WEBVTT NOTE This file was generated by Descript 00:00:00.010 --> 00:00:02.349 Jethro: Welcome to Artificial Intelligence Real Talk. 00:00:02.349 --> 00:00:10.959 I'm your host, Jethro Jones, and today we are talking about AI and how schools can use it and like what do we do? 00:00:11.080 --> 00:00:15.580 I mean, this is what we talk about all the time on this podcast, but today we're talking with Sam Bourgeois. 00:00:16.020 --> 00:00:21.720 And, uh, pretty excited to chat with him because he has been in the IT space for years. 00:00:21.720 --> 00:00:27.750 And, uh, so we're just gonna have a conversation, gonna riff off on a couple of topics and, and go from there. 00:00:27.750 --> 00:00:31.440 So, uh, you can listen to this podcast wherever you get your podcasts. 00:00:31.440 --> 00:00:33.240 Artificial intelligence, real talk. 00:00:33.600 --> 00:00:34.950 Thanks so much for listening. 00:00:34.950 --> 00:00:37.170 Sam, where do you think we should start? 00:00:37.779 --> 00:00:40.299 Sam Bourgeois: Man, uh, it's always a good convo with you. 00:00:40.539 --> 00:00:51.099 Um, I think what's been on my mind lately is I've got this, uh, this course in development and I wanna put this content in as a, as a en enrichment opportunity for that. 00:00:51.219 --> 00:00:52.989 Course, and that course is centered around it. 00:00:53.919 --> 00:01:02.169 Uh, district leaders, uh, instructional leaders, potentially superintendents, even teachers as leaders in the classroom, right? 00:01:02.709 --> 00:01:04.869 And the course is all about. 00:01:05.354 --> 00:01:08.714 AI risk management, cybersecurity risk management. 00:01:09.104 --> 00:01:11.294 So we're on an AI podcast. 00:01:11.444 --> 00:01:16.124 I'm gonna tell you, let me, let me tell you a story and then you tell me where we can go with this. 00:01:16.124 --> 00:01:17.684 So I had this really cool idea. 00:01:17.924 --> 00:01:22.574 Um, now I know we have similar backgrounds with our, with our, uh, with our children. 00:01:23.354 --> 00:01:27.489 son, for everybody who's listening is a neuro neurodivergent 10-year-old. 00:01:28.639 --> 00:01:33.019 he is super, super excited about who would win books. 00:01:33.709 --> 00:01:38.119 I don't know if you've seen those, the Who's Gonna Win Tiger Shark versus Great White Shark or whatever. 00:01:38.869 --> 00:01:41.239 the other day I'm getting ready for a party. 00:01:41.239 --> 00:01:44.419 It's the holiday season and I've got phone in hand. 00:01:44.419 --> 00:01:47.884 I'm trying to get something done, and he's just peppering me nonstop with questions. 00:01:47.929 --> 00:01:49.279 So I say, I've got this idea. 00:01:49.279 --> 00:01:50.149 So I pull up my phone. 00:01:51.254 --> 00:01:55.544 Go to my chat, GPT Pro, which is not training the, the data in the, in the masses, right? 00:01:55.544 --> 00:01:57.254 So I've got it, you know, internalized. 00:01:57.404 --> 00:01:59.984 I hit the talk button, I dunno if you ever do this. 00:02:00.734 --> 00:02:02.654 And I just put it in front of him and he just starts talking. 00:02:02.654 --> 00:02:04.604 He goes, who would win? 00:02:04.724 --> 00:02:06.884 Uh, great white shark or tiger shark. 00:02:06.974 --> 00:02:10.994 And then the lady comes back to him with a British accent and he says, oh, that's a great question. 00:02:11.264 --> 00:02:14.144 Let's, let's unpack that for a moment, blah, blah, blah, blah, blah. 00:02:14.204 --> 00:02:18.704 And my kid just goes off and has this amazing conversation. 00:02:18.764 --> 00:02:20.804 And the funny thing is my, um. 00:02:21.194 --> 00:02:32.234 My, my a BA person, my a BA clinical specialist, is in this, she's there watching and she's just like, mind blown, like, whoa, this is great. 00:02:32.234 --> 00:02:36.434 And she's telling me after the fact, she's like, he's practicing his conversation. 00:02:36.824 --> 00:02:38.684 He's waiting and pausing. 00:02:38.804 --> 00:02:40.784 He's treating this like a real person. 00:02:41.144 --> 00:02:43.814 So I was like, awesome. 00:02:43.814 --> 00:02:44.204 Dad. 00:02:44.204 --> 00:02:45.134 High five moment. 00:02:45.134 --> 00:02:45.854 But then I was like. 00:02:46.694 --> 00:02:52.424 I totally didn't do like a risk assessment to see where this is gonna go and like the drawbacks, right. 00:02:52.424 --> 00:02:52.754 So I don't know. 00:02:52.754 --> 00:02:53.599 What are your thoughts on that? 00:02:54.964 --> 00:02:57.664 Jethro: Yeah, well, I, I love that example for a few reasons. 00:02:57.964 --> 00:02:58.594 One. 00:02:59.110 --> 00:03:00.610 Uh, you, you're right. 00:03:00.610 --> 00:03:05.079 You didn't do a risk assessment and like say, what could possibly go wrong with this? 00:03:05.079 --> 00:03:13.120 But the first thing there is what your, uh, what the specialist said, which is he's treating this like a real person. 00:03:13.660 --> 00:03:23.769 And to me that's the biggest issue that we have with AI right now is that people often think that it is a real person when it definitely is not. 00:03:24.010 --> 00:03:28.149 And so that to me is, is the, the groundwork where you need to start. 00:03:28.510 --> 00:03:37.029 This is not a person, this is a tool that might help you understand or do something a little bit better, but it is not a real person. 00:03:37.029 --> 00:03:42.399 So don't get confused and think that this is a real person, however. 00:03:43.089 --> 00:03:51.339 Was she right about him practicing, talking and using and speaking appropriately and being able to be understood. 00:03:51.370 --> 00:03:55.060 Let me share a little story with you as well that's along those same lines. 00:03:55.390 --> 00:04:08.620 Uh, my oldest daughter has down syndrome and has a speech impediment and is sometimes hard to understand, but she has a, uh, a home pod, uh, in her room that plays music that she loves to listen to. 00:04:08.680 --> 00:04:10.420 She loves music so. 00:04:10.915 --> 00:04:20.245 We were driving in the car and I invoked Siri on my, uh, car and said, play this kind of music, or play this song or something. 00:04:20.605 --> 00:04:26.725 I tried five times, I couldn't get it to work, and so my daughter leans over and says, dad, I got it. 00:04:27.025 --> 00:04:31.075 And she says, Siri, play this thing and then it does. 00:04:31.255 --> 00:04:32.965 And I was like, are you kidding me? 00:04:33.235 --> 00:04:35.545 So what has actually happened is that. 00:04:36.145 --> 00:04:57.955 My Siri account has been trained on my daughter's, uh, speech impediment, so it understands her better than it understands me now, which causes all sorts of frustration on my part, but she totally gets it, and she can, she does a great job with it, and that's, that's one of those things that these tools can enable. 00:04:58.570 --> 00:05:02.920 Kids with disabilities to have a more level playing field. 00:05:03.100 --> 00:05:04.600 Let me share another story. 00:05:04.750 --> 00:05:14.770 Um, my daughter needed to give a talk in church and so she, I had her write down and text me what she thought, uh, she wanted to say. 00:05:15.250 --> 00:05:26.200 And so she wrote this long sentence with no transition words, no periods, no commas, no nothing, but were things that I know she believes and understands, and that. 00:05:26.680 --> 00:05:29.620 And so I was like, okay, this is something that she would say. 00:05:29.770 --> 00:05:36.490 However, if she gets up there and reads this, nobody's gonna understand and nobody's gonna like care what she's saying. 00:05:36.790 --> 00:05:46.930 They'll just be like, there's a kid with Down syndrome speaking some gibberish, and like people are respectful and they'll be kind and everything, but she won't be able to communicate what she really believes. 00:05:47.275 --> 00:05:52.585 And so I went into Chachi pt. I put that in and I said, she needs to give a talk. 00:05:52.585 --> 00:05:53.455 Here's our religion. 00:05:53.455 --> 00:05:55.315 Here's the things we believe. 00:05:55.315 --> 00:05:56.695 Here's what she said. 00:05:57.055 --> 00:06:02.095 Now make this into a talk that would make sense to a normal person. 00:06:02.695 --> 00:06:14.905 It created a talk that actually communicated what my daughter really believes in a way that was incredibly powerful, which I just loved because she got to. 00:06:15.595 --> 00:06:16.915 To put this out there. 00:06:17.125 --> 00:06:22.465 Uh, and it was what she believed, even though she didn't construct the sentences herself. 00:06:23.035 --> 00:06:32.395 Now, to be perfectly honest, if she needed to give a talk and I was helping her, I would be the one writing the talk for her and try to make it sound like her as much as possible. 00:06:32.875 --> 00:06:36.745 The benefit in this situation is that I gave her the. 00:06:37.300 --> 00:06:41.170 The, the task to, to write what she wanted to write. 00:06:41.590 --> 00:06:47.800 I put into chat GPT and then made a couple of, uh, additions or subtractions so that, so that it would make sense. 00:06:48.130 --> 00:07:04.990 Now, going back to your first story in this story, what that enabled, um, there was a paper released in the summer of 25 that was called cognitive Debt, and it talked about how when you use AI, then you create cognitive debt because you don't remember the things that you wrote. 00:07:05.905 --> 00:07:14.905 But for people with disabilities, I believe that AI creates cognitive equity, that they are able to do things that they wouldn't be able to do normally. 00:07:16.045 --> 00:07:18.445 That the AI gives them the power to do that. 00:07:18.535 --> 00:07:42.175 And I wrote a paper on this myself called Cognitive Equity, so you can go look that up and, and gave the example of what my daughter went through and how we use this to help her communicate something that was so much better than what she could do on her own and how valuable and important that was because it gave her the opportunity to express what she believes and what she is interested in. 00:07:42.755 --> 00:07:49.085 To a room full of people who don't interact with her very often, and then they could see what she really believed. 00:07:49.085 --> 00:07:58.895 And that was a huge, huge mark, like huge improvement on her life because she gets to express herself in a way she never has been able to before. 00:07:59.414 --> 00:08:01.844 Sam Bourgeois: We, and you know, we've talked about this in the past. 00:08:02.054 --> 00:08:02.504 Um. 00:08:03.359 --> 00:08:05.009 And this, you know what it reminds me of? 00:08:05.009 --> 00:08:20.579 It reminds me of the conversations where, do you remember when we were first handing out iPads for like, again, my, my son is a SD, but there were, there were these iPads and they were like the, it was like the old storyboards that we used to do with like Velcro to help communicate. 00:08:20.815 --> 00:08:21.354 Jethro: Oh yeah. 00:08:21.385 --> 00:08:21.744 Yeah. 00:08:21.899 --> 00:08:23.939 Sam Bourgeois: was, it was like a game changer and people thought. 00:08:24.254 --> 00:08:25.694 I don't care how much it costs. 00:08:25.754 --> 00:08:28.844 Let's just get this thing so the, so the child can actually have a voice. 00:08:28.844 --> 00:08:32.054 Or, you know, if you even go back a little further from there. 00:08:32.114 --> 00:08:40.394 And you look at the, um, uh, the, the kiddos who are confined to a wheelchair, their mobility, just conversation. 00:08:40.394 --> 00:08:45.854 Their mobility comes from some of these technical improvements, technology, technology improvements. 00:08:46.244 --> 00:08:47.534 It's, it's really the same thing. 00:08:47.539 --> 00:08:52.154 It's like, but we have to ask ourselves, this is the question for the principal side of you, not the father side of you. 00:08:53.924 --> 00:08:57.254 We have to kind of reevaluate what is the, what's the learning outcome? 00:08:57.254 --> 00:08:58.034 What's the objective? 00:08:58.034 --> 00:08:58.724 What's the thing? 00:08:58.724 --> 00:09:03.194 So in your example was the thing to get up on stage. 00:09:03.674 --> 00:09:04.094 Okay? 00:09:04.394 --> 00:09:07.364 Mission accomplished was the thing to express yourself. 00:09:07.424 --> 00:09:10.004 Mission accomplished was the thing, the grammar. 00:09:10.484 --> 00:09:10.784 Okay? 00:09:10.784 --> 00:09:12.344 So we didn't, we didn't do that. 00:09:12.344 --> 00:09:15.194 But if, if that's not the thing that we're trying to measure. 00:09:15.974 --> 00:09:23.024 that's not the coursework, the course material, it's like, it's like, uh, when we were young men and we were told we couldn't have a calculator in math class, right? 00:09:23.114 --> 00:09:23.774 It's the same thing. 00:09:23.774 --> 00:09:23.894 It's 00:09:24.024 --> 00:09:24.354 Jethro: Yep. 00:09:24.564 --> 00:09:24.924 Yep. 00:09:25.029 --> 00:09:30.254 Sam Bourgeois: are, are you measuring work that I produced and wrote in my little blue book, the, the showing my work? 00:09:30.404 --> 00:09:34.814 Or are you measuring my accuracy to do three digit multiplication? 00:09:35.204 --> 00:09:35.474 Like 00:09:35.859 --> 00:09:36.249 Jethro: Yeah. 00:09:36.284 --> 00:09:36.674 Sam Bourgeois: me which one. 00:09:36.674 --> 00:09:37.184 It's right. 00:09:38.139 --> 00:09:47.169 Jethro: Well, and, and this is what is, is so important, is the, the purpose it, we need to go back to that every single time. 00:09:47.724 --> 00:09:54.864 What are we trying to get the kids to be able to do and if the purpose is for them to to learn something? 00:09:55.014 --> 00:10:00.654 If the purpose was for my daughter to learn grammar, it was a total failure, but that wasn't the purpose. 00:10:00.954 --> 00:10:13.764 If the purpose was for my daughter to be able to give a talk so that people could understand her in a way that they've never been able to understand her, but before then, not only was that purpose met, but it was exceeded at a grand scale, which was really amazing. 00:10:14.814 --> 00:10:28.915 And so again, we go back to your original story that you started out with the, the purpose for your son in that situation was for him to have a conversation about what would win with somebody. 00:10:29.334 --> 00:10:36.594 Or something I should say that could engage with him in a, at his level and in a way that was appropriate for him. 00:10:37.344 --> 00:10:39.685 And again, mission accomplished. 00:10:39.805 --> 00:10:48.654 And you and I as dads, sometimes we don't have the time, and this is where it becomes really valuable for teachers, because teachers don't always have the time either. 00:10:48.925 --> 00:10:56.394 They've got 20 to 40 students in their classroom and they don't have time to give individual individualized attention to each one of those kids. 00:10:57.269 --> 00:11:00.629 So where do we want their time to be spent? 00:11:00.869 --> 00:11:03.419 Do we want them to be, uh, creating. 00:11:04.134 --> 00:11:09.234 Personalized materials for every single kid when an AI could do that so much better. 00:11:09.535 --> 00:11:12.144 No, we don't want them to be using their time for that. 00:11:12.594 --> 00:11:19.134 I want my teachers to spend as much time as possible interacting with my kids, uh, in a way that is gonna help them. 00:11:19.314 --> 00:11:22.704 And I want the teacher to have the freedom and the power to make that decision. 00:11:23.094 --> 00:11:25.974 So where can we bring AI tools in to help with that? 00:11:26.185 --> 00:11:27.834 Now, if, let me. 00:11:28.420 --> 00:11:41.800 Put a little caveat in here if the AI tools are there, just to help make it so that the teacher can do the same dumb lessons she's always done and not change what she's doing and personalize it for the kids. 00:11:42.069 --> 00:11:43.064 That's not really beneficial. 00:11:43.865 --> 00:11:49.564 You know when when these new AI tools came out, everybody was like, oh, I can have it make worksheets for me. 00:11:49.714 --> 00:11:52.204 Well, worksheets are not really that valuable. 00:11:52.265 --> 00:11:53.375 Let's not do that. 00:11:53.645 --> 00:11:58.745 So let's do something different and let's do something that is valuable for our kids. 00:11:59.045 --> 00:12:00.875 And teachers have to ask the same question. 00:12:01.175 --> 00:12:03.334 What's the real purpose and value here? 00:12:03.785 --> 00:12:05.735 And what I've said a hundred times is. 00:12:06.834 --> 00:12:09.114 We should not use AI to circumvent learning. 00:12:09.324 --> 00:12:11.214 We should use AI to enhance learning. 00:12:11.665 --> 00:12:13.374 Think about the actual purpose. 00:12:13.614 --> 00:12:18.594 What is that you want to happen, and then use a tool that's gonna help get you to that point. 00:12:19.104 --> 00:12:23.785 That's, that's the key, and that's what we need to be using AI for a hundred percent. 00:12:25.124 --> 00:12:26.504 Sam Bourgeois: I couldn't, I couldn't agree more. 00:12:27.314 --> 00:12:30.014 What are your, what are your thoughts on the risk, on the risk profile? 00:12:30.014 --> 00:12:32.534 So, my example was a silly one, but I, here's where I was at. 00:12:32.534 --> 00:12:33.284 This is what I was thinking. 00:12:33.284 --> 00:12:33.794 I was like. 00:12:36.269 --> 00:12:41.639 Honestly, I, I think my kids get too much screen time and, and it doesn't matter what the number is. 00:12:41.669 --> 00:12:45.359 By the way, just for the record, there's always gonna be too much screen time if you ask me. 00:12:45.479 --> 00:12:48.059 Like, I would like to have more green time, not more screen time. 00:12:48.059 --> 00:12:48.239 Like, 00:12:48.269 --> 00:12:48.489 Jethro: Yes. 00:12:48.744 --> 00:12:49.104 Yep. 00:12:49.499 --> 00:12:52.439 Sam Bourgeois: even if it's 15 minutes a day to be, you know, less. 00:12:52.439 --> 00:12:52.739 Right. 00:12:53.274 --> 00:12:53.724 Jethro: Mm-hmm. 00:12:53.909 --> 00:12:58.349 Sam Bourgeois: is I didn't put that on a device that he has access to all the time. 00:12:58.379 --> 00:12:59.874 'cause I'm, I'm afraid that that might. 00:13:01.184 --> 00:13:02.684 Take away from human interaction. 00:13:02.834 --> 00:13:03.224 Okay. 00:13:03.824 --> 00:13:07.004 I thought about like, I training the data on this? 00:13:07.034 --> 00:13:07.784 No, no. 00:13:07.784 --> 00:13:08.984 I'm not training the data on this. 00:13:09.314 --> 00:13:16.814 I actually thought about does this actually, uh, this actually affect my training of my GPT experience? 00:13:16.814 --> 00:13:26.684 Because like I'm always asking like, let's say, let's say higher level, higher order questions, I'm asking things about forensics, data forensics, cybersecurity, or something like that. 00:13:26.684 --> 00:13:28.874 And by having a conversation about sharks, is that gonna. 00:13:29.279 --> 00:13:30.419 You know, of, 00:13:30.610 --> 00:13:30.939 Jethro: Yeah. 00:13:31.180 --> 00:13:31.540 Yep. 00:13:31.769 --> 00:13:32.729 Sam Bourgeois: affect the learning, right? 00:13:33.149 --> 00:13:37.799 So I asked some of those questions, but what are your thoughts at the school level? 00:13:37.949 --> 00:13:46.199 How do we ask the right questions and how do we determine what's appropriate for use in a classroom at the, at the building level and at the district level? 00:13:46.199 --> 00:13:46.799 What are your thoughts there? 00:13:48.354 --> 00:13:59.665 Jethro: Yeah, so I, I am most typically in favor of giving teachers as much autonomy and, and permission to experiment as we can. 00:13:59.754 --> 00:14:08.754 So, so that's the first place is let's, let's let them be the ones to make the most decisions and give them the tools that they can then make those decisions about. 00:14:09.354 --> 00:14:10.329 So that's where I would. 00:14:10.854 --> 00:14:11.515 Start. 00:14:11.604 --> 00:14:17.155 And that's because they're the ones who are closest to the kids and they're the ones who know what the kids need the best. 00:14:17.155 --> 00:14:19.375 And so that's, that would be the first place. 00:14:20.035 --> 00:14:24.984 The other thing to be thinking about is, is going back to what we said before, the purpose. 00:14:25.104 --> 00:14:26.905 What, what are you trying to accomplish? 00:14:26.935 --> 00:14:31.074 And make sure that the tools you're using allow you to accomplish that purpose. 00:14:31.135 --> 00:14:33.805 And, and if they don't, that's an issue. 00:14:33.805 --> 00:14:35.515 You gotta go, you gotta go fix that. 00:14:36.055 --> 00:14:36.505 Um. 00:14:37.194 --> 00:14:44.785 So those two things first would be what I would think about the next thing would be what's gonna happen with the kid who uses this? 00:14:44.844 --> 00:14:47.905 What's going to be the long-term effects of them using it? 00:14:48.265 --> 00:14:51.505 And so, you know, uh, the calculator is a good example. 00:14:51.685 --> 00:14:52.555 If somebody, if. 00:14:53.290 --> 00:14:59.050 If somebody uses a calculator but they don't have an idea of number sense, then the calculator is essentially pointless. 00:14:59.050 --> 00:15:00.819 'cause they won't know when it's wrong. 00:15:01.119 --> 00:15:10.270 If they do 25 times 25 when they meant to do 25 plus 25 and they get 5,000, they're gonna know if they have number sense. 00:15:10.359 --> 00:15:11.500 That's not the right answer. 00:15:11.500 --> 00:15:15.040 If they don't have number sense, they're just gonna copy the answer down. 00:15:15.430 --> 00:15:16.925 And so that's where you really gotta be. 00:15:17.604 --> 00:15:26.844 Intentional about talking about what it is that you're using, how you're using it, and why, so that you can make a more informed decision about the output that you're getting. 00:15:27.175 --> 00:15:39.594 Because if you don't know what that output is, then it's gonna be really difficult for you to say, this is exactly what it needed to be, and this is how, how I understand it, and this is the right, the right response. 00:15:40.344 --> 00:15:47.275 So you have to be thoughtful about that, and teachers have to have continuous conversations with principals and with students about that. 00:15:47.515 --> 00:15:55.944 Students, when they're using it need to be able to articulate why and how they're doing what they're doing, instead of just saying, oh, I just made an image. 00:15:56.245 --> 00:15:58.255 Okay, but like, what's the purpose? 00:15:58.464 --> 00:15:59.545 I just had to do my homework. 00:15:59.574 --> 00:16:00.714 Okay, but what's the purpose? 00:16:00.714 --> 00:16:01.405 Why did you do that? 00:16:01.405 --> 00:16:02.454 How did you go about it? 00:16:02.814 --> 00:16:06.535 Because you can actually understand a lot more from the questions somebody's asking. 00:16:07.030 --> 00:16:15.489 And the things they're asking it to do, you can understand if they understand what they're trying to accomplish and other times, like they clearly can't. 00:16:15.489 --> 00:16:20.229 In my daughter's example that I shared, she had no idea what was going on. 00:16:20.379 --> 00:16:24.339 She was like, oh, I sent you something and now I read this thing that you sent me back. 00:16:25.060 --> 00:16:26.349 Okay, whatever. 00:16:26.709 --> 00:16:51.820 And you know, that's fine for what we were trying to accomplish, but if that's the case in a presentation in school, for example, that's probably not the outcome that you're looking for, but, but if the kid is super nervous about speaking in front of others and is so nervous about it that they can't handle writing the actual content, they are going to speak. 00:16:52.600 --> 00:17:02.110 You can give them the, the tools to write that faster so that they, they're not worried about punctuation or spelling or grammar because it's already laid out nicely. 00:17:02.709 --> 00:17:06.315 That is a benefit to them If the purpose is to get up and speak. 00:17:07.195 --> 00:17:11.335 But if the purpose is other things, then you need to use other tools to get them to that point. 00:17:11.755 --> 00:17:15.505 And so that's where like, there's no way to say, here's a hard and fast rule. 00:17:15.744 --> 00:17:18.534 Use AI for this purpose and this purpose only. 00:17:18.865 --> 00:17:24.655 It has to be case by case, situation by situation, making the best decision that you can. 00:17:24.804 --> 00:17:27.775 And nobody likes that answer because it's too flimsy. 00:17:28.394 --> 00:17:31.154 Sam Bourgeois: You know, you know where my mind was going as you were talking, I was thinking. 00:17:32.009 --> 00:17:33.239 are, what are you testing for? 00:17:33.269 --> 00:17:34.919 Like what's, what is the assessment? 00:17:34.919 --> 00:17:36.749 What's the evaluation looking for? 00:17:36.839 --> 00:17:37.169 Right. 00:17:37.229 --> 00:17:47.489 And I was thinking about those nervous times that we've all had in life where we've had to get in front of the class and do a presentation on XY and I was thinking, you know, what I use today, there's a tool. 00:17:47.489 --> 00:17:50.969 So anybody who's watching this, if you wanna go check it out, it's called synthesia. 00:17:51.419 --> 00:17:52.499 Uh, I hope I pronounce that right. 00:17:52.499 --> 00:17:56.429 But, um, Synthesia Online is, is relatively. 00:17:56.804 --> 00:17:58.094 Attainable, budget friendly. 00:17:58.154 --> 00:18:04.004 It's not too expensive, but, um, you can use the avatars that exist, but you can also create your own avatar. 00:18:04.274 --> 00:18:06.464 And so I was just thinking about me like, what do I do? 00:18:06.554 --> 00:18:17.534 I put my shirt on and I do a talk and I read myself, and then I get my avatar, and then, um, I can just kind of dump in text scripts that I've written and I can have the avatar read it. 00:18:17.534 --> 00:18:18.914 My avatar doesn't make mistakes. 00:18:19.229 --> 00:18:21.509 There's no noise from the kids in the other room. 00:18:21.569 --> 00:18:23.969 There's no like, I don't have to shave, right? 00:18:23.969 --> 00:18:29.009 Like so I'm just thinking about like, what about the kid who says, well, I'm gonna create an avatar of myself. 00:18:29.009 --> 00:18:34.739 I'm nervous in front of people, but you wanted me to the material, create a presentation. 00:18:34.739 --> 00:18:37.199 I did that and then I gave it to my avatar. 00:18:37.199 --> 00:18:39.869 It's my voice, it's my likeness anyway. 00:18:39.929 --> 00:18:46.319 I'm not trying to be too wild and challenging, but I'm just kind of thinking through like a lot of fun conversation to be had here. 00:18:46.319 --> 00:18:47.129 What about the teacher? 00:18:47.459 --> 00:18:48.899 Who does what I do do. 00:18:48.899 --> 00:18:55.109 We look down on that teacher and say, you did a flipped classroom, but you cheated, you know, you used your avatar to read the lessons. 00:18:55.109 --> 00:18:55.589 It was like, 00:18:56.020 --> 00:18:56.440 Jethro: Yeah. 00:18:56.759 --> 00:18:59.219 Sam Bourgeois: it, I did what I, what I was trying to accomplish. 00:18:59.219 --> 00:18:59.459 Right. 00:19:00.370 --> 00:19:00.850 Jethro: Yeah. 00:19:00.940 --> 00:19:20.080 Well, we've all sat through classes with a teacher or a professor who rambles on and on and on and doesn't get to the point and talks about a million different things, and when in reality it would be much better if we just had the exact information that we needed to know, and then we could have those rambling conversations. 00:19:20.575 --> 00:19:35.905 When we're not trying to teach a specific topic, so, you know, Synthesia is a, a good example of an opportunity where you can produce a perfect lesson essentially with no errors, no bird walks, nothing. 00:19:36.295 --> 00:19:44.035 And if that's what you're trying to do is teach a very specific thing, it is crazy to try to do that yourself. 00:19:44.500 --> 00:19:59.410 With a bunch of kids, with people interrupting when a better way to do that is say, here's exactly what you need to know in a clean, well thought out presentation with slides and bullets and all this kind of stuff that makes it very clear what's going on. 00:19:59.800 --> 00:20:02.650 That is, is really powerful. 00:20:03.040 --> 00:20:07.840 Now, there, there are a lot of, uh, scripted type, uh. 00:20:08.440 --> 00:20:15.310 Um, uh, curriculums where the teacher basically says, you know, they read from a book everything that's happening that day. 00:20:15.640 --> 00:20:21.610 In those situations, why not have a computer or AI do that? 00:20:21.940 --> 00:20:25.870 If that's really what the point is, the AI is not going to mess up. 00:20:25.870 --> 00:20:27.610 It's going to read the script exactly. 00:20:28.120 --> 00:20:29.980 Why not have it do that? 00:20:30.850 --> 00:20:32.050 Those situations? 00:20:32.050 --> 00:20:32.620 Yes. 00:20:32.710 --> 00:20:34.000 You, you might as well. 00:20:34.180 --> 00:20:37.210 What's the benefit of the teacher being the one to do that? 00:20:37.480 --> 00:20:43.600 Well, the real benefit is that the teacher will notice when the kid needs some additional help or needs to slow down. 00:20:44.110 --> 00:20:48.040 And that's great and they should, should provide that and help with that. 00:20:48.490 --> 00:20:55.030 But if we are like, here's the exact thing you need to know, here's how we know exactly how to teach it, and this is what it looks like. 00:20:55.585 --> 00:21:07.645 We might as well put that into something like Synthesia or something else to say, here's the information that needs to be had in a clean, clear way to make sure you don't mess up and you really understand it. 00:21:08.455 --> 00:21:12.475 Let's, let's go with that, and that is a perfectly acceptable way to use it. 00:21:13.135 --> 00:21:16.615 However, that's not what most teaching really is when it comes down to it. 00:21:16.795 --> 00:21:22.465 Most teaching is us having a conversation, getting to understand where each other's coming from. 00:21:24.265 --> 00:21:24.285 Excuse me. 00:21:25.255 --> 00:21:27.835 And then making decisions from there. 00:21:28.105 --> 00:21:31.585 And that's the kind of thing that I want more of from my kids' teachers. 00:21:31.885 --> 00:21:36.535 And I want less of the stuff that an AI could do better that we should just hand over to the ai. 00:21:39.774 --> 00:21:47.459 Sam Bourgeois: I was in a presentation, uh, in October of this, of this past year, the talk was, uh. 00:21:47.939 --> 00:21:50.639 An AI guru and he was trying to kind of open everyone's eyes. 00:21:50.639 --> 00:21:51.479 It was a great talk, by the way. 00:21:51.479 --> 00:21:54.239 I'm not, I'm not, not poo-pooing it at all. 00:21:54.269 --> 00:21:55.169 It was a great talk. 00:21:55.589 --> 00:21:56.549 Very inspirational. 00:21:56.939 --> 00:21:59.309 But one of the things that he said is he had a mentor. 00:21:59.729 --> 00:22:02.579 Um, this is a business conference and an education conference. 00:22:02.579 --> 00:22:06.689 He had a mentor who was just full of all nuggets of wisdom, just great experiences. 00:22:06.689 --> 00:22:15.599 And so what this guy did was he took all of his writings, his books, manuscripts, a GPT and called it like, I'm just making this up. 00:22:15.659 --> 00:22:17.099 Imagine Jethro, right? 00:22:17.099 --> 00:22:19.049 So GPT. 00:22:19.169 --> 00:22:28.409 Imagine if we took all of your writings, all of your brilliant musings, all of your perspectives, and built a GPT, and then we had an agentic conversation. 00:22:29.279 --> 00:22:31.199 Now, I'm not suggesting we don't have this podcast. 00:22:31.199 --> 00:22:39.029 I'm not suggesting you, you know, you, you, you, you trademark your likeness and all your writings and then do a bot instead of having real human interaction. 00:22:39.389 --> 00:22:43.259 My point is we're talking about individualized instruction. 00:22:43.259 --> 00:22:56.544 Imagine if we had that teacher likeness in the future that could answer questions authority without rambling in a way that the kid wants to have the conversation say, you know, I, I wanna learn had. 00:22:57.299 --> 00:22:58.739 had that experience in college, by the way. 00:22:58.739 --> 00:23:03.329 I had a, he was a Jamaican, I think he was a Jamaican chemistry professor. 00:23:03.389 --> 00:23:03.989 Brilliant. 00:23:04.319 --> 00:23:08.039 But he talked a lot about alligators and sharks, and I didn't know what the heck he was talking about most of the time. 00:23:09.449 --> 00:23:11.039 and he was funny. 00:23:11.039 --> 00:23:11.819 He was really funny. 00:23:11.819 --> 00:23:12.659 He was a great guy. 00:23:13.019 --> 00:23:22.349 But wouldn't it have been great for me to have that silly, rambling 90 minute class Tuesday and Thursday, and then go home with my phone and talk to, I think his name was Dr. 00:23:22.349 --> 00:23:23.009 Darbo, by the way. 00:23:23.009 --> 00:23:24.249 So, Dr. Darbo, if you're watching this. 00:23:24.929 --> 00:23:34.229 Have my Dr. Darbo, GPT and have a conversation about inorganic chemistry it's meaningful for me, when I'm ready to learn, when I'm ready to ask questions. 00:23:34.499 --> 00:23:38.399 How incredibly powerful would that be, right? 00:23:38.489 --> 00:23:40.469 I mean, that's the future. 00:23:41.515 --> 00:23:41.815 Jethro: Yeah. 00:23:42.145 --> 00:23:55.205 And, and like that, that's certainly very possible, and you could already do that without even getting all of his stuff in there because there's enough information in the models already that they could, they could be. 00:23:55.645 --> 00:24:02.215 Answer that, but here's the real key, like it's not enough to just have the conversation, right? 00:24:02.545 --> 00:24:11.725 And just having a conversation with the teacher is typically not enough because each one of us learns and we have our own learning path, and we learn in our own way. 00:24:12.115 --> 00:24:19.135 And, and this is not getting into all the multiple intelligences stuff and all, all that kind of thing, but just our own experiences. 00:24:19.135 --> 00:24:26.905 You and I are gonna walk away from this conversation having different insights that matter to us from what we said. 00:24:26.905 --> 00:24:29.245 And anybody listening is gonna have their own insight. 00:24:29.575 --> 00:24:39.445 Now it's possible and very likely that many of the insights will be similar, but the reality is, is that everybody has their own learning path, and it is unique to them, as unique as their fingerprint. 00:24:40.135 --> 00:24:46.945 In fact even more unique because even identical twins are gonna have a different learning experience than Than their, than their twin. 00:24:47.455 --> 00:24:56.285 So we all have this unique experience, and as you go through life, you build on what it is that you learn all throughout your life. 00:24:56.965 --> 00:24:59.935 And that makes you into the person that you are. 00:25:00.355 --> 00:25:07.525 And there's culture, there's genetics, there's uh, what you actually learned, like academically officially. 00:25:07.735 --> 00:25:12.535 There's also the things that you learned from, uh, negative personal interactions and things like that. 00:25:13.135 --> 00:25:19.180 And what I want is for us to be able to recognize and value whatever learning. 00:25:19.815 --> 00:25:22.185 That happens wherever it comes from. 00:25:22.755 --> 00:25:27.825 And our problem in schools is that we focus on the learning that happens within the four walls of the classroom. 00:25:28.275 --> 00:25:30.915 And that's all that quote unquote counts. 00:25:31.215 --> 00:25:35.745 Because if you already know how to do something, you're still gonna take that test in class. 00:25:35.925 --> 00:25:40.875 You're still going to have to do that report, even if you can de demonstrate. 00:25:40.965 --> 00:25:42.255 I definitely know this. 00:25:42.315 --> 00:25:44.325 Most teachers are not gonna let you outta that. 00:25:45.415 --> 00:25:49.525 However, it's incredibly powerful when you do let kids out of that. 00:25:49.765 --> 00:25:54.925 My second year teaching, I had a student who was so smart and so far advanced for the rest of my kids. 00:25:55.315 --> 00:25:57.325 I knew there was nothing I could teach her. 00:25:57.670 --> 00:26:03.280 As a student in my class, and I said to her, look, I'm not gonna be able to do anything to help you grow. 00:26:03.400 --> 00:26:16.060 So you need to come up with your own thing that you wanna spend your time learning, and you don't have to do any assignments in class, and I will exempt you from everything, but you've gotta be learning at your own rate, at your own pace. 00:26:16.480 --> 00:26:17.920 And she was like, are you serious? 00:26:17.920 --> 00:26:18.550 I said, yeah. 00:26:18.550 --> 00:26:20.440 And she's like, all right, I wanna do Victorian literature. 00:26:20.440 --> 00:26:22.780 And she read four Victorian. 00:26:23.215 --> 00:26:29.575 Literature books, and I don't remember them all, but I know Withering Heights and Pride and Prejudice were two of them. 00:26:30.085 --> 00:26:33.385 And I was like, what in the world is this girl doing? 00:26:33.385 --> 00:26:40.525 But she was totally into it and loved what she was doing, and then she wrote a bunch of stuff about it and, and did a great job. 00:26:40.885 --> 00:26:45.265 Definitely better than what I did in my own English degree in college. 00:26:45.595 --> 00:26:46.915 It was, it was great. 00:26:48.025 --> 00:26:49.885 But she did her own thing. 00:26:49.975 --> 00:27:05.095 Now, what would be really valuable is if she had a, an AI chat bot that was there to help her work through that stuff and talk about goals and how to make plans and what she was trying to do and what she was doing well and where she was struggling, that would've been nice. 00:27:05.335 --> 00:27:11.815 But the thing that was really valuable about my time with her is that we talked during class. 00:27:12.160 --> 00:27:15.730 Once a week and she just said, here's where I'm at and here's what I'm doing. 00:27:16.030 --> 00:27:18.490 And I, and I said, this looks good. 00:27:18.490 --> 00:27:19.900 Let me give you some feedback here. 00:27:20.110 --> 00:27:22.750 This could be improved, that looks great, whatever. 00:27:22.900 --> 00:27:26.560 And we just did that each, each week for the whole school year. 00:27:26.950 --> 00:27:30.580 She produced more in that year than any of my other students. 00:27:31.510 --> 00:27:41.530 Because she was operating at her own level, and what I didn't have was Subway to help push her and keep her going, except just my interactions with her. 00:27:42.040 --> 00:27:42.670 And so. 00:27:43.270 --> 00:27:48.760 If we can have some way to personalize everything that we're doing in class, that would be great. 00:27:48.790 --> 00:27:50.320 Here's a real simple example. 00:27:50.800 --> 00:27:53.650 You're teaching a math class and you have story problems. 00:27:53.650 --> 00:28:03.130 You're trying to teach Pythagorean Theorem and you have kids say, this is what I'm interested in, and then your questions that use the same numbers, just use something that they're interested in. 00:28:03.580 --> 00:28:08.290 And so, you know, it doesn't matter what it is because it's all about learning the math. 00:28:08.530 --> 00:28:09.040 So. 00:28:09.415 --> 00:28:20.605 You have 500 questions that you can generate instantaneously that each one relates to, gives each kid 10 different options for how they want to answer that specific question. 00:28:21.145 --> 00:28:24.505 And then like that could be generated in a heartbeat. 00:28:24.595 --> 00:28:31.465 And that is the amazing thing because then a kid might actually be interested in it if they're like, when will I ever have to use this? 00:28:31.465 --> 00:28:36.655 And you're like, oh, here's a place where you could use it and something you're interested in that becomes really valuable. 00:28:37.754 --> 00:28:37.994 Sam Bourgeois: Yeah. 00:28:38.369 --> 00:28:42.179 Yeah, the diameter of the death star compared to the opening 00:28:42.265 --> 00:28:42.685 Jethro: Yeah. 00:28:43.199 --> 00:28:43.799 Sam Bourgeois: the tunnel, right? 00:28:43.799 --> 00:28:44.039 Yeah. 00:28:44.099 --> 00:28:44.309 Yeah. 00:28:44.339 --> 00:28:44.519 I, 00:28:44.545 --> 00:28:45.115 Jethro: Yes. 00:28:45.119 --> 00:28:45.749 Sam Bourgeois: totally agree. 00:28:45.959 --> 00:28:46.349 I totally 00:28:46.495 --> 00:28:46.975 Jethro: Yeah. 00:28:47.245 --> 00:28:49.825 So those are the kinds of things that we want to do, right? 00:28:49.919 --> 00:28:55.799 Sam Bourgeois: we did that whenever we were in the classroom, but it was exceedingly difficult and taxing 00:28:55.945 --> 00:28:56.455 Jethro: Oh, yeah, 00:28:56.669 --> 00:28:58.169 Sam Bourgeois: and we couldn't do it for every kid. 00:28:58.199 --> 00:28:59.069 We could just do it 00:28:59.125 --> 00:28:59.515 Jethro: yeah, 00:28:59.669 --> 00:29:01.559 Sam Bourgeois: a handful whenever it was possible. 00:29:01.589 --> 00:29:01.919 Right. 00:29:02.215 --> 00:29:02.605 Jethro: yeah. 00:29:02.845 --> 00:29:05.095 And so, so what great teachers do. 00:29:05.680 --> 00:29:12.490 They default to, uh, things that they think most of their kids will get and will like, and that's great. 00:29:12.550 --> 00:29:13.990 I, I so appreciate that. 00:29:14.470 --> 00:29:22.720 But they could do so much better if given the proper tools and the proper understanding of how to use those tools and when to use them and when to make 'em right. 00:29:22.750 --> 00:29:24.850 Like that is incredibly powerful. 00:29:27.505 --> 00:29:29.290 Oh, you just muted yourself somehow. 00:29:31.154 --> 00:29:31.634 Sam Bourgeois: Apologies. 00:29:31.724 --> 00:29:31.964 I guess 00:29:31.990 --> 00:29:32.200 Jethro: There you go. 00:29:32.204 --> 00:29:33.044 Sam Bourgeois: I was quiet too long. 00:29:34.604 --> 00:29:39.734 Um, you know, what I think about though is I think about the, think about the risk. 00:29:39.734 --> 00:29:42.614 I, I have to, that's just my security brain, right? 00:29:43.064 --> 00:29:44.984 And I don't like to stifle innovation. 00:29:45.074 --> 00:29:49.814 I don't like to, put up, put up too many blocks and obstacles, but. 00:29:50.894 --> 00:29:56.864 I do think about data that we're collecting and, and I, I worry about that. 00:29:56.864 --> 00:30:02.324 Like it concerns me like, not to change the subject from ai, but like, you know, you were talking about Siri. 00:30:02.744 --> 00:30:07.934 I mean, so Siri everything you say, waiting for the queue, the, the trigger. 00:30:08.024 --> 00:30:08.624 Hey, Siri. 00:30:09.284 --> 00:30:16.334 Um, the question I have is like, are we just piling on all this data and metadata. 00:30:17.264 --> 00:30:20.294 You know, like what is, is there, is there a risk there? 00:30:20.714 --> 00:30:26.054 You know, is it, are we creating profiles that can be used, know, potentially in a negative way? 00:30:26.054 --> 00:30:31.694 Like I, and again, I'm not, not thinking about it like, uh, like barcode tattoos or anything like that. 00:30:31.694 --> 00:30:45.164 What I'm thinking about is like we create these learning profiles and is it possible that the profiles don't reflect the learner, and that if given a different opportunity for a different path, they could be. 00:30:45.539 --> 00:30:47.939 On a different trajectory, they could go faster, slower. 00:30:48.359 --> 00:30:54.419 Um, are we creating biases in the system based on that, on that profiling of information? 00:30:54.419 --> 00:30:59.069 Are we saying, now this kid, you know, I'm not saying we'd write 'em off, but this kid's obviously a low performer. 00:30:59.069 --> 00:31:01.019 Let's, let's slow things down for them. 00:31:01.769 --> 00:31:04.409 know that there's always gonna be a response, like, no, no, no. 00:31:04.409 --> 00:31:14.579 The, the AI could always encourage and uplift and train, but from that general perspective of say least privilege, and I say. 00:31:15.374 --> 00:31:16.124 data's bad data. 00:31:16.124 --> 00:31:16.844 I don't want any data. 00:31:16.844 --> 00:31:18.374 I don't want to, I don't wanna possess your data. 00:31:18.374 --> 00:31:19.934 There's liability in anything that I have. 00:31:19.934 --> 00:31:20.144 Right. 00:31:21.134 --> 00:31:26.384 as schools start to compile all this information about learners, what are your thoughts about that? 00:31:26.384 --> 00:31:29.204 And it's, eh, we gotta do what we gotta do. 00:31:29.204 --> 00:31:29.444 Right? 00:31:29.444 --> 00:31:31.934 Like we, it's part of the, part of the success. 00:31:33.100 --> 00:31:33.430 Jethro: Yeah. 00:31:33.610 --> 00:31:34.810 You know, I think one of the. 00:31:35.290 --> 00:31:40.450 One of the worst things is that we have all this data about students already and we don't use it to benefit them. 00:31:40.660 --> 00:31:42.580 So, so that's an issue too. 00:31:42.790 --> 00:31:51.820 And, and that's a real problem because, uh, we're missing out on opportunity to bless our kids' lives with the information that we do have. 00:31:52.150 --> 00:31:53.800 So there are some aspects of that. 00:31:53.800 --> 00:31:54.760 On the other hand. 00:31:55.205 --> 00:32:10.925 We definitely should not be keeping a profile of these kids because they will change, and we certainly don't want to do anything that would force a kid lower in their capability than they're actually at. 00:32:11.165 --> 00:32:15.905 We'd never want to do something that would limit a child's potential for growth. 00:32:17.170 --> 00:32:18.910 I can definitely see that happening. 00:32:18.910 --> 00:32:30.670 If you are, if your references are always about sports, and so then the AI only gives you sports related, uh, content, then it never gives you a chance to see something else. 00:32:30.670 --> 00:32:37.750 And so in, in the design of these things, those kinds of considerations I think should be made as well. 00:32:38.260 --> 00:32:45.220 That being said, you, you don't want to just be capturing everything and, uh, having it be, um. 00:32:45.760 --> 00:32:46.810 There forever. 00:32:46.900 --> 00:32:51.640 You know, you want the kids, you want kids to be able to be forgotten from the system. 00:32:51.790 --> 00:32:56.590 And to be honest, with the way AI is right now, nobody knows how to do that. 00:32:56.770 --> 00:33:02.770 And nobody understands how to make that actually happen because we don't understand how it works well enough. 00:33:02.770 --> 00:33:09.190 And I'm not just talking about me, you know, the uneducated principal over here, I'm talking about act. 00:33:10.045 --> 00:33:16.645 Actual data scientists who are creating these tools don't know what's happening inside the black box of ai. 00:33:16.675 --> 00:33:18.145 And that's, that's very real. 00:33:18.355 --> 00:33:25.165 They don't know what's being saved completely, and they have some ideas, but they're not totally sure exactly how it all is working. 00:33:25.165 --> 00:33:28.225 You can correct me if I'm wrong, but that's how I understand it. 00:33:28.225 --> 00:33:28.675 So 00:33:29.794 --> 00:33:30.334 Sam Bourgeois: No, you're, you're 00:33:30.475 --> 00:33:31.105 Jethro: go ahead. 00:33:31.264 --> 00:33:31.714 Sam Bourgeois: no, you're right. 00:33:31.714 --> 00:33:40.684 And there's, there's some, there's some ethical thought exercises that I've gone through, and if, if you guys have never heard some of these perspectives, I'll give you one or two that are kind of the juicy ones. 00:33:41.374 --> 00:33:42.409 You know, there's, there's a lot of people who would argue. 00:33:43.169 --> 00:33:46.019 That, you know, ai, whatever the heck that is, right? 00:33:46.019 --> 00:33:46.739 Like it's, you know, 00:33:46.900 --> 00:33:47.229 Jethro: Yeah, 00:33:47.549 --> 00:33:49.079 Sam Bourgeois: your, your LLM, whatever it's you're using. 00:33:49.270 --> 00:33:51.910 Jethro: the marketing term for what's been going on for decades. 00:33:51.989 --> 00:33:52.529 Sam Bourgeois: exactly. 00:33:52.660 --> 00:33:52.930 Jethro: on. 00:33:53.189 --> 00:34:01.139 Sam Bourgeois: Um, there's, there's a, there's a, that some people say, you know, all that art, that AI art, not AI art. 00:34:01.169 --> 00:34:10.529 It's just a, very poor copy, a very poor amalgamation of real art that's being plagiarized and copied. 00:34:10.829 --> 00:34:11.069 And if. 00:34:11.549 --> 00:34:12.509 That's what you're going for. 00:34:12.539 --> 00:34:12.839 Okay. 00:34:12.839 --> 00:34:13.259 Got you. 00:34:13.259 --> 00:34:13.559 Got it. 00:34:13.589 --> 00:34:14.009 Great. 00:34:14.069 --> 00:34:14.699 Super duper. 00:34:15.149 --> 00:34:20.819 Same thing could be said about all the, the writing that we, you know, that we might produce from these things. 00:34:20.819 --> 00:34:31.079 I mean, there's the, the story of the, the attorney, uh, I think it was up north, uh, he had a big case, did a bunch of research, turned in all of his information, cited all of his works, and the whole thing was made up. 00:34:31.109 --> 00:34:32.099 Like none of it was even 00:34:32.199 --> 00:34:32.529 Jethro: Yeah. 00:34:32.769 --> 00:34:33.219 Yep. 00:34:33.389 --> 00:34:38.039 Sam Bourgeois: So we hear those things and those are like the, I call it the fud, you know, the fear, uncertainty and doubt. 00:34:38.769 --> 00:34:39.099 Jethro: Yep. 00:34:39.329 --> 00:34:39.779 Sam Bourgeois: those things. 00:34:39.779 --> 00:34:40.144 That's not my point. 00:34:41.024 --> 00:35:00.764 my point is like, there are ethical considerations to be made and I'm, you know, I'm thinking about eu, like eus got a lot of regulations around privacy in particular, uh, their new ai, uh, their new ai, uh, framework, uh, that just came out middle of last year, middle of of 2025. 00:35:02.444 --> 00:35:08.354 I think that's gonna be interesting to see where the United States goes with some of those things about data privacy and protection. 00:35:08.504 --> 00:35:09.914 And you used the word I was really. 00:35:10.814 --> 00:35:11.204 on that. 00:35:11.204 --> 00:35:14.474 You said, um, I'm paraphrasing the right to be forgotten. 00:35:15.434 --> 00:35:17.084 You know, do we, is that a right? 00:35:17.174 --> 00:35:21.524 Is that a, is that something that as a US citizen, do we have a right to that? 00:35:21.524 --> 00:35:23.174 Can I say, I wanna be forgotten? 00:35:23.174 --> 00:35:24.554 I don't wanna be a part of your system. 00:35:24.944 --> 00:35:26.264 I don't wanna train your model. 00:35:26.264 --> 00:35:29.624 You know, like, are we, I, I wonder Jethro like. 00:35:30.614 --> 00:35:36.914 All the people selling us the stuff, the AI stuff, they turn on AI from the textbook manufacturer. 00:35:36.914 --> 00:35:39.464 They turn on AI from PowerSchool, they turn on ai, whatever. 00:35:40.184 --> 00:35:48.044 Is it possible that they're just selling us a platform that we're actually doing the work to train to 00:35:48.210 --> 00:35:48.500 Jethro: Yeah. 00:35:48.524 --> 00:35:49.994 Sam Bourgeois: information back, right. 00:35:50.755 --> 00:35:51.145 Jethro: Yeah. 00:35:51.235 --> 00:35:55.285 I mean the, the challenge with this is that the, the training. 00:35:55.825 --> 00:36:03.144 Data is valuable and worthwhile, uh, to the companies and for us, right? 00:36:03.475 --> 00:36:06.834 So if it knows that I like sports, then it can. 00:36:07.930 --> 00:36:10.839 Bring up things that are related to sports for me. 00:36:10.930 --> 00:36:16.750 And, you know, there's, there's all kinds of ways where that knowledge about you is beneficial. 00:36:17.230 --> 00:36:20.589 That's why people love the algorithm on social media. 00:36:20.890 --> 00:36:36.279 And I would, I don't know that people personally love it, but they like being on social media and like seeing things they like because the algorithm has been trained on the things that you look at, the things that you leave up, the things you know, that you're paying attention to and click on and like, and all that kind of stuff. 00:36:36.279 --> 00:36:36.700 So. 00:36:37.089 --> 00:36:48.789 So those things do matter and, and we want to take advantage of that, but we also have to recognize that that might not be the best, the best way to manage things. 00:36:48.819 --> 00:36:52.240 And there may be benefit in starting fresh every time. 00:36:52.419 --> 00:36:56.979 There may be benefit in starting fresh on some things and going back to other things in other ways. 00:36:57.009 --> 00:37:03.339 And you know, the truth is we just don't know s the answers to so many of these questions yet. 00:37:03.895 --> 00:37:09.115 And, and a lot of people will say that and say, we don't know, so we just keep using it. 00:37:09.415 --> 00:37:18.295 But what we really need to be thinking is, let's, since we don't know the answer, let's be intentional and start asking some of these questions so that when we see something that's a red flag. 00:37:19.299 --> 00:37:23.619 We can shut it down or we can not take it to begin with. 00:37:23.740 --> 00:37:30.399 And so for example, I, I gave the example of teachers using AI to just create worksheets, right? 00:37:30.999 --> 00:37:39.159 If that's what the tool is there for, then there's no point in having the tool in my mind, because we don't need more worksheet creators. 00:37:39.490 --> 00:37:39.789 So. 00:37:40.464 --> 00:37:44.094 That's not how I would suggest we teach anything in education. 00:37:44.514 --> 00:37:55.254 Um, and, and what I mean by that is, is that everybody does the same exact thing and it just makes it so easy for the teacher to grade and correct and, and give feedback on. 00:37:55.554 --> 00:37:57.324 And what we really want are. 00:37:57.700 --> 00:38:04.689 Opportunities for individualization and understanding where people are at and helping them in their own personal learning journey. 00:38:04.899 --> 00:38:11.109 That extends far beyond what happens in the four walls of the classroom, and so that's what we want to be looking at. 00:38:11.169 --> 00:38:16.359 If the tool is just to recreate standardized testing, then let's not use it. 00:38:16.689 --> 00:38:22.930 If the tool is to make it easier for us to assess really what kids understand, then. 00:38:23.994 --> 00:38:27.144 That sounds a lot better, and we can start with those kinds of questions. 00:38:27.144 --> 00:38:36.474 What kind of education system do we want to have and is it worthwhile for this tool to be used to help us get to that point of where it's at? 00:38:36.864 --> 00:38:39.114 Tho those are the kinds of questions we should be asking. 00:38:39.114 --> 00:38:45.924 And when something gives us a red flag and it's like, oh, we're going to use your data to train the our future models. 00:38:46.539 --> 00:38:49.269 We need to be thoughtful about that in some situations. 00:38:49.269 --> 00:38:59.109 Yes, we should be doing that because if we're in a school, and this is training us on how to teach reading better, I want the data to train the model so that kids learn how to read faster. 00:38:59.829 --> 00:39:11.619 That's not a bad thing, but if the, if the data is used then to say, uh, you know, we're gonna train this model and we're gonna use your personal information and refer back to you later. 00:39:11.634 --> 00:39:26.904 If that's not a good thing and we just don't understand how this stuff works well enough, nobody understands how this works well enough to really say, this is the true harm in using your data, and this is the true benefit in using your data. 00:39:26.904 --> 00:39:27.955 We just don't know yet. 00:39:30.535 --> 00:39:35.245 So for that reason, we start with don't use my data to train the model 00:39:35.414 --> 00:39:35.774 Sam Bourgeois: Mm-hmm. 00:39:36.444 --> 00:39:39.535 Jethro: until we understand what it's for, and then maybe we can. 00:39:39.704 --> 00:39:41.534 Sam Bourgeois: Or create enclaves whenever possible. 00:39:41.534 --> 00:39:42.284 Create enclaves. 00:39:42.284 --> 00:39:42.734 There's a happy 00:39:42.955 --> 00:39:43.314 Jethro: Yeah. 00:39:43.364 --> 00:39:43.724 Sam Bourgeois: can we, 00:39:43.884 --> 00:39:44.274 Jethro: Yep. 00:39:44.414 --> 00:39:44.744 Sam Bourgeois: Yeah. 00:39:45.564 --> 00:39:45.774 Jethro: Yeah. 00:39:45.774 --> 00:39:54.115 So we're gonna do all this stuff in this own siloed box over here so that it's not referring back to anything else, not connected to anything else. 00:39:54.415 --> 00:40:00.625 And then as we can learn better, then maybe we can say, all right, let's go some, let's take this somewhere else. 00:40:00.625 --> 00:40:08.004 So, for example, Claude, I think, is doing this thing where, when the, when the context of your message gets too long, your check gets too long. 00:40:08.619 --> 00:40:12.879 It'll summarize it all and save it so that you have that context. 00:40:13.299 --> 00:40:21.069 That is a good way to say, here's what it's remembering about us in our conversation, and then you can actually make a decision about that. 00:40:21.309 --> 00:40:23.949 Most of the time, you can't make a decision about it at all. 00:40:27.779 --> 00:40:28.499 Sam Bourgeois: That idea. 00:40:28.559 --> 00:40:29.189 I like that idea. 00:40:29.189 --> 00:40:29.669 It's interesting. 00:40:29.669 --> 00:40:31.169 I hadn't, I hadn't really thought about that. 00:40:31.259 --> 00:40:36.779 Um, I also thought about maybe we create systems that are kind of school safe. 00:40:36.929 --> 00:40:38.339 If that's, if that even makes sense. 00:40:38.339 --> 00:40:41.789 Like a pseudo anonymization. 00:40:42.284 --> 00:40:42.644 Right. 00:40:42.644 --> 00:40:45.014 Like, I mean, we, we already do that for the most part, right? 00:40:45.014 --> 00:40:46.544 We already attempt to do that. 00:40:49.694 --> 00:40:50.234 interesting. 00:40:50.264 --> 00:40:50.414 Yeah. 00:40:50.414 --> 00:40:51.194 Interesting thought though. 00:40:51.194 --> 00:40:57.854 I, I think, uh, I think we've been promised that in many industries by many tools and it hasn't actually existed. 00:40:58.214 --> 00:41:00.254 So that's, I do con I have concern there. 00:41:01.209 --> 00:41:02.169 Jethro: Yeah, for sure. 00:41:02.529 --> 00:41:05.230 And a lot this comes down to trust. 00:41:07.029 --> 00:41:16.760 Um, the, the companies and you have to determine if you can trust them, and, and that is a huge question mark for many of these companies that, that you just don't know about. 00:41:17.339 --> 00:41:20.009 Sam Bourgeois: Well, it, and it it, you might do a risk assessment. 00:41:20.459 --> 00:41:21.989 That was where I started this conversation. 00:41:22.019 --> 00:41:24.149 That was my, that's my security guy, right. 00:41:24.464 --> 00:41:30.284 Uh, risk assessment may actually be a quality assessment, but then you don't know what happens behind the scenes. 00:41:30.284 --> 00:41:32.864 Like didn't, didn't Apple own PowerSchool. 00:41:32.864 --> 00:41:36.524 If you go back far enough, like I I, those are the kind of questions we have to ask ourselves. 00:41:36.669 --> 00:41:37.059 Jethro: Yeah. 00:41:37.094 --> 00:41:46.394 Sam Bourgeois: if, if the industry has already demonstrated how they will operate data brokers, uh, click bait. 00:41:47.474 --> 00:41:48.044 economy. 00:41:48.374 --> 00:41:48.674 Right? 00:41:48.674 --> 00:41:52.874 Very inhumane approach to how we interact as humans with our technology. 00:41:53.684 --> 00:41:59.444 that's what the industry has already demonstrated to us, why would we expect anything different if they sold to an education market? 00:41:59.834 --> 00:42:01.844 And that's potentially a concern. 00:42:02.024 --> 00:42:02.294 Yeah. 00:42:03.024 --> 00:42:03.384 Jethro: Yeah. 00:42:03.474 --> 00:42:08.724 And then what happens when the company that you have contracted with gets acquired by somebody else? 00:42:09.324 --> 00:42:13.584 Uh, and do you, are you forced into that new contract? 00:42:13.584 --> 00:42:15.444 Do you want to be part of that new company? 00:42:15.834 --> 00:42:29.214 And, you know, let's say you're working with a, a local mom and pop ai shop that is providing you a, a good service, and then they sell to PowerSchool or HMH or Pearson or any of these other publishers, and they're like. 00:42:29.874 --> 00:42:32.334 All right now that's managed by them. 00:42:32.394 --> 00:42:36.354 And it's no longer this little safe box on your desk in your school building. 00:42:36.745 --> 00:42:44.365 It's part of their server and it's connected to their thing, but now you have insights into all the, all the other stuff that they produce and publish. 00:42:44.365 --> 00:42:47.185 And is that a benefit or is that actually a hindrance? 00:42:47.544 --> 00:42:49.404 And those are the questions you gotta ask. 00:42:49.404 --> 00:42:50.274 You gotta wonder about. 00:42:50.609 --> 00:42:59.069 Sam Bourgeois: And God forbid they're not gonna, they're not gonna give you a question answer back and forth on this one, but you know, God forbid they, they get breached, which is 00:42:59.229 --> 00:42:59.589 Jethro: Yep. 00:42:59.909 --> 00:43:00.779 Sam Bourgeois: happened just a 00:43:00.850 --> 00:43:01.390 Jethro: Yes. 00:43:01.394 --> 00:43:01.564 Yep. 00:43:02.234 --> 00:43:04.964 Sam Bourgeois: If they were breached, what happened to all that training data? 00:43:05.054 --> 00:43:12.524 You know, like imagine all those profiles and learners, like, not to blow this outta proportion, but we, we see what happens in the real world. 00:43:12.524 --> 00:43:16.004 We know what Cambridge Analytica did in 2016. 00:43:16.064 --> 00:43:21.584 If memory serves with our US elections, we know what, what they would do with the data if they had access to it. 00:43:21.584 --> 00:43:26.324 So how would that data be used, nefariously, should there be a breach or, or some kind of leak or exposure? 00:43:28.274 --> 00:43:34.720 Jethro: All, all kinds of things that, that we just don't know the answer to, and we have to recognize that we don't know the answer. 00:43:34.724 --> 00:43:34.894 And. 00:43:35.859 --> 00:43:46.180 Make the best decision we can with the information we do have and be ready to intervene when things, uh, are not going well, which is a, a scary place to be for sure. 00:43:46.720 --> 00:43:51.549 But at the same time, you can't just ignore it and say, this is, we're not talking about this. 00:43:51.549 --> 00:43:54.910 We're not doing anything with it because it is the world that we live in. 00:43:54.910 --> 00:43:58.810 And, and just because you block it at your school doesn't mean the kids aren't using it at home. 00:43:59.245 --> 00:44:01.435 And we don't have any control over that. 00:44:01.524 --> 00:44:15.535 But the reality is, is they have access and we can at least be partners with families in that rather than, uh, just saying, one, you're on your own, or two, we're unlocking the floodgates here. 00:44:15.805 --> 00:44:17.964 Neither one of those are good solutions. 00:44:20.304 --> 00:44:20.894 Sam Bourgeois: Well said man. 00:44:20.984 --> 00:44:21.464 Well said. 00:44:21.879 --> 00:44:22.240 Jethro: Yeah. 00:44:22.329 --> 00:44:23.919 Well, Sam, this has been awesome. 00:44:23.979 --> 00:44:33.819 Thank you so much again for, for doing this and being part of this and, uh, everybody who's listening, thank you for listening to Artificial Intelligence, real Talk, and any final words from you. 00:44:33.819 --> 00:44:34.930 Sam, I'll let you have the last word. 00:44:36.134 --> 00:44:40.514 Sam Bourgeois: Man, I'm, I'm just, it's always a pleasure chatting with you and, uh, as you mentioned, it's always good to learn. 00:44:40.514 --> 00:44:45.344 This is, this is something we will never replace with AI, is these kind of real, authentic conversations. 00:44:45.344 --> 00:44:46.304 So thank you for your time. 00:44:46.980 --> 00:44:47.634 Jethro: That's right. 00:44:47.725 --> 00:44:57.024 Even I said I was gonna have let you have the officer, but now I'm not even, even when we do this kind of a thing with ai, it still is not the same as doing it with another person. 00:44:57.115 --> 00:44:59.365 So you, you are absolutely right. 00:44:59.515 --> 00:45:00.055 Thanks man. 00:45:00.280 --> 00:45:00.700 Sam Bourgeois: Take care. 00:45:01.120 --> 00:45:01.270 Bye.