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AI Avatar of Killed Man Testifies in Court
Episode Notes
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YouTube version: https://youtu.be/-X7YUK-qgr0.
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Joseph:I'm your host, Joseph. And with me are four zero four media cofounders, Sam Cole Hey. Emmanuel Mayberg Hello. And Jason Kebler.
Jason:What's up?
Joseph:Let's go straight into one that you wrote, Jason, along with Matthew Gault, our regular contributor. The headline is, I love that AI. Judge moved by AI generated avatar of man killed in rogue rage incident. Let me just straight away play some of the audio and video, if you're watching on YouTube, of this avatar. It's just a few seconds I think.
AI:Hello. Just to be clear for everyone seeing this, I am a version of Chris Pelkey recreated through AI that that uses my picture and my voice profile. I was able to be digitally regenerated to share with you today. But here is insight into who I actually was in real life. Take a look.
Joseph:Then the video carries on and it shows actual footage of Chris with family members and friends if I recall correctly. Jason, what did we just see in here?
Jason:Yeah. Yeah. And then at the end, let's play one more a little bit where he basically forgives the man who killed him, which is very odd or at least very was very weird to watch. But, yeah, this is Christopher Pelkey. He's a man in Arizona who was killed in a road rage incident by a man named Gabriel Jorge Cites.
Jason:And what you're hearing is the end the very, very, very, very end of the trial where Jorge Citas is being sentenced. And so basically, he had already been found guilty, and this is a sentencing hearing where, as part of it, everyone is allowed to submit a statement, more or less, like a victim testimony, more or less. And so what this means is people who know Gabriel Horcasitas can, you know, submit, like, testimony saying, this was a one time incident, like, he's a good family man, things like That, like, that those are sort of the other types of statements that were submitted. And then Christopher Pelkey's family was like, you know, he was such an amazing person. We're very sad that he's dead, of course.
Jason:Like, this is just a normal part of sentencing. And then the judge considers all of that and comes up with how long the person should be in prison.
Joseph:So That happens every single day in cases all across The States. Very, very standard. And usually doesn't involve AI.
Jason:Usually doesn't involve AI. And I guess what I'm saying is, like, this AI was not cross examined or anything like that. Like, this is a prerecorded statement, and we'll get into how it was made. But this was submitted to the court as essentially Chris Pelkey's quote unquote own statement. So in this case, you had a man who was killed who, from beyond the grave, submitted a statement about who he was as a person and at the end, like, directly addresses the killer and says, you know, like, I I forgive you, which is it's just very wild to think about.
Jason:I I think that this is very much, like I think this trope is over way overused, but this is very Black Mirror to me. Like, this is the type of things that Black Mirror examined, especially early on in its its run where it's like, you'll be able to digitally recreate people after they die and they'll you can like continue to have a relationship with them. In this case, it was a man who was killed who is testifying at the trial for I mean, ended up being a manslaughter, but testifying at the trial for the man who killed him.
Joseph:Yeah. And and maybe here, this is where we can just drop some more audio and video of that of that latter part of the video where as you say, he's all sort of directly addresses his killer.
AI:To Gabriel Horkasidas, the man who shot me. It is a shame we encountered each other that day in those circumstances. In another life, we probably could have been friends. I believe in forgiveness and in God who forgives, I always have and I still do.
Joseph:So how do we get well, actually no. I I I was gonna save this for later, but I almost want just want to immediately address it. The family says, this is almost like the victim impact statement from Christopher. That is not true. Right?
Joseph:It is a creation that has been made and we'll get into that in a second by the family. And then, of course, not even talking about this family's grief or or what they must be feeling. I just mean on almost a factual, legal basis, it's not him talking. Right? I mean, what did you what do you make of that?
Jason:Yeah. I mean, I think that this case is a little bit, you know, it's it's really weird because you have a grieving family, and I don't want to downplay that at all. But you have a grieving family that's trying to figure out how to cope with this situation. And, basically, his sister, who we spoke to, a woman named Stacy Wales, she wrote this. Like, this was actually not the actual words were not generated by an LLM that was trained on Christopher Pelkey or anything.
Jason:Like, she wrote his words or quote unquote his words, and then her husband, so Christopher Pelkey's brother-in-law, is the one who recreated his voice. So they they use an LLM to, like, train train on his voice and recreate his voice. And then they also used a LoRa, which Emmanuel has talked about a lot, is basically mechanism for, like, recreating a person from an image. And so that is that is what like, how this was made.
Joseph:Yeah. I mean, Emmanuel, could you maybe talk a little bit more about that tool just for a second? Like, is it an app? Is it a tool? Is it just free to use?
Joseph:Does it just require one image? What's the deal with it?
Emanuel:I would really define it as a method most commonly used with stable diffusion, which is an open weights AI model that can do all sorts of things. People know it mostly from its ability to generate images, and essentially, it's just a way of very quickly training stable diffusion to recreate the likeness of a person or an object or a scene or a style. It's just it's a way to like, training stable diffusion took a lot of time and a lot of training data, and Allure is a way to use just a few images or inputs to make it do something very specific that it wouldn't be able to do otherwise.
Joseph:Gotcha. That makes sense. So very accessible, it sounds like. You know, it's basically anybody could use it. And I presume that's why, you know, somebody like a member of the public or whoever may turn to it.
Joseph:Jason, what did well, two things. Why did Christopher's sister want to make this? And then second of all, sort of what did they make of the result? Were they were they happy with it? Or so the the why and how good was it?
Jason:Yeah. I mean, it sounds like she did this because she was having trouble writing her own victim impact statement for the trial. I mean, I sort of can't imagine being in this situation and knowing the words to say. And also, I mean, thankfully, I've never been in in that situation, but sort of knowing, like, what to even ask for or how to feel about it. It should be noted that the family actually asked the maximum sentence time because the family was able to submit, like, what they wanted.
Jason:But interestingly, like, Christopher Pelkey's AI statement said that he forgives, you know, the person who killed him, and and he didn't specifically and I say he, but obviously, like, this video doesn't specifically ask for anything. But the tone of it is one that's sort of like, it's very unfortunate that this happened. He says at one point, you know, in a different life, we could have been friends. And it's kind of hard to know, like, what to make of of the whole thing, I guess. And
Joseph:Like, truth wise, like, is that really what he would have thought? Like, what do you mean?
Jason:Well, I can talk more about that. I mean, I think that there's there's no way of knowing what he would have thought because it it's just regardless of how well you know someone, I think that, you know, I I have lost someone who was very, very close to me. And the first thing that happened after she died was all of these people who barely knew her started saying, oh, she would have loved this, she would have said that, she would have done this. And first of all, like, she wouldn't have done most of those things. Like, I know for a fact.
Jason:But also, you can never know. You can never know what someone and that that's one of the, like, really awful things about death. And I think that's actually that's actually, like, really important to this case because this is fiction. It's it is fiction masquerading as a legal document because you have no way of knowing what Chris Pelkey would have said or would have done because he is dead, and you just simply can't know that no no matter how close you were to him. And so you essentially have, like, his sister who has written something for him and and really, like, it's masquerading.
Jason:I mean, people have called it a puppet. Like, the story went pretty viral. Not not just our version, but it was widely covered in the press. And you you just can't know.
Joseph:Yeah. Because some other people covered it because the the video the videos came out, and I'm gonna play another one in a second. And then we spoke to, you know, the sister and I got more detail. But you did mention, you know, kind of framing this as a legal document and it is literally like it's been entered into court and this AI avatar has, in a legal sense, testified in this hearing. Someone who should know about legal documents and the sorts that should be allowed and potentially shouldn't be allowed, you know, are judges.
Joseph:And here is the judge's reaction to seeing this AI played in their courtroom.
Jason:I love that AI. Thank you for that. And as angry as you are and justifiably angry as the family is, I heard the forgiveness, and I know mister Hortecito's proceed appreciate it, but so did I.
Joseph:So the audio was, you know, not the the best quality there, but basically, the judge says that I loved the AI and, you know, the family could have appreciated it, but so did the judge. Some of the coverage didn't really focus on on the judge's reaction. Of course, it's in the headline of ours because it's it's pretty important. What did you make of the judge's reaction when you saw it, Jason?
Jason:Yeah. I mean, I was really surprised that it was accepted into the court. And, you know, I'm not a lawyer, especially not a well, I'm not any kind of lawyer, but I have less familiarity with the criminal legal system than I do some of some of the, like, other types of lawsuits that we cover all the time regarding, like, lawsuits and privacy and things. Yeah. Copyright.
Jason:But I I know very little about the proceedings of like a criminal court. But I have to imagine that judges have pretty wide leeway to determine what can be accepted and what cannot. So I was shocked personally that he accepted this statement and said, you know, that he liked it. And I think it really does raise questions about how well informed judges, lawyers, victims, suspects, etcetera, are about how AI tools work. And we know that, like, law firms are sort of foaming at the mouth to use AI tools because it can really cut down on the amount of time that it takes to do things, to go through, like, really big legal documents.
Jason:Like, you know, Sam has written several articles about lawyers who have, like, written documents for the court that hallucinated, you know, other court cases because they used an LLM. And in some cases, like, the judges chastised the lawyers for doing so. And, you know, in this case, the judge didn't chastise the family for doing this. He said thank you for doing this and and accepted it. I mean, I think Sam can talk a little bit more about how the legal profession is using AI, but I don't know.
Jason:I think it opens up a lot of questions, like, you can can a a victim's family call a chat an AI chatbot trained on someone's text messages to, you know, testify in a court, like, against in a murder case? Like, I have no idea. Like, it it raises up it raises all sorts of questions
Emanuel:to me.
Joseph:Yeah. Sam, what do you think? On one side, we have the judge here embracing it, and then you've covered all of these cases where lawyers have basically, you know, effed up because they've been using AI in in their own sort of writings. What do you make of it?
Sam:I mean, I thought that was a big part of why this was such a strange and kinda shocking story. A lot of judges are threatening lawyers with, like, fines and fees and severe punishment for using LLMs in compiling documents for courts. Like, we see a couple times most recently, I think the MyPillow attorneys did this, but we've covered a couple times where lawyers are compiling cases, and they're citing other cases that are comparable. It's like, you know, see this case, that case, to kinda hold up their own argument. And either the opposing side or the judge catches that the cases are just not real.
Sam:They don't exist. That's because they're using AI. I don't I mean, you know, who knows which one? There's many. But, for example, they're using ChatGPT.
Sam:You can imagine them kinda typing in, like, make some cases like, cite some cases for me as part of this case that I'm working on, and then they plug that straight into a court document and submit it. And that's really sloppy. And it would piss me off as someone who hired that lawyer, and it pisses off the judge because the judge is like, this is a waste of time. This is a mockery of the profession that you're in. So to see this judge in particular say, be so moved by it is just I don't know.
Sam:It's like, you went to law school, bro. Like, what are you talking about? This is purely the conjecture of this guy's sister. It's not anyone's words but hers and her husband's and the family's. So it's just it was amazing to me that the judge was so I don't know.
Sam:I don't wanna say gullible, but, like, that's kinda what it is. And then they were asking for the full sentence. So, like, really, was he so magnanimous as to forgive his killer?
Jason:It should be noted that the judge gave the killer the maximum sentence Yeah. As the family asked for. So it's like, it's pretty the the forgiveness from the AI avatar did not sway the judge to go more lenient.
Sam:And and it meant to.
Jason:It wasn't meant to because it it would get came from the family. And the sister told us here's what she told us. She said, quote, our goal was to make the judge cry. Our goal was to bring Chris to life and to humanize him. And it's like, I think you can feel a lot of potentially different ways about it because I'm sure that any family that's been through this will say that they feel like they've, like, lost their voice.
Jason:Like, Chris cannot speak for himself. He cannot speak to what happened that day, but that is just, like, how life is. It's like a a it's the definition of of a murder or or any like, any case where someone dies, it's like they cannot describe what happened to them.
Emanuel:I just Yeah. I want to note that there's a long history of people more likely to put their critical thinking aside where new technology meets death. And I think there that's because there's such a longing and, like, the unknown about death that people accept really wild ideas. That's something that I covered a few times when we were at Motherboard. So for example, in 2015, when VR was all the rage, there were quite a few projects that claimed to let you connect with your dead loved ones by creating some sort of VR experience that recreate the likeness of a lost parent or something and having some voice acting in there and that letting you communicate with the dead, which again, obviously, is not true.
Emanuel:There have been a lot of kind of holocaust memorial project that use holograms and other new technologies, which again are, like, well intentioned as I think the family is in this case. But as Jason said, it's you're not communicating with someone who has died. It is more like talking to a psychic, which I think, as a culture, we're more likely to acknowledge is a scam. But for some reason, when you put the label of technology on it, it is something that you can present seriously in a court. And with AI being the hot new technology, we've seen a ton of this stuff around death.
Emanuel:I will remind people that Sam covered this company called Replica many times and that it is essentially an AI girlfriend app. It is a companionship AI model, but it grew out of this project where someone created an AI model of of their dead partner, and that kind of had this huge glowing feature in The Verge. And, again, it was seriously engaging with this idea that this allowed someone to talk to the dead. And then, you know, five years down the line, it's just like a sex robot of some kind. So, yeah, just just like this is a thing that continues to happen over and over again, but it is definitely not something you'd see admissible in court usually.
Jason:I mean, you're absolutely right. And I would just add that one of the core projects of AI in general is to recreate consciousness. Like, that is the the goal of it when we talk about, you know, super intelligence and the singularity and things like that. It's like to create a conscious being, and we don't need to dive into it now. It's there's many reasons to be very skeptical of this, but that's the entire selling point.
Jason:That's, like, behind all the AI safety. And then there's a lot of, you know, transhumanists and, like, AI developers who specifically want themselves to be to live on as an AI. They want their own consciousness to be, like, uploaded into the everlasting cloud. And so I think that that is very often there like, there's so many AI startups that that have this as as their goal and just to sort of, like, transcend death in some way. And it it and there's been many, many projects like this.
Jason:And so, yeah, to see it in in accord, I mean, when I saw it, I was I was shocked. And it's like, I'm I'm very rarely shocked by anything with AI anymore, but I'm like, oh, you've gotta be kidding me. Like, I cannot believe that this was accepted.
Joseph:Yeah. Alright. Maybe we'll leave that there When we come back after the break, we're gonna talk about our interactions with Meta and I suppose Silicon Valley PR Reps more broadly. And specifically, it's about Meta's plans to put AI sorry, facial recognition, same sort of thing, into its smart Ray Bans. We'll be right back after this.
Sam:Well, well, well, we're back. Well well well, Joseph, what is going on here? So Joe Rosemary, the headline is well well well, meta to add facial recognition to glasses after all. So if you're a long time reader of 04/2004, you know what we're alluding to already. But a while back how long ago was it, Joe?
Sam:Was it, like, maybe earlier this year or last year?
Joseph:I believe it was last October. October '20 '20 '4.
Sam:Okay. So, yeah, in October, these two Harvard students did something pretty wacky with Metas. They have these, like, Ray Ban glasses, like, that you can wear, and they have cameras in them. So these two Harvard students got ahold of these glasses and did something with them. So do you wanna walk us through that original story first before we get into the smugness of it all?
Joseph:Yeah. So they take these meta Ray Ban smart glasses. I always change the order of those words every time I say them. But they took those, and they have the camera on board. And then they basically strung together all of these different technologies, which would include PIM Eyes, which is the off the shelf facial recognition tool.
Joseph:Basically, anybody can use. People have used it to identify January six riot riots. People have used it to docs sex workers. People have used it in all sorts of abusive and then somewhat interesting ways as well. But they paired basically PIM eyes with these Ray Ban glasses, and they called it eye X-ray, if I'm remembering correctly.
Joseph:But we'd also go a step further in that PIM Eyes gives you the web page where that matching face was found online. So let's say you're looking at somebody with the with the glasses, captures their face, it then puts their face through PIM eyes, and it brings up, let's say, the website of the law firm that this person works at. Then, you know, we could take the name attached to that, put that through an LLM and look for more information. And the idea was that you could basically dock somebody just by looking at them, finding where they live, finding where where they work, all of this other stuff, and puts that all together into one package. And they made this video, which went viral on Twitter slash x of the two students using it.
Joseph:They said on dozens of people without their knowledge, like unsuspecting. Unsuspecting. And I would say victims, you know, maybe some people were okay with it. But just going around and revealing the identities of people who were anonymous members of the public. And this is, you know, the big big fear when it comes to putting not just facial recognition tech in the hands of anybody, but facial recognition tech in the hands of anybody in a surreptitious manner in that I can just look at somebody and my Google glass from a million years ago or now my meta Ray Bans are going to reveal to me who that person is where ordinarily, will be anonymous.
Joseph:And as you walk down the street, I'm never gonna see them again. Now I know who they are and I know everything about them. And I mean, it's a terrifying proof of concept. So we covered that at the time, and we'll get into more detail in a second. But Meta pushed back a lot against that article, and they didn't really like that we were reporting it.
Sam:The wording that you used in the story that we're talking about today is they let me get it right. They chewed my ass off.
Joseph:Yes. That's a technical term.
Sam:Yeah. So with that context in mind, what is Meta announcing now as of last week?
Joseph:Yeah. So there's a report in the information that Meta is actually working on facial recognition tech for its Meta Ray Bans. And, like, we don't know all that much, but basically, they're working on it actively to put that capability into the glasses, and they're also do or they're also exploring this other thing, which is not having or potentially not having the lights turn on on the glasses. So usually, when you put the metal ray bands into recording mode or whatever you want to call it, a little light will appear which will indicate to other people, oh, hey, that person's recording. I don't think enough people wear these glasses for that to be common knowledge, to be perfectly honest.
Joseph:Like, you know if someone's shoving an iPhone in your face or a GoPro in your face, you don't know that the little red light on the pair of Ray Bans means you're being filmed. Regardless, Meta is reportedly looking at getting rid of that as well. So after all that coverage we did as students and have met us you know, a little meltdown about it, well, well, well, they're putting facial recognition into the glasses themselves anyway.
Sam:Yeah. And they were super pissed when the first article with the students came out. Because, obviously, these are really this is, like, a really privacy invasive thing to have people walking around doing facial recognition in real time to everybody around them without their consent. I don't know. I find that to be pretty dark world to imagine living in, but Meta was like you know, they were I mean, walk us through what they said in response to your first story because they were pretty upset with, like, every element of the story.
Sam:Yeah. Like we said, they they really did chew your ass off
Joseph:I mean, they basically
Sam:and forth in emails.
Joseph:Yeah. They basically disagrees with the premise, and I and I won't go into every single sentence they they wrote. You can go and read the article for that, but I'll give like the summary of it. They when I reached out for comments saying, hey, look, these students have taken your technology made by Meta and Ray Ban's, I suppose as well, and they've paired it with this facial recognition technology and these people search databases. Can I have your comment?
Joseph:Blah blah blah because we're writing this up now. And they initially asked, hey, just to clarify, this could be done with any sort of camera. Right? It's not something that's intrinsic or inherent to the meta RayBands. You could do this with a stationary camera or whatever, and then you've strung those different technologies together as well.
Joseph:I mean, yes, that is true. But as I explained to the meta spokesperson, the students didn't strap a GoPro to the helmet or their face and then walk around trying to dox people because that would be really, really obvious what they were doing. And again, by the students' own admission, the entire point was to do this in a stealthy manner and to do it on unsuspecting people. If you're shoving an iPhone in somebody's face, that's not gonna be unsuspecting. We're all used to that by now.
Joseph:So they take issue with that and I explained it, whatever. They then take an issue with the headline, which we did, which which was someone put facial recognition tech onto Meta's smart glasses to instantly dox strangers. They had some sort of issue with the word onto Meta's smart glasses where they're like, oh, you're suggesting that the glasses were modified in some way. And I'm like, I don't know, man. Onto, into, slapped on, shoved to get like, it doesn't matter, man.
Joseph:Like, it's completely meaningless distinction, and the impact is that this technology is being used in this way. We then record a podcast about it that people can go back and listen to if they wanna get much more detail there. Headline of that was the smart glasses that docks strangers. And then the response was and I think I'm just gonna read this out. This is the only section I'm gonna read out, but it kinda gives you insight into Silicon Valley Press Reps.
Joseph:And they said, you say in the podcast that the glasses don't have facial recognition capabilities and you've previously acknowledged that this could be done with any camera or recording device, but a headline saying smart glasses that dock strangers clearly makes it sound like this is the issue that is specific to the glasses or that the facial recognition was executed on the glasses themselves versus the reality, which is that this was all run by a program on their laptop. This is despite the fact that students themselves have said publicly, we do not want this to be a criticism of their product at all and we just hand we just have them on hand. This could have been done on a phone camera. And he finishes the quote and says, I realize we may not agree on everything here, but surely you can appreciate how headlines like this are misleading for readers. As I explained in this well, well, well piece, no, I don't appreciate that whatsoever.
Joseph:And I don't care if the Harvard students were saying, well, we didn't want this to be a criticism of Meta's glasses. It's like, dude, you took them and you built an instant doxing device. Like, it doesn't matter what your intention was. And in fact, that's actually more worrying. Like, you've clearly built in not fully understanding what you've actually unleashed here.
Joseph:And this is just what it's like dealing with Silicon Valley Reps, you know. And I and I guess that's something I actually just wanted to ask you, Sam, and Jason Emanuel as well. Like, is this what it's like interacting with PR reps from tech companies? Like, what what do you all think of that?
Jason:Is that a rhetorical question? Yes. No. Yes.
Joseph:It's literal because I just because I want you to fill it in as in is this an extreme I I to be this isn't, like, the most extreme thing. It's just a guy moaning at me in emails, like, who really cares? It's because they're now announced they are doing facial recognition that's important. But, like, I mean, what did you make of it, Jason?
Jason:I mean, I thought it was absurd. I thought it was it was absurd then, and now I think, well, well, well. Like, I don't know what else to say other than that. But, yes, this is it's interesting because I think we try to be as transparent as we can about how we do our journalism and what what that means, like what where our information comes from and and that sort of thing. And I think part of us doing our articles is going to the people and companies that the article is about and saying, well, what do you think of this?
Jason:Like, give us a comment. Like, here's a thing that's happening. Like, what's what's going on? And we actually very often, at this point, have to go to companies and say, give us a comment. Like, answer these questions.
Jason:Here's a statement. Here's a comment. And that's actually not the ideal. The ideal is, like, make someone in your company available for an on the record interview to discuss this situation so we can have a back and forth dialogue. And that happens pretty much never anymore.
Jason:I mean
Emanuel:I know. When was the last time? When was the last
Jason:I mean, it happens never and but and when it does happen, it's like Mark Zuckerberg is talking to a friendly podcaster for three hours. He's like talking to Lex Friedman for three hours. But, like, when is the last time that any tech company did, like, an on the record hard hitting interview with a real journalist? Like, I don't know when. I don't know when.
Jason:And when they do it, it's to promote like a specific thing. And so it would be interesting to have this debate with Mark Zuckerberg or, you know, we understand he's a he's a busy person. So how about someone who's working on the smart glasses project? How about an on the record conversation with the PR person? And it's like, in this case, none of this was on background, which means you can use the information or sometimes it means you can quote it, but not say who who it came from.
Jason:Like, the definition of what on background even means is different for every person. And if you're listening to this, you have no real reason for knowing what that is. But basically, it's like when you deal with spokespeople at companies, they usually immediately demand to go off the record, which we can either refuse to do, which is tricky Tricky
Joseph:like Depends on the story, but sometimes we do it. Yeah.
Jason:Sometimes we do it. I mean, I think we try not to because it's like not ideal, but sometimes we do just because we're trying to be fair to them. We're trying to explain what the story is. We're trying to sometimes they wanna go off the record because something is like a giant misunderstanding and it's like not actually a story. And, like, this is rare, but sometimes it's like we have something wrong and they wanna tell us, like, hey.
Jason:This is, like, wrong. And if they were to say that on the record, then maybe we would do a story saying, like I don't know. It's just like it's it's a it's a tough thing to even explain.
Joseph:Denies x y z when it's almost like it's straight up wrong. But as you say, they're super rare anyway.
Jason:Yeah. And so it's like it's like trying to get blood from a stone, I guess. It's like getting information from companies through official channels is like they're doing PR. We are sort of doing, like, due diligence just being like, yo, like, here's what we're writing. What do you have to say about it?
Jason:And it's become like a really antagonistic type of back and forth, or it's become like a box that you tick because company like, companies broadly, they're like, we don't give a shit. Like, here's here's some, like, canned statement that doesn't mean anything. And then we put it in our article because we sort of have to because that's just like how it works. And it's like half the time that companies are lying is the wrong word, but half the time they they are, like, trying to, like, split hairs so finely that it doesn't mean anything to any reader. And as you said, Joseph, it's, like, on to, into, taped to, like, who gives a shit vibes.
Jason:And then the other times, it's like they are they are doing some sort of, like, gymnastics with their boss where their boss is, like, very mad that a specific word or a specific company is in the headline or something and that and they're, like, willing to go to the mat with you to, like, demand that you change a headline because someone at their company doesn't like it. And it's, like, we don't change it unless it's wrong. And if it's wrong, then we'll fix it. But I don't know. That's a lot.
Jason:But it's dealing with these people is a nightmare.
Emanuel:It seems to me like the last time we had anything resembling a revealing conversation with a comms person at a tech company was back when Joe and Jason did this big feature about Facebook global moderation, and that was in the wake of Facebook being blamed for inciting violence in Myanmar and the genocide there. And back then, it seems like the comm strategy or the the their response to that was like, we're really sorry this happened. This was really bad. Here's what we're trying to do. Here's why this happened despite our best efforts, and now we've revealed information that helps you better understand the company, and we've learned lessons and yada yada yada.
Emanuel:And that's the story. And I feel like since then, especially since Zuckerberg's transformation into, like, this right wing pro Trump figure is the PR people are just pushing back for the sake of pushing back on any story that they don't like because it's like a game and they want to score some points. So whatever it may be, they just want like, you wrote a negative story, it seems to me, my read on their strategy as a whole, and this is true about many tech companies, is that they want some sort of pushback in the article, and it almost doesn't matter what it is. It can be their comment, it could be a denial, it can be getting you to change some fact about the story, so there's an update at the bottom. Maybe you have to change the headline.
Emanuel:Very rarely, I don't think we've even done that here at four zero four Media, but that gives the reader the overall impression that the media is wrong in its portrayal of Facebook, and Facebook gets to have its own voice in a way that is criticizing the publication that is criticizing it. And I'm, like, really heated up about this at the moment because, you know, I just published a story today from Matthew Gault about Kanye's, like, Nazi song all over Instagram, and there isn't a good story for Facebook to to to tell there, but they're trying to split hairs or find any way to push back on the article just for the sake of pushing back. And I think historically, I'm like I try there's there's obviously an antagonistic relationship between the press that is critical of whoever they are covering and the comms people at those companies or of those politicians or whatever, but I used to have the attitude that it's like, I have my job, they have their job. And a lot of the time, they can be really helpful in providing information about maybe I did I I never want to be wrong in a story, so I if I reach out to a press person and I'm like, hey, what about this thing happening in Facebook?
Emanuel:And they're like, actually, you got this totally wrong. Let me tell you what is happening. That is very good for me as a reporter to get that information. But increasingly, I'm, like, finding it hard to put myself in their shoes. It's like, imagine you're the coms person of Facebook, and Joe publishes this story about these students who are putting facial recognition in these glasses, and your remit from your boss is to go and chew his ass out or whatever you call it in the article, and you kind of, like, make your stand and fight with him.
Emanuel:And, like, I've had screaming matches on the phone with PR people, and then, you know, a couple of months later, they're like, fuck all that. It's going in the glasses anyway. It's just like, what the how like, what is their morale internally? And at what point you're like, this is so embarrassing for me as a human being to, deliver these messages that I know are, if not lies, then bending the truth to the to the point where it's unrecognizable.
Joseph:Yeah. And I think that's actually a really good place to end it all out.
Jason:No. No. I have one more thing to say. I'm so All
Joseph:I was gonna add was that what you said, Emmanuel, where they pushed back and they're looking for an update with the student glasses one, they didn't even get an update in the end because I'm not because we're not even going to take that because the points were stupid. You know? Sorry, Jason. Go ahead.
Jason:Well, what I was gonna say is often if you're doing, like, a big story or a scoop story, a lot of the strategy is also, like, time delay too where it's like, I'm gonna get you on the phone. I'm gonna ask you what your deadline is. I'm gonna demand to talk to you off the record. We're gonna talk and have, like, a maybe an interesting conversation off the record where the PR person is like, oh, I, like, really wanna help you. This is really bad.
Jason:I'm gonna have to go back to my boss and see what we can say on the record, blah blah blah. Like, there's often a lot of that, and you try to be nice to them on, like, a human level. Like, a lot of it is, like, a human level. Like, we like, this person says, I'm trying to figure out what's going on here. Please give me a few minutes to figure out what's going on here before you publish your story.
Jason:So then they go and and, like, say that they're gonna do it, and then half the time, they either don't say anything at all or they give you the same statement that they've given you a thousand other times. This happened a lot when I was writing about AI for, like, on Instagram. They give the same statement month after month after month, or they, like, link you to a company blog post that they've already published. And in the meantime, maybe we get scooped. Like, maybe someone else publishes a story.
Jason:Maybe they take your story and they go to a friendlier outlet and say, hey. Four zero four Media is gonna write about this. Here's our side of the story. Why don't you write about it? And there's, like, a we don't have time to get into it, but, like, some outlets are very friendly to companies.
Jason:Or sometimes the companies go out and put out their own blog post preempting your story to try to get ahead of it and do damage control before you even publish it. And that dynamic is something that we need to consider every time we do a story, and it's really tricky. And it's like, it would whatever they're doing in, like, PR school where they're just, like, don't give out any information. I don't know. The the relationship doesn't necessarily have to be super antagonistic, but we have to, like, draw a line somewhere where it's like, we've asked you for comment.
Jason:We've told you the story is coming. We've given you a deadline, but, like, we can't always wait because half the time, the companies will go and, like I'm not talking about meta. I'm talking, like, broadly. They'll, like, pull some fuckery that messes with our job and messes with our livelihood, and and that's something that we have to to weigh as well.
Joseph:Yeah. And that's after you always are trying to be fair and reasonable. And then to some people, it's more just of a game as well. Well, that was a really, really good group therapy session. I'm glad that we did that.
Joseph:How about we leave that there for the moment? If you're listening to the free version of the podcast, I'll now play us out. But if you are paying for a four media subscriber, we're gonna talk about baseball and AI. I'm thinking it as Moneyball two point o. Jason can correct me on that in a minute, although I think that's correct.
Joseph:It's gonna be really interesting. You can subscribe and gain access to that content at 404media.co. We'll be right back after this. Alright. We're back in the subscribers only section.
Joseph:Jason, this is a 5,000 word article you wrote in, I don't know, twenty minutes or something. Like, I don't know where it came from. It's crazy. But there's a lot of words. Sorry?
Sam:How about the mos?
Joseph:Yeah. Okay. So let me read the headline, and we can get right into that. The simulation says the I keep wanna say Oreos. I'm sorry.
Sam:Dude, this not the horrendous start.
Joseph:Can you read the headlines?
Sam:The simulation says the oils should be good. You're following baseball at all, you know that that is not the case currently.
Jason:Do do you want to so this article is not really that much about baseball, though maybe it is. But maybe Emmanuel and Sam, do you wanna speculate on my mental state?
Sam:Oh, poor. Yeah. Don't need to speculate. It's not a speculation. It's also everyone everyone in the Orioles fandom that I come across is not well, And I'm having a great time.
Sam:I'm a fan, and I think this is fantastic. I love when they suck. It's really fun. But it's more interesting than when they're winning. So yeah.
Sam:Poor. You're not doing well.
Joseph:I'm I'm deliberately going into this blind because I'm yet to read it. I'm gonna sit down with a with a coffee or whatever. I'm gonna read the whole thing because I am interested. But I'm just gonna be going in blind here because I think it'll be actually useful for the podcast. So very briefly, the Orioles were bad.
Joseph:Right? Then they brought in AI. Was that the idea, Jason?
Emanuel:Just to be super
Jason:basic. Okay. So I'm a big baseball fan. Big baseball fan. Have played baseball my whole life.
Jason:Huge Orioles fan. The Orioles have not won anything since I've been alive. I'm 37 years old. They've never won a World Series. The last time they won a World Series was in 1983, '5 years before I was born.
Jason:Every year, I get my hopes up even when I know they're gonna be bad. I get my hopes up because that's what you do as a baseball fan. And for the last few years, they have been good. But starting this year, this year has not gone gone very well. And so the Orioles, for, like, all sorts of reasons, have been not a very successful franchise over my lifetime.
Jason:And the biggest reason for that was they had, like, a pretty shitty owner who didn't wanna spend a lot of money and who also, like, meddled a lot with the baseball people. And and what that means is basically, like, he was a rich guy who didn't wanna lose money, so he didn't wanna spend for, like, the good players. I'm just generalizing. And also, he hired he was, like, making decisions for the baseball team that was like, oh, I like that guy. Go go sign that guy versus, like, making informed decisions about what would be best for the the franchise.
Jason:And so they sucked ass, to use a technical term, for a very long time. And in, I believe, 2018, it's it's in my very long article, but in 2018, they fired their general manager, which is the person who makes all the decisions about what players are gonna be on the team, like who they're gonna sign, who they're gonna trade for, blah blah blah. They fired that guy and they hired a guy named Mike Elias and another guy named Sig Mejdal. And Mike Elias came from the Houston Astros who won a lot of world series, perennial contender, very well run organization. And the way that the Astros became good was they essentially started relying on, like, advanced newfangled statistics to decide who to bring into their team.
Jason:And
Joseph:Which just to bring it back to Moneyball That was gone. Which because I fucking love that film. I watched half of it on a flight, and then I couldn't finish the film. And I had to land and find what streaming service was on because it was engrossing. But BS, basically, Brad Pitt brings in like a numbers guy.
Joseph:Right? And
Jason:Yeah. Bobby Kodak and Brad Brad Pitt.
Joseph:Yes. Pretty, you know, based on a true story, blah blah blah, and that was a while ago. But this sounds like it's like the evolution of that. Sorry. Continue.
Jason:Yeah. So so Moneyball was sort of the first wave where it was the Oakland A's, and what they determined was that teams were undervaluing on base percentage, which is like how often a player gets on base in favor of, like, batting average and home runs and things like that. And so they realized they could sign all of these players for cheap who were undervalued by other teams. And they had a lot of success, and then they made the movie Moneyball. What is happening now is, like, the moneyballification of anything you could possibly think of, and it's not something that's easy to calculate like on base percentage.
Jason:On base percentage is just like how often you get on base. Like, anyone could could calculate that. So what has happened is baseball teams have started looking at all of these advanced statistics such as and and alongside of that, they've tried to, like, remake players in the image of what they want to, like, choose for more or less. And so
Joseph:They're not they're not going out and finding players who are like, oh, that person is or will be really good for that role. It's almost like preempting it. Is that is that what you're saying?
Jason:They're basically taking people who I mean, some some players are good at everything, but they're taking players who have, like, one good trait more or less. Like, they're they're taking pictures, pitchers who have, like, a specific type of curveball, for example, which is a type of pitch you can throw. And then they're sending them to academies, like physical places that have experts who have, like, tons and tons of AI cameras and sensors, and they make them wear, like, motion capture suits and things like that. And they're like, you are throwing a curveball the wrong way, and we're gonna teach you to do it a different way because our simulations suggest that if you throw a curve ball in this specific way and you move your body in a totally different way, you will be successful. And there's this place called Driveline in Washington State and there's a few others that have made millions and millions of dollars doing this.
Jason:And basically, they take like shitty players and they turn them into good players by like using technology to rebuild them from scratch very often. And so the Orioles were doing none of this for a very long time. And then they hired this guy, Mike Elias, and he was like, we're gonna do only that. So in his first year, they fired pretty much everyone who works for the team, like all of the coaches, all of the training staff, all of the, like, developmental people, all of the scouts. The scouts are the people who go and, like, pick which players to sign.
Jason:And they brought in all new people, and some of them had baseball playing experience, but a lot of them, similar to Moneyball, were like quant analysis people and like AI people. And like Sig Medjdal, who I I just mentioned, he was working in baseball, but his background is a NASA biomechanics scientist. And so they basically, like, hired all of these scientists to be like, we are going to be the most forward looking baseball team in the major leagues, and we are going to, like, create these baseball playing robots who are gonna be good at baseball because we are going to teach them how to be good at baseball. They'll they'll have some, like, skills that we like. We're gonna teach them other skills.
Jason:We're gonna change how they swing the bat. We're gonna change how they throw the ball. Like, all of this stuff that if you've ever played a sport, you have, like, an intuitive way of doing things. They were like, fuck that. We're going to re remake people in our image.
Jason:And so they do that from 2018. They tell us, me and Sam, fans of the team, we're
Sam:gonna Personally. Yeah.
Jason:They're like, we're gonna suck for
Joseph:a while.
Sam:And that was the end of the sentence.
Jason:Yeah. They're well, they were like, we like, part of the strategy is we're gonna be bad on purpose is what they said, more or less. Because if you're bad on purpose, then you get to draft at the at the top of the draft, meaning you get the best new young players. And they were bad for several years. And then suddenly, in 2022, they were, like, a little bit better.
Jason:And then in 2023, they were, like, the best team in the league. They had the best record. They lost in the playoffs, but they had the best record. And then last year, they had a really good record again. And so it was like, cool.
Jason:These guys are geniuses. They took this mid market team. Like, Baltimore is not a big city. They don't have that much money. And they used their, like, AI and their stats and their, you know, computer genius to beat the Yankees.
Jason:Like, beat beat all these really well funded teams, and there's been, like, millions of puff pieces not puff pieces, but, like, interesting articles about how, like, the Orioles are hot shit because they figured out that how to how to do this. And then this year starts and the expectations are similarly very high, but the Orioles are really bad with the exact same players that they used previously. Like, they they're just not good. And so the entire fandom is melting down being like, what happened? Like, all of these players who are good, this team that was good, like, what happened?
Jason:And that is like the the
Joseph:big Do we know?
Jason:Question. Well, so that's the thing, and and that's like what has changed about being a baseball fan in general is that there's this stuff that you can actually see on the field where it's like, Orioles lost 20 to nothing. Twenty twenty four to two, they lost a game, which is insane to lose, like, a game like that. It's like the Orioles keep losing, but every time anything happens on the baseball field, there's, like, tons and tons of cameras and sensors that are detecting what is happening, like ball tracking. Like, you can tell how fast someone is swinging, how fast someone is throwing, how fast someone is running, how fast they hit the ball, what angle they hit the ball at, where the ball is going.
Jason:And that is then run through it's called Baseball Savant, and it's run by MLB, like Major League Baseball. It's run by them. And they'll be what actually happens on the the play, like, you might hit the ball really hard, but a defender happens to be standing there and catches it, and that's an out, and that's, like, not good for your team. But, like, the expected outcome of hitting the ball really hard was a base hit, and so that's good. And so there's, like, the actual stats that are happening where the Orioles are losing and their best players are playing really shitty.
Jason:And then there's, like, the expected stats where it's like, well, actually, like, they're doing good. They're just having bad results because of random probability, and this is, like, outside the realm of what is expected. And so now to be a fan and to, like, understand what's going on, you have to both watch the game and, like, be sad that your team is losing, but also have the patience to say, like, well, if they just keep trying the exact same thing that they're doing, it should statistically turn around because you can't keep flipping a coin and landing on tails every single time And more or less. Imagine. Does any of that make any sense?
Jason:It's not like
Emanuel:Few things. First of all, I'm sorry this is happening to you. Very upsetting.
Jason:Thank you.
Emanuel:Second, I'm sorry to keep referencing Moneyball, but Joe and I don't even know the rules of baseball, so this is our point of reference. But it's like the narrative of that story is that up until then, I think, the way that teams managed the drafting of players is they were like they were old guys who would go to like high school baseball games, they had an eye for athleticism and like the magic of baseball, and they just had a feeling about like who's good and who's bad, and they were really good at picking players. And then somebody introduced this more scientific way of thinking about the game and just looking at the math. And the the story of Moneyball and I think of like modern baseball is that appeared to be true. It's like if you just crunch the numbers and you were looking for the right things, then you would be much more successful at the game than this outdated way of recruiting and drafting players.
Emanuel:It appears that even though the Orioles have very good math people, it is not working out. Is that because their math people are actually wrong? Like, is the math bad? Is is are other teams seeing transparently what their strategy is and undermining it? Or is there something to, like, this romantic idea of, like, actually, maybe we do need people who kind of have an eye for the game or an eye for pitchers and like we kind of we're we're kind of like too locked into the spreadsheet and that is actually the problem.
Emanuel:Like, what is your what is your take on that?
Jason:Yeah. So this is like the gazillion dollar question about like what is actually happening here and, you know, I have my theories just as someone who I have no reporting to back this up. Like, I'm not a baseball reporter. Like, I'm not in the clubhouse. People are there are good baseball reporters who are asking, what the fuck is going on with the Orioles?
Jason:And, like, talking to them and being, what's going on? But my feeling is that their their players are good. Like, their players definitely are good. Like, sort of universally, the industry is like, their players are good. And but what I think is happening is that they've taken good players and they have, like, overloaded them with information and, like, changed things that come very naturally and intuitively to anyone who plays a sport where it's like, just go out there and let your instinct take over.
Jason:See the ball, crush the ball, do a good job. And then there's also, like, this part of baseball where, like, it like, for example, you have a runner on third base and less than two outs, meaning you can make an out and you can, like, knock a player in even if you just, like, hit a fly ball or hit a ground ball or whatever. It used to be baseball wisdom that you, like, choke up on the bat, you you see the ball, even if it's, like, not a perfect strike that you're gonna, like, crush, you just try to hit the ball somewhere so that the person can score. When I watch the Orioles, they are like, I'm gonna fucking crush the ball. I'm gonna swing and try to hit a home run every time because that is what the statistic like, the the simulations say that scoring a run-in baseball is really hard and the best way to score a run is by hitting a home run, and so they need to just, like, try to crush the ball every time.
Jason:And so the Orioles have, like, this ungodly low statistically improbable, like, success rate with runners in scoring position, which means, like, when there's runners on second and third. Rather than, like, hitting base hit, they're trying to hit home runs and they're striking out. And so I think that what is happening is, like, rather than just telling the players, like, hey, you're good enough to make it to the major leagues. Everyone agrees that you have, like, ungodly baseball talent. Go out there and play intuitive baseball.
Jason:They're being told like, they have iPads in the dugout where they're like, this guy is statistically likely to throw a ball in this quadrant of the strike zone in this count, make sure you're looking for that. And it's like, I think the players are like being overloaded with information. They're being treated like robots. Like, I think that's what's happening.
Emanuel:It's it's overfitting is what they would call it in like AI training. They're like overfitting to the to the data. Sorry. Follow-up question.
Jason:Wait. One one more thing is that they're taking like these players who are like really good and have like really natural swings where it's like, here's how I've done it my whole life. They're changing what they're doing at like really high levels of baseball, like where it's like, oh, maybe you change that when you're a kid. But like you can't like take an adult who has played baseball for like a really long time and been like, you've always swung like this. Now swing a totally different way and then have them face the best competition in the world.
Jason:And, like, I think that that it probably there's some aspect of it where it's like, this doesn't feel natural to me. And maybe they got to a point where they're like, okay, this actually does work for me, but it doesn't feel super natural. But then the other teams are adjusting because they're like, the Orioles are doing this. You can get them out by doing this other thing because they all have the same analytics that the Orioles do. And so maybe they're finding some weakness.
Jason:They're exploiting it, and then the Orioles are like, well, we're doing what the computer says that we should do, and we don't know how to do this other thing because we've been re trained as, like, players to to do this thing and it's just, like, not working. So that that's my theory for why it worked for, two years and then the league adjusts and now they have to adjust back. But like, who knows whether they can do that or not because they they've now been like taught to do it this other way, if that makes sense.
Joseph:The meta shifted.
Jason:Yeah. It's like the game got patched, dude. Like, they patched the game, the meta shifted, and they're doing the old meta and that's not working anymore.
Emanuel:My follow-up question is, I just there there are a few sports I I don't know. I'm not like a sports guy, but it's like, really don't know baseball. But I read the story with great interest, And one of my takeaways were like, baseball sucks because it is so mathematical, and it's so about the stats. And, obviously, that exists in other sports, but not to this degree. Like, I think I've to, like, an NFL game, and the appeal there is, like, huge guys run fast.
Emanuel:And I've seen basketball games, and the appeal there is just like, wow. These guys are just, like, so good at getting the ball in the net, you know, from far away. And I know you've said it in the story and I noticed about you, like, sometimes you don't even watch baseball. You listen to it because it's just like you're just downloading the data of the game, and that, like, is the game. And I guess it's like two questions, like, what is the appeal of that?
Emanuel:And two, what like, why is why is it happening to baseball more than it's it's happening to other sports? Dude, it's interesting to you as well.
Jason:It's interesting because they have something called GameDay, which is an app where it just, like, shows, like, little dots about, like, what is happening when I can't listen to the radio. And it's, like, I can just see that in my brain more or less. Like, obviously, like, what actually happens is slightly different, but it's, oh, I'm downloading the information. I'm, oh, outside pitch to Ryan Mountcastle. He probably swung at that and missed.
Jason:Like, definitely. I mean, the appeal is like it's a strategy game. It's like a turn based strategy game literally with some like real time elements in the middle where it's like, okay, you do this here, you do that there. But the I mean, this this came through in Moneyball. And and in this way, Moneyball was accurate where it was like, you have the old crusty guys who's like, that guy's got mojo.
Jason:Like, you're just gonna put him in and he's gonna pitch for till his arm falls off. And that was, like, part of the magic of baseball for a long time where it was, like, you you just had these players who, like, felt like they were good and you would let them pitch for like a million pitches and then their arm would fall off at some point, you know, and they'd get injured or whatever. Well, now, like and and when their arm doesn't fall off and they do a good job, they became like heroes because they were like, oh, this guy, like, is the badass who pitched for like a million pitches and and won the game all by himself. But that doesn't happen anymore. And that's like a big debate in baseball is that analytics and all of this stuff is like ruining the game.
Jason:Because, for example, like, I went to the game on Friday in Anaheim where the Orioles played, and we had a really good starting pitcher and he was doing a really good job and he was just, like, crushing the other team and he didn't even have that many pitches. And he got to the eighth inning and he got the first out of the eighth inning on one pitch, and then the manager just took him out. And the person that they brought in almost blew the game, like, immediately. Like, this guy was having no trouble whatsoever, and they changed the pitcher and the the new pitcher almost blew the game. And that happens, like, almost every single day because the statistical analysis suggests that if our pitcher kept pitching, maybe he would have gotten hurt.
Jason:Maybe he would have been less effective because he's thrown, like, x number of pitches. And, like, in baseball and other sports, there's, like, momentum where it's like, oh, this guy's, like, doing really well. Just leave him in or whatever. And you have that feeling where it's like, oh, this guy's gonna do a really good job. And then what happens now instead of like letting that guy have that chance, they're like, we're taking you out of the game because the computer suggests that we should take you out of the game.
Jason:And that's really annoying to watch. It anytime that happens, I'm like, I want them to fire the manager. And, like, if I'm drunk, will, like, post that on Blue Sky and no one will care and people will be like, what's wrong with Jason? But I'm just like, it sucks as a fan where it's like, I I don't want this to happen. I I don't want it to feel like robots are playing a game, basically.
Jason:And that's sort of what it's starting to to feel like in some ways. Yeah.
Sam:Can I answer Emmanuel's question? Yes. Please. Because Emmanuel's question is, does baseball suck or why does baseball suck? A lot of people say baseball is too slow.
Sam:The appeal of baseball is being outside for three hours seated eating garbage where something happens tangentially in your periphery. That is the appeal to me. It's a great fucking time if you can get some friends out there with you, get a little drunk on $17 Modelos and Coors Light. That's the appeal. And the fact that it's slow is fantastic.
Sam:I cannot stand soccer. It's too fast. I can't watch it. People are running around. It stresses me out.
Sam:Baseball is very meditative and relaxing to me. Jason's gonna be the 80 year old guy sitting right in the front, like, right behind home with the score pad, pen and paper, scorekeeping with a gun, like, with a speed gun doing, like, actual he's in the game. Like, he's the coach. And I think that's beautiful, and those guys are locked the fuck in. And I think that there is room for the both in the sport, and I think that's really beautiful.
Sam:I'm in the bleachers way up eating a boog's sloppy fucking hot dog with crab cake on it paying no attention.
Jason:And, like, and pudding and hollering when something does happen, though. Yes.
Sam:And, yeah, and when something happens, it's great. And then when when nothing happens, I'm paying no attention, and I don't give a shit. And I think that's that's the appeal.
Jason:That's the as a player as well, by the way. It's like, you know, I played bass my whole life. It's the only game that you eat in, like sunflower seeds. You eat Yep. Sunflower seeds.
Jason:You eat huge. Yeah. Like, I mean, chewing tobacco was a big thing. I never did that, but it's like Yeah. People like, Major League Baseball players stopped doing chewing tobacco during the game, like, last year.
Sam:It's like It's a big, like, it's a big dicking around kind of sport, and I love that. I played outfield softball for, like, a very little bit. Was fucking horrible at it. Got reamed at by a coach, like, once a day for not understanding my rights and lefts. And all I did was sit on my ass and pick clovers for four hours, and I loved it.
Sam:And I think maybe that's where my love of doing nothing in a baseball game comes from. We all have our paths.
Jason:Yeah. I did write I did write 5,000 words about this in like two hours because it's like, it's my it's my hobby where it's it's all up here. It's like I've been watching this shit every day for thirty seven years. Like Do
Sam:you feel better? Do you feel good now?
Jason:No. No. I mean, yeah, I feel it felt cathartic, but, like, you know, I'll feel better when the Orioles play better.
Sam:Do you
Jason:what just like regard it's like Lucy with the football situation where they'll play, like, really bad and I'll be like, oh my god. Fuck this team. Fuck this game. I don't care. And then the next day comes like, that's a nice thing about baseball is they play pretty much every day.
Jason:And so the next day comes and I'll be like, excited for the game. We'll be good we'll be good today. And then the game starts and they, like, they they're losing. I'm like, fuck my life again.
Sam:It's a masochistic situation with the Orioles.
Joseph:I think that they should just try to score more points than the other team, and then Yeah. That should be it.
Jason:It is very interesting because I felt I feel like this article is good. People don't really come to us for sports content. I I feel like it's I mean, for good reason because we're not a sports blog, but I do feel like there's relevance to other things. And if you have, like, interest at all in baseball, like, check out the article. Like, you don't have to be an Orioles fan to to read this.
Jason:I I I tried very hard to make it not like a I'm an Orioles beat reporter article. So I don't know. Check it out.
Joseph:Yeah. Or if you're just interested in how technology is changing sports and culture, you know, go check it out. It's in the show notes. And with that, I will play us out. As a reminder, four zero four media is journalist founded and supported by subscribers.
Joseph:If you do wish to subscribe to four zero four media and directly support our work, please go to 404Media.co. You'll get unlimited access to our articles and an ad free version of this podcast. You'll also get to listen to the subscribers only section where we talk about a bonus story each week. This podcast is made in partnership with Kaleidoscope. Another way to support us is by leaving a five star rating and review for the podcast.
Joseph:That stuff really does help us out. Here is one of those from MJ Redd. Only podcast I pay for, well worth support independent journalism. This has been four zero four Media. We will see you again next week.