Future of Work Insights from Revelio Chief Economist Lisa Simon

(00:06 - 00:19) Rachel Murray: Hello, and welcome to the SheGeeksOut podcast, where we geek out about workplace inclusion and talk with brilliant humans doing great work, making the world a better and brighter place. I'm Rachel. (00:19 - 00:25) Felicia Jadczak: And I'm Felicia. Okay, let's just get into it. There's so much to talk about. I don't even know where to start, honestly. 

(00:25 - 00:31) Rachel Murray: Well, first of all, we should say that we are recording this on Wednesday, July 24th. Yes, important.

(00:31 - 00:50) Felicia Jadczak: Although if you're like me, truly, I don't know what day it is. I don't know what time it is. Although you just told me, but who even knows? But yes, technically it's Wednesday, July 24th. So if you're listening to this and something has happened, like aliens have attacked, just know that we didn't know about it until me later.

(00:50 - 00:54) Rachel Murray: Yeah, or so many other scenarios that are not on my bingo card for 2024. So

(00:56 - 01:08) Felicia Jadczak: I feel like that's my go-to now. Every time I go offline, I tell you, I'm just like, text me if aliens attack, I guess. I'll let you know. I don't know. I don't even know anymore. It's been a wild, wild ride.

(01:08 - 02:25) Rachel Murray: It really has for all of us and everyone who's listening for sure. But we're going to talk a little bit about some news that came out last week around SHRM, which is the Society for Human Resources Management. For those of you who are listening and are in that space, You may be familiar with what has happened recently as they decided to pull the word equity from their language around DEI. So they're saying they're focusing on diversity and inclusion, and they have faced both accolades and pushback. And there's been a lot of conversation around it. And it's also, you know, it's happening at an interesting time when, this is why we're timestamping it because literally a week ago when we were like, oh, maybe we should talk about this and how all companies are sort of making an assumption that we are going to be in a Trump administration next year, which as we all know, would probably eradicate any work We do. And now the conversation has just shifted so much and it's been interesting to see the most recent shift. But maybe we can start with the SHRM piece. Felicia, do you want to? Yeah, let's start with SHRM.

(02:25 - 04:59) Felicia Jadczak: I mean, I think it's a great way to tie into the political shifting that we are referencing as well. But yeah, as you said, it's been received with a lot of variety of responses. I think for us in our sphere, where we're sort of in this middle of the Venn diagram between HR folks, people folks, DEI practitioners, culture, leadership, all that kind of good stuff, it seems like most of the folks in our networks are very anti this move. And I will say, I think for me and you, we were really surprised to see this come out from SHRM. myself back on that. I was surprised, but not surprised. You know, Sherm is an interesting organization. It has, I don't know, 300,000 members, something really wild. The CEO, Johnny Taylor, I'm not his biggest fan. I'll just say, I don't think, you know, he and I align with a lot of stuff. So I wasn't really that surprised to see this, but it was, Disappointing and I'm super interested to see how this plays out given the shifting in you know last week you and I were both like This is it, Trump presidency, pack it up. All right, here we go, Handmaid's Tale, whatever, whatever. Now, I know I'm feeling way more optimistic and hopeful that this is not a done deal and that we have a chance against a Trump presidency. For Johnnie Taylor, he was a White House advisor during the last Trump presidency in the Trump administration. And I think he's been quoted as saying something like, you know, we want to make sherms in the White House helping the White House make decisions. So for me, part of the statement of saying we're taking away equity and equity rolls up into inclusion, which I don't agree with that at all. was sort of like a little flag saying, you know, I'm pretty sure a Trump presidency is happening and we're going to sanitize our DEI statements and approaches as much as possible to be in alignment with an administration that does not care about supporting equality, these concepts, representation, any of this, and really rolling backwards. Because we started with D&I back in the day, and equity was added in as we had a more nuanced understanding. So I think it's sort of this idea that, oh, we're going to pull back from really you know, reflecting too hard on ourselves.

(04:59 - 05:15) Rachel Murray: Yeah, well, and equity means fairness, right? It's about being fair. It's about treating people fairly and justice, you know, and it's and that concept is so different from diversity and inclusion. You know, there's obviously they're all connected, but they are all connected.

(05:15 - 05:58) Felicia Jadczak: And so, you know, I'm not saying that, you know, it's like I think there is an argument to be said that equity, you know, kind of can roll into equity or into inclusion. But it's not just it's not an umbrella term, right? And, you know, equity, the way that we define equity is we define it as access to resources and opportunities in order to help people succeed. And part of that is the acknowledgement that not everyone is starting from the same starting line. And so if we're saying, oh, well, we're just going to only focus on inclusion without acknowledging or naming equity, then it's really trying to downplay, in my mind, these differences that are so deeply rooted in systemic inequities that our country is built upon.

(05:58 - 07:20) Rachel Murray: Right, which is completely agreed. It's exactly why it makes sense that there's this fear of talking about it if what could happen could happen, right? And it's such an interesting time. I mean, we're literally watching the news and like so many of us are just seeing now, you know, major donors and tech companies leaders of tech companies, pouring money, and VCs, pouring money into the Trump campaign because they want access to power. They want to- Absolutely. Right? Yes. Preach. Yeah. Then my favorite part was, and this is where we were just chatting about this before. One of the biggest notes was Elon Musk said that pledges $45 million to a month, a month, not even total, a month for the to the Trump campaign. And, you know, that is like, that was like, wow, okay, we see what is happening here. And then the news yesterday comes out, oh, I would never do that. As Elon Musk, all of a sudden, now that the political winds have altered, and it just goes to show how fickle people with a lot of money can be in order to access power.

(07:20 - 07:42) Felicia Jadczak: He's totally like, oh, this is not a done deal. Let me let me rethink, regroup. And you know, what's really interesting is I am very curious to see how VCs especially respond, if at all, because I never pronounce her name right, but I'm just going to say it and then feel free to correct me if I mess it up. Anderson Horowitz. Is it Andreessen?

(07:42 - 07:43) Rachel Murray: I don't know.

(07:43 - 09:24) Felicia Jadczak: Those people. One of the biggest VCs out there. They After Elon pledged $45 million a month, which I'm still eye-rolling so hard if anyone is curious how I'm patiently reacting to this, they came out and they were like, well, we're also going to make some pretty big donations to Trump. And they told all their employees this. And they used Musk as part of their justification for why. And they basically were like, oh, if they, and I'm air quoting, a visionary, a tech visionary like Elon Musk is doubling down on Trump, then we should too, which don't even get me started on that line of thinking. And, you know, they basically were like, we believe that Trump is going to be really good for entrepreneurship. And so that was, you know, a very big shift in, how I think a lot of tech companies and VCs are approaching this current political landscape because it really you know we've been talking about this for the past week or two at least but in 2016 when Trump first got elected and you know came into power in 2017 You and I saw a very, very distinct reaction against Trump led by tech companies. And a lot of these companies were like, wow, holy shit, this is not good. We got to stand up for this and stand up against this, rather. something that we're not seeing that same response this time around. So I'm super curious to see if now that Musk has changed horses, as it were, if any VCs will follow, because if they do, then it's just super pathetic because they can't even convince anything.

(09:24 - 09:45) Rachel Murray: Well, yeah, and it just goes to, I mean, it just goes to show how everything has been so performative, you know, whether it's what happened in 2017 or in 2020 and now it's like, what is your true colors? What are you standing for? And if you're literally just standing for late-stage capitalism, just say it.

(09:46 - 10:34) Felicia Jadczak: Yeah and you know so like in that sense I'm kind of like just sure keep telling us what you really believe because I do think that there is this now and it's not just this moment this particular unique moment but we're seeing this in general over the last you know probably two-ish years or so there's been such a backlash and a you know moving away from DEI and all this stuff that's you know social justice and all these things associated with it and so part of me is like All right, just tell it like it is. If you really believe that if you are racist, sexist, ableist, a horrible evil person, then I'd rather you just say so as opposed to pretending to be someone that you're not. Right. Because like, you know, just show us your true colors. And then my point is, like, stick to it. Like, don't backslide. And be like, oh, never mind.

(10:34 - 10:57) Rachel Murray: I'm not really evil. Come and hang out with me. It's sort of like, I mean, honestly, it is very much like the way the RNC are working toward a full abortion ban for the entire country, and yet not once did they actually mention it during the entire time of the RNC did they mention abortion because they know that is not a popular opinion.

(10:57 - 11:05) Felicia Jadczak: Well, it's going to set off a lot of white women who they are counting on to be part of their base, and this is a divisive issue.

(11:06 - 11:44) Rachel Murray: Yeah. Yeah. Yeah. So we should just rename this podcast the We Hate Elon Musk podcast, which I would be totally down for because I feel like if there's any opportunity for me to complain about him I will but and there's goodness knows a lot more to talk about but this isn't a political podcast so even though we kind of yeah yeah I mean yeah it does all tie in right I mean ultimately we do talk about it here because the work does tie we have to because nothing is in isolation nothing is in isolation we can't talk about the stuff we can't do this work in a silo and you know like we could probably spend not even a whole episode but a whole

(11:44 - 12:43) Felicia Jadczak: podcast season just unpacking Kamala Harris' presumptive nomination and all the associations and pros and cons and responses and reactions and thoughts and feels and all that. That's probably something we'll have to put a pin in that for next. We'll talk more later, but we should probably get into our show today. Let's do it. We have a good guest. And so our guest today is Lisa Simon, Chief Economist at Rebellio Labs. She leads the economics and client success team. She's providing key insights on workforce trends. She's got a PhD in economics from the University of Munich. Her expertise spans labor market data analysis, the future of work, and adapting and changing labor markets. We get into all things workplace research, including conversations around skills, uselessness of job titles. I think we see that is very pertinent given my issues just now, employee expectations, and a lot, lot more. So we're going to get into that.

(12:43 - 13:26) Rachel Murray: Amazing. And before we welcome Lisa, we want to share an exciting resource with you. Did you know that we offer a fantastic newsletter packed with the latest news, insights, and resources on workplace inclusion? We bet you didn't. Now you do. I hope so. It is humbly, we think, the best resource for learning how to support a truly fair and inclusive work environment. Don't miss out. Sign up today. You can do so at SheGeeksOut.com forward slash newsletter to stay informed and inspired with a little less politics. We're just going to put that out there. Less political. Well, for now. True. We've got a long 100 days ahead of us.

(13:26 - 13:27) Felicia Jadczak: All right. Welcome, Lisa.

(13:30 - 13:33) Lisa Simon: Hi, thanks for having me.

(13:33 - 13:56) Rachel Murray: So happy to have you. We are so excited to talk with you about all of your incredible work. But we'd love to just start out by asking the very first question, which is always about your origin story. So we'd love to know about your journey through academia and now your leading role at Revelio Labs. How has your passion for economics and data science shaped your career path?

(13:57 - 17:04) Lisa Simon: Yeah, that's such a big question. Let me see where I start. So I started econ as an undergrad actually in a double major and was doing policy on the side so so both international relations and economics. And thought that sort of sounded really cool at the time without probably knowing too much what I was getting myself into. But I actually really love the topics that we're discussing and poli sci more than than sort of the classic economics themes that come up at the beginning of your of your undergrad sort of very micro macro based topics. So really love the the poli sci part but didn't really understand the methods there. So I think that wasn't really speaking to me the sort of very qualitative word based argumentation lines. So I think I was really intrigued by the opportunities in economics to quantify impacts and really understand cause and effect. And so I think that's that's how I got into get really empirical microeconomics that I then. did a master's in later on in economics and public policy. And sort of that's where I first understood all the different topics that you can work on with this toolkit under my belt. So I got really deeply into health economics for a moment, and then started getting interested in education economics and labor economics, which is where I eventually did my PhD in. And I think I was sort of always motivated by the questions and answering them well, more than sort of, you know, the tools used, but I thought I think the tools used in economics are just really handy and understandable to really tease out cause and effect. you know, put some uncertainty around point estimates and things like that. So I think that's how I got to be a labor economist. And then after my PhD, I think I had a very classic labor economics sort of education training behind me and then decided to sort of get a little bit deeper into the tech side of things and was lucky enough to do a postdoc at Stanford with Susan Athey. who was at the time sort of at the forefront of questions around applying AI methods to causal inference research at the time. So I got this sort of technical side of my training added into it, more data science tools and and more of a data science burnish, I suppose. Yeah, and then ended up going to Rebellio Labs, which was another career pivot. But I think I found a very good home for my skills and ambitions, I suppose.

(17:06 - 17:20) Felicia Jadczak: Thank you for talking us through that, quite a journey so far. So let's talk a little bit more about your current role. So could you maybe share a little bit with our listeners what Rebellio Labs does and also your role as chief, is it economist or economist?

(17:20 - 17:21) Lisa Simon: Yeah, chief economist.

(17:21 - 17:29) Felicia Jadczak: I don't know why I have like a brain fart when it comes to pronouncing that. What does your role entail at Rebellio?

(17:30 - 20:43) Lisa Simon: Yeah, for sure. So we're at Rebellion Labs. It's a workforce intelligence company. What that means is that we really want to help understand what any company looks like in terms of their human capital. I use the word human capital as a labor economist. I say that lovingly. It's not a slur. people sometimes misunderstand this term. So really understand the employees at any company, which is a harder task than you would imagine because there's actually fairly limited good data out there in terms of really understanding what companies look like. So how fast is a company growing? What does it look like in terms of its gender and ethnicity distribution or roles and locations and skills and activities and all of these things. That's what Rebellion Labs brings to the table. And we supplement that with a bunch of interesting additional data sources, such as sentiment data, layoff data, job postings data that sort of brings a forward-looking view into what companies are looking to hire. And it's amazing the amount of different applications that this data finds. So it gets used from anything from investment management and sort of investment decisions to sourcing, finding the right talent, to talent intelligence, people analytics, benchmarking. site selection, the list goes on and on in terms of what we're able to do with this data and able to offer in terms of data and services. And I get to lead the economics team at Rebellio Labs. So that's the team that's really in charge of producing a lot of the cool research and great content that we're able to distribute and sort of showcase a variety of use cases for this data. I always say I have the coolest job in the world because that's sort of an applied labor economist. Getting to play around in this data that we have is a little bit of a dream. So yeah, that's the role of a chief economist, I suppose. I was laughing as I was preparing for this interview and saw this question. I always, we at Revalue Labs are of the opinion that the job titles are sort of meaningless because just the job title itself means something completely different at every company. That's one of the main things that we that we solved is to sort of standardize across different companies and industries across the economy, the the job titles. So what a chief economist does at Revalue Labs is probably not representative of what it does at other companies. But yeah, the requests for, you know, outlooks on the inflation have increased for me as I became a chief economist. That's not necessarily something that I'm an expert on. So it's amusing.

(20:43 - 21:03) Rachel Murray: We won't ask you questions about the inflation. We'll stay away from those. I'm kind of curious. You mentioned that there's a lot of data that's missing that you would love to have access to in order to enrich all of your research. So I'm just curious. This is going to happen from time to time where we have unauthorized questions. So feel free.

(21:04 - 21:06) Lisa Simon: Yeah, it should be a conversation.

(21:06 - 21:19) Rachel Murray: Love it, love it. So if you had a magic wand, what data would you love to have access to? And do you see a future where this data could be accessible on a wide scale?

(21:20 - 22:39) Lisa Simon: Yeah, so I think companies having to, you know, declare and report numbers of headcounts that sort of go beyond one number, that's the total headcount of W-2 full-time employees. That would, of course, make our lives a lot easier, but also, of course, reduce the need for this data a little bit more in the first place. So I suppose it's a bit of a give and take, but that's probably the big one. If companies were to break down their employee base more, both by full-time, part-time contractors, perhaps by some demographic information as well. I think that's sort of the big one. I do think there's a world in which we'll see that. I know of many great initiatives and one that's sort of probably most promising in that regard to make that a reality and bring those suggestions to the SEC. So I think that's a potential future that we'll see.

(22:39 - 23:07) Felicia Jadczak: With all the access that you do have to the data that you can get your hands on, what are some of the more surprising trends that you may have seen or noticed over the last couple of years in the labor market? And you mentioned just now full-time salaried employees and contractors, and there's all sorts of other types of employees. I'm curious if maybe that's tied into some of the trends, but I won't answer your question for you. What trends have you noticed? These are just my speculations.

(23:08 - 26:04) Lisa Simon: Yeah, I mean, there's there's so many things that we can discuss and feel free to do, you know, double click on anything that I say, but I think, by and large, we've just seen such a such a remarkable few years on the labor market sort of starting out with COVID that's completely changed the way in which people work and work gets done. So this remarkable shift towards remote work and how quickly people have adapted to it. And I think one of the surprising trends that we've seen after COVID ebbed off was how much people loved working from home and the whole remote work trend sort of not going away as quickly as you might have predicted previously. So I think there's sort of remaining tension between employers and employees to keep working remotely or have some form of hybrid work arrangements. I think that's definitely a very surprising trend. The other one, I think it's sort of post, if we're thinking post COVID, we saw the great resignation and sort of this massive hiring spree that a lot of tech companies went on at the end of 21. And then now we're seeing the complete sort of opposites. I wonder if this is the boomer, maybe not boomerang, but sort of the other end of the pendulum swinging the other way where people are now sort of staying put, nobody's hiring, nobody's going anywhere. And people have this deer in the headlight moment where where nothing is happening. I wonder if that's partially because people were switching around so much previously and have perhaps found like the right match where they're happy to stay a little bit longer than we've previously seen. But I think there's something else underlying and I wonder what will happen once the large parts of the economy sort of regain some of its momentum as we were previously seen. It's interesting because this is all sort of happening alongside a very gloomy workforce, actually, we're seeing sort of very negative sentiment among a lot of employees. So there's sort of this, this interesting trend going around, while in theory, the economy is doing very well, and labor markets are very, very solid, despite sort of slight signs of, you know, very welcomed cooling, of course, but Yes, employees are just not not very happy and I think there's just a lot of other merits and and gloom going around that that probably has less to do with employment and sort of more to do with the general state of the world.

(26:04 - 26:26) Rachel Murray: Well, I would love to dig in on that and double-click on that. Is this part of your work, too, is sort of assessing the why, the looking into why these are, why this is happening, essentially? Because I, again, I know Foolish and I both certainly think about this a lot and have a lot of thoughts. Why people are so unhappy and why people are staying put.

(26:27 - 28:00) Lisa Simon: Yeah, so I think I don't have the answer and we certainly sort of haven't haven't explored the end of it. I do think that part of it is probably this improved match rate that we saw as people sort of were switching around so much. previously, I think there is likely something where people found better matches than they were previously in and are sort of staying put. The other part is plain uncertainty, I think, both on the employer and the employee end. And I think this is a big challenge that I was thinking as we're looking to the future is sort of regaining some trust between employers and employees. I think they've sort of double, what's the word, double, like backstabbed each other in the past couple of years where employees lost some of their loyalty towards their employers and just switched around a lot and sort of went on this exploration. And employers, on the other hand, going through a few rounds of mass layoffs that didn't feel particularly necessary, perhaps at times. And so I think there is sort of this moment where people are staying and looking whether there is this trust that can be regained, and then what happens after? How do we move past this moment of, well, in the end, employers and employees, you know, need each other?

(28:02 - 28:45) Rachel Murray: Wow, Lisa, could not agree with you more. Yeah, that is exactly how I think both Felicia and I feel, that there is just a trust that has been broken and there is just a feeling that there is also this uncertainty and it's like the devil you know versus the devil you don't know. And just one quick follow-up and then I promise I'm going to pass it over to Felicia. is one thing what we're seeing a lot of, which I'm assuming you're still seeing in your research, is that even though people are saying that the typical, like, maximum amount of time that a lot of employees are staying now are like two years versus, you know, 10 years ago, where people were staying much longer than that. Are you still seeing that trend, even though people are staying put?

(28:47 - 29:25) Lisa Simon: Yeah, I think sort of looking at a longer time horizon, for sure, work employment spells have shortened and certainly time with employers have also shortened. I think a lot of that has to do not so much that people are just staying in places shorter, but that it's a bit of a distributional result of which industries have grown in employment over the past years that just typically have sort of shorter tenures and shorter employment episodes.

(29:25 - 30:34) Felicia Jadczak: You know, Rachel and I were talking just this morning, actually, about the dynamics between managers and employees. And, you know, what you said about that, that like loss or of trust or having to rebuild really, I think, spoke to me because that's what it feels like. Right. And I do feel And this is just me not being actively on the job market, FYI, Rachel. But I do feel like what I've seen is that it feels like a lot of employers are still kind of like almost punishing employees for the great resignation with just these sort of indiscriminate layoffs and being like, you know, you're indispensable. And I can because the market's so tight and it just feels like there's so much anecdotal you know, stuff out there that I've seen from people being like, it's so hard to get jobs right now. So, you know, one of the questions we want to ask you was. What you think are, are really sort of the biggest challenges that are currently facing the workplace in regards to employer employee dynamic. And I feel like this is probably a big one, but I'm curious if there's anything else to say either on that front, or if there are other challenges that you've noticed from your data analysis that we haven't talked about yet.

(30:35 - 33:31) Lisa Simon: Yeah, I think this is definitely a large part of what we're seeing right now, right, where job postings, for example, are staying open longer than we've seen before. And a lot of job postings never being filled. So this sort of occurrence of what we call ghost job postings, so just sort of phantom postings that just don't get filled for months on end. And with employers just sort of, you know, it's cheap to have a job posting open and just sort of do some cream skimming in terms of seeing what candidates come in, and then maybe, or maybe not hiring. If someone exceptional comes along without really sort of filling a particular need. Yeah, it's interesting that you use the word punishing employees. I think that's sort of part of the problem is that I don't think employers think that far ahead in terms of what they're doing or not doing to their employees. I don't think there's sort of a retaliatory theme going on. It's just sort of a lack of foresight and sort of planning ability. So that's just my take on that. But I think what really one of the biggest challenges ahead is that we haven't fully seen the boomer generation retiring and the actually really, really tight labor market that we're in for. Some of that in the US recently has been mitigated by sort of influx of quite a lot of migration. So I think that's part of the reason we've seen the US economy do much better. And instead of the past two or three years or so, compared to some of the European counterparts, just in terms of like growth and dynamism. Whole other story, we could get into that. But I think that's sort of one part that goes into that. But I think we are still in for a lot tighter labor markets. So hiring will get harder and people will want to hold on to their employees more. And I think what we'll invariably see is just sort of this bigger focus on retaining employees and reusing, reskilling, and retaining them at all costs, even if perhaps not in their current capacities. So I think this sort of idea of linear career pathways and people just doing one job And to my point, job titles are meaningless. I think we can go towards what we like to think of as an activity space or just what people are actually able to do. And using talent in a much more flexible way is probably one of the trends ahead, if I'd have to make a prediction.

(33:33 - 33:54) Rachel Murray: Wow, that is fascinating. And I want to skip ahead actually to another question that's related to it because you made me think about AI in talking to this obviously super hot topic. Would love for you to just talk about what human-centered AI is and how you think this might play into what you just shared.

(33:54 - 37:32) Lisa Simon: Yeah, yeah. So I guess you read human-centered AI somewhere on my CV. I used to be part of a an institute at Stanford for human-centered AI that was very mindful of keeping AI as sort of a human, augmenting human, enabling technology as opposed to replacing. So I think that was sort of the main focus. And it's really interesting to me because I've been doing a lot of research on the impact of AI on the workforce for many years. And as we were thinking through what the impact or the potential impact on the workforce of AI would be, I think we always have these ideas of what sort of the breakthrough technology that would touch the labor market the most. And I don't think my prediction was anywhere close to what the actual realization of this was. when we're thinking about what AI is good at is are things like pattern recognition and sort of, you know, predicting, recognizing, yeah, recognizing patterns, seeing, seeing things that are reoccurring. But this proliferation of AI now in as a as a generative machine for Um, you know, generating text, generating images, uh, code and so forth is, is not what I was expecting. And so I have to rethink a lot of sort of my priors in terms of what the impact of, of, of AI was going to be. Um, Not that I don't think the other, um, the other predictions are in invalid. I just think the, the sort of the bulk of it just looks different from what we were, um, what we're expecting, um, perhaps back in 2019 or 2020 or so. So generative AI and the workforce I think is such an interesting topic because we're at the very beginning of everybody's learning curve with it. I think people are experimenting with it and seeing where it's useful. I'm sure there's a lot of power users out there that will tell you that they're already using it every day, but that's I think a small minority, a sliver of the workforce where that's the case. And the potential is enormous, but I think it's a question of how it gets employed and everybody sort of finding their right level of adoption and dance with it. So how much it gets used for writing, for coding, for planning. I've seen a lot of advice or suggestive evidence that people should stop learning to code and I think that's such a misguided view of the world where you know you'll just tell an algorithm what to output and then sort of employ it blindly. But I think the people that will really succeed or be successful in the future will be those that can do both, right? That can both sort of give the right prompts, but also check that, you know, the general idea is the right one, that the architecture of code is correct, that sort of the larger view of the work that gets done. Yeah, like I say, I'm very excited by this whole topic and how it will play out on the labor market.

(37:32 - 37:34) Rachel Murray: Are you nervous about it?

(37:34 - 39:14) Lisa Simon: Yes and no. So I do think that sort of blindly applying and letting it run its course can particularly do some sort of distributional damage in the sense that we do see that roles that sort of are likely just more exposed to things that AI can do tend to, for example, be more female focused. So if you think of sort of the top 50 roles, I think that have sort of a large overlap in the tasks that AI can also do are admin roles or HR roles, they're sort of all more female focused. So I think there's sort of this slight danger in that. Having said that, I don't think anyone is actually sort of fully replacing any of these roles at all. I think what is going to happen is sort of a reconfiguration of roles where more menial tasks, more repetitive, annoying tasks get automated away. And then the people, you know, the human in the loop gets to do a lot more interesting work, a lot more impactful and just fulfilling work. And that, on the other hand, has, you know, tremendous, tremendous upside, both in terms of earnings in terms of career pathways forward. And just, yeah, just sort of a sense of fulfillment, I suppose. So I think there's sort of a yes or no answer to this.

(39:15 - 40:46) Felicia Jadczak: I've seen a lot of memes circulating recently were around this exact topic where it's basically I'm going to paraphrase here but it's basically saying, you know, I want AI to take over. the tasks that are things like laundry and dishes, not AI takeover writing and making art and that's kind of where we're headed right now where it's like oh AI is making art and it's like no that's what we need to do as humans. AI needs to do the boring stuff so we want to do the creative, exciting, fun things. Yeah, hopefully we'll be able to shift it a little bit. But bridging to the next question I want to ask you with this topic still, so I'm sure you are aware and have been following META's recently announced AI Council, which is for white men. And you talked about things like pattern matching, which is something that AI is really good at. But we also have to remember that AI is created by human beings. And so we're building in our inherent biases and issues around that as well. And so when we also have oversight that's really limited, that's for me at least a potential issue. So I'm curious with that in mind, what kind of impacts you've seen or think that diversity, equity, inclusion, which of course is what we're really interested in in our work, what kind of impact that sort of approach or lens might have on organizational success or Is there anything around that kind of topic in your research and your data analysis that's come up for you?

(40:46 - 41:10) Lisa Simon: Yeah, I think just as you were describing the sort of current use cases of some of the generative AI, I was just starting to play around actually with Metas AI bots and it was sort of giving me prompts around like, Imagine a laser sword used in combat and massacre. Only a guy could have coded this up. What is the use of it? 100%. Are you serious?

(41:10 - 41:16) Felicia Jadczak: A laser sword? You're like, who was the Star Wars fan who built this thing?

(41:16 - 45:35) Lisa Simon: So I think the use case and what do we do with this is a big question, absolutely. I absolutely think there's sort of issues that we have to think through. And what we're seeing at the moment, in particular, in terms of who is developing a lot of the technology around AI, has a massive representation problem. So actually, five or six years ago or so, developers in this space were actually fairly evenly distributed, at least among men and women. I was just plotting this on a graph actually last week. And then sort of with the proliferation of AI technology, a lot more people sort of went into this space. And we saw this gender balance actually go completely out of whack, especially sort of around last year. But we actually saw sort of a drop in the gender representation, I think by 10 percentage points. So it was roughly even an hour sort of hovering around 40%. women versus 60% men. So that invariably has impacts in terms of what this gets used for, how deeply things get thought through. I think I'm a little bit more hesitant to say that there's this sort of biases in terms of the output. I think that depends a lot more on the input data use than who is sort of you know, training the algorithm. So that's a, you know, that's a whole different question in terms of what is actually the input and the training data that these models get trained on. And I think that's sort of a big topic that these companies have to solve. And already they're hitting this limit of, you know, just running out of actual training texts that, you know, for these models to keep getting better. But especially in our work recently, we have seen a lot of very interesting just results in terms of diversity, equity, and inclusion. So just to name a few, around 2020 with the Black Lives Matter protests, we saw this big return and big focus on DEI roles being hired into sort of corporate America. So big excitement in that space. And then just sort of a year and a half later, we were actually seeing that these roles were leaving at extremely fast rates from companies again. Partially sort of being laid off, but I think more importantly, just people leaving out of their own, just out of their own will to pursue other things. And I think there was just sort of a lost momentum in this cause that had a lot to do with expectations being set wrong and people not having the tools and resources available to sort of be successful in these roles. So that was a really sort of disheartening trend that we were observing last year and then one that's definitely continued this year as well. And then, of course, there's a very charged political climate around the whole topic to begin with. So we're also seeing just a lot of renaming of these initiatives and, you know, roles again, to the point that job titles are meaningless. Job titles for DEI officers, I think, are also being, you know, called something something very different. There's one result that I that I think is also interesting, just as we're thinking through maybe gender and yeah, just gender trends on the labor market. We've recently come across this surprising new gender gap that I thought you might be interested in.

(45:35 - 45:41) Rachel Murray: Is it going to be good news, Lisa? Is it going to be good news? I feel like the answer is no.

(45:41 - 47:38) Lisa Simon: It's really not. And I really didn't want to believe it when I first saw it. So of course, we know the gender pay gap. we've seen results that women sort of talk about themselves differently when they describe themselves sort of in less active terms and focus perhaps more on their strength in terms or what they were able to achieve. But now we found another gap in terms of how other people talk about men and women in their recommendations. So what we looked at were public recommendations on people's profiles, where past bosses or colleagues have written a recommendation or sort of a review is probably the wrong word for, but just a reference is the right word, I suppose, of former colleagues or former yeah, just people that work for them. And there was this massive gap in terms of how men and women were talked about. And we really restricted the sample to really just engineers that were comparing apples to apples, the software engineers at similar companies. And this gap persisted. And the things that we were seeing was that men were really given technical and complex terms in terms of how they were being talked about and how their work was being described. And then for women, more of a focus on their personality and their wonderful outgoing nature and a joy to work with and all of these sort of fluffy terms, even though they were both engineers and sort of, you know, should have been described in sort of similar ways. So just when you think that there are no other gender gaps left, there's one, a new one to uncover. So that's some of the joy and tragedy in some of my work.

(47:38 - 48:05) Rachel Murray: Well, I will say one thing that I think is changing that I've noticed, again, anecdotally, is it seems that there is actually, the good side for this is that there's actually more of a desire to hire people who maybe are quote unquote the fluffly personality based recommendations, we were talking about this, the hard skills. Those are actually the hard ones is those. And then you can teach the technical. I think that's right.

(48:05 - 49:09) Lisa Simon: I think you're right. I was having this conversation with one of my friends and she rightly said, well, maybe that's That's exactly what you want to be lauded for, instead of the technical skills. And we've actually found some evidence for that, too, because those things are also easier to test, right? The technical skills, you can pass a coding test. But whether someone was diligent and respectful and professional, is of course harder, so that's true. And we see a greater return to having a recommendation on your profile for occupations that rely more heavily on such skills, so especially sales and yeah, marketing or just anyone sort of relying more heavily on just soft skills has a higher return to having one. But still, I thought that the engineers that were being called wonderful was just a little bit too much.

(49:09 - 49:21) Rachel Murray: Yeah. No, it's really a great point. I'm so glad that you talked about this because I think it's just, it's a good reminder for anyone who's writing reviews or recommendations to ideally include both.

(49:22 - 49:23) Lisa Simon: Yeah, I think that's right.

(49:23 - 49:44) Rachel Murray: Yeah, no, that's great. And I know that we've covered a lot about the future of work and trends, but I wanted to just make sure that there isn't anything else you wanted to add, especially on employee expectations in this sort of new world that we live in, if there's any sort of future considerations that we haven't already covered.

(49:44 - 50:48) Lisa Simon: Yeah, I think one topic that we're currently very excited about our work activities. And by that, I mean, the the things that people actually spend their days doing that are typically covered in maybe your job description or your bullet points on your CV. And we've sort of finally found a way to build a taxonomy around the things that people are actually doing and are able to break them down. And so I think to my previous point that we'll see work roles and occupations be a lot more flexible with who does what and perhaps people reinventing themselves a few times in their lives and just drawing synergies on what they were previously doing even if it was perhaps in a different field or a different context. I think that's some of the things that I find exciting and interesting and I think will create a whole new challenge for both hiring managers and people analytics and just HR in general.

(50:50 - 51:31) Felicia Jadczak: With that in mind, I want to come back to something that you've mentioned a couple times in our chat so far, which is around this idea that job titles are meaningless. And so, in a sort of like future world. If we toss this idea of job titles out the window. How can we hire or assess people or even know if a role should have more technical recommendations in the language versus soft skill recommendation language? Has that come up at all in your thought process or is it more just around like in Revelio Labs and sort of more, I guess, like immediate working in terms of how that plays out?

(51:33 - 53:40) Lisa Simon: No, I think it has a very real and direct implication for the real world in terms of how people are being hired and evaluated. I say job titles are meaningless just because they are so diverse and everyone has a separate one in their respective job and workplace. But I think what it comes down to is that what you really want to know is not what was someone's previous job title, but what were they actually doing and what are they able to achieve? Were they able to manage a team successfully? Were they able to fulfill or manage a project, deliver a certain software or ship a package, whatever it is. I think that understanding what people are able to achieve is a very real way in which work could get organized and in which companies just think about talent in general. I think recently there's been a big push towards skill based hiring. And I think that's sort of maybe the the flip side of we have in mind we just think skills aren't sort of the right metric of of measurements. So skills are. sort of one word inputs into what activities can become. And so we like to think of jobs as a bundle of activities and just sort of a more meaningful way of measuring what actually needs to be achieved. So if you sort of break down the things that need to get done in a particular company, you could sort of endlessly reconfigure who does what and perhaps the old ways in which occupations fall into the bundles of activities that they were previously doing is sort of the most efficient or perhaps best way of organizing a company.

(53:40 - 53:51) Rachel Murray: Right on. That's super helpful. Thank you for sharing that. I'm curious to know, in your view, what norms or practices in today's corporate world should be challenged or rethought?

(53:52 - 55:14) Lisa Simon: Yeah, I think just continuing on that line, this idea of linear career pathways, I think, is probably one that is outdated. And even when I think about my own career path, I don't think I was necessarily ever thinking about doing exactly what I was doing now. And it was just sort of thinking what I needed to know in order to do the next step. And I already also don't know what I'll do next. It might be something that is probably related, but might not have the same job title. Well, who am I kidding? I'm a little bit of a snob about being an economist. So maybe that's not true. But in theory, at least, I could do something that uses all the same sort of things that I'm able to do, but in a very different context. And I think as people progress through sort of an increasingly varied future, this idea of linear career path is probably something that will let go off more and more. And I think just individual biographies and pathways will become the norm where there's not just sort of this

(55:15 - 55:27) Rachel Murray: one straight line from A to B to C. Yeah, I wonder how that will impact higher education, which is already evolving quite rapidly.

(55:27 - 56:07) Lisa Simon: Well, we might see sort of a re-emergence or sort of a revival of what I'd like to call sort of generalist education majors. So your liberal arts colleges might see a revival where you just want sort of well-rounded people that are able to make good judgments and the right moments and sort of all the rest in terms of technical knowledge and all of that as sort of bonus and perhaps more of a on the job or like a vocational learning type of thing.

(56:07 - 56:09) Rachel Murray: Interesting. Interesting. Thank you.

(56:10 - 56:13) Lisa Simon: Well, we got deep into the philosophy there.

(56:13 - 56:14) Rachel Murray: I know, I'm like, I could go.

(56:14 - 56:34) Felicia Jadczak: That's great. We're all about here. Well, I don't know if this next question will be deep or not. I think it will be, maybe. But looking ahead, what kind of impact do you hope to have through your work, whether it's linear or not? What would you like to be most remembered for in your professional life?

(56:34 - 57:26) Lisa Simon: Oh, what would I like to be remembered for? I think that's very deep. I think if I can show that you can use data for answering just about any question, and that more data is always better, even if it might not be as established yet as previous sources. Yeah, that there's no bad data, only good uses of imperfect data. this trend to really doing evidence-based decision making and research and policy making in particular. I think that's something. If I can have a small impact on that, that would be great.

(57:26 - 57:35) Rachel Murray: We could literally have an entire other podcast episode dedicated to the fact that people don't even value necessarily science and data and what is truth anymore.

(57:38 - 58:06) Felicia Jadczak: I know. And I, I was like, I have, I have a quick follow-up question, which I don't think we'll have enough time to get into, but it made me think too, about how data is treated globally, because here in the U S we have a lot of data around workforce employment and identity and things like that. In Europe, it's really different because it's so much more restricted and protected. And so I'm sure you love getting access to us company data, but that's not the whole story. If we want to look really holistically at this kind of stuff. So.

(58:07 - 58:23) Lisa Simon: Yeah, I wrote my PhD thesis in using social security data in Germany, and you had to go into a special room without any access to the internet and leave your phone and not take pens. It was a whole experience, but that's a different topic.

(58:23 - 58:33) Rachel Murray: We talked with another economist a few months ago, too, and she ended up having to use all of her data from Finland, apparently, because, yeah, they had a lot more information than the US.

(58:33 - 58:43) Lisa Simon: And then and then you ask about the external validity of those findings. I mean, nothing against Finland. You know, very different country from the US.

(58:43 - 58:54) Rachel Murray: No, don't ruin it. Well, okay, final question that we love to ask all of our guests. What are you currently geeking out about that's different than anything we've already discussed?

(58:55 - 59:23) Lisa Simon: So I'm actually currently in Spain and I was harvesting salt over the weekend from the Mediterranean Sea and I got very, very absorbed by this activity. That is so cool. Salt from the cliffs and drying it out over the weekend and everyone is going to get some salt for the future and the present from me.

(59:23 - 59:26) Rachel Murray: That's incredible. How long does that process take?

(59:26 - 59:39) Lisa Simon: I mean, it's quick in and of itself. The salt is already dried down by the cliffs and you just have to sort of scoop it out carefully and then just like lay it out for another day to dry and then, you know, break it up in even pieces.

(59:39 - 59:49) Rachel Murray: And can you go like anywhere? Are there like spots where you go? Are they like sanctioned by the government? You can only get your salt from these particular places?

(59:49 - 59:55) Lisa Simon: No, I don't think anyone cares. Salt water is the one thing that's in abundance.

(59:55 - 01:00:02) Rachel Murray: Fair enough, fair enough. But I'm like, I love salt so much. I would totally expect it to be kept.

(01:00:03 - 01:00:18) Felicia Jadczak: Well, I have a, I would like to double click on this geek out answer because it's great. No one's ever shared this before with us. So love it. Did you go to Spain specifically to collect the cliff salt or are you there?

(01:00:18 - 01:00:40) Lisa Simon: I'm visiting family and I saw other people doing it and I thought, you know, it's all there. Let me go get some utensils. And so I started doing it and then found myself sort of three hours later on the beach still scooping salt and found the exercise to be extremely cathartic. That's amazing.

(01:00:40 - 01:00:51) Rachel Murray: I'm literally going to Google this right after and see if I can get in on this party because that does sound like a good time. Thank you so much, Lisa, for sharing your wisdom with us.

(01:00:51 - 01:00:57) Lisa Simon: Thanks for having me. Glad if some of it was useful. I'm glad.

(01:00:57 - 01:01:11) Felicia Jadczak: It's all useful, including the salt. Lisa, if people want, if our listeners want to follow up with you, if they want to learn more about the work that you're doing, um, how can people either follow you, get in touch or is there anything else that you'd like to plug?

(01:01:11 - 01:01:29) Lisa Simon: Yeah, absolutely. You can find us on rebellialabs.com forward slash news, uh, subscribe to our newsletter. It's, um, you know, a weekly newsletter on little, uh, insights on the workforce. And, um, you can find all the information about myself and all the other contributors on there.

(01:01:29 - 01:01:47) Rachel Murray: I will say we both get a lot of email in our inbox, and this is one of the emails that we genuinely read the whole thing from top to bottom. So I speak highly of their newsletter. Thank you so much, Lisa. Thank you. Thank you.

(01:01:50 - 01:01:58) Felicia Jadczak: Thanks again, Lisa. Well, for anyone who's still here listening, we hope you enjoyed listening to our interview with Lisa as much as we enjoyed the conversation.

(01:01:58 - 01:02:13) Rachel Murray: And thank you so much for listening. Please don't forget to rate, share and subscribe. It makes a huge difference in the reach of this podcast and by extension this work. And don't forget to visit us on YouTube, Instagram and LinkedIn to stay up to date on all things Inclusion Geeks.