ATP Insights featuring Mark Keough: Unlocking Workforce Potential with Evidence-based Skills Intelligence

How well do you actually know your workforce? In this episode of the Asia Tech Podcast, host Michael Waitze sits down with Mark Keough, Co-founder and Executive Director of SkillsAware, to discuss how evidence-based skills intelligence is changing the game for modern organisations.

In a fast-paced, project-driven world, traditional resumes only tell a fraction of a person's story. SkillsAware uses a blend of analytical and conversational agent AI as a controlled "guardrail" to map, rate, and verify an individual's true capabilities - capturing up to 1,000 hidden skills per person while keeping a vital human-in-the-loop.

👉 Watch the full video on https://skillsaware.com/videos/atp-insights-featuring-mark-keough-unlocking-workforce-potential-with-evidence-based-skills-intelligence/

This audio file is taken from the original video, “China Rewrites AI Chip Design Strategy,” published on the YouTube channel @asiatechpodcastofficial. 

About SkillsAware

SkillsAware is an AI-powered skills recognition engine developed through a collaboration between SkillsIQ, a skills-focused not-for-profit and Edalex, an award-winning EdTech and SkillsTech company, building on decades of technology and skills expertise. Its SkillsTech platform and associated services captures and maintains an evidence-based indicator of the plethora of skills that individuals accumulate progressively.

SkillsAware enables organisations to identify the skills that exist within their workforce and highlight strengths and gaps so they can plan for the future. SkillsAware assists with skills-based hiring and resourcing and supports and contributes to productivity, performance, opportunity and reward goals. SkillsAware has relevance for individuals, small, medium and large enterprises and industries in the recognition of current capability, prior learning and experience.

Learn more on our website - https://skillsaware.com
Connect on LinkedIn - https://www.linkedin.com/company/skillsaware/
Connect on Facebook - https://www.facebook.com/SkillsAware
Follow on YouTube - http://www.youtube.com/@Skills_Aware

Transcript

Michael Waitze: Thank you so much for coming on the show. We wanted to have you on because we wanted to talk about how evidence-based skills intelligence helps organisations improve workforce planning, productivity, hiring, and internal opportunity. And before we get to that in detail, why don't you tell us a little bit about SkillsAware?

Mark Keough: Thank you for having us. SkillsAware is an Australian-based but international organisation. We are a startup and, like a lot of people in the AI world, we're learning every day and finding new journeys, new pathways, and new information. But essentially, what we do is we've used artificial intelligence in a guardrail sense - a controlled, privacy-aware sense - to manage evidence of learning, including self-claimed learning, which is a bit unusual.

We allow people to tell us the story about their life experience, plus any learning they've gained through their organisation, plus any learning they've gained through certified authorities. Then we pull that all together for whatever the purpose might be. We are doing several things with our early clients, such as credit transfer and recognition of prior learning - or in North America, they often call it PLA.

We are working with people to accelerate and make it cheaper and easier to get recognition against formal qualifications, micro-credentials, and so on. Also, we work with organisations to expose skills within the organisation where people have got a lot of experience. They have learned a lot of things, but the organisations are unaware of this because they've hired them into a specific role based on a very short resume. But really, people have much more experience than what they show on their resume, so those are the two business cases we tend to play into. You have both an agent and an analytical AI function within SkillsAware. 

Michael Waitze: Can you run through how each one of those things works? Maybe start with the analytical AI and then the agent, and how it changes the way organisations approach not just skill development, but the understanding of which skills individual employees actually have, because that's kind of what you're referencing as well.

Mark Keough: True. One of the things we did is we brought in a 70,000-reach skills database into our backend so that whatever experience you've got, we can map it against those skills. You would typically upload some evidence - whatever that might be, like textual evidence, a reference, a job description, or a resume - and our analytical AI will map that against the 70,000 skills. This allows you to use your evidence over and over to get recognition against those skills.

The other process is the agent AI, where we use an agent we call the "skills assistant" to have a conversation with the participant, candidate, or learner. Through that conversation, it draws out more and more evidence. From there, we come to the way in which we rate evidence, which is a key part of our intellectual property; we have a rating system specifically to rate evidence.

Michael Waitze: I was going to ask you, how does that work and is it interactive? In other words, would that agent talk to me directly and say, "Michael, explain to me how you know this or how you know that?" For example, like in the US, if I passed the Series 7 or Series 30, whatever it is, I can do all these other jobs because I've been doing that for a long time. Is it interactive in that way, and does it score it as well?

Mark Keough: It's completely interactive, and it's not an assessor. We can talk about privacy in a minute, but the important thing about AI is using it as a guardrail tool rather than an open tool. There is a lot of fear about letting AI go rampant and wondering if it's going to replace all humans. In our model, humans are really important. What happens is that you would load your evidence - whatever that is, including your informal experience. You might have been volunteering at a music club or doing something else; you load all of this in, and the agent will ask you more and more questions to exude more information. Then we have an algorithm that rates the evidence. It doesn't rate you; it rates the evidence.

Michael Waitze: Oh okay, that's an important distinction. Thank you for clarifying that.

Mark Keough: Yeah, so it doesn't assess you in your capability; it assesses the evidence and whether it's relevant. That's the thing. But there's also a bit of gamification in here. What happens is you get into a gamified loop where people go, "Oh, I've got more evidence, I'll update my score and get a better score, a better score, a better score". Then, when they're ready and happy that they've got all of their evidence in, it can go off to a human assessor to evaluate. That might be in a university, a community college, a vocational college of some kind, within the context of their employment, or just for their own portfolio.

Michael Waitze: Yeah, so this is the other thing I was going to ask. Let's say I go through this whole process, whether I'm a new employee or a long-tenured employee at a specific company, and I use the SkillsAware platform. I go out and say that I have all these skills and I have evidence for them. Who is actually using that data? What's the point, and who's using it?

Mark Keough: In our early pilots, what we're discovering is that recognition of learning against formal qualifications provides the highest payoff. If you try to get credit or RPL (Recognition of Prior Learning) at an institution, there is a whole lot of paperwork involved that drives everyone insane. In fact, most people say it costs more to get recognition for your prior learning than it does to just do the course. Our primary business case is about reducing that cost by something like 70% - a 70% reduction in the cost of recognition of learning against a formal qualification.

However, in the process, we reveal a whole lot of other information because suddenly you've got a portfolio of all the things you've ever learned. In a resume, you might only have 20 things listed because everyone says to keep your resume short and recently relevant. But actually, you're a whole human, so let's recognise the whole human. What research tells us is that everybody has about 800 to 1,000 skills or capabilities. You just cannot represent those in a traditional resume, but you can represent them in SkillsAware, and you can represent them backed by evidence.

Michael Waitze: Are we suggesting then - and again, it's early days, so I'm just trying to surmise what's going to happen here - that the idea of Bob having 775 skills that no one has ever discussed before (because he only put 21 of them on his resume) is going to become more important than a job title or standard credentials?

Mark Keough: I think so. We live in a project-driven world, right? People are hiring for skills and moving individuals from project assignment to project assignment. Organisations these days do not hire someone into a 40-year role; it just doesn't happen anymore. We want people who can be with us for a while and be properly rewarded for their effort, but we want to move them from project to project rapidly. Just imagine construction, engineering, or defence - we are constantly moving people around, and they might be on more than one project at once. We need that visibility, and we need it fast.

Michael Waitze: Do you think we'll be in a situation where an organisation using a platform like SkillsAware will think, "Oh, we need to find someone who does this specific thing, so we need to go out and hire them," and then someone else will say, "Wait a second, we already have Lisa over here who has that skill and did that for four years somewhere else," even though it has no formal licence or credentials associated with it?

Mark Keough: Absolutely, and there's one more point: there might even be a regulatory or compliance requirement for Lisa, so where is the evidence? What we're making sure of is that not only is the skill identified - and there are plenty of big systems like Workday that have skill identification systems - but this is an evidence system.

We still struggle with the question of whether you can trust the evidence. That's a challenge for everybody with AI and just with human nature. Can you stop people from loading fraudulent evidence? That's tough, and you have to have good policies and procedures. But what we can do is present the evidence and keep the human in the loop to work it out, check the evidence, and make sure it's fit for purpose. In the end, I do believe you can trust people. Once people realise they are only going to be hired and recognised based on trusted evidence, they will put up the truth.

Michael Waitze: Yeah, I mean, I can't imagine the number of people I worked with at Morgan Stanley and Goldman Sachs who didn't lie on their resume. I think it's an edge condition, and the people who do it spectacularly generally get caught at the end of the day. Most people don't do it because they don't want the downside ramifications of saying they graduated with an MBA from Harvard when they've never even been there. That's just stupid.

Mark Keough: Exactly. One of the things we've built into the SkillsAware platform is an endorsement capability. We've worked with the United States Chamber of Commerce Foundation, who built an open tool called Linked Credentials (LinkCreds). We've taken that open intellectual property and incorporated it into SkillsAware. Through that, you can get an encrypted endorsement from a previous supervisor or peer, which adds a degree of validity and veracity to the evidence you're uploading. We're taking this stuff seriously, but it's not a perfect world. Anyone who says they have a perfect AI solution isn't telling the truth. The truth is, we use AI for productivity gains while keeping humans in the loop. We don't want to use it to replace people, human decency, or honesty; we just want to stop having to shuffle bits of paper around.

Michael Waitze: Well, it allows scale. This is the thing I keep talking to people about, and I'm on record saying that I don't think we'll see massive job losses associated with artificial intelligence or generative AI. I think it's going to create a whole new category of roles that need to get done but weren't getting done before because the AI wasn't there. It's just a different shift, like every other piece of technology over the past 50 years.

Mark Keough: Yeah, absolutely. I view AI as just another one of the big shifts that has gone on over the last 30 or 40 years. I'm sad to say I'm old enough to have been around when I got my first personal computer, which had a floppy disk and no hard drive - just 5.25-inch disks.

Michael Waitze: Only you and I would know about those, but go ahead!

Mark Keough: So, you know, we've seen a lot of change, and this is just another big change.

Michael Waitze: I was thinking about this this morning, and tell me if you think this is insane, but I don't think you get to have a strong opinion unless you've seen two or three of these big tech cycles. I don't want to pick a specific age because I don't think that's fair, but I think it was Mark Rudd who said, "Don't trust anybody over 30." I would say the same thing might be true about opinions on technology cycles in reverse. The point is, if you haven't seen multiple tech cycles, all you can do is make exaggerated, frightening claims about what this current cycle means without any context. 

Mark Keough: If we look back to 2006 and imagined what the iPhone would look like in 2026, we would have been really frightened about its power, sparking all sorts of conspiracy theories and fears. My view of AI is that while it takes humans out of certain loops, we've been through these cycles before. If humans were taken completely out of the equation, we'd just evolve away. The notion is crazy.

Michael Waitze: Can I make a counter-point, Mark? I don't remember the exact year because I wasn't alive, but when the printing press came out, it was supposed to be an existential threat to humanity because people were going to have way too much information and know things they shouldn't. Now, we're worried about people not having enough information or not reading enough. It's the same cyclical pattern.

Mark Keough: I remember a similar story from around 1812. The head of the British Post Office said that with the invention of the telegram, it would never take off because people wanted to see actual handwriting on paper.

Michael Waitze: Right, exactly!

Mark Keough: And then suddenly, with the telegram, you could send a message across the world. Look, I don't mean to dismiss the risks, but we are the ones in charge of managing those risks. While we remain in charge, let's use technology for productivity purposes.

If you can recognise what people truly know, isn't that much better than the current system of shuffling papers and sending resumes? I started this kind of work about 25 years ago when I had a global job at Monster.com - you probably remember them well. My job back then was to match skills with jobs. What we discovered was that the education world and the job world were like oil and water. My lifelong ambition has been to bridge the two, and that's exactly what SkillsAware does: we match the education and experience people have with the right jobs. People have struggled with that for years, but we feel like we've found a solution.

Michael Waitze: Let's talk about this at scale. What does a SkillsAware organisation understand about its workforce overall that a non-SkillsAware organisation completely misses?

Mark Keough: There's a traditional problem in most economies where some employers think, "If I train my staff or highlight how good they are, they'll leave." That's not the modern world anymore. Today, people are highly mobile and constantly moving around. Many people are even working for more than one organisation at once. This platform is about making sure that what is known about them is clear, allowing mobility to be rapid and scalable.

If you need to assemble a large workforce quickly - for instance, in emergency services - it becomes invaluable. I won't name the specific organisation, but let's look at a highly volunteer-oriented emergency care service. The problem they face is they onboard volunteers for one specific role, but they don't actually know what else those individuals know. In an emergency like a cyclone or a tornado, you want to get the right people to the right spot as fast as possible. That is the scalable opportunity we're targeting. We aren't at that massive scale just yet - we are still a startup running pilot projects - but that's the vision, and the investment community is very interested in how this works.

Michael Waitze: How long has SkillsAware been around?

Mark Keough: We've been developing the software for about 18 months, backed by startup investment. Now, we're at the stage of running multiple pilot projects across Europe, North America, and Australia, and we're hoping to launch some in Asia soon. They are going well, but like anything new, you have to educate the market a little bit, bring your investors along, and adjust the software to suit real-world requirements. It's a classic startup scenario, but we are patently clear about what we're up to, and we're looking forward to scaling up.

Michael Waitze: Awesome, good luck with that, Mark. It certainly can't hurt to know exactly what skills are sitting inside your organisation, nor can it hurt to know the skills of the people trying to join it. It sounds like an incredibly interesting platform. Thank you so much for coming on. Where can people find you? On LinkedIn?

Mark Keough: You can find us on LinkedIn or simply visit www.skillsaware.com. We'd love to hear from anybody who's interested in what we're doing.

Michael Waitze: Awesome. Thank you so much for doing this today, Mark. I really appreciate your time.

Mark Keough: My pleasure, nice to meet you.

Michael Waitze: Very nice to meet you as well.