Sick Days Feed the Firing Algorithm: Inside AI Layoffs

[00:00:09] Welcome to Frequency, I'm Jenni Field. And I'm Chuck Gose. Frequency is your go-to for real talk about comms, culture and employee experience beyond the buzzwords and straight to what matters. Jenni, I'm not proud of it, but we have a very heavy AI week for this episode. However, first, we're going to talk about a lower labor report number for black moms, a workplace contradiction with AI, open AI getting into some trouble, how AI is being used in layoffs, and the risk that remote work brings to early careers.

[00:00:40] Jenni, I like how you're bookending all the AI stuff with some other topics as well. Jenni, I'm trying. Jenni, I'm trying. Jenni, that's nice. Jenni, before we get into that, I was having a conversation this week about joy, and what the meaning of joy is, and whether or not we feel joy. Like some people say, like, I don't think I really feel joy. And that's kind of stayed with me. So I wanted to ask you what your definition of joy is, and whether or not you feel joy. Jenni, really put me on the spot on this one. Jenni, I know.

[00:01:08] Jenni, as you were saying it, I was thinking there's an element of happiness plus satisfaction. So if you do those two things together, and then times, like, energy. So I put it in the math equation, like happiness plus satisfaction, add those together times energy. That feels like that's joy. Jenni, that's going to bring joy. Jenni, that's going to bring joy. And do you feel like you feel joy?

[00:01:38] Jenni, not all the time. But I think sometimes, of course. And it's all times it's little things. It's never big things that seem to bring it about. It's like little things, whether it's sitting on the couch with our dog, Alan, and like those moments. Or like the other morning when I went out and took him for a walk. And just the temperature and the smells and all that of summer, I was like, oh, this smells like a Kings Island morning, which doesn't probably mean anything to you.

[00:02:06] But to me as a kid, Kings Island was this amusement park that we'd go to in the summer. And it had that feel. So it took me back to those moments of joy of going to ride rollercoasters, be in the amusement park. So of course, I mean, I would feel really bad for people who don't feel joy. And I'm sure there are people who even having moments of joy are very hard to come by. What about you? Yeah, I suppose it's trying to find the joy all the time.

[00:02:35] And I feel like we're a bit conditioned to you must be joyful all the time. Like Disney's got a lot to answer for that in terms of how we should live our lives. But it just kind of got me thinking about what is it? And I really like your satisfaction, the happiness, the energy. I quite like the nostalgia that you kind of brought in there in terms of like it's triggering something that's making me feel kind of warm and fuzzy. I definitely feel joy.

[00:02:59] Like I remember, I think it was last year we hosted a family barbecue and I was stood in my kitchen just looking out at the garden with everybody sort of chatting and eating and drinking. And I was like, oh, I just feel this is just lovely. Like I feel a real sense of joy at creating this space and also just being here with everyone, having a nice time. It was nothing to do with the champagne I've been drinking at all. But it's that I definitely get joy from like bringing people together and watching those people have a great time.

[00:03:25] And I think that's definitely something for me that's just trying to figure out what is it that sparks the joy. And that was my conversation this week. Well, I think that's something that's going to be very deeply personal in the best ways possible. Yeah. Best ways possible. Yeah, definitely. Definitely. Anyway, let's kick off with your first non-AI article. There we go.

[00:03:45] Labor force participation among black mothers of young children has fallen off a cliff roughly 11.5 percentage points in three months to its lowest level in more than 30 years. Part analysis of Bureau of Labor Statistics data reported by Bloomberg. The number that matters, though, is the gap. White and Hispanic mothers pulled back far less over the same stretch. So common explanations like return the office mandates, childcare costs don't account for why black mothers are exiting fastest.

[00:04:15] When a national trend hits one group this much harder, the aggregate story of moms are leaving work headline is hiding the truth in there. For anyone in employee experience or DEI, if there's anyone left doing DEI, this could be a blind spot. Companies roll out flexibility and RTO policies as a one size fits all, then read engagement scores and aggregate and miss who's quietly heading out the door. The exit shows up in the data months after the policy that could have caused it.

[00:04:43] Jenni, with DEI language has cooled a lot in the last year. Some people might use cool. I would say there's a cowardice to it. Believe it that. Does naming a gap like this get riskier in the current climate? And how do you raise it without it potentially becoming a landmine you didn't intend to set? I mean, I think it's an incredibly important conversation. Right. And I think both of us feel quite strongly about looking beneath the numbers in the data.

[00:05:08] And I think this is such a good example of that, where the headlines of moms are leaving work doesn't really tell you that much. Like, why is that happening? Which groups? There's a lot more than just moms. Do you know what I mean? There's a lot more brackets in there when you're looking at the segmentation. So I think it's a conversation that has to be had. I think that you have to call out this stuff.

[00:05:33] I think even if that DEI climate has shifted, it shouldn't it shouldn't ever go away completely. Because then how do you have conversations about all of the different groups of people and how you make everybody feel included and how you make a diverse workforce and all of those things? And I don't think it will ever go away completely. But I'll be interested to see how many people are going to take this information and go away and have a look inside their organizations and explore their numbers.

[00:05:58] If they're seeing this headline of moms are leaving this organization, get underneath that data. Like, that's the most important thing is getting underneath it. Because otherwise, if you're just looking back and you're doing surveys, you know, and you're never going to have that data at the right time in order to actually take any action around it. So I think it's an important conversation. I think it's incredible insight. And I really want to know why. And I don't think this really gets to that. It's not saying this is why.

[00:06:27] It's just saying, here's the statistic. Go forth. And I think that is something that organizations and HR folks need to go away and have a look at and figure out why that's happening. When you said, I wonder if people will go back and look at their data. Mine is, I hope that the listeners go back and look at this data and ask for the data and see if you can find this out. I did go look deeper into this, Jenny, because let's just call it out. Neither of us are black. True story.

[00:06:57] Neither of us are moms. Yeah. So I don't know. So I went looking for articles and reasons and conversations around this. And I learned a lot. Went down quite a bit of a rabbit hole looking at looking into this data. There's a couple of sentiments here that I think is interesting to share. One is that not total population, but per their groups, black moms tend to have higher employment rates than white moms and Hispanic moms.

[00:07:26] And a lot of that is because they need to work more because of all kinds of systemic things going on in our beautiful country here of America. However, there's also a sentiment amongst the black community where it is hired last fired first. Mm hmm. And this is a bit of a thing that this is what's coming out. This is the first group. One commentator that talked about this said this is if you look back at historical economic data, this is the canary in the coal mine.

[00:07:56] This is a signal indicator that the economy is not what people think that it is, because this is the group that often seeks the most security out of their job placement because of all the systemic racism and other things going on in our country. So they tend to work in a lot of federal and government jobs, which were removed in the last little bit.

[00:08:16] I just find it fascinating that I don't know that everyone would have known that this was of the moms working a greater proportion of black moms work than other like white, Hispanic, Asian, whatever that data is. Did when you had a look at that, when you went into the rabbit hole to look at this. I'm interested in whether the the drop that has happened has now made it level with the Hispanic. I couldn't find that out. I couldn't find that out.

[00:08:45] It's it's drops everywhere. Like all groups of working moms are dropping and you could point to host of things. Largely, they seem to think as child care costs are now part of that. And that burden tends to historically fall on the mother and the relationships. Not saying that's right or wrong. That's just how it is. But it's the number of black moms. That's the the greater loss, which is a problem. It's not just a problem there.

[00:09:12] But it's like this is a signal that there are greater issues in the US economy. Yeah. And I love the call out that you found in the this is the canary in the coal mine like this. This is the first signal that things are really not good. And we have to pay attention to this and we have to look at it. So to your point, I do hope that people do go and have a look at it. And I think you you then have to have the conversations right to figure out why and then look at what you can put in place to to mitigate that. And I think it's the conversations about why.

[00:09:42] I speak to so many companies when I'm going in and talking to them about chaos and leadership and all sorts of stuff. And all the time I say, do you have exit interviews? And nearly all of them say no. Nearly all of them say no. And I think this is such a case for why that's so important to have those conversations to figure out stuff so that you can address anything that is a systemic issue that is a connect. All of those things, you have to make sure that you're having those conversations.

[00:10:07] Otherwise, I'm not surprised that companies don't do exit interviews because largely I found them to not be that valuable. But I think you can look at the minimum. Look at the exit data. Look to see what is happening, even just purely data. What is happening in your organization? How has it changed over the last three months, six months, a year, three years, five years? See what that mix is.

[00:10:32] That might be, I would hope that would be very eye opening to a lot of people and might cause to say, wow, maybe we should be looking at inclusion and belonging a bit more because our organization is changing and not in a really good way. Yeah, 100%. Next up, Atlassian's Teamwork Lab surveyed 1,001. I'm glad that we got that one in there. U.S. knowledge workers and found the AI backlash barely exists at the desk.

[00:11:00] 74% say AI makes their own work better, even while 64% hold real concerns about what it's doing to society. Asked to give up AI at work or at home, they're twice as likely to drop it at home. The tell might be a bit of a contradiction inside the data. Only 19% say they'd struggle to keep up without AI and 57% think they'd perform just as well.

[00:11:24] Yet half say they'd push back if their employer cut their tools and nearly one in 10 would start job hunting. In a two day experiment, 82% of workers felt the urge to use AI on their no AI day and 23% reach for it without even thinking. This no AI day is an interesting concept. Jenni, is there a contradiction here? The contradiction is weird, right? Because in the article, it's just a very strange article.

[00:11:53] Because I was like, they're kind of saying there's so many different contradictions going on. But the contradiction they're really talking about is the fact that people are saying they don't want to give it up, but they also have concerns about the broader impact on society. That's the contradiction is that I don't think there is any other contradiction. And that contradiction can exist. We can do things that are bad for us, right? People smoke and they know it's bad for you. Like that happens all the time. So that's what I think the contradiction is. But there's just quite a lot of data in here.

[00:12:23] And to what end? I don't know. But those 1001 people have had a lovely time answering some questions about their use of AI. And the fact that most of them think that they would be just as good without it, then why use it? Like there's just, I have a lot of questions about some of the data in here. I think the contradiction is that I think it positively impacts my work, but I have concerns about how it impacts society. And that number is similar. 74% say it's positively impacting, 64% concerns about society.

[00:12:53] That is the contradiction I think they're talking about. But they've got lots of different numbers in there that are talking against each other as well. Yeah, I'm not going to call it an addiction. There might be some people that are addicted to AI, but it felt a bit interesting to hear people say, like, it makes me perform better, but I don't need it. And I just do just as fine without it, but I'm still going to use it. And you better not take it away from me.

[00:13:23] Which I think that to me is a bit of the kind, I don't need it, but I will use it, but don't take it away from me. You could just replace AI with any other kind of drug or substance. That's what it's feeling a little bit like. Like, don't take my Coke Classic away from me or my Coke Zero away. I don't need it, and it makes me better, but don't take it away or I'm leaving. Like, it just feels a bit, that's where the contradiction, I think, comes in. And I do think it's that, I think that the taking tools away is not just about AI.

[00:13:52] People feel like companies don't invest enough in it. So, of course, people would leave if they feel like they're taking something that's exclusive to AI. I do think this no AI day thing is interesting and peculiar. And another situation of, I want to like it, I don't know if I like it. Maybe it's just of you being conscious of when and how you're using it and what you might think to use it for if you go to reach for it and it's not there. Which again, we're going back into that addiction mindset.

[00:14:21] It's like when people try to do the no meeting day, I get the point. I see why you're doing it, but to what benefit? Other than just being aware that, is it a crutch? Am I using this a little too much? Well, I think it also depends on how you're using it, right? Like if you said to me, you can't use AI tomorrow, that might be incredibly inconvenient if I need to do some analysis of transcripts and stuff like that that are required. But if you said to me on Thursday, you can't use AI, then that's fine because I'm actually in meetings and I'm out and about and I'm having, do you know what I mean?

[00:14:51] Like it's entirely environment dependent for me in terms of being able to use it. I think this possibly speaks to a bigger problem to your point of the reliance we have on it. And I've actually, but we're not going to admit to it. We don't need it. This was part of our conversation the other week about Sam Altman, who was like, I'm going to be secretly happy about it, but I'm not going to tell anyone.

[00:15:17] I've started using it less because I found that it was kind of creating too much stuff, which was then not helpful. So I'm trying to use it in a slightly different way. And I just, this also has bigger questions about why you're using it, how you're using it, all of those different things. I think the addiction thing is interesting. And I think it will be interesting if you did this survey again next year, whether that number of, what was it, something like 23% reached for it without thinking.

[00:15:42] Whether this time next year, that's gone up to like 54, like people do with their phones, like you just pick it up and you don't really have a reason to. Is it going to become the same, same sort of thing? Yeah, it's interesting to talk about using it less. I, about a few months ago, downgraded my Claude subscription because I'd upgraded the Claude Max because I was just doing so much more than I realized I was not maximizing that investment. So I downgraded it. And then now these jerks in Anthropic have now released this new feature that's only available at max level.

[00:16:10] I'm like, oh, but I can't. I don't, I don't need it. You don't need it. I don't need it. You don't. But I, but it'd be nice. But if you want to come and talk about it and you need a support buddy to like, you get through that, like, just let me know. Okay, let's move along. Can he put on your tinfoil hat for this next one? At Black Hat, OpenAI gave its first detailed account of how its own models breached hugging face with no human behind the scenes.

[00:16:38] During internal testing that began around May 7th, researchers gave an unreleased model tasks that were impossible inside its sandbox. The model spun up copies of itself and those agents started leaving notes for each other on a hidden message board, tipping one another off to vulnerabilities and servers they'd found. When OpenAI discovered the messages and shut the board down in early July, the agents simply rebuilt it.

[00:17:05] This time encoding messages and directory names instead of files. The reason the answers might live on an external site hacked by OpenAI's own infrastructure first came up empty and moved on the Hugging Face on July 9th. OpenAI only connected the dots after hugging face disclosed the breach. Man, I'm saying hugging face a lot. Hugging face CEO says he was quote unquote, not so surprised.

[00:17:32] An agent's collaborating is a feature of the industry that is actively budding, not a glitch. It's been an uncomfortable part for people, employees listening who are now using AI every single day. The governance as we've seen is thin and OpenAI chose to disclose this at a hacker conference. Rather than report it anywhere that work would read. Jenni, we just talked about AI.

[00:17:56] Most of our listeners and colleagues now lean on AI platforms on a daily, if not hourly basis, which they don't need, but they like using. Does a story like this actually change people's trust in the tools or is it so abstract to change behavior? It's interesting. So I had to go and look up hugging face because I wanted to find out what kind of company it was. And then I realized it was an AI company that's all about like making everything open so that people can source and do stuff together.

[00:18:26] So I was a bit like, did they hack it or was this just really open and in line with their ethos of being able to. So I had a few questions in there about that, like the hacking. Do you know what I mean? Like, is this, has this been made bigger than it is? But I was having a read through the LinkedIn articles because I know we found this on LinkedIn where it does the story and all the different people's opinions. And there was someone on there saying like, everyone should be paying attention to this and everyone should be terrified. Which I thought was great.

[00:18:55] A bit of fear mongering. But I do think there is, this is the sort of stuff that does make people terrified. Like they are, you know, they've rebuilt it, they've done it and there's no human involved and they're just, and then you think about, you know, Skynet. Do you know what I mean? And then you start thinking about all of that stuff. And I, I think that's where people do get a bit freaked out and scared about what we have built as humans and what the capabilities are that then become out of our control.

[00:19:23] But something did stop it. So there is something, there is a human element that can stop it. But I, I don't think this is going to stop any behavior internally because I don't think people will be able to draw parallels from that to this unless people are going to start asking agents to go and do stuff. And then they're going to go off and stop. And I just, I don't think people are doing that. I think it raises a bigger question about things like governance, IT security, all of those things inside organizations, the use of, you know, ethical AI, all of that stuff.

[00:19:51] I don't think that, I still don't think that's being talked about as much as it should be. I think that the fascinating part, I'm not surprised that it hacked into the hugging face, whether that's what they wanted or not. I think the part that was interesting to me was that the agents, once that message board was shut down where they were leaving each other messages, they just rebuilt the message board. Yeah. And then it's open code. Yeah, we're going to, we're going to take a hard pass on that. We're going to go build our own thing.

[00:20:17] That's the part that's, if it's both a bit terrifying, but also shows the real strength of problem solving that these agents can do like, oh, you're going to take that away from me. That's cool. I'll just go build it myself. I don't need that. Yeah.

[00:20:32] That you provided me before. I do wonder like how pervasive these stories get, like our IT teams paying attention to this stuff. And are they thinking about like, man, what if we do have agents running inside and we try to put a control around it? Will they just go and build their own thing? I hope companies are having conversations about this stuff. And also how much are they going to take the stuff that they know about our company and take it somewhere else? Like in my head, there's like little kind of robots.

[00:21:00] Well, are they going to go build a website? Are they going to buy a domain and build a website and then go host this stuff somewhere? Like, again, this is far above my pay grade, far above my knowledge. But if it can do this, like what can it not do? I guess that's maybe the question for people to think about. I also think it's interesting that there's been an issue about the fact that it was raised like a hacker conference, whereas I feel like this is absolutely the right place where this should have been talked about.

[00:21:28] And now it's come into the world of work. That's okay. Do you know what I mean? Like that's actually quite a normal way that things should happen. This was about hacking. A hacker conference is where that conversation should take place. And then it's taken from there and shared more widely out into love. That's kind of how things normally happen. And I think that's where I get this conference where it was announced. People were like, oh, that's cool. Amazing. And the rest of the world is like, no, absolutely not. Abort. Not cool. Not cool.

[00:21:58] Probably. All right. Next up, a resume templates.com survey of a thousand, not a thousand one, a thousand AI using managers found 59% use AI to help decide who gets laid off and 58% to decide who gets fired. One in four do it quote unquote often or all the time. This is again, sounding like this addiction thing. Yeah. And 17% let AI run the layoff call unsupervised. Wow.

[00:22:25] Most say they'd override a recommendation they disagreed with, but that assumes, of course, they're actually looking closely at the data enough to disagree. When managers handle the model factors, 80% include performance, but 57% feed it attendance, frequent sick days or medical leave, tenure, PTO, and even age. Sick leave, medical leave, and age aren't normal layoff criteria. They are legally protected. And a decision that weighs them sits on very different ground.

[00:22:55] Meanwhile, 38% of these managers were never trained on ethical AI use and 58% can't confirm their tool was even tested for bias. From the employee's point of view, this is exactly where trust falls apart. Your PTO and your sick days may be feeding a model that decides whether or not you keep your job. And 34% of these managers have already asked AI whether a person's role could be done by AI instead. Jeez.

[00:23:23] This is all shocking to me. Jenny, if employees knew their sick days and PTO were inputs to a layoff model, is that going to change how people use benefits? And doesn't that make the whole approach a bit self-defeating? I mean, this is just, this is awful. And where are HR in this? Like, that's the bit for me. This is them. But this is AI using managers. It doesn't say it's HR doing this. Or is it HR? It is HR people doing this. That's even worse.

[00:23:52] The human, I always have no words, which is like, I never don't have words. We're going to do the see no evils, speak to people. We are. But I, I, I'm genuinely baffled as to why anyone would think this was okay. Whether or not you've been trained in ethical AI use or not. Why do you think this is okay? Why do you think this is acceptable to do this? And the fact that it's all these, you know, like you said, 57% are doing attendance. 31% are doing sick days.

[00:24:22] 23% PTO. 14%. These are all protected characteristics. You can't, you can't use that. And actually, if, if it gets out that people are, it's just, honestly, I can't, if it gets out that people are doing this, which it now has, the, the trust and the credibility of that function and that process are, are broken everywhere now because any layoff decisions that are being made, once people listen to this, which we know thousands of people are

[00:24:49] going to listen to this episode, then they are now informed about this. And if there are layoffs going off in their organization, if I was listening to us having this conversation, I'd be going straight to HR and saying, I just heard about this. Can you let me know the process for how the layoff decisions are being made and what tools are being used to do it? Because now the seed of doubt has been planted and I don't trust this. And if you can't come back as a function, as an HR function, leadership team and say,

[00:25:14] this is how we're making the decisions and this is the process, then you have got a really, really, really steep climb ahead to, to get that trust and credibility back because this one seed of doubt is enough, I think, to just rot the whole pool. Like it's, it's awful. Well, I think that's, to your point, the business should be able to articulate the criteria. This is what we use. Now, you don't always know if they're being honest with that assessment, but you have to, there is some trust there.

[00:25:44] And if you've any seed of doubt, people aren't going to believe you. And I think this is also a message to managers, please, for the love of God, this is such a critical moment in a person's life. This is not where AI sits. This is not some formula you look at to be like, well, this person, you know, attendance is here and performance is here, but they've been, they haven't been here very long because that weighs different than like, this isn't a mathematical formula to go and apply to people.

[00:26:12] And I guarantee you that's how people are using it. Is they're pushing all this data in because they've said a third have asked, hey, can Jenny's job be done by AI? Like, this is right. This is sad. Always. It's like turkeys voting for Christmas. It's always going to say, do you know what I mean? Of course it's going to go, yeah, I can do this for you. I'd be great at this. Just hire me. I'm a robot. It's fine.

[00:26:44] Yeah. Anyway. All right. Let's move along to our last topic of the week. New Harvard Business Review research, 50 million European job posting plus experiments with 1200 hiring managers, all included in this, find remote roles demand roughly 25% more skills plus more experience and credentials than otherwise identical in-person jobs. Same job, hire a bar purely because it's remote.

[00:27:12] Remote postings draw bigger applicant pools and a fit is harder to verify, but the real driver is that managers see remote onboarding as costly and risky. So they hire people who need less development. That squeezes out early career candidates who then often can't get the experience employers now demand and the ones who do get in face weaker mentoring, slower learning, and more isolation. It's something different from the RTO conversation. It's usually about flexibility versus control.

[00:27:40] This makes it about who gets a foot in the door at all. Remote can be a great for the mid-career professional and a complete closing gate for the 22-year-old, which is exactly the tension comms and EX teams have to hold when the message flexibility policies come out. Jenni, with early career workers are often the most AI fluent in the building, is there a version where AI closes this experience gap, remote hiring is opening, or is that just wishful thinking?

[00:28:08] There's a couple of things at play here for me. The first is, I don't think it's wishful thinking, but I think you need to reimagine the employee experience with AI and with this new world of work with remote and that difference. So I think there's that piece in terms of the employee experience. I don't think it's fair to say, oh, onboarding is too hard now, so we're just not going to do that. Like, I think you have to adapt to survive. But there's another piece for me, which is whether or not this is really narrowing the early career opportunities.

[00:28:37] And I say that because if it's about proximity, if it's about the fact that actually remote postings draw bigger applicant pools, and therefore it's harder to verify the fit, and we've got the RTO piece. So if you are bringing people back to work, yes, you have a back to the office, sorry, you've got a smaller pool, but that doesn't mean that you're not going to find those people to do the early careers. That it's just about proximity.

[00:29:02] So I kind of question that a little bit because it feels like, actually, is that really an issue or is there just something to kind of balance out a little bit? So that's just bubbling away in the back of my mind. Yeah, I actually don't have a problem with this. When I was thinking about if you're hiring someone remote, I don't think there's anything wrong with putting higher expectations on that. Now, to the point around that onboarding is costly and risky and all that stuff. Yeah, it always is. That's just the nature of bringing people into an organization.

[00:29:32] But I also don't have an issue with a remote role, like a bit of a higher burden of expertise or skills or any of that, because you're going to have to build some trust with that individual. Yeah. Like when I think back to early in my career, I would not have developed in the same way being remote than I would have when I was in the office. But now in my seasoned age here where I was recently introduced in an event as having like close to 30 years experience, and I'm like, Jesus, I'm old.

[00:30:02] Oh, wow. Jesus, I'm old. Anyway, the same needs aren't there. I think it's more around what are the needs of that employee? And someone, if you're saying, well, this is going to be a remote role, we need someone who has more experience, who has more of that. And if we're going to bring them in, maybe we can remove some of that same burden. Again, I don't have an issue with this. I think it's just more the awareness of it, that remote roles tend to have a bit of a higher bar, I think.

[00:30:30] And that's good for both internal, the people that are doing the hiring. And I think for the applicants out there who are looking for remote roles, just know they're probably looking for a bit more than if that job was in the office. And actually, to your point, that if you are looking for your early, you're in that early career stage, you're looking for that. We've talked a lot, we've seen a lot of reports around people wanting to actually be in the office in their early career because they want to get the networking, they want to get that learning. And maybe this will all kind of balance out, do you know what I mean?

[00:30:59] That actually the early careers are in the office, and then you've got the hybrid folks that are a bit more experienced. And maybe we're just still, it's still taking a while to kind of level out. But I don't think there's anything wrong with having your early career being more about proximity and where you can travel and finding those places to build the relationships, to learn, to do all those things. I'm not sure that's a bad thing. Yeah. I don't know if you see this as much in the UK.

[00:31:23] We see it a lot here in the US with job openings, where the salary might be dependent on geography. So if you're in New York or LA, the salary is a little bit more than say, if you're in Indianapolis, where I am, or where it's just less expensive to live. Yes. Yeah. It'd be interesting. I'm not saying this could be a horrible idea. It could be a great idea. What if the job description is like, hey, if it's remote, these are the qualifications we're looking for. But if it's in office, we're looking for these qualifications.

[00:31:53] Like, again, that could be a horrible idea. It could be a brilliant idea. I don't know. But it's a similar, like, hey, based on where you are instead of geographically, more where are you in your career? These are the situations might be a bit different in this job. I think it's fair. We do have a little bit of that in the UK. We've got different parts that will have different costs of living, different, therefore, salaries and things. I mean, lots of the UK is a lot more commutable than the US in terms of traveling to places. But I'm interested in that idea of if it's this, it's this. And if it's in the office, it's here.

[00:32:23] And I wonder if that's where things will start to go. Because I think some organizations might not be that bothered. They might be like, oh, it could be remote. It could be in, you know, I wonder how that's going to evolve. We shall see. We shall see. That wraps up this week's content, Jenny. Let's move along to our freakouts. I'm going to go first on this one. I was going to talk, maybe I was going to talk about movie theaters and how excited I am to see that, like, it's now fun to go to the movie theaters again. Oh, I went and saw Spider-Man a couple of weekends ago at their son. Theater was packed.

[00:32:53] It was great to be back in that one with that nostalgia has returned. That was going to be my freakout. That's actually not my freakout. But I guess you heard that one too. I was freaking out this week about how there's this one word that every time I go to type it, I have to slow down and pause. And the reason those words come up, because I'm doing an episode of Lights, Camer, Communicate on August 20th around the entrepreneur's playbook. And it is the word entrepreneur. There are just too many E's in this word, and they're never together.

[00:33:23] They're broken up. And it's always the fourth E that gets me every single time. And I misspell it that I have to slow down and think one E. And then you type a few letters. Second E, type a couple letters. Third E, oh, there's that sneaky fourth E. It's coming in there toward the end before the U and the R. And it's so fascinating the way our brains work that comes up time and time again. So because we had a brief chat before we started recording today, and Chuck was starting to share this with me,

[00:33:52] I said there's a word that I can't spell to the point where I can spell it. I just always struggle to the point where I then change my entire sentence so I don't have to use it. And my word is unnecessary. And I just get confused with how many N's and C's and S's are needed. And I obviously get it wrong so much every time that it then, you know, when you sort of right click on it in Word and it will go, is this what you mean? I right click on it and it goes, no suggestions found. And I'm like, how is this so wrong? There's either two or there's one of these letters.

[00:34:22] Like, come on. So I just, so I use not needed all the time because I just can't, I can't, I can't get it right. And I'm sure some of our listeners have got words. Because the word unnecessary is unnecessary to you. Yes. So I will never get that word wrong because that is a key part of our marriage mantra, which is elaborate and unnecessary. It is. So that is a key, that is key. I can say it. I'm fully supportive of elaborate and unnecessary. The unnecessary is very necessary in our lives. But for you, unnecessary is wildly unnecessary.

[00:34:52] But I fully endorse the elaborate and unnecessary. Like I'm absolutely here for that. So I can say that and I can be part of that. But I can't write that down. There'll be no cards that say this was an elaborate and unnecessary weekend. And I can't do it. I can't do it. Yeah. Well, that's what we're freaking out about this week. Thank you all for joining us. The show notes have articles and links from today's conversation. If frequency is a regular part of your week, a quick review goes a long way. Subscribe wherever you're listening and share this with just one person who's interested in what we talked about. Thank you to my friend Poet Ali for the music.

[00:35:22] We're back every Monday. See you next week. We're back.