Digital Credentials and Machine Learning Aim to Change How You Hire

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Because people are pressed for time and they need to make hires, they use arbitrary ways of cutting the field down to a select few that they can put through a more rigorous interview process. By the time they’ve done that, they’ve now already summarily dismissed the people who may actually be best fits for those jobs.

Ginette Methot: I’m Ginette.

Curtis Seare: And I’m Curtis.

Ginette: And you are listening to Data Crunch, a podcast about how applied data science, machine learning and artificial intelligence are changing the world. This show is produced by the Data Crunch Corporation, which uses machine learning, data visualization, and automation to transform your data into a profit center.

Curtis: If you’re not getting the value from your data that you want or you’re not really sure how to start, head over to our website, that datacrunchcorp.com and let us know what you’re working on and what your goals are. We’ll read through your notes and if nothing else, we’ll provide some perspective and some creative strategies for your specific case that will help you find success and profit, and if your use cases. Interesting enough, we might just featured on the show.

Ginette: Today we’re going to see how a clever idea and the skillful use of data is starting to disrupt how people get credentials. The use case here has the potential to remove gender and racial bias in the hiring process, help companies understand specific talent gaps in their workforce, and help learners find lucrative educational pathways they can take.

Curtis: This is Jonathan Finkelstein, the CEO of Credly, a company disrupting the education space.

Jonathan: Most people pick up skills in settings that may not have always been a formal classroom or learning environment. If you look at somebody’s college transcript, if they’re lucky enough to have gone to college or completed it, it says remarkably little about people’s abilities and their knowledge. In fact, just looking at that artifact, you’ve got usually a few letters abbreviated for some course title that most people aren’t likely to even remember and many people never actually get to complete college, and so how do we actually do a better job helping people move from one setting to the next with evidence of what they actually know and what they can actually do. And so we really at Credly set out to say, what does a world look like in which people get to own the evidence of their own achievements and not have to reprove themselves every time they walk into a new setting or a new environment.

Curtis: Before Credly had you started other companies?

Jonathan: In some ways it feels like one continuous venture, but no, this is, ah, this is my third company. They’ve all kind of built on each other in in some way. But my first company after college was a company that essentially created the first real time online meeting platforms. Uh, I know we take for granted Facetime and Skype and all of our various messenger applications, but believe it or not for some of your listeners, there was a time before that. My first company built the first collaborative or synchronous classrooms on the web for learning and meeting, and we mostly focused on workforce development. And then after that I worked on helping take that product expertise around helping people connect to experts and develop expertise from people on the other of the planet. And we worked with large organizations that were trying to figure out how to move their learning and their mission online and create communities and communities of practice for helping people advance in their careers, and from there we realized, well there was a lot of great learning happening online, but for all the work that was going into creating engaging learning and assessments and opportunities for people to upskill in their careers, there was remarkably little, almost nothing, being done to update how we actually proved or showed that we have the actual skills we developed. We were still just seeing at best you got a printed certificate for completing a course or a program. Maybe you got employee of the month pin, but what about all the other data that you leave behind and that those are the tracks you leave in the sand, if you will, for all of the other things that you do. We thought there should really be a way of structuring that data, making it portable, and helping people surface individuals who might be a good fit for future opportunities and perhaps even reach people they might not have thought to connect with before.

Curtis: It’s an interesting problem to try and solve from I think a business and a data perspective. So if we could, let’s dive in a little bit to the data perspective here, ’cause this is an interesting data problem, right? How do you even begin to think about how do you aggregate a dataset like the one you’re talking about authoritatively and so that it makes sense to people, how do you do that?

Jonathan: Such a good question. Part of it, and maybe the biggest part of it is the cultural change that goes with this idea. We’re just not accustomed either as businesses or organizations or as managers or individuals of having a culture of recognition. We might say, “thank you.” We might send out a, an attaboy or an attagirl email or give someone a pat on the back. But when it comes to actually documenting what somebody has done or embedding the ability to record that into the kinds of systems we use and do everyday, traditionally there’s no consistent or common way to do that, which is remarkable because when you think about it, we’ve come up with standards and data standards for things like courses and how you take digital content around courses and allow it to move from one website or one format to another. We’ve done it with video and we’ve done it with other, um, other, you know, the content that goes behind learning.

We’ve done it with the data we capture about performance and what people, you know, how our businesses are doing. But we haven’t really done it in a consistent interoperable way around the human capital. And so the first part of this is to have identified a structure for how would you actually describe achievements, whether they be certifications or credentials, individual skills or competencies, in a way that is inclusive to capture all the different kinds of outcomes that matter in the world. And so Credly began many years ago, even before we officially formed the company, working with a broader community around interoperability standards to create and identify what the common of structured information should be. This is a movement that took flight using a word called a digital badge or an open badge. In other words, what’s the most, what’s the, the, the lowest common denominator of an achievement that could be surfaced from any environment.

And so we, we built our approach around this new and evolving standard around open badges. Think of it like, what’s the title of this achievement? What’s the standards it might align to what are the different steps somebody had to complete? Who is asserted that somebody actually has this skill? Does it expire and have an expiration date? What’s the kind of type of credential that we’re talking about here? What kind of context can we offer? And so we began to work with organizations who already had a demonstrated need to recognize or desire to recognize people and began to move them into using a structured approach. And what’s nice about that is creates consistency. It also helps people work backwards from what are they actually trying to communicate with the world about what an achievement means. And at the end of the day it actually creates much more rigor and credibility for both the organization who issued a credential and the person who earned it because people know what to expect and they can actually see transparently a lot more about what this recognition is all about so now you’ve got, you know, you’ve got organizations like the project management institute, which is one of the most, one of the largest issuers of credentials in the world.

Moving from issuing a paper certificate to having a very rich dataset that describes what it actually means to be a project manager when you’re on your PMP or if you work at Cisco and you become a CCNA and get your, your networking admin credentials, people who may or may not understand what that actually means, can see everything you had to do and everything, you know, which also makes it machine readable and discoverable in ways that were not possible before.

Curtis: Can we dive into maybe an example of one of these? ‘Cause I’d really like to have something where . . . take the project management one that you are talking about, what kinds of badges so to speak would be generated as a result of one of these courses and take any example you want. But just to get some concrete details around this.

Jonathan: Yeah. And by the way, everything I’m about to describe, your listeners can also, if you visit our site at youracclaim.com and you sign in, there’s a search and you can actually look at a lot of these and get a feel for how different kinds of credentials are described. So if I’m looking right now at the PMP from project management institute, and I am seeing that there is a, a brief description of what this credential is about, and it indicates that earners have this globally recognized PMP have demonstrated their extensive knowledge and their mastery of project management. And it goes on to explain what that means. So the idea here is how do you help anyone, whether they’re inside the trade or outside, comprehend what at a high level what this achievement is. Think of it kind of like the description on your resume for a key experience.

Then what you’ll see is a set of skill tags. What are the skills that were demonstrated on the way to or in, in having earned this certification or credential. And there you’ll see data tags, things like project assessment or your communication management or project planning, quality assurance. These are skills that are applied by the organization that issued the credential, but they’re also pulling from realtime labor market insights. So the author of the credential is able to put attributes on this credential that not only speak directly to its skills, but also speak to the language of the job market. This data that we are pulling in is looking at job descriptions and resumes and identifying what are the most common ways people actually refer to these skills. So we’re trying to help normalize the language that both employers and job seekers use to connect, connect with jobs. And then you’ll also see a list of criteria which might be deep linked to other achievements or to assessments or rubrics or externally available resources around the program that somebody completed. Then you might see in the case of the PMP that they align with the, the PMP standards that PMBOK standards, uh, which is the project management body of knowledge. You’ll see that it links to certain ISO standards. So again, it helps position this credential into the broader ecosystem.

Curtis: So there’s lots of questions here to unpack, but one I wanted to ask before we maybe dive more into the data side is this is a really interesting, really cool idea. How did you come to the, you know, the Aha moment where you said, why is this not being done? Like, the discovering this idea? How did that come about?

Jonathan: It’s a good question. I’m not sure if there was one Aha moment, although I can think of a few that might qualify, but I’m lucky I have a degree from a, uh, uh, a university that affords me privileges I may or may not actually deserve. And people make judgements about me without even knowing me, that they, they make assumptions that most of the time, not always, but most of the time will work in my advantage, to my advantage. And yet it’s bizarre because I have that college degree largely because of who I was in high school. Why should we have such a heavy reliance on proxies like degrees, which have value, don’t get me wrong, but I watched for a long period of time working in the learning and the workforce development and the training space in which, you know, people with the most important in demand necessary skill learn them either through a series of great and important measurable life experiences.

They earn them by going to boot camps or training programs or just beg, being good at what they do at their work and in turn becoming so good that they can be relied on to to do those tasks. And I kind of feel that the world is very unfair to most people, and if we’re going to put labels on people, let’s put labels on people that (a) They get to control and direct in terms of who gets to see and, and they should have ownership and access to them. Be able to direct how and where they tell their story. To me it’s always kind of felt like it should be. It takes a village to help people get ahead in the world and it behooves everybody who interacts with everyone else to like do their part, to tell that person’s story. We know that when we talk about what we do as resume worthy achievements that come from credible places, people, organizations who are willing to go on the record and indicate what what somebody can do.

I think of this and I’ve, I think about portable skill recognition as a, as a benefit of employment today. If you’re going to deposit a direct payment into someone’s bank account for their week or two or month of work, you should be depositing verified skills into their human capital bank account that show what they actually have done and what they contribute. I think that sort of should be a right for every employee and there’s no reason that you should leave a job and then have to tell your, be relied on to tell your your own story and it’s not just about leaving a job. Companies actually see much better results to the bottom line when they switched to a culture of recognition, they can determine who in their team, whether it’s a team of 10 or 15 or a global organization of half a million people find who’s got the talent in a consistent and trusted way.

They create standards that help people be able to showcase what they know. So two people, whether one’s a male or female or one’s white or one’s black, be able to tell, tell their story in a consistent way that removes biases. And we know there are many biases in the workplace. We know that there’s still pay gaps between men and women that are significant, where women are earning 80 cents on the dollar for what men earn for doing the same job. And women of color have an even greater disparity. And so a lot of the reason that’s happening is because we put a lot of unstructured, unverified data into the top of the funnel. We call those job applicants and resumes. And then because people are pressed for time and they need to make hires, they use arbitrary ways of cutting the field down to a select few that they can put through a more rigorous interview process. By the time they’ve done that, they’ve now already summarily dismissed the people who may actually be best fits for those jobs. I really think that by structuring the information, by making this part of our culture, by helping businesses see the real-time benefits of doing it, we can actually change the way we deploy human capital, and that’s, that’s a big deal.

Curtis: I love the way you just described that because essentially you’re changing the way we’re measuring something with this new data set, right? A better data set, a better way to measure someone’s capabilities and therefore leading to better outcomes. Right. Less bias, all these kinds of things. That’s pretty cool. Can we spend a little bit of time on the . . . so you mentioned like once you have this data set and you have the attributes and the tags, all these things at then not only is beneficial to humans, but it’s also a machine readable, right? You can throw machine learning at it. Analytics. It’s more discoverable. Can you talk a little bit about what you’re doing in the machine learning realm to get more value out of this?

Jonathan: So there’s a number of things, both things that are happening today and also signs of really interesting things that are, that are to come. First of all, we’re able to help organizations that issue credentials better understand the patterns of behavior among the people who earn them, better think about where they could provide upskilling opportunities. So once you’ve started to issue credentials, to whether it’s to your, your company or to people who are members of your organization for the certifications they earn, you’ve now got a consistent map with high quality structured data and you can begin to look at things like where are the heat maps? Where do I have geographical heat maps? Like people who are learning data science are more concentrated over here or in this part of the organization. Or people who earn their data science credentials are more likely to go on and earn credentials from AI projects that they do.

Or maybe they’re being deployed and, and taking on learning opportunities related to robotics or project management. So you start to look at rather than creating a top down approach to thinking about career progression and to talent and staffing, you can actually watch more organically and appreciate the the actual pathways people take and begin to learn from that and apply it in making recommendations to people about what might be a good next step. Imagine being able to tell someone at your organization who was who received a credential based on their leadership skills that people who had earned that had gone on to earn $20,000 more by pursuing these two additional skills that compliment their work. We know that industry certifications do have an impact on people’s earning, earnings power and potential. Our colleagues at Strada Education Network and Lumina Foundation, just this last week published a study showcasing the impact that industry credentials, non-degree credentials actually have on people’s incomes, and it’s real.

It’s, it’s not completely distributed fairly among men and women, but there is . . . having the transparency and the appreciation for the role that non degree credentials play is, is really important. So you can begin to use that information and those insights to provide guidance to people about pathways. You can provide information to people using a consistent set of data to improve their decision making, so imagine bringing this data into applicant tracking systems and into the interview processes so that you can, you can surface surface different candidates and draw from different pools than you might traditionally reach from. We also see organizations using the data to think about their own L&D development practices, so they might identify, oh, we have a hole in our curriculum. We need to actually maybe provide more courses that relate to communication skills based on either the need or the gaps that we’re seeing in the in the info.

Curtis: Super interesting. I’m also really interested in the business side of this and how this actually gets implemented. You mentioned that you can earn a badge for leadership, for example. How do you say they did this thing and therefore we know they did this thing and they’d get this leadership badge. How does that shake out?

Jonathan: It can happen in different ways and in different kinds of settings. That’s one of the things I love about it. In our platform, there is a set of tools for defining and issuing a credential. So sometimes that means that this happens by your manager or the person who, who issued or conducted your assessment coming to our platform and and issuing the credential to everyone who just completed the leadership program. And, you know, that’s putting in a list of names or a spreadsheet or pulling on some contact lists. And and off it goes, but many times it’s integrated deeply into the environments in which these skills are being assessed or managed. So for example, we have partnerships with all of the leading assessment providers, places where you go to take your exam from IBM or Cisco or Adobe, and as soon as you are, you sit for, whether it’s online in a proctored online format, or go to a test center and take a test.

And when you’ve successfully passed that test, the credential is automatically issued to you. Or we work with learning management providers where when you have a skill or competency that’s been demonstrated in a, an online course or through a performance review, it can automatically trigger that credential being deposited into your, into your Credly account. So sometimes it happens very organically because we’ve created essentially rules engines and different products and places that people use every day. Or it can be through a set of, some people call it, you know, stacked inputs or stackable credentials. One thing might lead to the next, might lead need lead to the next, but at the end of the day, the experience is very familiar to the earner, which is they’re aware that they achieved something of value. And that thing of value is represented as a, a, a portable, secure piece of data that helps them tell the rest of the world what it is that they can now do.

Ginette: A big thank you to Jonathan Finkelstein and a huge thank you to all of our listeners. It means the world to us that thousands of you tune in every episode and we really love this support from your reviews. Thanks again and we’ll see you next time.

Attributions

Music

“Loopster” Kevin MacLeod (incompetech.com)
Licensed under Creative Commons: By Attribution 3.0 License
http://creativecommons.org/licenses/by/3.0/

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