1 00:00:01,200 --> 00:00:06,800 Hello, my name is Holly Owens and welcome to Ed up edtech the 2 00:00:06,800 --> 00:00:10,500 podcast that keeps you. In the know about all the latest 3 00:00:10,500 --> 00:00:14,300 edtech happenings. We interview guests from around 4 00:00:14,300 --> 00:00:17,500 the globe to give you deeper insights into the Ed tech 5 00:00:17,500 --> 00:00:21,500 industry, the field of instructional design, and more, 6 00:00:21,800 --> 00:00:25,200 we're proudly a part of America's leading podcast 7 00:00:25,200 --> 00:00:29,900 Network the Ed up, experience. It's time to sit back and enjoy. 8 00:00:30,000 --> 00:00:33,000 Enjoy the latest episode of Ed up attack. 9 00:00:39,300 --> 00:00:43,900 Hello and welcome to the first collaborative podcast of the Ed 10 00:00:43,900 --> 00:00:48,000 up, AI podcast and the Ed up. Ed Tech podcast with Holly 11 00:00:48,000 --> 00:00:50,700 Owens. And our guest today that we're 12 00:00:50,700 --> 00:00:53,000 going to be talking to and interviewing and learning 13 00:00:53,000 --> 00:00:56,300 everything about in terms of AI and everything else is Eric. 14 00:00:56,300 --> 00:00:59,500 James Stevens. Iarc welcome. 15 00:00:59,700 --> 00:01:01,800 Thank you, both, for having me here. 16 00:01:01,800 --> 00:01:04,000 I am very excited to have this conversation with you because 17 00:01:04,000 --> 00:01:07,000 this is just cool stuff. Absolutely, it's going to be 18 00:01:07,000 --> 00:01:09,600 fun. I'm super Sighted. 19 00:01:09,800 --> 00:01:14,800 And I can jump in with the first question Eric and you can feel 20 00:01:14,800 --> 00:01:18,100 free to address it how you want and work in what you're doing 21 00:01:18,100 --> 00:01:20,800 right now and everything else. Cuz I know that right now, you 22 00:01:20,800 --> 00:01:24,900 have your own daily job that you're doing full time and then 23 00:01:24,900 --> 00:01:29,300 you're also starting something and are and an entrepreneur for 24 00:01:29,300 --> 00:01:32,100 rhizome. So how would you describe what 25 00:01:32,100 --> 00:01:36,900 you're doing at your they job with AI and then also with that 26 00:01:36,900 --> 00:01:40,700 other projects, okay? I like that question the job 27 00:01:40,700 --> 00:01:42,900 that I have. Now, I'm a business intelligence 28 00:01:42,900 --> 00:01:48,400 developer working with power bi. And so this is a company that 29 00:01:48,400 --> 00:01:51,800 construction company that's been around for over 100 years but 30 00:01:51,800 --> 00:01:54,000 now they're asking themselves, like, what can we learn from our 31 00:01:54,000 --> 00:01:57,100 data? And that's where I love to be 32 00:01:57,100 --> 00:02:00,100 in. Love to work is figuring out 33 00:02:00,300 --> 00:02:02,100 complex problems. What's that? 34 00:02:02,100 --> 00:02:04,800 A lot of fun? I've had chat gbt open the whole 35 00:02:04,800 --> 00:02:08,699 time asking like what does this mean in this environment or I 36 00:02:08,699 --> 00:02:10,199 used? Do this at Tableau. 37 00:02:10,500 --> 00:02:12,000 How do I do it? Power bi. 38 00:02:12,300 --> 00:02:14,500 And it will tell me the different calculations that I 39 00:02:14,500 --> 00:02:16,700 need. It's been a lot of fun, but 40 00:02:16,700 --> 00:02:19,300 that's not why we're here, we're here because we're talking about 41 00:02:19,400 --> 00:02:22,400 Ai and star. I am working on the sting of 42 00:02:22,400 --> 00:02:27,700 called project rise up and I am building an AI powered teaching. 43 00:02:28,000 --> 00:02:33,100 I believe that one of the biggest things that teachers 44 00:02:33,100 --> 00:02:36,900 need back in their lives is time and one of the biggest time 45 00:02:36,900 --> 00:02:40,200 constraints that they have is the S of grading writing 46 00:02:40,200 --> 00:02:43,100 specifically. I want to be able to create 47 00:02:43,100 --> 00:02:47,900 something that helps teachers. Do that task better and faster. 48 00:02:47,900 --> 00:02:51,800 In a way that students also learn how to write better than 49 00:02:51,800 --> 00:02:57,300 they are right now as someone who has been thinking about and 50 00:02:57,300 --> 00:02:59,500 writing about the ethical use of Big Data. 51 00:02:59,500 --> 00:03:05,100 Since 2016, I feel like I I cannot. 52 00:03:06,500 --> 00:03:08,600 Watch someone else build something. 53 00:03:09,400 --> 00:03:12,700 And then critique it, if I was an academic, that still what I 54 00:03:12,708 --> 00:03:15,200 would be doing is I wouldn't have a saying but now that I 55 00:03:15,208 --> 00:03:18,200 know how to do data and now that I know about these different 56 00:03:18,200 --> 00:03:21,500 things I want to be able to be the one to build it to be able 57 00:03:21,500 --> 00:03:24,500 to say, hey let's bring in a variety of people. 58 00:03:24,500 --> 00:03:27,500 Let's do these different things. At this first phase of product, 59 00:03:27,500 --> 00:03:32,300 rhizome that were talking about is a Grassroots data collection 60 00:03:32,300 --> 00:03:36,100 for student essays. I want to create an AI that can 61 00:03:36,300 --> 00:03:42,400 Assess student writing, I fundamentally, I'm against using 62 00:03:42,400 --> 00:03:46,100 data that's been scraped or bopped from the web or from a 63 00:03:46,108 --> 00:03:49,700 University universities can sell writing from their students. 64 00:03:49,700 --> 00:03:51,200 I don't think that's a good thing. 65 00:03:51,300 --> 00:03:54,500 I don't think people know a lot about that, they don't assume 66 00:03:54,500 --> 00:03:58,300 that and that's totally true. That's definitely a need to 67 00:03:58,300 --> 00:04:01,600 know. It is idea who owns an essay, so 68 00:04:01,600 --> 00:04:05,100 I believe that the person who wrote it, owns it and I want to 69 00:04:05,100 --> 00:04:08,100 collect it from them. I applied to this idea, 70 00:04:08,100 --> 00:04:10,500 accelerator called Builders and backers, and they're being 71 00:04:10,500 --> 00:04:12,900 funded by Heartland forward. Either be amazing people. 72 00:04:12,900 --> 00:04:15,600 Take you so much all those people, but they gave me five 73 00:04:15,600 --> 00:04:19,000 thousand dollars in order to conduct an experiment. 74 00:04:19,200 --> 00:04:23,300 Other people are hiring coders to build things or their bill 75 00:04:23,300 --> 00:04:25,600 buying product. I wanted to give that five 76 00:04:25,600 --> 00:04:28,900 thousand dollars away. I'm giving away five thousand 77 00:04:28,900 --> 00:04:32,200 dollars to ten different people, 10 people get 500 bucks. 78 00:04:32,200 --> 00:04:35,200 I already gave away one person hurting semper, she's awesome. 79 00:04:35,200 --> 00:04:38,400 Gave her 500 bucks last weekend and this weekend I'm giving away 80 00:04:38,400 --> 00:04:42,600 to someone else $500. I am asking people to post about 81 00:04:42,600 --> 00:04:43,700 it. I'm trying to share it. 82 00:04:43,800 --> 00:04:46,700 I'd convinced my kids to pass out flyers with me. 83 00:04:46,700 --> 00:04:49,700 Last night, I went over to, I went to the University of Tulsa 84 00:04:49,700 --> 00:04:53,800 and we did break into library, but we found somebody to let us 85 00:04:53,800 --> 00:04:56,100 into the library. We just surpassed out flyers to 86 00:04:56,100 --> 00:05:02,500 people because I want this aai and not be an individual person 87 00:05:02,500 --> 00:05:05,500 building, it has to be a collaboration and it has to be 88 00:05:05,500 --> 00:05:08,700 done on ethically sourced data and that's what I wanted. 89 00:05:09,900 --> 00:05:12,600 Well, this sounds amazing. I'm so glad that were partnering 90 00:05:12,600 --> 00:05:17,400 for this episode because this is totally Ed up at Tech jam 91 00:05:17,400 --> 00:05:20,900 without Eric this journey, I know you boast three episodes 92 00:05:20,900 --> 00:05:23,700 and then add as they'll walk. But now I'd it's back up and 93 00:05:23,700 --> 00:05:26,200 going I can't not. Isn't that what we talked about 94 00:05:26,200 --> 00:05:28,900 when we were talking with Linda? E is how that's how it works 95 00:05:28,900 --> 00:05:31,600 though. You stop it and then you go back 96 00:05:31,600 --> 00:05:33,000 to and you go back to the drawing board. 97 00:05:33,000 --> 00:05:37,300 So we're glad you're back. You're back at this spot here. 98 00:05:37,300 --> 00:05:41,600 Tell us about more about what people can do to help you 99 00:05:41,600 --> 00:05:44,400 collect this data. The you mentioned, the 5,000, 100 00:05:44,400 --> 00:05:46,700 and the 500. And obviously, we'll put 101 00:05:46,700 --> 00:05:48,900 everything in the show notes if you're interested in 102 00:05:48,900 --> 00:05:52,000 contributing to Eric and the data that he is collecting. 103 00:05:52,300 --> 00:05:56,300 So, tell us a little bit more about that situation right now. 104 00:05:56,300 --> 00:06:01,000 There are really Things that people can do to really help 105 00:06:01,000 --> 00:06:04,600 build one is the actual like helping collection of essays. 106 00:06:04,600 --> 00:06:07,500 So if you have essays submit them and I'm not I don't just 107 00:06:07,500 --> 00:06:10,600 need them from current students. I'm about to get my perspective 108 00:06:10,600 --> 00:06:12,500 on my dissertation. Exactly. 109 00:06:12,500 --> 00:06:15,400 So it's between 3 and 15 pages, right? 110 00:06:15,400 --> 00:06:17,500 But it could be for any discipline, right? 111 00:06:17,500 --> 00:06:20,500 Because and the reason that it's called rise own as this is 112 00:06:20,900 --> 00:06:24,800 because I believe like writing is a rhizomatic thing. 113 00:06:25,400 --> 00:06:27,400 A rhizome is something that grows nebula. 114 00:06:27,500 --> 00:06:29,600 Ashley, there's no single point of origin. 115 00:06:30,000 --> 00:06:32,000 Writing has no single point of origin. 116 00:06:32,000 --> 00:06:37,900 There is an every discipline is infested with this writing 117 00:06:38,000 --> 00:06:40,300 thing, any writing from any class. 118 00:06:40,600 --> 00:06:44,400 I will take because I believe fundamentally that what makes a 119 00:06:44,407 --> 00:06:48,000 good transition in a history class is a good transition in a 120 00:06:48,000 --> 00:06:51,100 biology class, anybody who's selling something otherwise is 121 00:06:51,100 --> 00:06:54,700 selling you something. That was fun of it. 122 00:06:55,200 --> 00:06:58,700 But so there's the one there's actually like collecting data or 123 00:06:58,700 --> 00:07:01,500 collecting assays. I'm a this I'm hoping to 124 00:07:01,500 --> 00:07:04,900 graduate students are hearing me well, except their writing and 125 00:07:04,900 --> 00:07:06,500 I'll accept their students writing. 126 00:07:06,500 --> 00:07:10,300 They have the other thing is that I'm collaborating with the 127 00:07:10,300 --> 00:07:13,600 Ed up experience as a whole with joy Holden and we're doing a 128 00:07:13,608 --> 00:07:17,400 state of student writing survey where professionals like 129 00:07:17,400 --> 00:07:20,700 yourselves education leaders teachers can go out and share 130 00:07:20,700 --> 00:07:23,800 their opinions about what they feel on the state of Writing. 131 00:07:24,100 --> 00:07:25,800 We're going to take those results, are going to publish a 132 00:07:25,800 --> 00:07:27,400 white paper and that's going to be fun. 133 00:07:28,000 --> 00:07:31,700 The Third Way that people can help is by signing up to learn 134 00:07:31,700 --> 00:07:35,200 more. This next phase right now is 135 00:07:35,500 --> 00:07:40,800 phase one that's getting my data base to is training my data. 136 00:07:41,200 --> 00:07:43,900 Now I'm going to be sitting by myself, reading whole bunch of 137 00:07:43,900 --> 00:07:47,300 sentences and Grading and training an algorithm about how 138 00:07:47,300 --> 00:07:50,200 would Eric rate of paper. Or I'm not even going to find a 139 00:07:50,207 --> 00:07:52,800 team of five people. And I'm so we could say like, 140 00:07:52,800 --> 00:07:55,600 how would this group of five people read these essays? 141 00:07:56,200 --> 00:07:59,600 I'm going to use a crowdsource model where people can log-in. 142 00:07:59,600 --> 00:08:02,500 I could vet there, I can make sure they have credentials and 143 00:08:02,500 --> 00:08:05,800 they should be assessing essays. And then I'll give them, they'll 144 00:08:05,800 --> 00:08:09,700 be able to enter into this platform and be able to help me 145 00:08:09,700 --> 00:08:12,200 train my sentences. I'll give them a sentence. 146 00:08:12,200 --> 00:08:14,200 I'll ask them a question. Be like, Mark, this? 147 00:08:14,200 --> 00:08:15,700 How, what do you feel about this? 148 00:08:16,000 --> 00:08:20,700 And tell me why, and then my goal is essentially every single 149 00:08:20,700 --> 00:08:25,300 essay that I get is going to be Greg graded and red based 150 00:08:25,300 --> 00:08:28,400 against a rubric criteria, right? 151 00:08:28,500 --> 00:08:32,200 And as a as an instructor, I love that so much, right? 152 00:08:32,200 --> 00:08:37,500 And he singled I say understanding each criteria is 153 00:08:37,500 --> 00:08:40,600 going to be great at twice, double blind peer review. 154 00:08:41,400 --> 00:08:43,900 I have like, when you look at the, I'd like the question. 155 00:08:44,100 --> 00:08:46,300 Does this paper have a good transition? 156 00:08:47,200 --> 00:08:51,300 That question is probably 15 different questions about 157 00:08:51,300 --> 00:08:54,100 transitions that you as an individual. 158 00:08:54,100 --> 00:08:58,600 Do not have the time to ask every single paper. 159 00:08:59,700 --> 00:09:01,800 I can train an algorithm to do that. 160 00:09:01,900 --> 00:09:05,100 Let's say that my Final count is 20 criteria. 161 00:09:05,500 --> 00:09:10,100 That means that every sentence from every submission that I get 162 00:09:10,300 --> 00:09:15,900 will be read 40 times. And that's the data that were 163 00:09:15,900 --> 00:09:18,500 feeding the, that's why is a large language model? 164 00:09:18,700 --> 00:09:23,200 That's why it's big data is because we're creating metadata, 165 00:09:23,500 --> 00:09:27,000 my contention, is that the number one problem with all 166 00:09:27,600 --> 00:09:31,300 artificial intelligence at out there today is not the 167 00:09:31,300 --> 00:09:34,400 algorithm. It's the quality of data that 168 00:09:34,400 --> 00:09:36,800 they're using. That's what I want to address 169 00:09:36,800 --> 00:09:40,000 fundamentally. I'm going to need help creating 170 00:09:40,100 --> 00:09:43,900 all of that data so you can sign up and help me do that. 171 00:09:44,100 --> 00:09:46,700 That comes, you can create an account and Le box score boards 172 00:09:46,700 --> 00:09:48,500 and stuff, and that leadership boards will be fun. 173 00:09:49,100 --> 00:09:51,100 Yeah, that will be fun gamified a bit. 174 00:09:51,100 --> 00:09:53,200 Make some competition out of it, I love it. 175 00:09:53,400 --> 00:09:56,200 Exactly. Not my brain is going a thousand 176 00:09:56,200 --> 00:09:58,200 different directions. Every time we chat, that's what 177 00:09:58,200 --> 00:09:59,700 happens. But that's a good thing. 178 00:09:59,900 --> 00:10:04,000 I'm thinking about, in terms of AI has become everybody's an 179 00:10:04,000 --> 00:10:06,500 expert right now, and it's very new. 180 00:10:06,500 --> 00:10:11,200 It's a very new frontier. So as you are embracing this 181 00:10:11,200 --> 00:10:15,800 entrepreneurship into the AI space, how How are you dealing 182 00:10:15,800 --> 00:10:17,400 with that? And like your life and 183 00:10:17,400 --> 00:10:19,600 navigating? All these are people, like I 184 00:10:19,600 --> 00:10:22,500 know this and a eyes bad here because New York City public 185 00:10:22,500 --> 00:10:25,300 schools has already banned. It's not allowed there or 186 00:10:25,300 --> 00:10:27,400 institutions of are abandoned. How are you? 187 00:10:27,600 --> 00:10:30,500 Navigating that space? As you're stepping into this 188 00:10:30,500 --> 00:10:36,100 entrepreneur a journey I think part of it is recognizing when 189 00:10:36,100 --> 00:10:40,200 to step I mean in early January I was reaching out to Jason. 190 00:10:40,200 --> 00:10:42,800 We were talking about fuss do a series of different things and I 191 00:10:42,808 --> 00:10:46,200 was like, okay this to me I was Ramping up because I like to be 192 00:10:46,200 --> 00:10:48,400 a voice. I like to be on the stage and I 193 00:10:48,400 --> 00:10:50,600 just saw exactly what you mentioned. 194 00:10:52,000 --> 00:10:57,700 Is that this is just going so fast and so, there's so much. 195 00:10:58,300 --> 00:11:02,400 You cannot be an expert. I think the only true experts on 196 00:11:02,400 --> 00:11:06,100 AI that exist, are the experts that were talking about AI 197 00:11:06,200 --> 00:11:09,200 before November 20, 20? Those are the people that we 198 00:11:09,200 --> 00:11:11,300 should really be thinking were attempted to. 199 00:11:11,600 --> 00:11:15,600 But here's what I think, the reason that there are so many 200 00:11:15,600 --> 00:11:23,200 experts in AI, Is because so many experts exist, an AI just 201 00:11:23,200 --> 00:11:28,900 makes an expert better. A lawyer, who knows how to use 202 00:11:28,900 --> 00:11:33,800 chat, GPT is not really going to do well, teaching a marketing 203 00:11:34,100 --> 00:11:37,900 person or marketer how to use chat CPT for her skills. 204 00:11:38,500 --> 00:11:41,100 Right? A car mechanic is going to use 205 00:11:41,100 --> 00:11:43,600 chap TP differently than a doctor. 206 00:11:44,200 --> 00:11:47,300 But the point is it that this is The Equalizer. 207 00:11:47,700 --> 00:11:52,200 We are giving everybody Access to information at your 208 00:11:52,200 --> 00:11:54,700 fingertips. As rather than going in trying 209 00:11:54,700 --> 00:11:58,400 to compete, what everybody else is doing, I just want to go and 210 00:11:58,400 --> 00:12:03,400 support what everybody else is doing knowing confidently. 211 00:12:04,500 --> 00:12:06,600 That there is no one else that is going to build what I'm 212 00:12:06,600 --> 00:12:10,800 building is everybody else is worrying about algorithms and 213 00:12:10,800 --> 00:12:19,700 I'm focusing on data. That's awesome and I don't know 214 00:12:19,900 --> 00:12:22,800 I want to ask this question. Algorithms are so important 215 00:12:22,800 --> 00:12:24,700 especially on social media sites. 216 00:12:24,700 --> 00:12:26,400 I'm going to hold back on that one real quick. 217 00:12:26,400 --> 00:12:29,200 I'll let Jason Jump in, I'm going to hold back on the 218 00:12:29,200 --> 00:12:31,700 algorithm question, the vs the data. 219 00:12:31,700 --> 00:12:35,800 So Jason, you'd pop in here. I definitely want to come to 220 00:12:35,800 --> 00:12:38,400 that and there are go with dings. 221 00:12:38,600 --> 00:12:42,400 So as you were talking Eric, I had these clusters in my mind 222 00:12:42,400 --> 00:12:45,100 that I was creating as you were walking you through. 223 00:12:45,200 --> 00:12:49,900 Through a project rhizome is actually doing the first cluster 224 00:12:49,900 --> 00:12:53,300 is how your project is a microcosm. 225 00:12:53,300 --> 00:12:57,300 In many ways of a lot of the issues and concerns and Concepts 226 00:12:57,400 --> 00:13:00,600 that were thinking about with a. I when we think about 227 00:13:00,600 --> 00:13:08,400 transparency and ethics and who is managing knowledge bases. 228 00:13:08,400 --> 00:13:12,900 If we go into chat gvt, sometimes it's really hard to 229 00:13:12,900 --> 00:13:15,100 figure out where that knowledge is coming. 230 00:13:15,300 --> 00:13:19,200 In from and who's controlling that data or sourcing that data, 231 00:13:19,500 --> 00:13:21,100 I think you got to change as we go forward. 232 00:13:21,100 --> 00:13:28,300 But it's always been a question built into the use of AI and the 233 00:13:28,300 --> 00:13:31,000 other concept that you brought out is you're talking about 234 00:13:31,000 --> 00:13:33,700 project. Rhizome is social building, 235 00:13:34,000 --> 00:13:36,500 right? And really creating in public 236 00:13:36,500 --> 00:13:41,100 and using people, and I think associated with that connected 237 00:13:41,100 --> 00:13:45,100 to that is this question of what happens to the expert. 238 00:13:45,200 --> 00:13:48,900 But in the age of a, I think there's a lot of anxiety about 239 00:13:48,900 --> 00:13:53,400 that and I was literally reading a book titled, the new laws of 240 00:13:53,400 --> 00:13:59,500 robotics by Frank Pasquale, and that's what he talks about. 241 00:13:59,500 --> 00:14:03,100 His argument is actually that AI makes the expert more valuable, 242 00:14:03,300 --> 00:14:08,700 but actually gives them more value, socially culturally, and 243 00:14:08,800 --> 00:14:12,100 hopefully economically. That's one of the con clusters 244 00:14:12,300 --> 00:14:15,800 that I started to create out of your talking, the other Idea 245 00:14:15,800 --> 00:14:18,300 that you brought up, which really spoke to me. 246 00:14:18,300 --> 00:14:20,700 Personally, I know, Holly is someone who teaches all the 247 00:14:20,700 --> 00:14:23,000 time, just like Lee spoke to you, too. 248 00:14:23,200 --> 00:14:28,900 It's just how much time you can save and how you can repurpose 249 00:14:28,900 --> 00:14:32,800 or time to do, very high impact things. 250 00:14:32,800 --> 00:14:36,800 For my perspective, that is fundamentally true. 251 00:14:37,100 --> 00:14:42,500 It used to take me four hours to create a personalized rubric for 252 00:14:42,500 --> 00:14:45,100 class. It now takes me four minutes. 253 00:14:45,200 --> 00:14:48,100 It's it. You turn take me and I minute of 254 00:14:48,100 --> 00:14:51,600 it. Yeah. 15 minutes to write 255 00:14:51,600 --> 00:14:53,700 student feedback and everything else. 256 00:14:53,800 --> 00:14:57,500 It now takes me about a minute and a half, right? 257 00:14:57,500 --> 00:15:01,200 Editing, a podcast. Used to take me two hours. 258 00:15:01,400 --> 00:15:06,500 It now takes me eight minutes. That's like that were, that's 259 00:15:06,500 --> 00:15:08,100 what we're talking about. That's why we're talking about 260 00:15:08,100 --> 00:15:11,800 the level of time-saving. And so, a project, like project 261 00:15:11,800 --> 00:15:14,900 rhizome, at least for me is a model. 262 00:15:15,200 --> 00:15:18,800 Others can use for how you can ethically sourced data and be 263 00:15:18,808 --> 00:15:21,800 transparent about where it's coming from and all of that. 264 00:15:21,800 --> 00:15:25,100 I want to follow this up with a question about project dry Zone 265 00:15:25,400 --> 00:15:29,700 and I think it's connected to a lot of those Concepts that you 266 00:15:29,700 --> 00:15:32,800 brought up, but then also your focus on assessment. 267 00:15:33,500 --> 00:15:39,500 So how personalizable is it? Because you mentioned using data 268 00:15:39,600 --> 00:15:42,400 from different disciplines different levels. 269 00:15:42,500 --> 00:15:45,000 So is their way, the project rhizome. 270 00:15:45,200 --> 00:15:49,400 Um would be targeting that feedback for a student of a 271 00:15:49,408 --> 00:15:51,700 particular skill level say, they're still struggling with 272 00:15:51,700 --> 00:15:54,300 something, it's not a student who's say a freshman in college 273 00:15:54,300 --> 00:15:58,600 versus a senior in college. Is that feedback tailored or how 274 00:15:58,600 --> 00:16:01,200 it was that working in terms of your individual project? 275 00:16:02,100 --> 00:16:05,700 Yeah. So I'll say this, one thing to, 276 00:16:05,700 --> 00:16:11,400 I think that the way that you described How you heard these 277 00:16:11,400 --> 00:16:14,100 different themes. And talking about clustering is 278 00:16:14,100 --> 00:16:16,900 exactly why artificial intelligence is intelligence and 279 00:16:16,900 --> 00:16:18,900 human life. Because that is what artificial 280 00:16:18,900 --> 00:16:21,200 intelligence does. It looks at a whole bunch of 281 00:16:21,200 --> 00:16:25,400 content and then it clusters it by topic and then predicts based 282 00:16:25,400 --> 00:16:28,300 on that clustering, what it should say that is the exact 283 00:16:28,300 --> 00:16:31,400 same thought process it. That is why it's called a neural 284 00:16:31,500 --> 00:16:33,900 network. It's mimicking neurons and so 285 00:16:33,900 --> 00:16:35,500 that's just a really cool thing for me. 286 00:16:35,700 --> 00:16:38,900 I'm glad that you did that to address your question, one of 287 00:16:38,900 --> 00:16:41,400 the data points. That I'm collecting is the 288 00:16:41,400 --> 00:16:44,000 level. So I'm accepting writing from 289 00:16:44,000 --> 00:16:48,000 any discipline when a user goes in and submits their writing I'm 290 00:16:48,000 --> 00:16:51,300 asking them a whole bunch of questions about their writing so 291 00:16:51,300 --> 00:16:55,100 that I can then tabulated that and find Trends and patterns 292 00:16:55,100 --> 00:16:57,300 later. So one of those questions is 293 00:16:57,700 --> 00:17:00,300 what is the name of the class? Is this, a history class is a 294 00:17:00,300 --> 00:17:01,800 biology class that kind of thing? 295 00:17:02,100 --> 00:17:03,900 The other one is at what level is it is. 296 00:17:03,908 --> 00:17:08,099 I'm accepting 9th grade writing through doctoral level writing, 297 00:17:08,200 --> 00:17:12,200 like through post-grad because So I believe this fundamentally 298 00:17:13,000 --> 00:17:17,300 that the core principles of a writing class and a postdoc is 299 00:17:17,300 --> 00:17:19,500 the exact same lesson plan. You're going to get in 9th 300 00:17:19,500 --> 00:17:22,200 grade. They're the same thing just the 301 00:17:22,200 --> 00:17:26,500 complexity changes but the core principles are what writing is 302 00:17:26,800 --> 00:17:29,800 stays the same? That's why writing is a meta 303 00:17:29,800 --> 00:17:33,900 discipline when we get to phase 3 or 4 when we get to the stage 304 00:17:33,900 --> 00:17:36,600 of developing the personalized feedback and probably tapping 305 00:17:36,600 --> 00:17:39,400 some like other large language models. 306 00:17:39,600 --> 00:17:42,500 Do that makes it sound better like chatty PT or something. 307 00:17:43,000 --> 00:17:46,600 But being able to say, okay, like what, how would you model 308 00:17:46,600 --> 00:17:51,000 this feedback if the student was in ninth grade versus in 309 00:17:51,000 --> 00:17:52,500 postdoctoral? They might be a bike, not be 310 00:17:52,500 --> 00:17:54,900 able to bit more short with them, over to the point. 311 00:17:55,600 --> 00:18:00,400 The, because we're collecting this data about the writing 312 00:18:00,400 --> 00:18:05,000 itself, will be able to find patterns, we will be able to 313 00:18:05,000 --> 00:18:09,400 bike me said before, ask AI to see what clusters exist. 314 00:18:09,500 --> 00:18:12,800 So that we may not see right there may be other clusters or 315 00:18:12,800 --> 00:18:15,300 themes and what I said but we didn't see them because we're 316 00:18:15,300 --> 00:18:17,800 not artificial intelligent and looking at everything over time. 317 00:18:19,300 --> 00:18:24,800 That's why Collecting the data is so important. 318 00:18:25,400 --> 00:18:29,400 One of the largest data models are one of the largest data sets 319 00:18:29,400 --> 00:18:31,700 that a lot of these large language models are being 320 00:18:32,000 --> 00:18:36,400 trained on are from high school essays written for the SATs, you 321 00:18:36,400 --> 00:18:40,100 can actually go and find a spout database of twelve to fourteen 322 00:18:40,100 --> 00:18:44,100 thousand student, written essays by the reason chat T.T like 323 00:18:44,100 --> 00:18:47,300 gives you a standard five paragraph essay. 324 00:18:47,800 --> 00:18:50,500 When you just type in a regular question is because it was 325 00:18:50,500 --> 00:18:53,700 trained. On high school, 5, paragraph 326 00:18:53,700 --> 00:18:56,100 essays. And they were being trained and 327 00:18:56,100 --> 00:19:00,500 graded by people who preferred long-winded writing. 328 00:19:01,800 --> 00:19:06,500 So the reason chat Jiggy T is for boasts, is because of the 329 00:19:06,500 --> 00:19:12,300 data and the metadata about it. I don't believe this might be 330 00:19:12,300 --> 00:19:13,900 getting on a tangent now. Right? 331 00:19:14,100 --> 00:19:17,000 I don't think that the solution to our problems is to embed 332 00:19:17,000 --> 00:19:19,700 English 101 into a biology class. 333 00:19:20,800 --> 00:19:24,400 I don't think English 101, is a good practice of writing because 334 00:19:24,400 --> 00:19:26,800 when you get to the business world, you're taught how to be 335 00:19:26,800 --> 00:19:29,900 more concise like you're taught to be using. 336 00:19:29,900 --> 00:19:31,800 What's called plain language, right? 337 00:19:31,800 --> 00:19:34,300 So there's the Obama passed, the plain language act 2010. 338 00:19:35,800 --> 00:19:37,900 That's what I want to embed, right? 339 00:19:37,900 --> 00:19:40,900 I was talking to people who teaching mbas and they say one 340 00:19:40,900 --> 00:19:42,900 of their biggest things that teaching their students, how to 341 00:19:42,900 --> 00:19:45,800 write less be more concise, tours, it better. 342 00:19:46,400 --> 00:19:48,800 And that's what how we train chat, Chiquitita, better Outlook 343 00:19:48,800 --> 00:19:51,700 to make this answer shorter. It's like when off on a big 344 00:19:51,700 --> 00:19:55,500 tangent there but your answer to that question. 345 00:19:56,000 --> 00:19:59,400 Bay's two or three there's going to be that personalized level of 346 00:19:59,400 --> 00:20:03,600 feedback based on a discipline and based on level. 347 00:20:04,100 --> 00:20:08,500 But rather than Starting with that discipline or that level 348 00:20:08,500 --> 00:20:10,200 and saying this is how each sound. 349 00:20:10,700 --> 00:20:14,700 We're asking the data first how it should sound, so reacting to 350 00:20:14,708 --> 00:20:17,900 the data and not coming in with our own biases and begin. 351 00:20:19,500 --> 00:20:23,600 And I like it. So, I was going to ask, there's 352 00:20:23,600 --> 00:20:28,000 a lot of pushback about this, like using this AI stuff and 353 00:20:28,500 --> 00:20:31,500 obviously not in this room, we're all just, let's do it. 354 00:20:31,500 --> 00:20:33,600 Let's use it. Let's have fun with it. 355 00:20:33,600 --> 00:20:36,200 Let's see what we're doing. How would you approach the 356 00:20:36,200 --> 00:20:38,600 situation of the people who are already resisting? 357 00:20:38,600 --> 00:20:43,200 This sort of situation where students writing is going to be 358 00:20:43,700 --> 00:20:45,500 filtered through a system and then they're going to get 359 00:20:45,500 --> 00:20:48,200 feedback. How would you deal with the 360 00:20:48,200 --> 00:20:51,300 reserve resistant? That is on the rise again. 361 00:20:51,400 --> 00:20:54,900 Again, with technology in this new innovation with AI in chat 362 00:20:54,900 --> 00:20:59,000 GPT, how would you approach that in the seat that you're in right 363 00:20:59,000 --> 00:21:01,800 now and deal with that? That's a loaded question. 364 00:21:01,800 --> 00:21:06,000 By the way, back in the day, back in the day, couple thousand 365 00:21:06,000 --> 00:21:12,200 years ago, Leto was a ranting and raving right about the 366 00:21:12,200 --> 00:21:16,600 creation of a new technology that would ruin thinking. 367 00:21:17,900 --> 00:21:19,500 He was talking about the alphabet. 368 00:21:26,000 --> 00:21:29,400 Every single time, something new happens. 369 00:21:30,800 --> 00:21:35,700 People will not like it and they'll disagree with it. 370 00:21:36,400 --> 00:21:40,300 And I think that has far more to do with one's experience in life 371 00:21:40,300 --> 00:21:43,300 and where they are in life and how much they're willing to 372 00:21:43,300 --> 00:21:45,800 learn something new versus not new. 373 00:21:47,100 --> 00:21:50,800 That determines that. So when I encounter someone 374 00:21:50,800 --> 00:21:54,900 who's I'm not gonna do that, my response is okay. 375 00:21:56,500 --> 00:21:58,500 I'll see you in five years. When you shout like, they're 376 00:21:58,500 --> 00:22:02,800 gonna, I know that because I have already seen this actively 377 00:22:03,500 --> 00:22:08,400 happening where I have a friend, he's a CEO of a company and he 378 00:22:08,400 --> 00:22:12,300 hires people, and before he would hire a teachers to create 379 00:22:12,300 --> 00:22:18,000 content for him now, he hires one teacher that uses chat GPT 380 00:22:18,200 --> 00:22:25,000 to create content for him. The people who are saying this 381 00:22:25,000 --> 00:22:27,000 is not something I need to worry about. 382 00:22:28,000 --> 00:22:32,800 Do not understand how fundamentally intertwined their 383 00:22:32,800 --> 00:22:37,300 lives, already are with AI and how they are going to be 384 00:22:37,300 --> 00:22:40,800 intertwined with a, I just in the product of sweets with 385 00:22:40,800 --> 00:22:45,000 Microsoft and Google that now hat, their copilot, and they're 386 00:22:45,000 --> 00:22:48,600 barred embedded in. Whatever we got, call it you 387 00:22:48,600 --> 00:22:55,700 cannot Escape it and if you're actively resisting it, You are 388 00:22:55,800 --> 00:22:58,700 actively putting yourself at risk. 389 00:22:59,000 --> 00:23:01,900 I am a huge fan like you need to be an early adopter. 390 00:23:03,000 --> 00:23:06,000 If only to be asking those heart, ethical questions to be 391 00:23:06,000 --> 00:23:07,800 getting. So you're not dealing with 392 00:23:07,800 --> 00:23:09,800 changing a procedures. Number of be the one to 393 00:23:09,800 --> 00:23:12,600 implement the change. Not the one that has to deal 394 00:23:12,600 --> 00:23:16,400 with someone else, child me to change and so I guess that I 395 00:23:16,400 --> 00:23:19,500 think there's always reason to be cautious, but I think that 396 00:23:20,600 --> 00:23:24,200 we're all good crap that we talk about our age demographic of 397 00:23:24,200 --> 00:23:26,900 everything that we've I've lived through like we can go through a 398 00:23:26,908 --> 00:23:30,100 lot like Wars and teres attachment so many things. 399 00:23:32,600 --> 00:23:38,500 Holy moly. We are living through a modern 400 00:23:38,500 --> 00:23:42,500 Industrial Revolution that is happening. 10 times as fast 401 00:23:42,500 --> 00:23:45,600 where you can see daily change instead of monthly or yearly 402 00:23:45,600 --> 00:23:49,100 change, we're going to seize bit out of like an update. 403 00:23:49,200 --> 00:23:52,000 You don't have to say, it's got to be in the SAS and it's got a 404 00:23:52,008 --> 00:23:55,400 spit out an update. Yeah, it's instantaneous. 405 00:23:56,500 --> 00:23:59,900 I think that there is going to be amazing things that happen. 406 00:23:59,900 --> 00:24:02,800 I believe that artificial intelligence will be the 407 00:24:02,800 --> 00:24:04,800 introduction of a permanent four-day work week. 408 00:24:05,100 --> 00:24:07,400 Like we like artificial intelligence will show us that 409 00:24:07,600 --> 00:24:11,200 working 40 hours a week is no longer required and we can have 410 00:24:11,200 --> 00:24:15,200 more Leisure Time and happiness. There's a lot of good have going 411 00:24:15,200 --> 00:24:18,000 to come out. I really do and we can go 412 00:24:18,000 --> 00:24:23,300 dystopia if you want to and it's gonna get there but also man, 413 00:24:23,300 --> 00:24:28,700 it's beautiful. I used to brought up so much 414 00:24:28,700 --> 00:24:32,300 Eric that I want to talk about the first is your point which I 415 00:24:32,300 --> 00:24:34,700 think is so pivotal for the higher ed sector. 416 00:24:34,700 --> 00:24:39,500 It's that AI has been around for a long for a while. 417 00:24:39,500 --> 00:24:42,700 This kind of tech has been around, will really change with 418 00:24:42,700 --> 00:24:45,000 Shao. Qi, PT, is that it was pushed 419 00:24:45,000 --> 00:24:50,600 into the public imagination and the ux was made so much more 420 00:24:50,600 --> 00:24:52,800 accessible. That's the big thing. 421 00:24:52,800 --> 00:24:55,900 That Chad, TBT did creating the chat function. 422 00:24:55,900 --> 00:25:02,900 So it was almost About the you. That's design of it, then the 423 00:25:02,900 --> 00:25:07,000 actual Tech and it's so worked into our lives. 424 00:25:07,400 --> 00:25:09,100 And so are going to it that we almost. 425 00:25:09,100 --> 00:25:11,200 And even notice there are a lot of us, don't even notice it was 426 00:25:11,200 --> 00:25:13,300 happening. Then the other thing you brought 427 00:25:13,300 --> 00:25:16,700 up and seemed to suggest was that Tech like chat? 428 00:25:16,700 --> 00:25:23,800 Gbt is the tip of the iceberg. He's our a just early moved. 429 00:25:23,800 --> 00:25:28,000 So I like to think about what people might think, 50 years 430 00:25:28,000 --> 00:25:30,800 from now. And one of the The things I 431 00:25:30,800 --> 00:25:33,800 think that they will do is 50 years from now. 432 00:25:34,200 --> 00:25:36,300 Children are going to be in school and they're finished. 433 00:25:36,300 --> 00:25:41,200 Show them chat GPT and they're going to be horrified about how 434 00:25:41,200 --> 00:25:44,600 bad it is. How awful a product that is? 435 00:25:44,600 --> 00:25:47,300 Instead Altman is also talked about this by the way. 436 00:25:47,500 --> 00:25:49,500 He said that. Just so you know, she actually 437 00:25:49,500 --> 00:25:52,600 be cheeps kind of awful as a user experience. 438 00:25:52,600 --> 00:25:55,000 It's down all the time you have to. 439 00:25:55,000 --> 00:25:59,200 Now spend all of these hours figuring out how to use it and 440 00:25:59,200 --> 00:26:01,600 super it Hank. He's less example Sager. 441 00:26:01,600 --> 00:26:06,900 This is awful Prada but it really gave us something that we 442 00:26:06,900 --> 00:26:09,400 can play with and I think that 50 years from now. 443 00:26:09,600 --> 00:26:11,900 It's good. Hey guys going to be so much 444 00:26:11,900 --> 00:26:14,800 more advanced in terms of being user friendly so you won't have 445 00:26:14,800 --> 00:26:19,400 to as a lot of us. Did I did spend weeks really 446 00:26:19,400 --> 00:26:22,800 play with it to be like oh I gotta use it now and I just 447 00:26:22,800 --> 00:26:26,900 going to continue to advance and it's advancing every day and I 448 00:26:26,908 --> 00:26:29,800 want to follow it up with a question Eric. 449 00:26:29,800 --> 00:26:33,700 That's Nected to that and you mentioned and I think you're 450 00:26:33,700 --> 00:26:38,000 absolutely right. That AI is an industrial 451 00:26:38,000 --> 00:26:40,800 revolution. That's changing every day every 452 00:26:40,800 --> 00:26:43,500 week. How do you stay on top of it. 453 00:26:43,600 --> 00:26:46,000 What do you follow? What do you look at? 454 00:26:46,100 --> 00:26:49,800 How do you feel like you're at least abreast of what's 455 00:26:49,800 --> 00:26:51,700 Happening? I'll say that. 456 00:26:51,700 --> 00:26:56,100 I don't feel like I am because just like you said, because 457 00:26:56,100 --> 00:27:00,200 Chance CPT is such an easy user interface. 458 00:27:00,600 --> 00:27:05,200 And because anybody can access it using their own expertise, 459 00:27:05,400 --> 00:27:09,300 there are just dozens of applications that I'm seeing 460 00:27:09,300 --> 00:27:13,700 every day. I love watching tic toc like a 461 00:27:13,700 --> 00:27:17,400 lot of the idea generation that I get is from other people who 462 00:27:17,400 --> 00:27:18,900 get on and share, what they're doing. 463 00:27:19,600 --> 00:27:23,200 I'm pretty active on LinkedIn, I'm constantly scouring. 464 00:27:23,400 --> 00:27:26,900 The news is social media, like I consume a lot of information 465 00:27:27,100 --> 00:27:29,700 from a variety of different resources and so I think that 466 00:27:29,700 --> 00:27:33,800 helps it A lot, I'm a big fan of the content just in Feinberg I 467 00:27:33,808 --> 00:27:37,700 think his name is and Rachel Woods on Tick-Tock specifically 468 00:27:37,700 --> 00:27:40,900 the AI exchange newsletter. I think is like the go-to place 469 00:27:41,000 --> 00:27:43,400 to get information. I also have a really good friend 470 00:27:43,400 --> 00:27:47,200 of mine, his name is Ben but we talk about data. 471 00:27:48,000 --> 00:27:50,000 He's the one that helped me with my dissertation research. 472 00:27:50,000 --> 00:27:52,300 During use the data scientist that I collaborated, with me and 473 00:27:52,300 --> 00:27:54,100 Katie. So, I don't know if that was 474 00:27:54,100 --> 00:28:00,700 like a I think the answer to your questions can be applicable 475 00:28:00,700 --> 00:28:01,900 for the people who are listening. 476 00:28:03,100 --> 00:28:08,100 Is that the best thing to do is to start listening and to start 477 00:28:08,100 --> 00:28:11,200 playing, don't ignore those articles that you're seeing and 478 00:28:11,200 --> 00:28:13,800 seeing that it's everywhere. Go and see it and then go and 479 00:28:13,800 --> 00:28:19,000 sit, down and chat gbt and try it. at work that I have like my 480 00:28:19,000 --> 00:28:27,800 full-time gig that I have, its I love being able to show people 481 00:28:28,300 --> 00:28:31,500 face-to-face, what this technology can do and just watch 482 00:28:31,500 --> 00:28:35,300 the AA happen, then have them come up to me, like my boss 483 00:28:35,300 --> 00:28:38,800 asked about, can you make me limerick about a leprechaun who 484 00:28:38,800 --> 00:28:40,400 wants raisins? It is, carrot cake, and I was 485 00:28:40,400 --> 00:28:42,700 like, that's what it takes to make you happy, man. 486 00:28:42,900 --> 00:28:45,300 Yes, I will. I get a raise after that. 487 00:28:45,300 --> 00:28:47,600 Yeah. And then like, I had rigged The 488 00:28:47,600 --> 00:28:50,400 Vaping. Yeah, of course, my friends 489 00:28:50,400 --> 00:28:52,800 quitting her job and she's write a resignation letter Indiana's 490 00:28:52,800 --> 00:28:54,600 like a zoo were on it already. Boom. 491 00:28:54,600 --> 00:28:59,500 Boom, let me email that to you like it's so much fun to see 492 00:29:00,100 --> 00:29:06,700 people's own curiosity and expertise emerge when they use 493 00:29:06,700 --> 00:29:08,500 it themselves and just to see bike. 494 00:29:08,500 --> 00:29:15,100 How Just imagine how much more creative and beautiful things 495 00:29:15,100 --> 00:29:18,900 are going to be. Because we have the ability that 496 00:29:19,000 --> 00:29:21,600 someone who I don't consider myself artistic, can go and make 497 00:29:21,600 --> 00:29:25,200 something beautiful. I think that's, I think that's 498 00:29:25,200 --> 00:29:27,600 amazing. And I love it that you say, you 499 00:29:27,600 --> 00:29:29,100 have to go, you have to play with it. 500 00:29:29,100 --> 00:29:31,500 I feel like people be before they write it off. 501 00:29:31,500 --> 00:29:35,200 That's the thing you need to do is just go play with it and ask 502 00:29:35,200 --> 00:29:37,100 it. Like you're you're seriously 503 00:29:37,100 --> 00:29:40,200 like just typing in a question or two. 504 00:29:40,400 --> 00:29:43,400 We need to do something. It's what we do every day owner 505 00:29:43,400 --> 00:29:45,800 and if the computer you're telling it to do things that you 506 00:29:45,808 --> 00:29:49,200 needed to do, so it's mimicking what we're already doing. 507 00:29:49,200 --> 00:29:53,800 So it shouldn't be scary for people so I want to know what 508 00:29:53,800 --> 00:29:56,900 are you like currently besides writing limericks and things and 509 00:29:56,900 --> 00:29:59,800 resignation letters. What are you currently playing 510 00:29:59,800 --> 00:30:02,600 with right now? In Ai and he like test cases 511 00:30:02,600 --> 00:30:04,400 things that you want to share with the audience that you're 512 00:30:04,400 --> 00:30:06,200 working on. I think we should all share like 513 00:30:06,200 --> 00:30:09,900 how we're were using this tool in our lives. 514 00:30:10,400 --> 00:30:15,100 For me, I'm I'm trying to build a tech company in the leanest 515 00:30:15,100 --> 00:30:20,200 way possible and so when I had questions I'm like I'm pretty 516 00:30:20,200 --> 00:30:27,000 good at generating content, what I'm bad at is formal writing and 517 00:30:27,000 --> 00:30:28,900 formal things I need to do, right? 518 00:30:28,900 --> 00:30:32,000 So what I can do is I want to thank that with all of your 519 00:30:32,000 --> 00:30:35,800 education and your background. Did he really do? 520 00:30:35,800 --> 00:30:39,400 It doesn't mean anything. That's the thing, that's the key 521 00:30:39,400 --> 00:30:44,300 there is I It's not how to do it and put it out there, but the 522 00:30:44,300 --> 00:30:48,200 think the path at the passions, are I feel like that about some 523 00:30:48,200 --> 00:30:50,600 scholar like scholarly writing is like that a lot. 524 00:30:50,600 --> 00:30:53,100 It's force a bit, not your choice on that. 525 00:30:53,100 --> 00:31:00,400 I think that being able to have an expert being able to pay chat 526 00:31:00,400 --> 00:31:03,400 gbt, I know you're not a lawyer, you can get around it, but hey, 527 00:31:03,400 --> 00:31:05,700 I have an appointment, my lawyer next week, but I have a question 528 00:31:05,700 --> 00:31:08,100 in the meantime. That's a really great way to get 529 00:31:08,100 --> 00:31:11,900 around their caveat is that they give you So I have, what do I do 530 00:31:11,900 --> 00:31:12,900 here? What does this mean? 531 00:31:13,600 --> 00:31:16,500 And then it explains it to me. I'm working in the construction 532 00:31:16,500 --> 00:31:20,500 industry. I have no idea how to build a 533 00:31:20,500 --> 00:31:24,100 building or what people use for different terms when they're I 534 00:31:24,100 --> 00:31:26,000 had. No, I'm looking at accounting 535 00:31:26,000 --> 00:31:27,700 data. I've never worked at accounts 536 00:31:27,700 --> 00:31:29,600 payable before. I've never done that. 537 00:31:30,400 --> 00:31:34,500 I have Chachi PTO bananas, say hey what does this mean? 538 00:31:35,200 --> 00:31:39,200 Or someone just said this in this context, what should I do? 539 00:31:41,300 --> 00:31:46,100 As someone who is neurodivergent and I have a bipolar disorder 540 00:31:46,100 --> 00:31:49,100 and I love, I can be overwhelming. 541 00:31:49,200 --> 00:31:52,600 Yes, my enthusiasm is wonderful for a podcast at work. 542 00:31:52,600 --> 00:31:58,300 I can be an overwhelming person. This lets me control that 543 00:31:58,300 --> 00:32:01,900 insatiable curiosity. I think the more you recognize 544 00:32:02,400 --> 00:32:06,400 that it's not a Google search where you put something in and 545 00:32:06,400 --> 00:32:10,400 you get a final output that you are talking to someone. 546 00:32:10,400 --> 00:32:13,800 It's a Chat, you refine the conversation. 547 00:32:14,100 --> 00:32:17,000 You can't go up to a stranger and give them a command. 548 00:32:17,000 --> 00:32:18,900 As they write me a press release for this. 549 00:32:19,200 --> 00:32:20,800 They're going to turn around be like, what the fuck are you 550 00:32:20,800 --> 00:32:23,200 talking about? No, you turn around to like, 551 00:32:23,200 --> 00:32:25,100 hey, how's it going? This is me. 552 00:32:25,100 --> 00:32:29,100 You introduce yourself, but you give context the more you treat 553 00:32:29,100 --> 00:32:32,700 artificial intelligence as its own actor. 554 00:32:34,000 --> 00:32:37,400 The better can't the better. You're going to get the outputs 555 00:32:37,400 --> 00:32:39,100 are going to get sorry. There are score. 556 00:32:39,300 --> 00:32:42,900 Well bleep that out. If I think they might like it 557 00:32:43,000 --> 00:32:46,900 adds emphasis, I don't know. I've no actress and leaving that 558 00:32:46,900 --> 00:32:47,900 out. I'm Gonna Keep it anymore. 559 00:32:48,200 --> 00:32:51,100 I'm not gonna find a an anchor. I probably have to put the 560 00:32:51,100 --> 00:32:55,800 explicitly, molar, whatever, or I will track it and got me down, 561 00:32:55,800 --> 00:33:01,600 who knows? And I love merits of your idea. 562 00:33:02,500 --> 00:33:07,400 I love your idea of using AI as a tutor, one of the things that 563 00:33:07,400 --> 00:33:12,700 has happened to me and I know this must sound meta is, AI has 564 00:33:12,700 --> 00:33:17,500 allowed me to get into AI. There are all these Concepts out 565 00:33:17,500 --> 00:33:21,300 there that as I read and look at everything on social media and 566 00:33:21,300 --> 00:33:23,400 learn and I follow Justin Feinberg. 567 00:33:23,500 --> 00:33:26,500 If follow Rachel, would I learn a lot from them and every once 568 00:33:26,500 --> 00:33:29,200 in a while up, Curious about something. 569 00:33:29,400 --> 00:33:34,200 And in the past 10 years ago I would have written a noted a 570 00:33:34,200 --> 00:33:36,300 notebook somewhere. Sometimes I'd look it up, 571 00:33:36,300 --> 00:33:39,100 sometimes I wouldn't. Now what I do is I take my 572 00:33:39,100 --> 00:33:43,700 device, I go immediately to poet is my go-to right now because 573 00:33:43,700 --> 00:33:47,200 it's a very, it's a very easy way to have everything in one 574 00:33:47,200 --> 00:33:49,400 spot and I'll ask it to teach me. 575 00:33:49,400 --> 00:33:53,700 So I was reading the other day about a i in ground truth it was 576 00:33:53,700 --> 00:33:55,400 just thrown out there that comes up. 577 00:33:55,500 --> 00:34:00,000 And so I was able to go in and use Gbt through Poe and just a 578 00:34:00,000 --> 00:34:04,400 skit, talk Chief me about this thing doesn't just doing web 579 00:34:04,400 --> 00:34:08,900 search because I was able to through the prom, be able to 580 00:34:08,900 --> 00:34:11,900 tailor it to myself. I was able to say, explain to me 581 00:34:11,900 --> 00:34:16,600 like you would a ten-year-old and give me at least one analogy 582 00:34:16,600 --> 00:34:21,900 that will allow me to grasp onto it, and doing that in the past, 583 00:34:21,900 --> 00:34:23,699 they've been very difficult or impossible. 584 00:34:23,699 --> 00:34:26,500 If I looked it up at all, I would have just ended up on 585 00:34:26,500 --> 00:34:31,699 dictionary.com or Wikipedia, which I'm still Blown Away by 586 00:34:31,699 --> 00:34:35,000 how in many ways inaccessible? Wikipedia is on the level of 587 00:34:35,000 --> 00:34:37,800 language. I'm constantly going in there to 588 00:34:37,800 --> 00:34:41,699 learn something Technical and on bombarded with technical 589 00:34:41,699 --> 00:34:44,100 language, even though it's recompete. 590 00:34:44,100 --> 00:34:47,699 Yeah, but even from there, I get lost and I don't know what to do 591 00:34:48,100 --> 00:34:50,699 now. It's a, I'm able to learn about 592 00:34:50,699 --> 00:34:53,699 Ai and so becomes a. So it allows me to get into 593 00:34:53,699 --> 00:34:56,900 discipline actually learn what I'm talking about in a little 594 00:34:56,900 --> 00:34:58,700 was going on. No. 595 00:34:58,700 --> 00:35:04,500 I so I was sitting down with my brother and he is he's getting 596 00:35:04,500 --> 00:35:07,300 real like next week actually sitting down for his PMP exam. 597 00:35:07,600 --> 00:35:10,300 And so and we were like he was telling me about like way that 598 00:35:10,300 --> 00:35:12,400 he's used it before and like he's just like trying to figure 599 00:35:12,400 --> 00:35:15,700 out like how he can go and prepare for his exam. 600 00:35:16,000 --> 00:35:18,400 He's also sharing with me that the way he likes to learn 601 00:35:18,800 --> 00:35:20,700 because you like that. So you can tailor, I like to 602 00:35:20,700 --> 00:35:23,100 learn by a now, they give me some analogies the way the he 603 00:35:23,100 --> 00:35:25,700 likes to learn is hey, here's this real world application and 604 00:35:25,700 --> 00:35:28,200 I have, how can I apply it? So it's like just like We're 605 00:35:28,200 --> 00:35:29,800 just like on the cuff. Right? 606 00:35:29,800 --> 00:35:32,900 And I was like, what if you were to go in a chat GPT and say, 607 00:35:33,100 --> 00:35:38,600 hey, I am taking an exam and two weeks here are some specific and 608 00:35:38,600 --> 00:35:42,200 you give them like the specific scenario that you're at work. 609 00:35:42,200 --> 00:35:46,300 That's a real life example. And then you say using the PMP 610 00:35:46,300 --> 00:35:51,700 guide, create questions for me, that helps me study, that will 611 00:35:51,700 --> 00:35:54,400 help me understand this thing at work. 612 00:35:54,700 --> 00:35:58,000 Easy peasy. As soon as you realize that it's 613 00:35:58,100 --> 00:36:01,600 Not just like accessing information but it's asking it 614 00:36:01,600 --> 00:36:05,500 to combine and synthesize information for you, it's really 615 00:36:05,500 --> 00:36:08,500 beautiful. What you can do it. 616 00:36:10,500 --> 00:36:17,200 I know how to say this, exactly. But I have been pulled into this 617 00:36:17,200 --> 00:36:21,900 thing. That is data and language. 618 00:36:21,900 --> 00:36:30,200 I have been steeping in data and language or It's it was in 2014 619 00:36:32,200 --> 00:36:35,600 when I first decided that my methodology for my dissertation 620 00:36:36,200 --> 00:36:41,300 was would be big data analysis. And I've been thinking about 621 00:36:41,400 --> 00:36:44,000 ethics of it since then I've been thinking about what I would 622 00:36:44,000 --> 00:36:48,800 do and I was at Justin thinking and thinking and it is was with 623 00:36:48,800 --> 00:36:51,300 the Advent like the reason that Things fall off last year, 624 00:36:51,300 --> 00:36:52,600 right? For a lot of different reasons 625 00:36:53,200 --> 00:36:56,100 but the reason it's being picked up right now is because I was 626 00:36:56,100 --> 00:36:59,100 able to see what other people were able to do with technology 627 00:36:59,600 --> 00:37:02,900 and that's what I hope that people walk away from this whole 628 00:37:02,900 --> 00:37:06,800 conversation is to go in and don't feel like you're being 629 00:37:06,800 --> 00:37:08,800 behind. Don't feel like you're behind 630 00:37:08,800 --> 00:37:10,900 because you're already. Behind right? 631 00:37:11,100 --> 00:37:13,700 That's like trying to say I'm behind in biology. 632 00:37:13,900 --> 00:37:16,400 Of course, I am in cellular biology since the 10th grade. 633 00:37:16,600 --> 00:37:19,000 Why would I be on top of biology? 634 00:37:19,300 --> 00:37:22,100 You're gonna be behind. The best thing that you can do 635 00:37:22,100 --> 00:37:25,500 is just be utterly amazed about what other people are doing and 636 00:37:25,500 --> 00:37:29,800 using that to inspire yourself. Like I did, we're not for me. 637 00:37:29,800 --> 00:37:31,600 It wasn't. Oh, I can write this prompt 638 00:37:31,600 --> 00:37:33,800 there with me. I can go start this company. 639 00:37:34,300 --> 00:37:36,600 I know how to do it and know what I need to do. 640 00:37:37,400 --> 00:37:42,200 And I am in power bi artificial intelligence to do it. 641 00:37:44,000 --> 00:37:48,600 That's yeah, absolutely. And I want to talk about from 642 00:37:48,600 --> 00:37:50,500 the ID perspective, the instructional designer 643 00:37:50,500 --> 00:37:55,500 perspective, how much time this saves using Chad GPT or other AI 644 00:37:55,500 --> 00:37:58,800 to write outlines or just get an idea of a storyboard because we 645 00:37:58,800 --> 00:38:02,300 spend so much time conceptualizing based off the 646 00:38:02,300 --> 00:38:06,300 content that the sneeze give us how this is all going to flow. 647 00:38:06,400 --> 00:38:09,900 They'll give us a PowerPoint but that's not necessarily in The 648 00:38:09,900 --> 00:38:13,700 Logical order or the order should be in for learning. 649 00:38:13,800 --> 00:38:17,200 And so I use chat dtp a lot just to outline stuff and I know 650 00:38:17,200 --> 00:38:19,700 people say that and it helps so much. 651 00:38:19,700 --> 00:38:23,000 It just gives you like a sense of relief that you don't have to 652 00:38:23,000 --> 00:38:25,300 go through this super critical process. 653 00:38:25,300 --> 00:38:28,300 You can refocus your efforts on the creative side of 654 00:38:28,300 --> 00:38:30,700 instructional design, and developing the interactive's and 655 00:38:30,700 --> 00:38:32,200 things. But with the Learners to 656 00:38:32,200 --> 00:38:35,500 behavioral changes and the assessments that are needed to 657 00:38:35,500 --> 00:38:37,800 exhibit that. So from an instructional 658 00:38:37,800 --> 00:38:41,000 designer perspective, this is something that I can't wait 659 00:38:41,100 --> 00:38:44,000 until people. We start incorporating These 660 00:38:44,000 --> 00:38:47,300 inter tools Microsoft is putting in the tools like they're 661 00:38:47,300 --> 00:38:50,200 articulates and the Dobies of the world start putting these 662 00:38:50,200 --> 00:38:54,800 into the tools to make it so much more manageable and I feel 663 00:38:54,800 --> 00:38:57,700 like we're going to level up as humans with a I like we're 664 00:38:57,700 --> 00:38:59,700 already doing it. We're going to just we're going 665 00:38:59,700 --> 00:39:03,100 to think more critically on higher levels because of this. 666 00:39:04,300 --> 00:39:08,600 So here is in my mind, a reality that will happen once the 667 00:39:08,600 --> 00:39:13,300 hardware patches up or if once things are catching up and this 668 00:39:13,300 --> 00:39:16,000 is what this is, what makes it so scary, right? 669 00:39:16,000 --> 00:39:18,100 That people have peed like a eyes, it would come and replace 670 00:39:18,100 --> 00:39:20,800 my job is because you have people like me thinking like 671 00:39:20,800 --> 00:39:22,600 this. And here's what people need to 672 00:39:22,600 --> 00:39:24,700 do is like you should be asking these questions. 673 00:39:25,000 --> 00:39:26,700 You should be the ones, implementing these things in 674 00:39:26,700 --> 00:39:29,800 your organization, because here's what's going to happen in 675 00:39:30,300 --> 00:39:31,600 five years. Right? 676 00:39:31,600 --> 00:39:34,300 A company is going to have Artificial intelligence 677 00:39:34,300 --> 00:39:36,800 connected it to its entire knowledge base. 678 00:39:37,400 --> 00:39:40,700 You're gonna have a new hire come in and say hey this is how 679 00:39:40,700 --> 00:39:44,700 I like to learn. You even need an instructional 680 00:39:44,700 --> 00:39:47,600 designer anymore say, I like, to learn this way. 681 00:39:47,600 --> 00:39:50,000 Can you teach me about this process? 682 00:39:51,000 --> 00:39:56,600 And now you have an interactive instructional designer that will 683 00:39:56,600 --> 00:40:01,700 answer your questions. Personalized based on the 684 00:40:01,700 --> 00:40:05,400 knowledge base from the company, based on how you like to learn. 685 00:40:05,500 --> 00:40:08,300 If you like to learn via problems are you like to learn 686 00:40:08,300 --> 00:40:11,400 via funny videos? But you can say, make me a funny 687 00:40:11,400 --> 00:40:14,500 video starring Bruce Willis that Has me about this principle. 688 00:40:16,500 --> 00:40:21,400 That's there. All the pieces are there and 689 00:40:21,400 --> 00:40:23,000 that's what everybody's going to be think. 690 00:40:23,000 --> 00:40:25,600 That's when 50 years from now. They're going to be looking back 691 00:40:25,600 --> 00:40:27,800 and thinking like wow, Josh apt for. 692 00:40:27,800 --> 00:40:29,400 What is that? Just like my kid is going to 693 00:40:29,400 --> 00:40:32,600 look at like the Motorola 120 e, razor fall off your bike with 694 00:40:32,600 --> 00:40:35,100 peanut phone that up. It was really fancy to that of 695 00:40:35,100 --> 00:40:36,700 blue screen instead of a green screen. 696 00:40:36,900 --> 00:40:41,900 Yeah. Anyway, it's just so much fun 697 00:40:41,900 --> 00:40:44,500 stuff out there and I hope that people are not intimidated by 698 00:40:44,500 --> 00:40:50,400 it, and they feel excited about it because you should be agreed. 699 00:40:52,100 --> 00:40:53,400 Yeah. And I think that, and you 700 00:40:53,400 --> 00:40:55,900 mentioned this before, and it there are just around 40 minutes 701 00:40:55,900 --> 00:40:57,200 Arc. I do want to on your time, and I 702 00:40:57,207 --> 00:41:01,100 know that you have to go, Holly have to go play with it, right? 703 00:41:01,100 --> 00:41:05,600 If you're out there, you're higher ed or any field, really? 704 00:41:06,200 --> 00:41:10,300 If you're concerned, if you're worried that is okay, those are 705 00:41:10,300 --> 00:41:13,700 emotionally valid responses. Make sure you get in and you 706 00:41:14,000 --> 00:41:18,000 really play with it. And I'll be totally honest, or 707 00:41:18,000 --> 00:41:21,700 I'm emotionally, I have good days, I have bad days with a, i 708 00:41:21,800 --> 00:41:24,100 Some days. I think, yes, this is going to 709 00:41:24,100 --> 00:41:26,600 allow me to do X, Y, and Z faster better. 710 00:41:26,600 --> 00:41:29,500 So on and so forth. And other days, I'm very 711 00:41:29,500 --> 00:41:32,400 negative about it and I go back and forth and I've learned to be 712 00:41:32,400 --> 00:41:36,300 emotionally, okay, with that, depending on my own State, what 713 00:41:36,300 --> 00:41:41,400 I'm working with, I think that for a lot of Educators, we need 714 00:41:41,400 --> 00:41:43,700 to do, we need to do our due diligence, which means playing 715 00:41:43,700 --> 00:41:46,600 with it, playing with the software, really reflecting on 716 00:41:46,600 --> 00:41:50,900 it and being okay with not feeling, totally, consistent 717 00:41:50,900 --> 00:41:53,900 emotionally, Lee with the tag. I think that a lot of people are 718 00:41:53,900 --> 00:41:55,900 there, and it's okay to be there too. 719 00:41:56,200 --> 00:41:57,300 All right. And I, so I do want to honor 720 00:41:57,300 --> 00:41:57,900 your time. Eric. 721 00:41:57,900 --> 00:42:01,200 So, very last question, if someone listening to this 722 00:42:01,200 --> 00:42:04,900 episode wants to talk to, you wants to have a conversation or 723 00:42:04,900 --> 00:42:10,200 reach out to you for any reason, I should they put 100% LinkedIn 724 00:42:10,300 --> 00:42:13,500 is where I live by. You could also check out the 725 00:42:13,500 --> 00:42:18,800 project, its www, dot project, rhizome.com, and you can get a 726 00:42:18,800 --> 00:42:23,700 whole bunch of stuff there too. Fantastic. 727 00:42:24,600 --> 00:42:27,200 I love it. I'm so glad you came back to 728 00:42:27,200 --> 00:42:28,800 this. I'm so glad you came back to 729 00:42:28,800 --> 00:42:30,800 this. I am very grateful for the two 730 00:42:30,800 --> 00:42:36,500 of you truly or not only having this conversation at being able 731 00:42:36,500 --> 00:42:38,800 to promote and all that kind of stuff. 732 00:42:39,200 --> 00:42:43,800 But I think like it is this community that we built on 733 00:42:43,800 --> 00:42:47,200 LinkedIn over the past year or two years, whatever that I'm 734 00:42:47,200 --> 00:42:50,500 just very grateful for. And I don't think that I could 735 00:42:50,500 --> 00:42:57,600 have approached the problem that I am trying to approach if it 736 00:42:57,600 --> 00:43:02,200 were not for the constant, iterative reactions and refining 737 00:43:02,200 --> 00:43:05,700 of ideas with people, that would not give you. 738 00:43:05,700 --> 00:43:08,500 So again, I'm just very grateful, thank you, both for 739 00:43:08,800 --> 00:43:13,900 doing absolutely anytime. Okay, you're so welcome. 740 00:43:13,900 --> 00:43:16,000 And thank you so much our for coming on the show. 741 00:43:16,100 --> 00:43:19,700 Coming on the first joint podcast and good luck with 742 00:43:19,700 --> 00:43:21,700 everything. And it's been a pleasure hear 743 00:43:21,700 --> 00:43:24,400 you talk with a. I Thank you so much. 744 00:43:29,700 --> 00:43:34,000 You've just experienced an another amazing episode of Ed 745 00:43:34,000 --> 00:43:35,100 up. Ed Tech. 746 00:43:35,700 --> 00:43:41,100 Be sure to visit our website at Ed up, edtech.com to get all the 747 00:43:41,100 --> 00:43:43,900 updates on the latest edtech happening. 748 00:43:44,600 --> 00:43:46,000 See you next time.