1 00:00:00,040 --> 00:00:02,040 If you've been listening to In the Loop every single week, 2 00:00:02,040 --> 00:00:04,240 you'll know that we have quite high quality standards. 3 00:00:04,640 --> 00:00:08,160 We spend a lot of time trying to find the perfect episode, the 4 00:00:08,160 --> 00:00:11,440 best way of telling the story, and we really care about the 5 00:00:11,440 --> 00:00:13,160 production. Today, that means trying 6 00:00:13,160 --> 00:00:15,800 something new. This is going to be our first 7 00:00:15,800 --> 00:00:18,560 ever interview, and honestly, I hope you're going to love it. 8 00:00:18,640 --> 00:00:22,080 I got to speak to somebody who spent 25 years trying to fix 9 00:00:22,240 --> 00:00:25,640 what can only be described as a broken system that fails 10 00:00:25,640 --> 00:00:27,760 millions of people every single day. 11 00:00:28,520 --> 00:00:31,720 And getting to sit down with her to dig into her story and her 12 00:00:31,720 --> 00:00:35,600 beliefs was so much fun. She's an expert in the topic. 13 00:00:35,600 --> 00:00:39,280 She's a fantastic speaker and an author, and it's the exact type 14 00:00:39,280 --> 00:00:41,920 of conversations that I want to bring you more of. 15 00:00:42,200 --> 00:00:43,880 I'm Jack Horton, and this is in the Leap. 16 00:00:44,440 --> 00:00:47,360 Today I'm investigating a question that affects every 17 00:00:47,360 --> 00:00:51,760 working person. Who decided this is learning and 18 00:00:51,760 --> 00:01:00,520 why hasn't AI fixed it yet? Picture this it's Monday 19 00:01:00,520 --> 00:01:02,440 morning. Sarah, a customer service 20 00:01:02,440 --> 00:01:07,120 manager at a Fortune 500 company, just woke up to learn 21 00:01:07,120 --> 00:01:10,000 that she has to complete her digital communications best 22 00:01:10,000 --> 00:01:14,560 practice course by tomorrow morning. 45 minutes of clicking 23 00:01:14,560 --> 00:01:17,120 through slides about not sharing inappropriate photos into a 24 00:01:17,120 --> 00:01:20,080 company slide channel. Meanwhile, another company just 25 00:01:20,080 --> 00:01:23,640 down the road has implemented an AI system that handles 60% of 26 00:01:23,640 --> 00:01:26,680 all customer support enquiries in six months. 27 00:01:26,680 --> 00:01:29,960 Sarah's job may not even exist, but hey, at least she's 28 00:01:29,960 --> 00:01:31,880 compliant. This isn't hypothetical. 29 00:01:32,160 --> 00:01:34,440 This is happening at companies across the world. 30 00:01:34,720 --> 00:01:38,240 Whilst the largest workforce transformation in human history 31 00:01:38,520 --> 00:01:42,560 unfolds around us, AI systems are already writing code, 32 00:01:42,920 --> 00:01:46,280 diagnosing diseases, creating and making decisions that used 33 00:01:46,280 --> 00:01:48,320 to require entire teams of people. 34 00:01:49,320 --> 00:01:51,600 We're in what experts called the great upskill. 35 00:01:53,040 --> 00:01:56,360 We need to rapidly train people to do things machines can't. 36 00:01:56,920 --> 00:02:00,200 Creative problem solving, emotional intelligence, complex 37 00:02:00,200 --> 00:02:02,000 reasoning and decision making skills. 38 00:02:02,400 --> 00:02:06,080 Yet the very thing that should be helping people succeed is 39 00:02:06,080 --> 00:02:09,199 currently failing most people. That's learning. 40 00:02:09,520 --> 00:02:13,240 Specifically, learning at work. Companies spend hundreds of 41 00:02:13,240 --> 00:02:16,720 billions of dollars on global training every single year. 42 00:02:17,240 --> 00:02:19,240 That's more than the GDP of some countries. 43 00:02:19,800 --> 00:02:22,800 And yet when was the last time you took a workplace training 44 00:02:22,800 --> 00:02:27,800 course that you actually found helpful, that felt relevant to 45 00:02:27,800 --> 00:02:30,760 your challenges, and that made you demonstrably better at what 46 00:02:30,760 --> 00:02:34,080 you do? Research has shown that most 47 00:02:34,080 --> 00:02:37,000 training is forgotten within 24 hours. 48 00:02:37,120 --> 00:02:39,440 To understand this crisis, I spoke to someone who'd been 49 00:02:39,440 --> 00:02:42,920 inside the system. Someone who's not just witnessed 50 00:02:42,920 --> 00:02:45,600 all the dysfunction, but who'd lived, breathed it, and spent 51 00:02:45,600 --> 00:02:49,600 her career trying to fix it, and came across the solution from a 52 00:02:49,600 --> 00:02:53,680 very unlikely place, A hospital emergency room, a bottle of 53 00:02:53,680 --> 00:02:57,200 vodka, and a moment of panic at 30,000 feet. 54 00:02:57,840 --> 00:03:00,200 This is the story of how workplace learning got broken 55 00:03:00,400 --> 00:03:02,720 and how we might be able to fix it with AI. 56 00:03:12,440 --> 00:03:15,360 To finances. I spoke to Laurie Hoffman, who 57 00:03:15,360 --> 00:03:19,120 sent 25 years in educational technology, working as a chief 58 00:03:19,120 --> 00:03:22,560 learning officer at major cororations and advising some of 59 00:03:22,560 --> 00:03:26,000 the biggest companies in the entire world on how to deliver 60 00:03:26,000 --> 00:03:28,840 great learning experiences. I think there's a number of 61 00:03:28,840 --> 00:03:31,240 reasons. If you look at early e-learning 62 00:03:31,240 --> 00:03:34,240 and I'll focus on the digital type of content, early 63 00:03:34,240 --> 00:03:37,520 e-learning was really about compliance. 64 00:03:37,520 --> 00:03:40,960 So it was all thou shalt do this, thou shalt not do this. 65 00:03:41,200 --> 00:03:44,680 So it was written in such an artificial way. 66 00:03:44,680 --> 00:03:49,120 There wasn't any storytelling. And so people kind of had that 67 00:03:49,120 --> 00:03:51,200 dread when they went into it the very first time because they 68 00:03:51,200 --> 00:03:52,360 knew what it was going to be, right? 69 00:03:52,560 --> 00:03:54,880 It wasn't going to be engaging, It wasn't going to be anything 70 00:03:54,880 --> 00:03:56,640 of interest. And basically what they were 71 00:03:56,640 --> 00:03:58,440 effectively reading was not even learning. 72 00:03:58,440 --> 00:04:00,880 It was a legal document to protect the company. 73 00:04:01,080 --> 00:04:04,080 A legal document not working. And when I did a little bit more 74 00:04:04,080 --> 00:04:08,120 digging, I found that Once Upon a time in the 1950s, you'd learn 75 00:04:08,120 --> 00:04:10,120 through apprenticeships. You'd be working alongside 76 00:04:10,120 --> 00:04:13,720 masters, getting real time feedback and practising skills 77 00:04:13,720 --> 00:04:16,160 in context. And now picture corporate 78 00:04:16,160 --> 00:04:20,240 learning today. Lots of boring videos that are 79 00:04:20,240 --> 00:04:23,480 very rarely helpful. This shift happened gradually, 80 00:04:23,480 --> 00:04:27,000 then incredibly fast. In the 1990s, companies started 81 00:04:27,000 --> 00:04:29,600 moving training online to save costs. 82 00:04:29,840 --> 00:04:33,080 And then, as corporate scandals like Enron and Worldcom wiped 83 00:04:33,240 --> 00:04:37,280 billions off the market, new laws made compliance legally 84 00:04:37,280 --> 00:04:40,000 required. Suddenly the primary purpose of 85 00:04:40,000 --> 00:04:43,760 corporate training shifted from developing people to protecting 86 00:04:43,760 --> 00:04:46,680 companies from lawsuits. So what started as a cost saving 87 00:04:46,680 --> 00:04:48,520 measure became a legal necessity. 88 00:04:49,000 --> 00:04:51,800 And legal necessities, once embedded in corporate 89 00:04:51,800 --> 00:04:54,880 bureaucracy, become really difficult to change. 90 00:04:55,360 --> 00:04:57,160 So the company says, well Jack read this. 91 00:04:57,160 --> 00:05:02,280 So therefore you know, tick mark Jack will not launder money. 92 00:05:02,320 --> 00:05:04,600 That is, that is essentially what what it was doing for, for 93 00:05:04,600 --> 00:05:07,280 for one example. I think the second one is, is a 94 00:05:07,280 --> 00:05:09,440 lot of people that get into corporate learning actually 95 00:05:09,440 --> 00:05:14,440 don't know learning. They have gone through school in 96 00:05:14,440 --> 00:05:17,920 some way, shape or form and creates this this fallacy that 97 00:05:17,920 --> 00:05:19,720 because they've gone through school, they automatically know 98 00:05:19,720 --> 00:05:22,000 how learning works. And they have, quote UN quote, a 99 00:05:22,000 --> 00:05:23,640 passion for learning. And, and you know, I have a 100 00:05:23,640 --> 00:05:27,080 passion for brain surgery, but you wouldn't allow me to ever 101 00:05:27,080 --> 00:05:31,400 perform that on anyone living or probably even expired. 102 00:05:31,520 --> 00:05:35,360 I think one of the worst ones I ever had to do was the company 103 00:05:35,360 --> 00:05:38,440 was launching an internal tool that at the time was very 104 00:05:38,440 --> 00:05:41,880 similar to Slack and Yammer. But before this, before those 105 00:05:41,880 --> 00:05:47,240 tools were ubiquitous and it was not an e-learning on how to use 106 00:05:47,240 --> 00:05:49,800 the tools. It was basically all the things 107 00:05:49,800 --> 00:05:53,720 you could and could not say basically how to be in general a 108 00:05:53,720 --> 00:05:56,520 good human being. And it even had things in it 109 00:05:56,520 --> 00:06:01,120 like please do not share photos that depict people without 110 00:06:01,120 --> 00:06:02,560 clothes on. And I thought, well, I mean, 111 00:06:02,560 --> 00:06:04,320 this surely does not need to be an e-learning. 112 00:06:04,320 --> 00:06:05,840 This has to be just a simple code of conduct. 113 00:06:06,320 --> 00:06:08,680 About 45 minutes. People had to go through that. 114 00:06:09,400 --> 00:06:11,960 And what ended up happening is everyone was afraid to even use 115 00:06:11,960 --> 00:06:16,000 the tool because the rules got so ridiculous and it was came 116 00:06:16,000 --> 00:06:19,160 down to you can't tag more than three people and just just 117 00:06:19,160 --> 00:06:21,120 stupid stuff. I think Laura's example 118 00:06:21,120 --> 00:06:24,240 perfectly illustrates this focus on compliance over developing 119 00:06:24,240 --> 00:06:27,360 people, launching internal communication tools, something 120 00:06:27,360 --> 00:06:29,600 that should encourage collaboration, but then made 121 00:06:29,600 --> 00:06:33,000 people watch 45 minute courses that were so restrictive that 122 00:06:33,000 --> 00:06:36,240 people feared even using the system. 123 00:06:36,520 --> 00:06:38,800 The resistance isn't to development, it's to 124 00:06:38,800 --> 00:06:41,400 dysfunction. But I wanted to know, why are we 125 00:06:41,400 --> 00:06:44,520 still stuck in this same place? Then a big part of the answer 126 00:06:44,520 --> 00:06:47,520 lies and something that most people have never heard of, that 127 00:06:47,520 --> 00:06:51,360 controls almost all corporate learning across the world, and 128 00:06:51,360 --> 00:07:04,800 it's called SCORM. So SCORM is this funny little 129 00:07:04,800 --> 00:07:07,800 piece of technology that used to be really relevant. 130 00:07:08,600 --> 00:07:11,360 It's called a shared content object. 131 00:07:11,360 --> 00:07:13,440 Basically is is is is what is what it is. 132 00:07:13,800 --> 00:07:17,520 And it used to be that mod learning was for compliance. 133 00:07:17,520 --> 00:07:19,200 So you needed to be able to prove that. 134 00:07:19,200 --> 00:07:22,000 OK, Jack took this hour long course. 135 00:07:22,000 --> 00:07:25,640 He passed the test at over 80%. We know what he questions he got 136 00:07:25,640 --> 00:07:27,600 right and wrong. We know the date he did it on. 137 00:07:27,640 --> 00:07:30,040 Yay, all good. And we send that to the 138 00:07:30,040 --> 00:07:33,240 regulators. OK, so with Jack does something 139 00:07:33,240 --> 00:07:37,160 wrong, we can pull that and say, well, clearly you know, it 140 00:07:37,160 --> 00:07:38,960 wasn't our fault because he passed the module. 141 00:07:38,960 --> 00:07:41,320 Now that's that's old school learning, but that's what we 142 00:07:41,320 --> 00:07:44,880 used to have in like 2000, OK. So SCORM is this technical 143 00:07:44,880 --> 00:07:47,880 standard, basically a set of rules about how e-learning 144 00:07:47,880 --> 00:07:51,560 should be packaged up and delivered to people, and it was 145 00:07:51,560 --> 00:07:55,600 created in the early 2000s with only one goal, compliance 146 00:07:55,600 --> 00:07:58,000 trucking. But what SCORM does is SCORM 147 00:07:58,000 --> 00:08:01,680 became the package that all learning had to be in, in order 148 00:08:01,680 --> 00:08:04,040 for it to be interpreted and understood by a learning 149 00:08:04,040 --> 00:08:07,680 management system. But what SCORM does not do is 150 00:08:07,680 --> 00:08:10,200 also take into account suspended data. 151 00:08:10,360 --> 00:08:13,200 What do I mean by that? Well, if you backtrack in a 152 00:08:13,200 --> 00:08:16,680 module or if you do a branching exercise or if you only watch a 153 00:08:16,680 --> 00:08:20,240 portion of a video or if you're learning something that isn't on 154 00:08:20,240 --> 00:08:23,040 the learning management system, say you go, you see something on 155 00:08:23,040 --> 00:08:26,000 Slack and what not that may not even track as part of your, 156 00:08:26,000 --> 00:08:28,800 your, your learning learning Canon. 157 00:08:29,480 --> 00:08:32,559 And so as a result of that, we, we got locked into this. 158 00:08:32,640 --> 00:08:37,440 Click next to continue type. And there's, I feel for 159 00:08:37,440 --> 00:08:39,480 instructional designers and and learning experience designers 160 00:08:39,480 --> 00:08:41,200 because there's only so much you can do with that. 161 00:08:41,480 --> 00:08:44,280 There really is only so much you can do and that, but that's how 162 00:08:44,280 --> 00:08:46,280 we ended up with the drag and drop and that's how we ended up 163 00:08:46,280 --> 00:08:50,520 with those really boring things because that's all we could do. 164 00:08:50,680 --> 00:08:53,760 So there's the problem, Scorn became the dominant standard 165 00:08:53,760 --> 00:08:55,600 that almost all these learning management systems. 166 00:08:55,600 --> 00:08:59,040 So the software that companies used to deliver training was 167 00:08:59,040 --> 00:09:01,640 historically built around. That's a multi billion dollar 168 00:09:01,640 --> 00:09:06,160 industry that had a financial incentive to maintain this 169 00:09:06,160 --> 00:09:07,960 system. But this raises a bigger 170 00:09:07,960 --> 00:09:10,960 question. If SCOM is so limiting, why 171 00:09:10,960 --> 00:09:14,040 hasn't it been replaced? And why are we still stuck with 172 00:09:14,040 --> 00:09:18,400 this 25 year old standard designed for compliance training 173 00:09:19,040 --> 00:09:22,600 in an era where personalization and adaptation should be 174 00:09:22,600 --> 00:09:25,000 possible? In an era where developing 175 00:09:25,000 --> 00:09:27,320 people has become more important than ever. 176 00:09:28,160 --> 00:09:30,520 Easy, easy answer to that money, right? 177 00:09:30,760 --> 00:09:33,840 So if you think about what marketing is doing, it's 178 00:09:33,840 --> 00:09:36,320 generating leads, it's generating interest and 179 00:09:36,320 --> 00:09:39,040 engagement with a product that's ultimately going to lead to a 180 00:09:39,040 --> 00:09:40,960 sale. And there's a much, much, much 181 00:09:40,960 --> 00:09:46,120 larger pool of people that you are say tempted to, to reach out 182 00:09:46,120 --> 00:09:47,680 to. If say you are a company that 183 00:09:47,760 --> 00:09:50,000 makes trainers, right? I mean, you're going to just 184 00:09:50,000 --> 00:09:53,760 say, yes, I absolutely will pay to get a, a million, you know, 185 00:09:53,920 --> 00:09:56,960 ads or whatever to, to, you know, to target ads to people. 186 00:09:56,960 --> 00:09:59,760 And because that's what you do as a, as a company, right? 187 00:10:00,320 --> 00:10:03,800 Learning. The reason it is a slower thing 188 00:10:03,920 --> 00:10:07,400 or was because things are changing is because even if you 189 00:10:07,400 --> 00:10:09,480 think of software manufacturers and you think of where the 190 00:10:09,480 --> 00:10:13,880 revenue is, it's not in somebody doing a learning course, right, 191 00:10:13,880 --> 00:10:15,920 because there's nothing that they're buying at the end of it. 192 00:10:16,000 --> 00:10:18,880 In other words, there's not a financial incentive to innovate 193 00:10:18,880 --> 00:10:21,960 in learning in the same way as marketing or sales technology. 194 00:10:22,080 --> 00:10:25,680 Marketing technology advanced so rapidly because targeting and 195 00:10:25,680 --> 00:10:29,040 personalization directly translated into more sales. 196 00:10:29,320 --> 00:10:32,920 And, well, where's the ROI of helping someone learn better? 197 00:10:33,200 --> 00:10:36,680 But the problem is, is AI and I'm using that as a as a 198 00:10:36,680 --> 00:10:39,840 vernacular. OK, so you know, when I say AI, 199 00:10:39,840 --> 00:10:43,640 because I'm trying not to mention specific tools, they're 200 00:10:43,640 --> 00:10:45,200 not going to be able to break into that. 201 00:10:45,200 --> 00:10:48,120 It's not going to be in a digestible format for them and 202 00:10:48,320 --> 00:10:51,040 they're probably going to be looking for, say, the script. 203 00:10:51,040 --> 00:10:53,200 And it's really hard to keep those scripts up to date because 204 00:10:53,200 --> 00:10:55,280 anytime you make even a micro change, you've got to go back 205 00:10:55,280 --> 00:10:58,120 and update all of them, reload all that, sort of. 206 00:10:58,120 --> 00:10:59,160 Stuff. Not only are we stuck with 207 00:10:59,160 --> 00:11:04,200 SCORM, a 25 year old learning idea, but modern systems can't 208 00:11:04,200 --> 00:11:08,000 actually help us escape it because AI can't read that 209 00:11:08,000 --> 00:11:10,080 format. It's like being trapped in this 210 00:11:10,360 --> 00:11:14,400 digital time capsule. So that's the other barrier for 211 00:11:15,160 --> 00:11:17,560 content to be able to be ingested and put into 212 00:11:17,560 --> 00:11:20,960 essentially A rag that can't combines knowledge management 213 00:11:21,320 --> 00:11:24,560 and L&D content. So it's kind of like you're 214 00:11:24,560 --> 00:11:27,400 going to have L&D speaks German, but knowledge management speaks 215 00:11:27,400 --> 00:11:31,000 French and the agent only speaks or coach only speaks French. 216 00:11:31,280 --> 00:11:32,680 So we'd only be able to pull from one. 217 00:11:32,680 --> 00:11:35,200 That's kind of the kind of the analogy there. 218 00:11:35,560 --> 00:11:38,840 The irony is almost painful. We're living in an age where AI 219 00:11:38,840 --> 00:11:40,960 could transform learning experiences. 220 00:11:41,320 --> 00:11:44,520 But for AI to understand the information, it must be able to 221 00:11:44,520 --> 00:11:48,120 understand scorn, but it can't actually ingest all of that 222 00:11:48,120 --> 00:11:50,200 information and do anything with it. 223 00:11:51,240 --> 00:11:54,000 So this is the real villain of the story, a technical standard 224 00:11:54,000 --> 00:11:56,000 that's holding an industry hostage. 225 00:11:57,280 --> 00:11:59,920 Luckily, Laurie has discovered something that could change 226 00:11:59,920 --> 00:12:02,520 everything, and it came from an unexpected place. 227 00:12:02,760 --> 00:12:04,840 Now Laurie's about to tell you a story that involves airport 228 00:12:04,840 --> 00:12:08,200 vodka and a medical emergency. And while it might seem like a 229 00:12:08,200 --> 00:12:12,600 detour, the story contains the key to understanding how we have 230 00:12:12,600 --> 00:12:24,360 to be able to fix learning. So what happened was I'm afraid 231 00:12:24,360 --> 00:12:26,800 of flying. I was in North Carolina and I 232 00:12:26,800 --> 00:12:31,760 had to take a small plane and I mean small like 1212 seater type 233 00:12:31,760 --> 00:12:35,400 tiny little plane from Raleigh, NC, Toronto and there was going 234 00:12:35,400 --> 00:12:37,640 to be storms. So I was absolutely not happy. 235 00:12:37,920 --> 00:12:40,760 So don't judge me. I looked around for some place I 236 00:12:40,760 --> 00:12:43,680 could have a glass of wine. Well I was informed that there 237 00:12:43,680 --> 00:12:47,680 is actually no bar in that wing of the airport. 238 00:12:47,880 --> 00:12:51,800 So I said, well, I'll go to the duty free and I bought myself 239 00:12:51,800 --> 00:12:53,920 again, please don't judge. It was desperate times. 240 00:12:54,080 --> 00:12:56,760 I bought myself of course the leader bottle that they sell it 241 00:12:56,760 --> 00:12:58,560 duty free. They don't sell the small ones 242 00:12:58,880 --> 00:13:00,440 of vodka. And I thought, well, I'll just 243 00:13:00,440 --> 00:13:03,160 make a little drink. And the the gentleman said to 244 00:13:03,160 --> 00:13:05,480 me, we don't get this till you land. 245 00:13:05,480 --> 00:13:08,840 We can't give it to you now. It's like, So what ended up 246 00:13:08,840 --> 00:13:11,400 happening was I told the the woman at the the gate, I 247 00:13:11,400 --> 00:13:14,320 explained I'm afraid of flying. And she said, OK, look, I'm 248 00:13:14,320 --> 00:13:17,040 going to tell you as soon as the your plane lands, you're going 249 00:13:17,040 --> 00:13:19,920 to run to the other terminal, have a drink of a glass of wine 250 00:13:20,080 --> 00:13:22,480 and come back and I will get you on this plane. 251 00:13:22,480 --> 00:13:25,000 And I said, OK, fine. She goes, OK, plane landed. 252 00:13:25,000 --> 00:13:27,000 She looked at me. She's like, go, I run to the 253 00:13:27,000 --> 00:13:30,440 other terminal, run outside, go through, get a glass of wine, 254 00:13:30,600 --> 00:13:32,320 come back and I get on the plane. 255 00:13:32,440 --> 00:13:35,040 It's AI survived. Obviously it was terrible, 256 00:13:35,040 --> 00:13:36,080 right? But anyway, the point of the 257 00:13:36,080 --> 00:13:40,920 story was when I went to get off the plane, I was so tense from 258 00:13:40,920 --> 00:13:43,880 the flight that I wrenched my back and I threw my back out, 259 00:13:44,240 --> 00:13:47,560 taking out my luggage and that what they had to do was put me 260 00:13:47,560 --> 00:13:50,440 on a wheelchair and push me through the airport. 261 00:13:50,880 --> 00:13:53,280 At this point, I'm crying. My you know, my mascara is 262 00:13:53,280 --> 00:13:54,600 running. And what happened was, is the 263 00:13:54,600 --> 00:13:56,480 guy from the airplane runs up to me. 264 00:13:56,560 --> 00:13:59,840 He can smell alcohol in my breath and he hands me my leader 265 00:13:59,840 --> 00:14:03,760 size bottle of vodka and that's how I was clutching it and being 266 00:14:03,760 --> 00:14:05,080 wheeled through Toronto Pearson but. 267 00:14:05,080 --> 00:14:06,440 The story doesn't just end there. 268 00:14:06,600 --> 00:14:09,040 What happened next will completely change how Lori 269 00:14:09,040 --> 00:14:11,680 thought about learning the. Point is, is my husband then 270 00:14:11,680 --> 00:14:13,280 because I couldn't move, everything seized up. 271 00:14:13,280 --> 00:14:18,040 I had to go to the hospital and that was where I saw the the 272 00:14:18,040 --> 00:14:20,400 process that happens when you go into an A&E. 273 00:14:20,920 --> 00:14:22,920 So you weren't seen by a nurse right away. 274 00:14:22,920 --> 00:14:25,960 In fact, there was a kiosk and it asks you certain questions. 275 00:14:25,960 --> 00:14:28,080 Are you experiencing heart palpitations? 276 00:14:28,080 --> 00:14:29,920 Do you have chest pain? Are you running a fever? 277 00:14:30,040 --> 00:14:32,080 Where have you traveled? This was even pre COVID. 278 00:14:32,400 --> 00:14:34,920 It did take my blood pressure. There was a cuff that I could 279 00:14:34,920 --> 00:14:38,120 use to take my blood pressure. It asks me, are you conscious? 280 00:14:38,120 --> 00:14:40,520 I'm like clearly I am if I've done all these other things. 281 00:14:40,760 --> 00:14:43,800 But that triage was what then went to the nurse and it decided 282 00:14:43,920 --> 00:14:47,120 who got to be seen by that intake nurse first. 283 00:14:47,760 --> 00:14:50,440 Then what happened is that they looked at everybody that was 284 00:14:50,440 --> 00:14:54,400 sitting in the, the A&E and it determined who was going to go 285 00:14:54,400 --> 00:14:59,200 first based on their urgency, based on also what specialties 286 00:14:59,200 --> 00:15:01,360 doctors they had available that had time. 287 00:15:01,480 --> 00:15:03,880 You weren't seen in the order you appeared. 288 00:15:04,040 --> 00:15:08,920 You were seen according to the severity of of of your injuries 289 00:15:08,920 --> 00:15:10,800 and what need to be treated right away and what you had 290 00:15:10,800 --> 00:15:13,680 resources for. If you flip that into learning, 291 00:15:14,000 --> 00:15:17,360 what's you need to look at is that if you took all of your 292 00:15:17,360 --> 00:15:21,200 learning requests and put them in order, you're essentially 293 00:15:21,200 --> 00:15:24,320 making somebody who might be having a heart attack wait while 294 00:15:24,320 --> 00:15:26,120 somebody who maybe has a splinter. 295 00:15:26,120 --> 00:15:28,720 You don't get seen first and that's not effective. 296 00:15:28,720 --> 00:15:30,440 It's not using your resources effectly. 297 00:15:30,440 --> 00:15:33,280 It's not helping the business. This is the fundamental insight 298 00:15:33,280 --> 00:15:37,080 into how you could revolutionize workplace learning. 299 00:15:37,200 --> 00:15:40,040 Right now, most corporate learning experiences operate 300 00:15:40,040 --> 00:15:42,560 like a fast food restaurant. Everyone gets the same thing in 301 00:15:42,560 --> 00:15:45,280 the same order. But what I was if it could 302 00:15:45,640 --> 00:15:49,120 operate like an emergency room, personalized and prioritize and 303 00:15:49,120 --> 00:15:51,720 optimize for real need. But we still face that problem 304 00:15:51,720 --> 00:15:55,680 of the world of learning being built around SCORM compliance 305 00:15:55,720 --> 00:15:59,480 and having this annual planning cycle around learning that makes 306 00:15:59,480 --> 00:16:03,280 agility almost impossible. Because of the way that L&D is 307 00:16:03,280 --> 00:16:06,240 set up and typically what happens in an in a learning 308 00:16:06,240 --> 00:16:08,080 company and I'm talking about enterprise. 309 00:16:08,360 --> 00:16:11,280 So for any listeners who are, you know, working more in a 310 00:16:11,320 --> 00:16:14,400 medium sized or especially a small size, you will probably be 311 00:16:14,400 --> 00:16:16,880 a lot more agile than this because you haven't had to deal 312 00:16:16,880 --> 00:16:19,800 with, with this type of this type of structure. 313 00:16:19,920 --> 00:16:22,680 But in an enterprise company and you know that's maybe dealing 314 00:16:22,680 --> 00:16:26,480 with 50,000 employees, what they do is they set budget at the 315 00:16:26,480 --> 00:16:29,440 beginning of the year and say, OK, this is what we're going to 316 00:16:29,440 --> 00:16:31,280 build. And and I call it the bun fight. 317 00:16:31,280 --> 00:16:33,640 What happens is all the business partners come in, you sit in a 318 00:16:33,640 --> 00:16:36,880 room and everybody gives like their magic list of what they 319 00:16:36,880 --> 00:16:39,200 would like to have built that year that will help them. 320 00:16:39,800 --> 00:16:42,600 And you do this. And then the business signs off 321 00:16:42,600 --> 00:16:45,480 and says, OK, and I will give you this amount of budget and 322 00:16:45,480 --> 00:16:48,560 your performance reviews are going to be based on whether you 323 00:16:48,560 --> 00:16:51,320 hit the targets for those those numbers or whether you did not. 324 00:16:51,440 --> 00:16:54,600 Picture this playing out across the entire organization in 325 00:16:54,600 --> 00:16:55,840 January. You're having to plan what 326 00:16:55,840 --> 00:16:59,640 skills people are going to need for December, and by the time 327 00:16:59,640 --> 00:17:02,080 December arrives, those skills might be completely irrelevant 328 00:17:02,080 --> 00:17:04,640 because the world changed, but you've already spent money on 329 00:17:04,640 --> 00:17:06,599 SCORM courses. I mean, the one that I tell in 330 00:17:06,599 --> 00:17:10,880 the book was, was a, was a bank that when we just put in a 331 00:17:10,880 --> 00:17:13,720 central intake. So this would be that kiosk, you 332 00:17:13,720 --> 00:17:17,079 know, where everyone goes through that, that we had at 333 00:17:17,079 --> 00:17:19,160 A&E. We just put in a simple like 334 00:17:19,480 --> 00:17:21,920 intake form saying if you're doing anything in learning, just 335 00:17:21,920 --> 00:17:23,640 fill this out and let us know what you're working on. 336 00:17:23,880 --> 00:17:27,280 And we discovered 17 learning units because it was like a 337 00:17:27,280 --> 00:17:31,440 global financial institution. 17 units were building agile 338 00:17:31,440 --> 00:17:36,480 learning courses and the cost was astronomical. 1 was an IT 339 00:17:36,480 --> 00:17:38,920 specific version because that operates a little bit 340 00:17:38,920 --> 00:17:40,520 differently. And the other one was a general 341 00:17:40,520 --> 00:17:41,800 version that they push out from global. 342 00:17:41,800 --> 00:17:46,920 So we got rid of 15 pieces of junk and and that duplication. 343 00:17:46,920 --> 00:17:49,680 Also think about it downstream for that learner, they log into 344 00:17:49,680 --> 00:17:52,240 their learning management system, type in Agile and then 345 00:17:52,240 --> 00:17:55,680 they'll get 17 versions. They don't know which one to 346 00:17:55,680 --> 00:17:57,880 choose. It's just so. 347 00:17:57,920 --> 00:17:59,600 So we're not helping them either. 348 00:17:59,720 --> 00:18:02,240 This is what the emergency room model could do for workplace 349 00:18:02,240 --> 00:18:03,760 learning. Instead of everyone getting the 350 00:18:03,760 --> 00:18:07,640 same generic course, people get what they actually need when 351 00:18:07,640 --> 00:18:11,720 they need it delivered by the right specialist in that moment. 352 00:18:12,200 --> 00:18:14,720 But implementing that vision requires more than just changing 353 00:18:14,720 --> 00:18:17,120 processes. It requires technology and 354 00:18:17,120 --> 00:18:31,040 specifically AI. Learning is going to be most 355 00:18:31,040 --> 00:18:34,600 effective and and best when it is personalized to each 356 00:18:34,600 --> 00:18:36,680 individual. So I can't say this is the box 357 00:18:36,680 --> 00:18:38,040 that all learning should go into. 358 00:18:38,040 --> 00:18:40,040 And I think we tried to do that for a very long time. 359 00:18:41,120 --> 00:18:44,600 We made learning very static and just the same for everyone goes 360 00:18:44,600 --> 00:18:46,040 through and they click next to continue. 361 00:18:46,680 --> 00:18:49,480 What I'm looking at is really effective learning is is one 362 00:18:49,480 --> 00:18:53,080 that is hyper personalized to you what it is that it knows 363 00:18:53,080 --> 00:18:54,760 you, it knows what you're working on. 364 00:18:54,800 --> 00:18:57,240 It knows how your day has been. It knows how many meetings 365 00:18:57,240 --> 00:18:59,960 you've had it it knows what projects you're working on. 366 00:18:59,960 --> 00:19:03,400 And it brings that in contextually to to actually be 367 00:19:03,400 --> 00:19:06,400 applicable in in where you are. I think the other thing that 368 00:19:06,400 --> 00:19:11,040 good learning does is that it is looking at impact and if there 369 00:19:11,120 --> 00:19:14,360 there is no impact, it pivots the learning in ways that will 370 00:19:14,360 --> 00:19:16,720 have impact. And so it's looking at what is 371 00:19:16,720 --> 00:19:18,600 actually successful. Now, this idea of 372 00:19:18,600 --> 00:19:22,080 personalisation gets thrown around a lot, but what does it 373 00:19:22,080 --> 00:19:24,840 actually mean? What does it actually look like 374 00:19:24,840 --> 00:19:27,440 in practice? I know a lot of people don't 375 00:19:27,440 --> 00:19:30,800 like the model, but Duolingo, if you look at how they use data 376 00:19:30,920 --> 00:19:34,400 and how they use it to not only personalized, but make the 377 00:19:34,400 --> 00:19:37,640 learning stickier and better, it's quite fascinating. 378 00:19:38,160 --> 00:19:40,640 And in L&D, again, we're just giving a we're giving a static 379 00:19:40,640 --> 00:19:43,400 course. I think also too, the thing with 380 00:19:43,400 --> 00:19:48,200 good learning is that it is getting you opportunities to 381 00:19:48,280 --> 00:19:51,400 practice and reiterate and be able to connect with, say a 382 00:19:51,400 --> 00:19:53,840 virtual coach who's going to look at how you're performing 383 00:19:53,840 --> 00:19:56,600 and it's evaluating and giving you bespoke feedback. 384 00:19:56,800 --> 00:20:00,920 Not the, you know, you got that wrong, let's try again feedback, 385 00:20:00,920 --> 00:20:05,840 but like actually hyper fixated and focused on what you are 386 00:20:05,840 --> 00:20:08,800 doing and how that relates to say, a rubric that the company 387 00:20:08,800 --> 00:20:11,400 would like you to perform to. All those things together are 388 00:20:11,400 --> 00:20:13,120 what makes an important learning experience. 389 00:20:13,280 --> 00:20:15,800 Imagine learning that understands your calendar or 390 00:20:16,000 --> 00:20:18,960 your current projects and adapts to your actual work context. 391 00:20:19,120 --> 00:20:22,520 Instead of this generic course on communication skills, you get 392 00:20:22,520 --> 00:20:25,320 specific coaching on how to communicate with a difficult 393 00:20:25,320 --> 00:20:27,000 stakeholder that you're meeting tomorrow. 394 00:20:27,520 --> 00:20:31,240 This is this closed loop system that SCORM could never provide. 395 00:20:31,760 --> 00:20:35,120 Learning that doesn't just track completion, but measures actual 396 00:20:35,120 --> 00:20:37,160 behaviour change and adapts accordingly. 397 00:20:37,520 --> 00:20:40,480 But Laurie goes even further. She envisions learning that 398 00:20:40,480 --> 00:20:43,440 breaks out of the traditional course format entirely. 399 00:20:43,720 --> 00:20:48,360 So the example that I, I gave in the book was, OK, you go on to a 400 00:20:48,360 --> 00:20:51,680 learning system or an app and you do level 4 Spanish. 401 00:20:52,320 --> 00:20:55,880 What happens is, is, oh, we know that level 4 Spanish means that 402 00:20:55,880 --> 00:20:58,440 you're probably at a, a pretty good level of Spanish. 403 00:20:58,760 --> 00:21:03,240 So the next time you log into say slack or any of your, you 404 00:21:03,240 --> 00:21:06,680 know, work tools, it'll come up and say Hola, do you want to 405 00:21:06,680 --> 00:21:10,000 change your language settings to, to Spanish to give you that, 406 00:21:10,160 --> 00:21:12,920 that type of practice and hands on feeling. 407 00:21:13,480 --> 00:21:15,800 And that is a whole other learning experience. 408 00:21:15,800 --> 00:21:18,120 And then we start to see how well you're doing with that. 409 00:21:18,320 --> 00:21:21,480 And we might say, hey, we see a lot of progress. 410 00:21:21,640 --> 00:21:25,480 Do you want to be connected with this person in Colombia who's 411 00:21:25,480 --> 00:21:28,600 working on a project that's very similar to the one that we know 412 00:21:28,640 --> 00:21:32,320 you've been working on and start to get that conversation 413 00:21:32,320 --> 00:21:34,160 happening? And so now you see how I've 414 00:21:34,160 --> 00:21:36,880 taken language learning. The person is probably still 415 00:21:36,880 --> 00:21:39,840 taking their courses or their whatever Babble or Duolingo, 416 00:21:39,840 --> 00:21:41,800 whatever it is that they're taking their, their Spanish in 417 00:21:41,800 --> 00:21:43,520 and they're probably getting tutoring. 418 00:21:43,520 --> 00:21:46,600 But now we've embedded it into the way that they are actually 419 00:21:46,600 --> 00:21:49,240 working and behaving in their, their day-to-day. 420 00:21:50,040 --> 00:21:52,520 So that's the way we need to think about, think about 421 00:21:52,520 --> 00:21:55,040 learning. It's, it's not just that course. 422 00:21:55,040 --> 00:21:57,320 The course isn't going to be the same like what I would log into 423 00:21:57,320 --> 00:21:58,200 a course. It's going to be totally 424 00:21:58,200 --> 00:22:01,400 different than what you would have Jack, But it would also be, 425 00:22:01,480 --> 00:22:03,760 there is tutoring, there's feedback loops, there's 426 00:22:03,760 --> 00:22:05,640 practice. All of those things are embedded 427 00:22:05,640 --> 00:22:08,040 within it. And they're also fed to me at 428 00:22:08,040 --> 00:22:11,200 times that work with how I'm also performing in my 429 00:22:11,200 --> 00:22:12,800 day-to-day. Maybe it has access to my 430 00:22:12,800 --> 00:22:15,040 calendar. It knows from the CRM what 431 00:22:15,040 --> 00:22:18,360 customers I'm speaking to. So it feeds all that in to 432 00:22:18,360 --> 00:22:20,800 really make a learning experience that is pertinent to 433 00:22:20,800 --> 00:22:23,480 me. So I actually perceive or 434 00:22:23,480 --> 00:22:26,600 predict that you will have a learning coach. 435 00:22:26,600 --> 00:22:28,880 And I hate using learning agent because I know I'm bastardizing 436 00:22:28,880 --> 00:22:31,440 the term agent because agent really means something else 437 00:22:31,440 --> 00:22:35,840 specifically, but that you will have a AI person, let's put it 438 00:22:35,840 --> 00:22:40,480 that way, who is like your Co companion that knows everything 439 00:22:40,480 --> 00:22:43,400 that you're working on. It reads your emails, it knows 440 00:22:43,400 --> 00:22:46,680 how you're interacting. It sees around corners for you. 441 00:22:46,880 --> 00:22:50,080 It coaches you through it knows you know things that you've gone 442 00:22:50,080 --> 00:22:51,400 through things that have gone well. 443 00:22:51,400 --> 00:22:55,520 It knows your everything. And it's serving up not only 444 00:22:55,520 --> 00:22:58,160 knowledge, but a critical learning experiences that are 445 00:22:58,160 --> 00:23:00,840 mapped to the goals of the company and, and your personal 446 00:23:00,840 --> 00:23:03,080 goals that, that, that you're, you're working on. 447 00:23:04,560 --> 00:23:07,920 That's really what I see that the future being so much so that 448 00:23:08,840 --> 00:23:13,240 when it comes to skills, there, there will be an aspect of, oh, 449 00:23:13,240 --> 00:23:15,960 we know we're missing the skill we need 16 people with this 450 00:23:15,960 --> 00:23:19,000 skill. We're going to have your coach, 451 00:23:19,360 --> 00:23:22,000 you know, talk to you about this skill and see if we can nurture 452 00:23:22,000 --> 00:23:24,640 you along. It would be so, so precise. 453 00:23:24,640 --> 00:23:26,440 And of course, it'll have all the good things like that. 454 00:23:26,440 --> 00:23:29,760 That coach will embed all the good things like practice and, 455 00:23:29,800 --> 00:23:33,480 you know, feedback, But it will also be doing it in, in, in a 456 00:23:33,480 --> 00:23:36,960 way that is actually then tied to do we see outcomes? 457 00:23:37,000 --> 00:23:38,640 Do we actually see these things happening? 458 00:23:39,760 --> 00:23:43,000 If I wanted to be really honest about where I do see three years 459 00:23:43,000 --> 00:23:48,680 from now, if I get a little nervous, is does the line blur? 460 00:23:48,800 --> 00:23:50,720 You will have that in your personal life as well. 461 00:23:50,720 --> 00:23:52,920 I do believe so you will have that, that persona. 462 00:23:52,920 --> 00:23:55,320 I already have it. If you, I mean ask your whatever 463 00:23:55,360 --> 00:23:59,400 AI tool you're using, like tell me my my 3 best personality 464 00:23:59,400 --> 00:24:02,440 strengths and my three worst and it will tell you like it knows 465 00:24:02,440 --> 00:24:04,720 things about you. I predict you also have one in 466 00:24:04,720 --> 00:24:06,880 your personal life. And the question will be, I 467 00:24:06,880 --> 00:24:09,440 think companies will want to tap into that personal 1. 468 00:24:09,760 --> 00:24:12,240 And I think there's still going to be a divide. 469 00:24:12,360 --> 00:24:14,360 Here's the thing. This isn't some distant future 470 00:24:14,360 --> 00:24:16,760 vision. This technology already exists. 471 00:24:17,240 --> 00:24:19,360 Companies are already beginning to implement these kinds of 472 00:24:19,360 --> 00:24:21,120 systems and mindsets, helping them do it. 473 00:24:21,280 --> 00:24:23,280 Definitely. I mean, I'm trying not to name 474 00:24:23,720 --> 00:24:27,000 companies and, and, and brands on that, but there there's one 475 00:24:27,000 --> 00:24:29,680 in particular that I, I do absolutely adore. 476 00:24:29,960 --> 00:24:33,480 And they've really caught on to this piece of combining 477 00:24:33,720 --> 00:24:37,680 productivity knowledge management and surfacing what 478 00:24:37,680 --> 00:24:42,200 you have in, in, in L&D and really what they're measuring it 479 00:24:42,200 --> 00:24:43,800 is from a productivity standpoint. 480 00:24:43,800 --> 00:24:45,840 And they've seen massive, massive increases. 481 00:24:55,880 --> 00:24:58,960 So to conclude, the learning trap is real, but it's not 482 00:24:58,960 --> 00:25:01,680 inevitable. We're stuck with systems 483 00:25:01,680 --> 00:25:05,280 designed 25 years ago for legal compliance, not growth. 484 00:25:05,760 --> 00:25:07,440 Scorn. That technical standard that the 485 00:25:07,440 --> 00:25:11,200 majority of people never hear about, has imprisoned corporate 486 00:25:11,200 --> 00:25:14,240 learning into this world of Click next to continue. 487 00:25:14,240 --> 00:25:17,000 But the real revelation came from Laurie's emergency room 488 00:25:17,000 --> 00:25:19,160 story. Touching a bottle of vodka 489 00:25:19,160 --> 00:25:22,160 whilst being wheeled through Toronto airport, she discovered 490 00:25:22,160 --> 00:25:25,480 the solution. Triage learning should work like 491 00:25:25,640 --> 00:25:30,720 a emergency room, prioritized by need, context and optimized for 492 00:25:30,720 --> 00:25:33,840 actual impact. And the technology to fix this 493 00:25:33,840 --> 00:25:36,800 already exists. AI can create learning coaches 494 00:25:36,800 --> 00:25:40,960 that knows your work, adapts your schedule, and provides just 495 00:25:40,960 --> 00:25:43,840 in time, support and mindset. Get to work with companies on 496 00:25:43,840 --> 00:25:46,960 implementing this technology into their learning ecosystem. 497 00:25:47,000 --> 00:25:49,360 And we're even enabling people to ingest SCORM. 498 00:25:49,440 --> 00:25:51,560 Finally. This learning trap therefore is 499 00:25:51,560 --> 00:25:53,960 not permanent. People do want to learn, just 500 00:25:53,960 --> 00:25:56,960 not in a dysfunctional way. Or as Laurie says. 501 00:25:57,080 --> 00:25:59,240 People are always learning. They're learning in other ways, 502 00:25:59,240 --> 00:26:00,680 maybe ways that you just can't see. 503 00:26:00,920 --> 00:26:03,360 Anyway, that's it for today. I hope you enjoyed the episode. 504 00:26:04,280 --> 00:26:06,560 Laurie is such a fantastic speaker and if you want to 505 00:26:06,560 --> 00:26:09,360 contact her, we'll put all of her contact information in the 506 00:26:09,360 --> 00:26:11,400 description below. If you've got any comments or 507 00:26:11,400 --> 00:26:14,560 feedback, I'd love to hear it. Just drop me a message on 508 00:26:14,560 --> 00:26:18,080 whatever channel you prefer. Anyway, I'll see you next week.