Ep. 27: Why Is AI So Polarizing?

[00:00:00] Foreign. [00:00:05] Welcome M to ChatGPT Curious, a podcast for people who are, well, curious about ChatGPT. I'm, um, your host, Dr. Shantae Cofield, also known as the Maestro, and I created this show to explore what ChatGPT actually is really, though, are the files in the computer, how to use it, and what it might mean for how we think, work, create and move through life. Whether you're skeptical, intrigued, or already experimenting, you're in the right place. All that I ask is that you stay curious. All right, let's get into it. [00:00:38] Hello, hello, hello, my curious people, and welcome to episode 27 of ChatGpt Curious. I am your grateful host, the Maestro, and today I'm asking the question, why is AI so polarizing? [00:00:51] People have seemingly chosen AI as the proverbial hill, the metaphorical hill to die on, and I find it fascinating. Like, absolutely fascinating. So we're going to talk about that real quick. First, an update from OpenAI. Since this is chat GPT curious, and I feel somewhat obligated to talk about Chat GPT in some way, shape or form. So, from the AI, uh, excuse me, from the open AI release notes on January 15, 2021. Wow, just had like a stroke there. [00:01:23] 2026. [00:01:25] Uh, improved memory for finding details from past chats. This is available for plus and Pro plans. [00:01:33] The little description here when reference. When reference chat history is enabled, ChatGPT can now more reliably find specific details from your past chats. When you ask, any past chat used to answer your question now appears as a source so you can open and review the original context. This memory improvement is now available for plus and Pro users globally. [00:01:56] So go search for the things if you need them. Uh, chat should apparently be better at finding them. I've always honestly had decent luck and I say always. I don't think I've always used this search feature, but I've used it a good amount, you know, in the past however many months. Um, and I had like a decent amount of luck with it. Definitely, uh, better than searching Apple Mail. Yes, that's what I use. I use it on my phone, use it on my iPhone, and I have always used it and I love it. Um, but the search is like, kind of shitty. Um, but search on, um, chat has always been pretty good. So I'm not like, in need of a huge improvement, but I won't complain if they did in fact improve it. So let's move on to today's main topic, which is why is AI so polarizing? It really feels to me like some People have done dug their heels in and they have chosen AI as the hill to tie on. Like, they absolutely hate it. They can't really say why, but they're so against it. And I wanted to sit with myself and dig into why that might be the case. Like, yes, I could probably ask someone, but I don't personally know anyone who truly hates it. I know of some folks who are scared of it, but I also don't need that kind of negativity in my life. So I'm gonna talk to myself, and you folks can listen to the conversation that had. Uh, uh, so first off, when folks talk about AI, I do believe that they are largely referring to LLMs. Like, when they say that they hate AI, they're against AI. I do believe that they're talking. They're referring to LLMs, which I think they don't even fucking know what an LLM is. Y' all listening to this podcast episode? You're listening to this podcast, rather, you've been through all the episodes in the beginning episodes and like, you know, LLM, large language model. You understand it's math. You know what's going on. I think the majority of people that are like, I don't like AI, they are referring to LLMs. They don't even know what an LLM is. And I bring this up because I think that it adds to my argument that people don't actually hate the technology. They don't even know what the technology is. [00:03:56] Right. To me, there is something deeper. There is something bigger and worth noting. I am not, you know, diving into this to try and convince anyone that they should use AI or they should use LLMs. I don't give a fuck. I literally don't care if you use them or not. I will. I gave up the business, left. The business of convincing a long time ago is the worst business to be in. So this is not me, you know, being like, oh, let me come up with some arguments and get them to use it. I literally don't give a. This is just me being curious and like, what is it? Why is this the thing that you're, like, so anti. You know, you're so against. And you tied to the environment, and you never give a. About the environment, and you never gave a. About the environment before. Like, what is it? [00:04:36] So side note or tangent from a tangent, if you want to dive into the topic of what is AI actually is, right, you want to answer the question, what is AI? I did an entire episode on it. That was episode seven, and I will link that in the show notes. But what do I think it is that folks actually hate? Right? Uh, what is it that folks are actually pushing back against that AI is just a proxy for. In my humble opinion, it is the forced and shittification of everything, literally everything, by people and corporations with way too much money. [00:05:08] And I get that. I understand that. 100 right there with them. I'm thinking about a fridge right now. Like, Lex and I just signed a new lease and where we extended our lease, um, we signed a lease for five years, which is amazing. And in California they have a, like a new law that goes. That went into effect January 1st. Like, there needs to be refrigerator, a working refrigerator in the apartment. Because I don't know if you knew this, but there needs to be. [00:05:35] That didn't used to be the case. And when I moved here from New York, I was like, what? This is wild. Some of these places don't have fridges. Like, I have to buy one. Like, I gotta move that thing in. Very weird to me. Uh, so now they have to have them. But the reason I was thinking about this is that fridges used to be like, amazing. And this is like before my time. This is like, you know, I'm watching reels and I'm like, this thing is a tank and has like a lazy Susan in it. And it's just done so well. And now we have, we have a lay everything and ification. So the definition of insertification, the process, or if you're in Canada, a process by which platforms and products systemically. Nope. Systematically get worse over time as companies shift priorities from users to creators, business, customers, and then onto shareholders. [00:06:23] All right? They are going away from the user, away from the consumer, and they're saying, can we increase the shareholder value? Can we put more money in their pockets? How do we do that? Make the products shittier? [00:06:38] All right? That's what they do. Uh, the Macquarie Makary dictionary. I don't know how to pronounce that word. Actually named in shittification the word of the year for 2023. And it's true. And I get it. I get the grumpiness, I get the being upset, I get the pushback, I get it. [00:06:55] But why choose AI as the pinata poster child, right? Because it's low hanging fruit. It's vague. Like I just said, like, you know, two minutes ago. Like, what even is AI do people know? They're just like, AI is bad. Like, well, what is it? What are you talking about? Because AI has actually been here for quite some time, I think you mean LLMs, but I don't even think you know what you mean. [00:07:16] Which is a good thing if it's. It's easy to make an argument against it. Right? [00:07:19] It doesn't always work great. We know this. Like, do I love it? Do I use it so much? I made a whole podcast about it. Yes. But we also know that sometimes you're like, what the fuck is going on? I made a whole episode about, you know, why it's so bad sometimes. [00:07:33] Uh, the next point. Why? Why? It's become the pinata poster child. There seem to be very few use cases for the average person. I think, you know, more people are slowly catching, um, on. But like, for most people in their day to day, like, they don't really need it outside of like maybe making a recipe or something like that. Like, it's not this, like, you know, life changing. So helpful thing. This. I've spoken about this before. This is the backwards marketing that OpenAI did, right? Where they said, here's a solution, go find a problem. That is not how you build a product. That's not how you market, right? Uh, you have people, you attract people, then you listen and then you build a solution for their problems that they know they have. This is completely backwards. It's just like, people are like, what is this trash? I don't even need it. I don't even want it. Which brings us to the next point. It is being forced on everyone. It is opt out, not opt in. And it seems impossible to opt out all, uh, right? It's just in everything. And you're like, I don't even want it. How do I get rid of it? Right? Uh, it's giving that U2 album that was automatically added to everyone's itunes account in 2014. Right? We have never forgotten about that. We have never gotten over that. That is what AI is doing. These AI companies are doing. [00:08:42] Next point. The media talks about it all the time, albeit, uh, you know, albeit often incorrectly. But it's everywhere, right? It is like a lightning rod. And it just gets all these stories. And whenever we see the stories, it's often in the context of a lot of money, like insane amounts of money. And it's just like, fuck, another company that's making so much money by putting out a shitty product, right? And suddenly people are like, I hate AI. [00:09:06] AI is the worst. And then the biggest one, in my opinion, is that the costs are associated with the environment, right? The environmental tie makes it so easy for folks to latch onto this and be like, it's Bad, right? Especially the water argument, which is largely incorrect. We've gone over that in what, episode two, Right, but water is concrete, right? It's visual, it's emotion, it's emotional, it's sticky. So most, they can feel like they can touch it and they can see it and visualize it, and they're using like bottles of water to represent this. Meanwhile, most people have no idea about baseline data center usage, regional water recycling, comparative industrial water use. We talked about this in episode two with things like agriculture, right? Your or your own personal use for energy, right in your house. People don't. They don't. They don't. When else do you measure M consumption in terms of bottles of water only for AI? And so suddenly you're like, fuck this, look how much water is being used. Meanwhile, we have no idea what, how much water is being used for anything else. And whether it's relatively small or large compared to other things. And we know that compared to things like agriculture, it's way smaller, right? So the claims feel true that they hear and people. That people hear and that they read. Even when, you know, even if the claim is incomplete or misleading, which makes it so easy to just be like, I hate AI, it's bad, right? [00:10:28] This, this focus on the environment is actually the main thing that prompted this episode because it comes up so much and I'm honestly just like, why this? Why now? Don't get me wrong, I am all. Or environmental protections. And after doing that second episode and like researching everything, I was like, oh my God, this needs to be like the most. The number one thing that we're focusing on actually right now, like Trump ice. That's the number one thing. The collapse of the United States, you know, as an empire, that's, that's what we need to be focusing on is getting our government correct and getting ice the out of here. [00:11:04] But environment like we all going to die. [00:11:08] And when I read all the things about it, I was like, holy shit. Which was what really made me be like, why do people suddenly care about AI when this is such a problem in so many other areas and there's so many bigger, you know, dial movers that we can, that we can move, right? That we can turn. [00:11:25] Data centers in general, they have been around as we understand them, this idea of like client server computing, mini computers, dedicated server rooms. This has been around since like the 80s. It's not new. [00:11:36] The average person, the average American never used the words Data center before 2025, right? And these things been around before then. This is not in the same kind of context that we know them, but at least since the 80s. So why now? [00:11:50] Worth noting, and I'm not trying to defend data centers. I'm just trying to present data, present information that speaks to, like, why this doesn't make sense in my head that people are so against this and you know, that it's not AI that they're against. It's the insertific of fucking everything. And I get that. But worth noting, it's a little tidbit about data centers. They are actually incredibly efficient, right? Yes. It's the technology that's in there. And, and because energy is expensive, they are, um, incentivized to like, really optimize the technology. But it's mainly because of economies of scale, right? That, that concept, that principle, when you, like we have. With the data center, you have centralized cooling, centralized power delivery, you know, hardware utilization. That's all happening in one place as opposed to like everyone having their own thing. We can understand that for anything that like, like a bus is like individual car, right? It's the same kind of concept. There is more efficient, right, Than. Than having a bunch of these cars on the road. We know this, right? [00:12:46] But flip side, two things can actually can absolutely be true at once, right? Data centers are extremely efficient per unit of compute, but total energy demand still rises because demand explodes, right? So like, if I use that, the car and the bus analogy, like, yeah, better to have a bus than a car. But if we have like a thousand million buses, it's like, okay, this is like, still bad, right? [00:13:07] And the issue here is that AI and corporations are driving this, this demand, right? So just want to, like, you know, I want to give information because y' all are curious, I think. Um, but back to my point, and the point of this episode is that AI didn't create data centers, but it catches all the smoke, all of it, right? So to give you a few more numbers, use a few more specific numbers, right? And this is about the energy side. We're talking about water before, um, we'll talk about actual, um, energy usage. Right? So US data center electricity use before 2024, 2025, I'm just going to go through a few years. 2010, right. This is about 1 to 1.5 of total US electricity was used by data centers. [00:13:57] Um, 2014, it was about 1.8%. 2018, it was about 2%. Right. Again, that's 2% of total US electricity. [00:14:06] Uh, going to date. It was going to date was data center electricity. [00:14:11] 2020, that was about 2 to 2.5%, 2022, we're up to 3%. And 2024, 2025, that's up to 4%. [00:14:20] Uh, so we see that this, this, it is going up. Right? And the percentage usage was pretty flat, around 1 to 2% for over a decade by 2010 to 2020. [00:14:31] Right. Because of like we were talking about it before efficiency gains, they were offsetting the growth. We see this step change from 2 to 3% to 4% and you know, occurring from 2020, 2024. And that aligns with the hyperscale expansion, uh, and AI workloads. Absolutely. But this is why it feels so sudden. But it's not like it's, you know, 50% of total U.S. electricity is going to these data centers. It's 4%. Um, but again, for what it's worth, I am not justifying the usage. Right. I'm not saying that we need all of this energy uses electricity usage. I've said this before. The US particularly open AI is taking a very American, you know, Ford F150 approach and just, you know, pushing for bigger, bigger, bigger, which is unnecessary. Right. I'm just trying to give some context to things because again, I think that it's not actual AI that people hate and are against, it's these other things. And if they dug into the numbers, they probably still would hate AI, but I think it's really driven by something else. Right. Because the average American, they don't know all these statistics. They don't know that data center electricity usage is only at 4% of total US electricity. They don't know that AI is only 5 to 15% of what a data center is used for. Cloud computing, enterprise workload, that's like 40 to 50%. Content delivery and media is like 25 to 35%. And then search, ads, recommender systems is 10 to 20%. I will say that I thought that recommender systems was way higher. [00:15:55] Uh, but either way, AI specifically we're looking at 5 to in like these, like LLMs, like that. We're looking at 5 to 15% of what a data center is used for. Right. The average American doesn't need to know these stats in order to hate AI. Right? Because it's not AI that they hate, it's what it stands for. The rapid and certification of nearly everything by people and corporations with way too much money. And I get it a, uh, 100% percent. Right. Again, I am absolutely not defending these corporations. [00:16:27] What we're seeing with these data centers, right, being built in these rural places is Fucking whack, right? This episode. I know we're talking about data centers a lot. It's not about data centers. But I don't like to just complain and like say shit. I want to give solutions. And the solution here with. When it comes to data centers, right, the action item here is unfortunately participatory democracy. Like we know participatory democracy is so fucking annoying. Or you just want to like chill out and be a good person and live your life. You're like, why I have to do all this? Why are people the worst? [00:16:54] Right? That's what we're seeing right now. Ice Trump the whole administration. You're like, why? You just stop being the worst. Is it that hard? Right now I gotta go and vote and do all this other. I shouldn't say that. Voting's the easiest part. Now I gotta go and go to protests and now I gotta go and call my representatives and I gotta write to this and I gotta call and do this and it's a lot. All right. And sign up for this and donate to that. It's annoying as. And you're like, just be good. But this is the best chance that people have at pushing back against the, against, you know, data centers coming to their area or data centers coming and having a detrimental effect to, to them, to their community. All right, so the, the demands to uh, include. Because, you know, yes, you'd think that your elected officials would actually know shit and have your best interest at heart. But they don't. Right? You'd hope that they do. But they don't. They don't. So the demands to include non exhaustive list here. Mandatory community review for large ideas for large data centers, transparent utility impact studies, rate payer protection clauses. We know we're seeing that, that people's bills are going up and that's up. [00:18:03] Uh, clear cost allocation rules. Right. Who pays for. [00:18:06] And environmental protections. Right. A very non exhaustive list. But all this to say like, unfortunately, when where these places where, you know, data centers are being put, people individually and as a, you know, as a community have to fight back because they're fucking elected officials, don't know shit and just want like a tax break on. On things. So, you know, do I think that AI deserves pushback and scrutiny and governance? Yes, absolutely. Fucking absolutely. What? A hundred percent? Yes. All I wanted to do in this episode was dive into some of the reasons why I think that AI is so polarizing and what I think is actually going on, you know, behind m the curtain, under the hood there. I don't have any action items for this, you know, is this episode, this whole episode, it's just observations. And sometimes I like this how I like to share things. And I, I think that this is what, uh, it's what the curious people do. So let's, let's head into the how I use Chat GPT and then we'll wrap it up. So each episode I include a section where I briefly discuss how I use Chat GPT that day or that week. This time I use Chat GPT to help me build some shelves. So if you follow me on social media, you saw, you know, a few weeks ago and on my birthday, I did it as well. Uh, I added some shelves to the house because we needed them. The closets are good, good size. But it's like one shelf. And I'm like, now everything's falling over. It's just stacked on itself. So I added shelves, uh, and I added some deeper shelves in the linen closet. Because a linen closet should have like a 15, 16 inch depth shelf. That like 11 inch depth shelf. That ain't it home. Your shit's gonna fall off. Like, it's fine for your clothes closet, but for towels, it's the worst. And so at one point Lex was like, this is kind of annoying. And I was like, I will fix it for you. Because it did have enough shelves in the linen closet. They're just shallow. Uh, so I took the ones that were in there. I took them out, which you. Which I could tell someone else had put them in because the cleats underneath were like a different wood and they weren't even painted. So, uh, I took them out and I put bigger ones but deeper ones in. I got some other, uh, what do we want to call it? Fabricated, uh, fabricated wood. I don't know, it was like mdf, uh, or something like, something like that. Um, Engineer Engineered Wood, that's the name that I'm looking for. Um, but specifically how I use it to help me build the shelves. I asked about what type of what, what size and type of screw to get. I went and did some searching about the different types of wood versus the, you know, engineered wood, MDF, M particle board, things like that. Um, I discussed with it the angle to miter the cleats because I did it at 45 degrees. And I was like, the front of the cleats that you can actually see, I was like, this is, this is too much. This looks aggressive. And it was like, yeah, 30 degrees is better. And I was like, oh, good to know. [00:20:54] I asked it and Got a better understanding of the load distribution of the shelves because some closets, like, don't have, um, they may only have like one stud on the side. And I was like, I. I hate putting anchors in. I hate it. I'm like, traumatized. I live in New York City and the walls are like Latham pla Oven plaster there. And I'm just like, I hung a TV once and it didn't fall. It was fine. But I was just like, I hate toggle, but I hate anchors. Like, give me a stud any day. I will find studs very easily. Get a stud, buddy. It's the easiest thing to use. [00:21:27] Uh, but I was just like, how important is this? I only see one on the side. One set on the side, uh, you know, versus this side. And it was just like, yeah, like the back is what's really holding it up. So I was asking and understanding about load distribution of the shelves. Um, I even had it try. [00:21:42] I even tried rather to have it generate a mock up of what the closets would look like with the shelves in it. I take a picture and I was like, add two shelves. And it, like, did a halfway decent job. Um, but overall it was super helpful and I highly recommend using it for your next DIY project. So that is all for today. Hopefully you found this episode helpful. And if you did consider leaving a rating or review, we hit 23 ratings. 23. We'd love to. 25. Who's gonna help us? Who's gonna help us? But we get to 23 ratings and we got a new review. Shout out to Kangy. Underscore D for the bomb ass review. I folks, I literally do read every single one of them. Sometimes I don't read them right before the episode and I should, because then I come on here and I'm like, do we have one? But I promise you, I read every single one of them and I am so damn grateful. [00:22:31] So thank you, Kangy D shout out to you using it, helping you out with that gym. This is dope. That's fucking dope. All right. [00:22:38] Don't forget, folks, I have a companion newsletter called the Curious Companion that drops every Thursday that is basically the podcast episode in text format. So if you prefer to read or you just want a written record, join the newsletter fam. You can head to chatgptcurious.com forward/newsletter or check out the link in the show notes. As always, endlessly, endlessly. One more time. Endlessly appreciative for every single one of you. Until we chat again next Thursday, stay curious.