Artificial intelligence (AI) has already transformed how we shop, watch movies and surf the internet. Now, it’s set to transform learning and development (L&D) — for the better. In this special episode of The Business of Learning, sponsored by CYPHER LEARNING, we spoke with Graham Glass, founder and chief executive officer of CYPHER LEARNING to learn more about AI-powered learning.
Listen now to learn more on:
- How AI can help create personalized learning journeys.
- How to begin adopting AI into your training programs.
- How AI can deliver more effective training at scale.
Listen now:
Additional Resources:
- Article: Artificial Intelligence in Corporate Training: Myths and Predictions
- Article: Eliminating Bias in AI With Implicit Bias Training
- Article: Improve Knowledge Retention With Hyper-personalized Learning
- Course: Managing Learning Technologies Certificate Program
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The transcript for this episode follows:
Speaker:
Welcome to Business of Learning, the learning leader’s podcast from Training Industry.
Michelle Eggleston Schwartz:
Welcome back to the Business of Learning. I’m Michelle Eggleston Schwartz, Editor in Chief at Training Industry here with my co-host Sarah Gallo, our senior editor.
Sarah Gallo:
Welcome before we begin, here’s a brief message from CYPHER LEARNING, the sponsor for today’s episode.
Speaker 1:
CYPHER LEARNING provides intelligent learning platforms to organizations worldwide. The company has three products, Matrix LMS for businesses, Neo LMS for schools and universities and INDIE LMS for entrepreneurs. With Matrix, CYPHER LEARNING helps businesses improve onboarding, optimized training and equip their employees with the right skills for their jobs in an effort evolving business landscape. Millions of users at thousands of organizations use the powerful yet intuitive platform to reach learning goals and improve business outcomes. Learn more about how Matrix can help your company www.cypherlearning.com.
Michelle Eggleston Schwartz:
Artificial intelligence has transformed many aspects of our lives, from how we shop to how we watch TV and now it’s transforming how we learn as well. AI can help learning leaders deliver the curated, personalized learning experiences that today’s employees are looking for. But there’s still many questions when it comes to AI enabled learning. To help answer them, we’re here with Graham Glass, founder and chief executive officer of CYPHER LEARNING to learn more. Graham, thank you for speaking with us today.
Graham Glass:
It’s my pleasure, Michelle. It’s great to be here.
Sarah Gallo:
Yes. Welcome to the podcast, Graham. Before we dive in, why don’t you tell us a little bit more about yourself, your background in the corporate training industry and also a little bit more about CYPHER LEARNING?
Graham Glass:
Yes, I’d be happy to. So, first a little bit about me and then a little bit about CYPHER LEARNING. So, I am first and foremost, an educator that I went to a fantastic school in the UK, one of the top 10 schools there. I loved my own educational experience there and then when I went to the University of Texas Dallas to do my graduate studies, I was invited to teach there. So, my first formal experience of being an educator was actually in higher education and I absolutely loved it and I think one of the reasons that my students always gave me really good scores at the end of the semester, is because I always managed to make my courses entertaining. They were project based. So, I always got them to build something really cool. They build that really cool thing, they enjoyed the process and as a side effect, they learn everything that was in the curriculum. But after that, I realized that I could probably have a better career focusing more on the corporate side than staying in academia, so I formed a professional training company. I was the first educator. I probably have taught over 1,000 people easily in corporate America, but we would do the same kind of thing teaching computer science all over the U.S. And we continue with the same theme, it was very practical, it was very engaging project based learning, but we built up a pretty solid team of educators during that process. So, I come from a background of having trained people in higher-ed and in corporations, but of course in this particular podcast, we are going to focus on the corporate side of things. So, about 12 or 13 years ago, I decided I was going to use my experience as an educator combined with my academic credentials in high-tech computing to build what we now call the world’s best intelligent Learning platform. So, we wanted to build something that did all the bread and butter basics, create a course, people enroll, take a course, but we wanted to make it smarter so that it could actually become your personal companion throughout your learning journey. So, that’s where CYPHER LEARNING is right now. We’re in 22 offices around the world, we’ve got millions of users, thousands of satisfied customers, but we really are focused on raising the bar in terms of what a learning platform is and making it more infused with AI and machine learning.
Sarah Gallo:
Perfect. Thanks for sharing Graham. It’s cool to hear your career story starting in higher-ed and moving into corporate training which is something we’ve definitely heard before. I think going back to what Michelle mentioned, there’s still so many questions when it does come to AI enabled learning. I think we should maybe start with the, why here? Why AI and learning? Have you had any experiences yourself in your career thus far that were maybe particularly challenging and the AI really would’ve helped out with?
Graham Glass:
Absolutely and it goes all the way back to my days in higher-ed. So, I’ll share just a couple of anecdotes with you where that would’ve been really handy. So, when I was teaching at the University of Texas Dallas, I was teaching courses that were actually very practical that could help people get jobs. So, I wasn’t teaching these highly theoretical mathematical subjects, but because of that, I would usually have over 100 students per course I was teaching and I was teaching four courses simultaneously. And so you can imagine if you are trying to teach essentially 400 people a semester, it’s really hard to track everyone’s strengths of weaknesses and provide any personalized experience. So, when I would get up on the floor of the university and start teaching various subjects, I would know in the back of my mind, well that person’s sitting over there is a little bit weak in that area that person’s over there is really rambunctious and they’re going to do a great job in this course. So, sometimes I could tailor a little bit to them, but most of the personalization really occurred in my office. So, someone would come by the office, I would review their work, maybe I grade a paper and I would say, you know what? Based on what the problems I’m seeing you having, I think you would do really good watching this particular video. So, I would give them recommendations basically, and they were somewhat personalized, but it was all 100% manual. And I do remember thinking, if there was a way to actually track this systematically using some technology, then I could actually take a lot of the recommendations that I’ve built up over the years and automate them. So, if somebody submitted a piece of work and they didn’t score well, it could say, Hey, by the way, Graham highly recommends this video to get better at this particular subject. So, that was the first time that I realized office hours are okay, but they’re not scalable. I also remember thinking that the materials that I created were really good, wouldn’t it be incredible if I could somehow take all of my experience in teaching this and make it available to 1,000,000 people simultaneously. That would be even better and by that time I’d be probably a billionaire, but that never happened. So, that was really my first experience of that. Similar thing happened in corporate training. So, I would typically teach courses with 30 to 40 people in them. We would have little breakout groups for certain people, I would do some individual training, but once again I’ve never met these people before, I’m going to be in a room for one week to two weeks with them. How can I actually provide this personalized feedback and recommendations in any scalable way? So, the corporate training environment was a little bit easier because there were smaller classes and you got to know [the learners] better, but I still kept on hitting that wall which is, “I wish this could be more personalized for these people.” And in addition, wouldn’t it be great if after the training, everything I’ve learned about them continues with them so when they’re actually in the job, my system could still make recommendations. So, we look at AI as not replacing the charisma or the inspirational thing that humans can provide, but we do want to automate a lot of the recommendations and things that we learn in a way that’s consistent and scalable. So, that’s basically where we see one of the biggest payoffs of using artificial intelligence.
Michelle Eggleston Schwartz:
Thanks for breaking that down. And you definitely highlighted why a one size fits all approach to learning is just not possible. Every learner has unique need and so they definitely require unique learning solutions. Can you elaborate more on how can AI help create personalized learning journeys?
Graham Glass:
That’s a great question. I think that if an AI is going to do a good job, then it needs to know lots about you. And if you think about it, when you go to Amazon, Amazon knows tons of stuff about me. It knows that my kids love Lego as an example. So, the more I interact with a system, the more it gradually deduces things about you and one of the areas that CYPHER LEARNING is the best of breed is in an area called competency based learning. And the idea behind competency based learning is to understand your strengths and weaknesses down to a fine grain. So, it doesn’t just know, Hey, you are good at marketing for example, but it will know you’ve got a particular strength in logo design, you’re a little bit weak in SEO management, you’re really good at pay for click. A lot of the fine grain aspects of what ultimately goes into your job title. And we can actually figure that stuff out automatically because in our system, you can tag content with the specific competencies that it’s teaching and you can tag assessments, even down to the individual question level about which specific competencies they are measuring. So, you can imagine a marketing course which it might start off by saying, Hey, I want to get to know you a little bit, can you take this quick quiz? And you go through the quick quiz and at that point in those you’re really good at logos, you’re not so good at SEO. Once it’s created that initial mapping of your strengths and weaknesses, that gives it enough fuel to start recommending areas to bolster your weaknesses. So, there’s no point in just focusing on your strengths, if you are fantastic at logo design, it doesn’t make any sense for it to say, and now we’re going to take a course on logo design because you’re already really good at it. So, the general idea is to start up with the mapping of your strengths or weaknesses, do a gap analysis of what you want to be strong in and what you are currently weak in, and then start recommending all kinds of things to help you close that gap. We have a much deeper support for competency based learning than any other platform in the world. The second thing is, and I do want to emphasize it’s not just all about recommending courses. It’s not just about recommending videos for example, or websites, but we can recommend individual people to network with, we can even recommend collaborative groups where other people are discussing similar topics where some of that stuff might rub off on you. So, it goes beyond just recommending courses. And then last but not least, we’ve got this quite unique feature called learning goals in our system, where you can say my learning goal is to either get good at particular job title or my learning goal might be to get really good at particular group of competencies and then you can actually see in real time your strengths, your weaknesses, you can see improvements over time, you can see a recommendations feed. So, hopefully this gives you a little bit of an idea about once the AI has figured out your strengths and weaknesses, it can give very targeted recommendations and it can track as you get closer to those goals, how well you’re doing.
Sarah Gallo:
Very cool. I love what you mentioned about that skills mapping aspect and that really is so helpful for the training manager, but also from a learner standpoint. We know that learners really are looking for those curated learning journeys. How can that really help learners visualize their future career paths at a company? What do you see that looking like?
Graham Glass:
So, one of the things that we decided to do quite a while back is that we wanted to eat our own dog food as they say. And so we use our own platform obviously at CYPHER LEARNING. So, we growing very quickly. We added 100 new people in the last six or nine months. So, we’ve created our own branded sites, skills.cypherlearning.com. And what we did is we’ve done some competency mappings of all the job titles inside of CYPHER LEARNING. Like senior technical support, click to pay analysts, financial analysts and for every one of those, there is a whole collection of competencies that we’ve mapped out. Then when somebody joins the company, we use world class automation system to say, Hey, this person’s joined the company, they’re joining as a senior software architect so automatically give them this learning goal which says, I want to master everything about my particular job title. So, them simply joining the company, it instantly associates their job, their persona, their learning goals, their competency maps right from the get go. And then at that point, our recommendations engine can start feeding them various tagged items on how to either master everything with their current job title or if they want to, the employee can log in and say, I want to add a new learning goal. And let’s just say, I’m a junior software engineer, well one of my learning goals is to become a senior software engineer. So if they add that as a goal, then in our system, the senior software engineer will have its own set of competencies and when it knows now that’s your new goal, it’s going to start making you recommendations towards how to become this senior software engineer. All of these appear as tiles in your dashboard and they have percentage signs that show you your 80% towards this learning goal, you are 60% towards this goal and you can always click on a goal and it will give you a really deep, fully traceable dive into exactly why it thinks that you’ve mastered certain skills and have mastered other skills.
Michelle Eggleston Schwartz:
Can you maybe talk us through the role of the learning leader when using AI? For instance, does using AI for learning mean you’re handing overall control to a machine or can trainers have some input too? What does that look like?
Graham Glass:
I actually think that the AI is more an assistant and I say this just based on my own experience of learning. So, when I fly into Dallas for example, which is where our corporate headquarters are and I’m hanging out with real life humans and they’re telling inspirational stories and using personal anecdote, that is just so much more engaging than just click, click, click, click, congratulations, your master things. And humans are very social, we like to be inspired, we like to be with around inspirational people. So, I think it’s really about assisting those instructional designers or leaders to take everything that they’re really good at and scale it so it can reach more people who can benefit. So for example, in our platform, we make it really easy for anyone to create a course. Those courses can be fully gamified and they can be broken up into small segments which themselves can use automation to make them more fun. So, I’ll just give you one simple example. We’ve got our own internal L&D team. And one of the things that they wanted to do was to create a course for onboarding, welcome to CYPHER LEARNING. So, the idea is that everyone who joins the company goes on the learning path and the first part in their path is the generic onboarding welcome followed by specific courses relative to whichever department they’ve joined. And as you probably know, onboarding is a huge pain point. Everyone who goes above a certain size, they hit that wall. How do I onboard people? So, this is something that we really excel at. So, we took our L&D team and they worked with all the department leaders and myself included and they put together some really fun videos where people all over the world will say, welcome to CYPHER LEARNING in their language which is really cool and then there’s a little bit of a backstory about how I started the company. Then it goes into the products, then it has quizzes about all of that stuff and it’s all mapped to competencies. So, we say everyone in the company should master the following 40 competencies quite early on because that shows that you have mastered what CYPHER LEARNING is all about. So, the nice thing is that the L&D team would interview us, they would record us, they’d take all the things that we’ve learned over the years. They package them up, they gamify them so you can get points and badges by doing really well. You can have team competitions between people in sales and people in marketing. We use automation to pop up encouragement messages as you go to make other recommendations and the nice thing is, that rather than me for example, personally onboarding now, every single person that comes on they’ve captured the things that I hope are somewhat inspirational to everyone in the company, but they’ve captured those things in a way that can scale. So, we could add 1000 more people and they would still get the benefit, but I wouldn’t have to personally be involved on a daily basis.
Sarah Gallo:
Perfect. Onboarding is definitely a challenge. We’ve seen that with our leadership as well so cool to see how these solutions are there to help. Another challenge that I know our listeners are facing, is really interpreting those mounds of training data. Graham, how can AI alleviate this pain point and make it easier to determine those knowledge gaps, program effectiveness and also other key metrics?
Graham Glass:
So, that is one of the benefits of just technology in general is that it can crank through a lot of information and give you insights and there are several insights that our platform currently provides already and there are some areas that we are going to be adding later on this year. So, some of the things that we have already is understanding your fine grain strengths and weaknesses and making recommendations. And those are things that there’s no way a human is ever going to be at track that in any kind of scale or taking a look and seeing how rapidly you progressing through the materials? How long you taking to get better at a particular competency? That’s something that your manager can have access to and they might say, you know what? You continue to struggle in this one area, maybe we’ll hire a third party consultant to work with you to beef up that particular area. So, that’s when where a manager can observe something being extracted from the raw data and then take some action. But another area that we are working on, which is not available yet, is at risk learners. So, one of the things that we can do is we can do predictive analysis on how well someone is doing over time and obviously, everyone has things happen in their life. You might struggle for a few days or a week doesn’t mean you’re in at risk in the long term, but there are some people who just continually struggle or fall behind the average for quite a while and those are things where we can say, flag those people, Hey in a HR, this is someone who’s struggling consistently maybe you need to have a talk with them and see how you can remediate this. One of the cool things about CYPHER LEARNING is we have one platform, but two branded versions. Matrix, which is for business which is the one I’m focused on, but then Neo for higher education because we love K through 20 as well. And if you want to make a big impact on the world, impacting young people especially kids at school is a great way to do that. And this technology is really useful for our Neo product as well because in schools and universities, they want to track students that they want to help students as early as they can for example, during their college life. So, I do think that AI and machine learning is a fantastic tool for this stuff, but it’s giving you the insight, most of the time it’s going to be the humans who decide what to do once they’ve got that insight.
Michelle Eggleston Schwartz:
Thank you for sharing all that. Speaking another pain point for a lot of learning leaders, it’s really securing those extra training dollars and training investment. It’s not easy especially for those smaller learning and development teams, some of which are teams of one. Are AI capabilities accessible and available to all companies or are they only in reach for very large companies with large more mature training programs and budget?
Graham Glass:
No, like in the case of Matrix, one of the things that people constantly tell us is that our pricing is really good. And unlike some companies, you can sign up for our platform with say 100 active learners. Now, obviously from a business perspective, we are targeting larger companies. If you look at learning platform companies that do well, they’re ones who are geared up to… We’ve got customers with 100,000 active learners. But that being said though, part of my personal desire is to allow small companies like CYPHER LEARNING [which was] a lot smaller two years ago, we would’ve loved this kind of stuff much earlier on. So, I don’t think it’s something which should only be the domain of very large companies. That being said, some of our competitors really are targeted almost completely for 1,000 active learners plus just based on their pricing and based on their color points. But our pricing makes this kind of thing available for all kinds of small, medium, large businesses.
Sarah Gallo:
Perfect. It’s great to hear that technology becoming more accessible like we’ve seen with VR training. In the past, it wasn’t as accessible as it is now so it’s good to see that progress in the industry. I think another point I want to mention here, Graham is that of course, introducing AI into your training programs can be daunting and it can worry someone where to start. Do you have any tips for our listeners who are just at the beginning of their journey in integrating AI into their training environments? What’s really the best way for them to get started?
Graham Glass:
So, that is an interesting question and I’ll tell you how we’ve addressed it and it’s based on our own customer base as well. So, we’ve got people in the K through 20 who are very interested in these capabilities as well in businesses. But there’s different sensitivities. So for example, you might have some organizations who want to turn off AI completely because they don’t trust them. You have some organizations who, well, if I do use it, maybe it’s going to suggest something culturally inappropriate so we want to have control over what recommendations are made. Some people might say, well, it’s okay if you recommend our courses, but we don’t want you to recommend external videos. So, if you think about the primary use case that we are focused on which is making recommendations for closing the gap on things you want to master, we’ve made our recommendations really highly configurable. So, there’s essentially a bunch of check boxes that you can set up and you can say only recommend courses, only recommend groups, only recommend resources, only recommend things that approved, enable machine learning or disabled machine learning. So, there are different ways that you can configure the recommendations engine so you can go fully automated or fairly manual. And I think that’s really the key to do things is to make it so that it’s configurable so the customers can decide to what degree they’re going to use some of these machine assisted recommendations.
Michelle Eggleston Schwartz:
Definitely. You need to out exactly what it is that you use this software for and really what your end goal is keeping that in mind.
Graham Glass:
Yeah.
Michelle Eggleston Schwartz:
Other key takeaways you’d like our listeners?
Graham Glass:
I’d tell the listeners bit about why we are calling ourselves an intelligent learning platform. When people hear the term learning management system, LMS, sometimes they’re feeling like this is something old, even though learning management systems tend to evolve over time. So, people tend to think about LMS as being something passive, something quite boring, maybe only used for compliance, just a bread and butter kind of thing. And that’s certainly not how we view our platform. We view ourselves as innovators in this space, we’re doing a lot of cool stuff with a variety of different customers. So, the challenge for us is even though in terms of from the market perspective and how people categorize it, they might say, Matrix is an LMS, we wanted to call it something a bit more inspirational. So for a while, we just called it learning platform because learning platform still gets across the learning management system part, but it’s a little bit more modern sounding. But then when we started getting into machine learning and artificial intelligence and we are going to be doing some AR VR work that’s going to be coming out next year, we’re involved in a lot of leading edge stuff. We already have voice control through Alexa that came out ages ago. So, what we wanted to do is to say, well, rather than just saying “learning platform,” let’s use the term intelligent learning platform because it gets people more interested. Like, well, what exactly do you mean? Where are the areas that your platform is intelligent or more intelligent than your competitors? So we’re using ILP, intelligent learning platform as a way to think about our platform. It is essentially an LMS in terms of its product category, but we just think it’s so much more. So, that’s just to explain to you listeners why we are hanging our hat on Matrix, the world’s best intelligent learning platform.
Michelle Eggleston Schwartz:
Great. It’s great to point out that differentiation there. Well, Graham, thank you so much for speaking with us today. How can our listeners get in touch with you after today’s episode if they’d like to reach out?
Graham Glass:
So, I’d tell the main thing to learn more about the company is to go to our main site which is cypherlearning.com and there is just a humongous amount of information there and it’s easier to sign up for a free trial of Matrix if anyone’s interested, product comparisons, reviews, awards, all kinds of stuff. And my personal email is Graham, G-R-A-H-A-M AT cypherlearning.com so I try to be a fairly accessible CEO.
Sarah Gallo:
Perfect. Well on that note, Graham, thanks again for speaking with us today, for more insights on AI enabled learning, you can visit the shownotes for this episode at trainingindustry.com/trainingindustrypodcast.
Michelle Eggleston Schwartz:
As always, don’t forget to rate and review us on your favorite podcast app. We love hearing your feedback. Until next time. If you have feedback about this episode or would like to suggest a topic for a future program, email us at infotrainingindustry.com or use the contact us page at trainingindustry.com. Thanks for listening to the Training Industry podcast.
