where should I be spending my time learning to get the sort of right goal for me, people are shooting from the hip, they're guessing. And I think the best thing we could do as an industry as an organization is stop people shooting from the hip, just give them the data and then trust them to make the best decisions.

Alexander Sarlin: 23:54

100%, I, you answered a very clumsy question with a very comprehensive answer. Let's go to the other side of the equation. So that's on the recipient side. What about from the hiring side of the equation? How can your hiring institutions understand their credential landscape?

Danny King: 24:09

Yeah, so there's a few sort of competing issues when it comes to okay, how can we slice and dice this you've got whilst traditional standard sort of degree education pathways versus non and then you've got the supplemental not replacing the degree but like, what are all these credentials I've never seen and what the hell is a digital badge. So that's another area of confusion and then you've got inertia. Inertia plus. Hiring managers don't want to take risks, even if something is fundamentally better as new. If they hire somebody, let's say with let's take an extreme example. Maybe traditionally, they would have required a degree for certain fields, and then they decided to hire somebody based on an alternative credentialing pathway. Even if in that one case, that person would be better than all the other candidates. They're taking a risk by hiring that person because that person doesn't work out is the hiring manager who the neck is on the line probably. So there's going to be an n hairy conservatism. And we need to break that. And I think the way that you break that is first of all, just slowly the zeitgeist is changing. And I think that there is more understanding. And there are many examples of people who have been hired that maybe have not an alternative career pathway in the education pathway. And they can point to that. But the second one is, on the credential itself, can you just remove a lot of the guesswork? Can you show? What was the syllabus? How can we verify that this student really understood that syllabus? Was all the extra curricular perhaps a lot of the soft skills that came into this? Can you give them more data to say, This is why you should trust this person? Are there other sort of styles of endorsement, like college credit recognition, even though it's an alternative credential, great organizations, like a study at the American College of Education, they can actually come in and help to say, No, you shouldn't trust this, this non degree courses is actually really valuable. But also just being able to show on the credential itself, what it means to earn this credential, that to me gets a very, very long way towards giving those people the confidence, then you've got the whole oh my gosh, like, how do I find people? Okay, like, I just want to hire backend engineers, right? So I need someone who's like Docker certified. And if you're coding Python, like, Whatever, whatever your requirements are just like, let me filter on my resumes and do what I think that what what a better model might be, instead of people trying to filter down on keywords, and it just feels a bit like a really inefficient funnel. And honestly, I don't think sets I decided for success. Instead, perhaps employers could start outlining, hey, we're looking for candidates that meet this kind of profile, have these kinds of skills, maybe this kind of experience, and then instead have a sort of matching of oh, okay, well, we know, like 3 million people that have some of those criteria, and there's 50, that have all of those criteria, would you like to talk to them. And I think more of a matching instead of a filtering down might be a better approach for both sides of the equation, and frankly, would be a lot less tedious on both sides as well.

Alexander Sarlin: 26:48

It's a great point. And the filtering aspect of this, I think is actually under undervalued as a obstacle to change, frankly, because when you talk about these hiring managers, what they what they have to do is use automated systems to make sense of all of the incoming resumes that are coming their way as well as even in outbound searches, they're using that kind of keyword search. And traditionally, that kind of keyword search really favors traditional credentials, because they're understood. And if you have a university degree or a computer science major from a certain tier of school, that definitely alerts these systems. Whereas if you have maybe a much more difficult, maybe a much more signal filled alternative credential from something else, whether it's a coding bootcamp, whether it's from a university, whether it's from a training program from a technical provider, it may or may not understand how to how to identify that candidate as somebody who might be worthwhile. I'd love to hear you talk about that aspect. Because the matching the matching world that you're talking about seems incredibly exciting vision of how hiring should happen. But given where we're at, how can we make incremental change towards it?

Danny King: 28:00

Yeah, and the key is incremental change, you really hit on headache, because good luck trying to have a revolution in credentialing. Believe me, I tried. You can't come into something that's as entrenched. Let me just let me just point out, we still call it a sheepskin for the non US listeners, you know, a degree often is called a sheepskin, because it used to be made out of sheepskin, rooted in the past and a lot of this. And that's for good reason. By the way, it's because there's there's inherently meant to be a conservatism. Because I'm speaking as an innovator, someone who loves making new things. Conservatism when it's, Hey, I need a doctor or a lawyer, or that's important. That's good, the level of rigor and level of oversight that is important. And so the question is, well, how can we then incrementally change whether it's hiring practices, or the filtering versus matching or how we deliver education? incremental change actually is, with education, you're literally experimenting with people's lives and careers, you do have to take a more scientific iterative approach, I think that really is crucial. So how can you do more iteratively? So let's say first of all, I think it's about giving data to all sides at universities, that the students are the recipients of the credentials, the hiring managers, give them all the data so that they're not guessing as often. That's the biggest thing we could do, like as quickly as possible, where people can make more informed decisions. And you said before, yeah, okay, well, what about this alternative credential, it might not literally might even match against your application tracking systems criteria or something like that, right? Yes, actually, that's probably a relatively good heuristic, on average, like 80% of the time, you're probably getting good people. But but it's the 20% of the time where you're missing people who might have been an order of magnitude better, right? You just don't know. And so I think there's a lot of potential in giving people more data because then it will feel like it's an arbitrage, right? It will feel like Oh, I found this amazing, not diamond in the rough, but just someone who would have been overlooked. So I'm excited about bringing data to alter the equation. I think the other side of things I'd be excited about is like you said, Yeah, I mean, this this filtering thing. Let's see what I mean by that. So as an employer, I think the Aboriginal For resumes that you look at for a job is something like 80 to 100. Does that sound right? Yeah,

Alexander Sarlin: 30:05

at least I think it might be even more. Yeah.

Danny King: 30:08

And then so if you're less than 100, it's just that easy math, if you're lucky, and you hire one person, you are definitionally 99%, inefficient. Now, from the, from the sort of Linda's point of view, or the or the applicants point of view, they're probably doing on average five to 20 into a different organizations, and again, is lucky to get a job at the end, on both sides, there's like high anxiety, they're both guessing they don't know if it's going to be a good fit. And you basically don't know until like, six months after the job, that sounds crazy to meet, especially because it's probably one of the biggest industries in the world, because every organization hires people. Right. So that's, like, how insanely inefficient is that we're in the information age. And we're still using these awful filters, where it's this funnel, and there must be a better way. And I think the better way is taking a much more data oriented and nuanced view of what a career is, and what it means instead of let's say, writing a scorecard, which you then use to create a job description, and you put that out there, and you hope that by essentially, people throwing spaghetti at the wall, some people will stick instead, if we could start to have this model of, okay, well, Alex has these credentials, and these non credential things, too. And therefore we're building this model of elixir is what he loves what he can do and where he would be a right fit. And it's not just would you be good at this job. Would you be good at this job at this time in your life in this area? Where is the demand? This financial sides of that as motivational sides of that there's flexibility to see maybe a new parent, right, whatever, right? There's all these and I think that having a better model and then saying, right, okay, Alex has like a 94% match with you. I'm not sure about that final six, you guys should go and talk, I think I think it would be. And I think AI is an area where we can dramatically simplify a lot of this as long as it's easy to integrate prep, and you can look into the black box and make sure that we feel good about the matching criteria is putting yourself out there in a in a in a broader, statistically appropriate, relevant way. And then let people subscribe to notify you when you meet that criteria, and you do the same for the employer. And then I think you've got a fundamentally different model that should be a lot less inefficient.

Alexander Sarlin: 32:10

I'm very glad you're bringing up AI in this context, because clearly the vision that you're painting a credible made huge strides in the space by digitizing the credential in the first place. And and part of the advantage of that there are many advantages. One is it made, the number of issuers of potential issuers of credentials are exponentially larger, you mentioned your 2200 customers, it also created metadata, and a huge amount of data and metadata around what people know and how they could be findable. And now this data rich world that you're talking about where matching is possible. This is a very complex data rich world. There's all these factors involved, as you're saying that there's motivational factors as financial factors. There's the diversity, equity inclusion factor, there's a lot going on in the hiring space. Let's talk about how AI might make that data vision that you just painted much more possible. How are you thinking about that from your position? That incredible?

Danny King: 33:08

Yeah, got it? Well, okay, so I always struggled to talk a bit about AI. So I've, like I said, a computer science background actually studied AI as part of my undergraduate as well. So I'm coming at this from a very technical side. And when I see people on the news, or just just often out there talking about AI, it's important for us to remember that there is no one definition of AI and AI is an awfully badly defined thing, actually, very, very broad means 100 things literally, it means these LLM chatbot style, which by the way, is an exciting and interesting and fascinating area to talk about. But that's only one tiny little subset of AI, although it's currently the most visible and I think exciting. But there are so many others, right, including things like much better matching algorithms, and so on and so forth. So we have to be careful with what what we mean when we say AI. So I think what I'm going to talk about is the broader picture of what are the implications for as computers get better at either advising, which I think is one big area, detecting patterns, and therefore helping people to match, which of course leads into the advice. And then identifying opportunities where we might have missed it. Because we're looking at very, very, very broad datasets, hundreds of millions of people literally at the credible devaluation with 100, millions credential, right, so the majority of that was actually in the last year. So like, that's a lot of data. So it's, I think it's then about taking very large datasets and summarizing it down and helping you not miss things that you might have done just as a human statistician, right, as an augment or something like that. So those are the three areas I think, right? So for me, it's if those three areas could coalesce and turn into statistically based, really, really broad analysis on all the options out there for the recipient, the learner and also the creators of the education, and then condense that and stop that solidified down into advice, which is actionable for all sites. That for me, feels a little bit like the Holy Grail, but very achievable. Right, so so that is where I think I get excited. Exactly.

Alexander Sarlin: 34:57

It's achievable with AI. I mean, you talked about 100 and million credentials, we talked about there being a million different credentials out there. And then the entire population of hiring entities, and issuers and recipients, I mean, this is a very big data set. But big data into action is exactly what AI does, right and find patterns, find recommendations. Algorithmic matching is the is exactly how the dating apps work, like you'd mentioned before, or how Uber and Lyft work or there's, there's a, there's a big precedent in being able to use very large datasets to match two sides of a platform. And I feel like you are very well positioned and incredible to be that platform that sort of puts together the two sides of that equation, you have a mission to create what what would you call the first verifiable repository of human capital? Can you unpack that term? For us? It's a really interesting way of looking at things.

Danny King: 35:52

Well, sure, happy to human capital, I think is the couple of words that I'm most excited about in that sentence. And notice, I'm not saying credentialing, right, I'm not saying education, or, you know, what I'm saying is human capital. And that's a very, very broad thing. And one person might provide a lot more sort of capital in one area in one company or in one market than in another. So we shouldn't look at this as is one size fits all, you are either a good X or not, it's more hey, can we can we find an area where you will provide the most value, whether that's a place in time or after having studied X or working in a particular place, or in certain projects, zooming into within organizations? Who should we match together, and so human capital is broader than simply education. And I think that over time, they, they can become one. So that's something I'm excited about. But yeah, becoming the sort of verifiable repository for human capital, verifiable is important, we should be able to trust claims on all sides of the table, it should be impossible for you to lie about having expertise, or exaggerate. Equally, it should be impossible for the employer to misrepresent what they are going to offer or what they can provide in terms of financial compensation. But more importantly, I think about what your life will look like and where you get to spend your precious life making an impact. And so I think, verifiable on both sides of the table, I think that's really, really important to us. And then the repository side. So being verifiable repository for the world's human capital, a credible fields, if we can get as much of that data into a standardized format as possible, some of it will be sitting with us, some of you will be sitting with our customers, some of it will be sitting with other organizations. But if we can standardize that data, and make it so that we can, like you said, query all the world's credentialing data in one place, what what could we learn from that? What patterns and statistics and pathways? And what can we help people to to learn from that? So for us, it's consolidating all this data, which right now is sitting in a million different university registrar's offices or employers databases, or all these different places, the credentialing data is really fragmented and non centralized. If we could change that, then I think we could literally change the world. And I think we could start to even potentially guarantee certain educational career pathways by helping people understand, hey, we've got so much data, there are so many statistics that we can point out to say, if you go and do this, this and this, and this, you should expect to this outcome with this level of certainty. Don't go forth and figure it out based on the data that can be so it's a centralizing of it, it's being able to trust it. And then it's remembering that the credential actually isn't the point. It's the human capital behind it that we should all remember to focus on. Yeah.

Alexander Sarlin: 38:19

I love this vision. And it strikes me hearing you talk about this, that there are a few places in the education, employment landscape that are close to that guaranteed model that you mentioned. So we've talked about top tier university degrees, if you've finished them, are probably as close as you can get to a credential that will virtually guarantee some kind of employment. Now most people don't work in the thing they majored in. They don't use the skill. There's just a recent report from Lumina Foundation about people not using the skills that they learned in university at their jobs. But the there is a guaranteed pathway there. If you go to Harvard or Oxford, you're going you're pretty much guaranteed to get a an information, a job where you have choices. The other that has risen in the last few years, I believe is technical skills like Cisco, AWS, you know, 30 certifications, this had been a very coherent cloud cloud computing, and there's been a very consistent ecosystem of his very specific, relatively modern tech skills where because there isn't traditional credentialing, a whole ecosystem has grown around that. And I think what you've been doing it a credible is moving that sort of logic into many different areas. You mentioned the road layers Association, that's an area that you maybe didn't have that kind of guaranteed pathway that very clear if I get this degree or if I get this certificate, if I get this training, I will have a job in I know I can get a job in this field making this much money and it'll be satisfying in these exact ways. I'd love to hear you just talk about that. That thought like, is this anywhere near the way you think about it? Or are you how do you think about that whole guaranteed pathway to helping people at an early age To pick educational options that really will drive them directly towards the goal they want. Yeah,

Danny King: 40:05

I would even guaranteed Of course, it's such a watertight word. Of course, I would even settle for, like most of the time, I could expect even just an order of magnitude better than I think a lot of people might have when

Alexander Sarlin: 40:17

you're present. Right?

Danny King: 40:18

Unless you're saying, Yeah, look, let's let you go to Harvard, you don't need to worry about this. This is almost certainly not a problem. But most people don't. And I'm actually not of the opinion that the reason that the Harvard degree has that sort of weight behind it, and all the other great is because the pedigree. So what they've done is like their reputation has been earned slowly and diligently over the over the centuries by consistent persistent good outcomes, right. So there's a right way to that. And I think that it's not an evil, and I think that we shouldn't ever throw that away. I think that there's there's a place for that. And it's important, it should not be the only way, right. And in theory, it should be, I believe we should have a true meritocracy. When it comes to skills, it should be possible for somebody went to Harvard, who has skills XYZ, let's say being a lawyer, and somebody who didn't go to university at all, but has the same skills, right? They should be equivalently valuable, it would be easier for you to get those skills in Harvard probably doesn't matter if it was easy or not. What matters is did you get the skills? Right? And that I think is it's out? So for me, it's okay, can we if you have the skills, if you have the credibility, can you communicate that, and no false negatives, no false positives, that that's the guarantee I think we should focus on. And then I think the rest will, over time evolve with with the market. And then the other side of this that I think is worth pointing out as well as proliferation of alternative or supplementary credentials. A lot of them are coming out of these tech companies. It's not always tech companies as well, there there are others. And they also kind of need to figure out how to get their their foothold and their brand out there and people knowing about oh, did you know this, this option that you could go and study? So one example actually comes to mind is this is really great pair of YouTubers, their brothers called John and Hank Green. Have you heard of them? Alex? Of course,

Alexander Sarlin: 41:52

yes, Ed Tech, you can't you can't avoid them the Crash Course. They're amazing.

Danny King: 41:56

They're amazing. Yeah, they may crash course these YouTube courses and so on. But then they also I think of about a year ago, they announced this thing called study hall, which understood correctly is YouTube courses with college credit, right? But they need to go and get that message out there that people know that hey, actually, there is a viable alternative to maybe the entry level courses that help get you into college, or there's this alternative. So I think also one of the benefits that Tildy my digital credentialing can provide over something like say a paper credential is what we like to think of it as a flywheel. If you can get people who have taken that course to get a digital credential, then they share it on a place like LinkedIn or on their resume. Or it might be even on places like Instagram or wherever. And they're sharing it in a moment of pride. Right? So it is advertising, yes. But it's genuinely heartfelt. I am proud of this credential. And who are they advertising it to? Right, they're advertising into probably John's like target demographic, right, which is the Friends of people who did this goal. So and I think the same is true for Google credentialing, or Amazon Web Services credentialing, or whatever it is, I like the idea of, can we help take these courses that really can move the needle in people's lives and careers, and then use the digital credential itself was a medium to actually further the messaging of that, hey, I took this course you should take that too. And then from there, you can click and sign up from the course yourself, getting the flywheel going, I think it's important that they have all the help they can get to push that message of, hey, you've got this other option, you should look at it. I

Alexander Sarlin: 43:18

couldn't agree more. I can't tell you how many times so I was at Coursera for years. And I can't tell you how many edtech entrepreneurs I have given some version of that story to that said, think about the Coursera certificate, somebody gets a certificate, they're at their moment of top pride. They just finished something difficult and meaningful. And they posted on LinkedIn. And they tell literally everybody, they know that they just did something meaningful and exciting. at Coursera. It is the best. Yeah, you could call it free advertising. You could also call it just pride in credential ownership ownership. So yeah, I couldn't agree more. And I love to hear that phrase, the credential flywheel that the recipients of these credentials become ambassadors of the of the value of them to others. And I think that's true. And that's it's true in almost all cases, right? When you see a Harvard Law School Alumni interview, go out there and talk about their experience. Harvard doesn't need the advertising but you see coding boot camp graduates, you see people who've Salesforce admins going talking about the Salesforce pathway, this is such a powerful and I think I love that you you've given it a name because I think it's a dynamic that is so powerful and really under appreciated in this credential space. I couldn't

Danny King: 44:28

agree more. And then when you scroll down on the link, they'll they'll post on LinkedIn and you'll you'll see there's like something like 15 comments on average, right? And it's like, Hey, this is amazing. Good work. So it's not just this moment, right? It's also this reinforcing community coming together to say that was a good thing you did and awesome get go you and and then there's other people who are like, maybe I should think that's a me too. So yeah, it really is this very human moment, which traditionally was maybe just giving someone that that piece of paper which maybe then you put on your wall. Now you can have the digital version of that which is whether it's your link In profile or some other more appropriate for view, I love this human moment. Oh, I did it, it's such a nice moment.

Alexander Sarlin: 45:06

It's that graduation moment where everybody throws their their caps in the air or somebody's hand, the principal hands, the high school diploma to the student, I mean, that that moment of celebration of achievement is so powerful. It's so viral. I think it's one of the it's just one of the most exciting moments in education. Let's put it that way. And I love that it is can be shareable in this digital age, and you can share it over and over again, you can do it's not, you don't graduate just once from digital credentials, you have series there. Actually, that reminds me one more quick question, before we get to our final questions, which is tell our listeners a little bit about the concept of stackability. You mentioned that college, even if you don't finish college, you still end up with a lot of debt. But the type of digital credentials that incredible offers often avoid that. give our listeners a little bit of understanding of that world. Yeah, happy

Danny King: 45:54

to. And the first thing I'll say is I don't want this to come across as Accredible offering these courses, because because it's not it's not customers that do it's the universities or the associations or these online courses. And we simply help to say, hey, this person did it. And this is why you should trust it. But again, in terms of being able to stack that let's try and break that down. Again, there's no definition of snatch credential, there are multiple competing different definitions. I don't think it matters. I think what the philosophy behind it is, is, can you bundle together credentials, you might there might be linear progressions, like the McGraw Hill example, where we talked about white belt all the way through to Black Belt and right stacking those is, yeah, I am now an absolute God at creating Excel spreadsheets, you can believe that. Or it might be more of a broader bundling of, yes, I've got this broad underpinning foundational degree. But then I took this marketing automation, that credential, and then it took this actually macroeconomic online course, and those things together, allow me to do this special thing. So I think it's the synergy, right, of combining things that are worth more together than it would have been, even if it's a multiple learning institutions, right, potentially even simultaneously. So that's interesting, right? Because then I can pick and choose from these different places that perfectly match what I'm trying to do with my life right now. So that, for me is kind of interesting. Another way to look at it, which is the way we look at it internally at Accredible is we think of it more as pathways. So again, pathways can mean many things. But can you give people a really clear understanding of what are the multiple pathways that are ahead of them that often branching and which organizations or courses might be able to contribute to those pathways that might be a career pathway or an education pathway? Or it might simply be life goals? Usually, it's a career pathway. And it may be that okay, well, I'm in a university. So I literally got all the choices, which are like, Well, where do I major and should I get bored might be, okay, well, I'm actually at the university or avoiding University, well, okay, here are all the different things that you could bundle to make your own customized pathway. So I think for me, it's less about the interconnectivity of particular credentials, and more about creating a portfolio a bundle, which evolves over your life and has multiple avenues at any time that you can move, take it a step in different directions, depending on what kind of pathway you want to walk down right now. Yeah,

Alexander Sarlin: 47:57

the pathways metaphor makes a lot of sense. And one vantage of whether you call it pathways or stackable is that it's it removes that it unbundled, it's not the all or nothing, it's not you go to Durham University, and you either come out with an incredibly valuable degree or you drop out and you get nothing, right. Every moment you spend learning or every class you finish every milestone that you meet in this credential world, you can verify and walk away with if you have to, or take a break and, and stop there and then come back later in life. I think that's another valuable aspect of it. But I couldn't agree more. So we could talk for hours about this. I feel like we this. There's so much we haven't even touched on yet. But we are running out of time. And I'd love to ask you our final questions. First off, what is the most exciting trend that you see around the corner? What's coming in the EdTech landscape that you feel like you want to highlight from your role as the CEO of credible?

Danny King: 48:52

Well, I think there's two points that you know, from from the greeter industry's point of view, I've said it multiple times during the interview, it's the use of data to help people make informed decisions, that is going to be completely life changing. For a lot of people, they're going to be able to get the same outcomes with far less time, money and effort, or they'll be able to get better outcomes. And I think we're on the cusp of that. And that's literally within a year, I think that people will be making better decisions. So that's incredibly exciting. And then for my company personally, for Accredible, I think it's finally I think it's a year of the of the digital credential. So it used to be 1112 years ago that if you offered a digital credential to an employer, they were like, What on earth is this thing? Now we're actually seeing it's expected in certain industries and it's like, oh, you you don't have the digital version. Okay, well, can you complete something the digital ones, I can verify it. So I think the acceptance and the normalization of Hey, where's my digital credential? That's something that for me of course, is personally very exciting. Yeah,

Alexander Sarlin: 49:47

and it's been a few years coming but it is it's it's here I'm really I'm couldn't be more excited about the digital credentials being gone mainstream, as well. And what is a resource that you would recommend to our listeners, this could be a journal, a blog, a book, a Twitter, feed anything are your XP, anything that works for you that you would recommend for somebody who wants to dive deeper into any of the topics we discussed today? Yeah,

Danny King: 50:13

I think probably my favorite is the attack after dark. I mean, unless it's a sub stat from Tony one, probably most people are already very familiar with that. But I just I love it. And I'm a big fan. Just been a soldier reasons as well. And surge. Again, I'm sure everyone's reading it if you're not when I started my company. So it was the thing I would wake up and read every day in the morning. Say that was great nostalgic safety net since the beginning. And I'd be remiss if we didn't plug our own boring blog regularly talks about these kinds of topics and issues. If you're interested to learn more, check out our blog, because we think about future of education, especially around credentialing a lot. And we'd love to have you read us love

Alexander Sarlin: 50:44

it. And Tony and Betsy Corcoran and founder of answers are very direct, very direct inspirations for what we do here at ed tech insiders to it. We know them both we've had we had Betsy on the podcast just a couple of weeks ago. So I love love EdSurge. It's changed to change focus a little bit, but the internet is great. And Edtech after dark is Tony's direct blog about the space incredibly veteran ed tech reporter and I know great, just a great just a great thinker in this space. So I couldn't agree more. We will put links to both of those resources at Tech after dark. That's Tony Wan's blog and the Accredible blog into the show notes for this episode, as always, Danny King, CEO and co founder of Accredible thank you so much for being here and talking to us about the digital credentialing movement.

Danny King: 51:28

Well, gosh, thanks for having me. I had so much fun Alex.

Alexander Sarlin: 51:32

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