AI in Recruitment - Benefits, Risks and Ethics

Transcript

Karen Kirton  00:00

We thought it would be timely to dive into the world of artificial intelligence and how that interacts with HR activities and learning. And before I do that, I just want to quickly mention that we've put together a special offer for our podcast listeners. And it is the opportunity for you to upskill with a free recorded masterclass from amplify HR on managing performance. And then to embed that knowledge you can then participate in a free short 10 question multiple choice quiz delivered by Yano On completion of the masterclass. So if you're interested in that free upscaling option, just head to our link tree which is Li n k t r.ie/make. It work podcast, and you'll see the link to get started. So with today's episode, I think it's important to define what we mean by artificial intelligence or AI. And I've been reading a bunch of research papers. And the most simple definition is along the lines of AI being technology that can autonomously perform tasks commonly thought to require human intelligence. And you may have also heard about machine learning or ml. And that is a subset of AI where those autonomous systems then improve their performance again autonomously as they learn through experience. And I took that definition from UK Government paper, which we'll put the link in for the show notes as well. So today, we are using AI in ways you may not even think about so you know, from Siri on our phones to our Hey, Google to algorithms that feed us the news that we read on our phone. And in HR, we're seeing AI emerging in recruitment and selection, onboarding, training and development, employee engagement and retention, remuneration and even performance management, and evaluations. So as you can imagine, this is a huge topic with lots of angles. And as I was getting into the research, I thought this could be its own podcast series. But today, we're just going to focus on AI in recruitment and selection and Lachy. I'm interested, have you tried any systems that use AI for recruiting it?

Lachy Gray  02:00

Yeah, no, no, no, we haven't not explicitly, maybe under the hood, without me realising and not for a particular reason. I think as a small business, we've stuck with what we know. Since we hire relatively infrequently, though, I do think there's an opportunity to improve how workplaces hire regardless of the technology, considering it's something that is being done every day, it does feel a bit like the Wild West, in many ways. They, every company does it differently. job sites, do it differently. LinkedIn and seek, for example, allow the job seeker to apply with one click, I think that focus on simplifying the process for the job seeker can come at a cost to the hiring manager, who then has to determine suitability from a resume, which is I think, you know, 2d document without any context or colour to it. So I think it's an area of work that's ripe for disruption. And technology is definitely part of the mix. But I don't think that tech is a silver bullet by any means. And I do like your AI definition. My CTO, Paul likes to just call it software. Because there's so much sort of judgement and jargon wrapped up in some of these definitions are like it, keeping it simple.

Karen Kirton  03:44

Yeah, it's a great point, at the end of the day, we need to remember these technology. You know, as much as we keep calling it artificial intelligence, it makes it sound quite scary. But it is technology, it is software. So yeah, and you know, I personally haven't used anything beyond the AI for recruitment that I assume is sitting in platforms like LinkedIn. And indeed, because you know, you're given candidates that are sorted by those that the platform thinks are best suited for the job.

04:13

And I I recruited recently, so this is my experience from a couple of weeks ago. I know these sorts of things change all the time. But, you know, I found it somewhat helpful, but not hugely accurate, as it would be if you know, I actually inputted it specifically into the system, what competencies were required, like essentially, you know, the software was determining what it thought was important. And there are platforms that automate hiring by allowing you to add in those preset questions and you have the candidate interview, you know, by video, or even by phone with a robot.

Karen Kirton  04:50

And I guess on the pros, then the recruiter doesn't have to spend so much time interviewing everybody. But on the day downside, you know, then what about the candidate experience? So I think if you have that kind of work volume, then yes, you might do it like i Many years ago, I worked for an organisation where we had apprentice drives, and you will get literally hundreds of applications from the school labourers. And so to your point, like, how do you differentiate? So I think a programme like that could help. But, you know, the the other big issue, of course, with using AI in recruitment is the potential for bias. So, you know, I think that that still has to be considered as well. But if I go back to the candidates experience, it's a tight labour market, people have options. You know, how would you feel Lachy? If I said to you, can you attend this video or this phone interview? And it's going to be conducted by AI?

Lachy Gray  05:50

Hmm. I don't know. Yes, it's brand new for me. I think a big part of interviewing is building rapport. And I think how would I build poor with a digital voice over the phone? It feels weird to me thinking about it. And then, as the hiring manager, how do you factor in that the job seeker was speaking to an AI rather than a real person, and how that may have impacted their interview? I guess, depends if I'll be working with AI in the role that might change my perspective, and probably safe to assume that's what will happen. In the following decades that, that AI will become a co pilot in in many roles. It actually reminded me of Star Wars, and watching Mandalorian, the Mandalorian series, my kids, in one of the episodes there at the new rebel Republic headquarters, and a scientist has a wellbeing check with a robot that asks him the same questions every time he goes in with the same tone expression. And when I saw that, I thought how impersonal that must have felt, especially for a topic like well being. So and I also don't trust their current algorithms. I think, especially if they're making decisions about me or on my behalf and impact my career.

Karen Kirton  07:26

Yeah, that's interesting, that trust mechanism. Because I think, you know, humans have bias. We all know that. And, of course, humans build AI. And I've actually been reading Tracy Spicer's new book called manmade. And I just finished it, and I found it. Overwhelmingly frightening, I think is probably the best description of how, as she says, the bias of the past is being built into the future. And now I would personally be very concerned at this point in time about relying on AI for hiring decisions. And you may have heard recently about Geoffrey Hinton, who's a leading AI scientist, he's the winner of the 2018 Turing Award. And it was very public that he stepped down from his role at Google, to warn the world about the dangers of AI. And I know that made a lot of headlines. And I think it's important if people are interested in this or considering AI in their business, that they actually do start to look at some of that information, don't just take your new software on face value, and you're just focusing on recruitment, you know, some examples Highview, you know, they gave a lot of criticism around their computers analysing facial expressions to assess personality and skills. So much criticism that the company later said that they would stop doing that. You know, there was a lot of media around Amazon when they built the tool to help with recruitment, but they found that it favoured men for technical roles because it was comparing job candidates against the company's own male dominated tech workforce. So you know, they said all the AI screening enhances women's in the resume like a college name. And that the company said they never actually used the tool. They abandoned it because they couldn't be sure that it wouldn't continue to find other ways to be biassed, even though they fixed that issue with the word women's. And I think that's, you know, one of the big problems when we get into that machine learning is that that black box idea, we don't always know what's going on. You know, there's also concern around Facebook because we know they can micro target. That's why advertisers love it. So what happens if we start putting up job ads? So we asked Facebook to only show those job ads to particular groups, and that could then cross into discrimination laws. So I find this really troubling and I think that it's hard when we don't even know what's going on behind that wall or in that black box, so to speak, to fix those bias problems.

Lachy Gray  10:01

Yeah, definitely, I have a healthy dose of scepticism. But I'm trying to separate the technology from the human side of it, as you say, humans are building it. And it's being these models are being trained on data from the past that humans have created. And that's what worries me. That's the part that worries me. What I find fascinating is that the models are mirroring societal values and behaviour that we've accepted, perhaps implicitly. And it's making them explicit now. And it's forcing us to talk about it. So I think that is a positive. That's true. And something that I learned recently, reading a book called the alignment problem, which is basically about how do you give human values to these models is that there are a few training sets of data that are used to train a lot of other models. And one of these training sets is called Word to veck, etc. And that was open sourced by Google. So it uses unsupervised learning, which is one type of machine learning, where machines given a whole bunch of data and told to find patterns and regularities within it, which it does really well. So if you give it Vietnam plus capital, it'll come up with Hanoi. If you give it German plus airlines, it'll come up with Lufthansa and so on. So this works for a really broad range of topics like grammar and cuisine and science and geography. But it also captures stereotypes. So it'll pay carpentry and sewing, and doctor, a nurse. And you see how quickly the pairings become sexism biassed. So then, if a model like this is used to help an employer search for candidates, things could quite easily go wrong. So assist them using word Tyvek might observe that John has a typical word on developer resumes, it's more common than Mary. So then a resume belonging to John ranks higher and relevance than an identical resume belonging to Mary. And as you said, I am this is the issue Amazon had. My understanding is this was the model that that their machine learning tool was using. And they were hiring mostly men. And that's because in the past, most of the hires were men. So yeah, the decider negative score to the word women's. But they interestingly, this is over a couple of years. So they they kept editing the model to remove the bias, yet, then they found the model was assigning positive scores to vocabulary. So words like executed and captured, which are more prevalent on male resumes. And that's when they decided to scrap it. But the book points out that the same thing happens with human employers. Yes, they give this example from the early 2000s of 5000 identical resumes being mailed out, this is in the United States, with names randomly assigned to sound either white or African American. And they found a 50% gap in the callback rates despite the resumes being identical. So it's not a new problem. But I think it is really shining a spotlight on it now. And interestingly, I discovered last year, New York City introduced a law that penalises employers for bias in AI hiring tools. The law requires employers to conduct an independent audit of the automated tools they use. So thinking how is it actually going to work? So is that the head of HR, so getting subject matter experts in from their business or outsourcing them? To work out how an AI model actually works? And what is decision making processes? That's very interesting, because this is what we've seen in the media, most recently, that the CEO of open AI was up before Congress during the week in the States. He was saying a similar thing about the importance of regulation in the space. And I think it gets to one of the core issues, which is trust, which is how are these models arriving at the decision or the outcome? And I don't see how I'll be able to trust it until I can see that happened happening. And I'm also interested, like how you represent your company's values into the model, because that's a big part of hiring in my experience.

Karen Kirton  14:56

Yeah, and I think that it what you're saying about our In that study were in the early 2000s 5000 identical resumes being mailed out. Yeah, we know that that happens. And this has been ongoing for many years across lots of different studies that we know that humans have bias in recruiting and what we have bias full stop, but but I think that we know that with humans, so as a business, we can put in steps within the processes to try and reduce that bias as much as possible. I think the danger with AI and with using a software platform is that people would just have that implicit trust and just say, Oh, it's going to work out the best candidate, and not necessarily consider that bias component to it. Which I think is why that New York law is so interesting, because it is making people stop and go, Okay, I need to understand that this is a perfect, this is not an infallible system. You know, I know my own experience with hiring recently. I actually, after each interview, I did a debrief with a colleague, and just, you know, went through the the President's resume and the interview with my colleague, and I just wanted to check and make sure, you know, do I have any prejudice in my hiring decisions? Before I make this assessment? You know, am I making this assessment for the right reason, should that person actually go through to the next stage, and that was really important for me, because, you know, obviously, I work in this space that I have for a long time. So I'm very aware that I can't remove all of my own bias and prejudice. You know, in HR, it's mostly a female industry. So you know, I need to be careful that checking myself on gender, I need to make sure I'm not just preferring females. You know, we work really flexibly and, you know, most of the team of parents, so our roles naturally attract similar people, I guess, from that standpoint. So we also decided to hire students so that we couldn't make sure that we had some age diversity in our team. And I think just really considering the diversity of candidates to interview, and then discussing those selection decisions. You know, I found really valuable, and I don't know how I could replicate that with AI, you know, and I would just be worried that it would feed me candidate for the very much like our current team, because that is what we're considered as high performers, and I wouldn't even know.

Lachy Gray  17:35

Yeah, interesting. I do like those examples. And I remember some research I read a while ago, found that I think was from Google, actually, excuse me, when we're meeting people for the first time saying an interview, we typically make a decision about them in the first 10 seconds, and then spend the rest of the time looking for information to confirm that decision. So confirmation bias, whether whether positive or negative. And Daniel Kahneman, who wrote the book, or many books about biases says we all fall victim to victim to them, and even him. Yeah. And He's dedicated his life to studying them. So we've had Yano experimented with a bunch of different things, trying to be mindful of the language used to the job ad, that it's that it's gender neutral, as much as possible. Refreshing everyone who's in the hiring process about biases. So just talking about it. What are some common biases? What should we look out for? Because we will be affected by them? That's just, I think, how our brains work. And we try and do a similar thing, actually, before our 360 feedback, because it's a recency bias. It's easy to think of feedback from two weeks ago, or situations from two weeks ago, and much harder from two months ago. Yeah. But has that been fair to the to the person that we're giving the feedback to? Being clear about how candidates will be assessed and ranked before we start, and trying to introduce some objective criteria? Because in my experience, hiring is very subjective. Especially if you don't use any tools. So you do an interview, and is that gut feel on one of you saying positive? In other words, I was so sure, but I can't really articulate it that makes it was really hard to know how to proceed. asking the same questions in each interview. So following a standardised process, and then a really interesting one, which we've only done since we went fully remote because we didn't do all our interviews on Zoom now is if someone wants to listen to it after the interview, so they weren't on the initial interview. If we say, well, why don't you just listen to the audio, rather than the video and audio. And that's an in, in an effort to just make you focus on what the person is saying. Rather than how they look what they're wearing, what's in their background, all that information is, you know, our brains, thinking it over and over, it's like, ah, what are those books in the bookcase? And see that? The rooms a bit messy? And the lighting is a bit weird? And what did they think about that, you know, all that stuff that we're going through, it's just not there. So the other thing I've tried is removing names from resumes, before sharing them. I haven't stuck with that purely from a time perspective. So I definitely think software can help with some of these. That I'm, I'm sceptical of it taking over the whole process yet. Until you've we've got that trust and transparency in every step in the process. So how's it arriving? At saying, These are the candidates that I think should proceed? And these are the ones that shouldn't? And why?

Karen Kirton  21:15

Yeah, I think in some ways, it's like, you know, when you do psychometric testing as part of a recruitment process, and depending on what tests you're looking, you're, you're assessing different things. But, you know, although it's hugely valuable, and the research shows that it definitely helps to make better decisions using that testing. It also can only be one of the inputs. So, you know, we don't recommend anyone uses psychometric testing, and then just says, Okay, well, now we're going to completely disregard all the other steps in a recruitment process, and just focus on this. And I think that's potentially at the moment where AI might see it is helping with some of the parts of the process, but not being a complete input into it. I think my biggest hesitation with AI is using it for that initial shortlisting, because I think that's the part where you may actually be disregarding people for no good reason. Yeah, or for reasons that, you know, could be biassed or could even be unlawful in terms of inadvertently discriminating against people. And I like what you said before, about, you know, when you get applications through for the job, and you know, you just get a resume, and it's really hard to know, you know, who don't want to talk to with all these people, you know, and I found that as well, the shift has gone from candidates, you know, putting together a resume and a cover letter, and really trying to put their best foot forward to just that one click on a software programme, it sends the details. So as a hiring manager, you can contact people, and they've got no idea what you're talking about, or which job was there. So the time it needed from a hiring manager's perspective, I feel is much greater now than it was, you know, even five years ago, which is probably part of the market as well, because it's still, you know, fairly tight labour market in many respects. But yeah, I should probably mentioned as part of that, that I think candidates are using AI, you know, not just the hiring managers. And I can give you an example related to that. But, you know, we have heard a trend of candidates using things like chat GPT to write their resumes, I actually don't mind that, I think that it can be a tool that's helpful to consolidate your thoughts into writing. And to get a first draft, I wouldn't use it as is. But, you know, with our hiring recently, because yeah, you don't get cover letters from anyone anymore. And I thought, well, how do we make decisions about who to talk to so. So we just messaged anybody that basically had skills and experience that were kind of aligned to the job. And just said, Look, we'd actually like to know a little bit more about you respect your time, please don't spend more than 15 minutes on this, but, you know, send us through a couple lines of voice message a video, like whatever you want. Just let us know something about you why you're interested in the job. And only about half of the people that were asked to do that did it and then one of them I'm fairly confident the candidate use chat GPT to write the response. Because it was along the lines of You know, a candidate for this job would blot and edit it, and it was just like, picking all the bits of the job ad out and it wasn't personal at all.

Lachy Gray  24:54

In conclusion, yeah, exactly.

Karen Kirton  25:00

really disappointing to me because, yeah, I thought, I don't actually want you to spend a lot of time I just want to know something about you. I wanted something personal. And I didn't get that. And I found that really, really tricking. I don't know, Lachy, have you come across anyone that you feel has been using AI and their applications? Or like, how would you feel if you've got a resume and you put all this has gone through a system like that?

Lachy Gray  25:29

Probably for a resume, I think it's fine. I think that's, that's what we're going to be doing in our roles. Especially as knowledge workers, we're going to be using AI as co pilot, produce first drafts for us to prove. So I think that's actually good. I, we have a similar thing we've been hiring recently. And as you know, I get frustrated with the sort of send through the resume. In the past, we used to ask some additional questions, ask them to write a very short story to sort of fictional thing just to get a sense of their personality and a cover letter. And some of the team is saying, you know, that's a cover letter to kind of on the way out. And I was saying, Well, I really like them, because it is that context and colour to the personality. It's, it's, yeah, it says this on my resume. But here's the context to it, you know? So how can we do that otherwise? And so we came up with the idea of asking the candidate to do a pitch instead of the cover letter, which is just that it's just in any way you like, tell us about you, and how your experience and so on, and why it's a great fit for the role. You know, why should we hire you? And some people do a promo in Canva? Some people do a video, some people do a cover letter? And I'm sure there are a lot of people who who don't, and who just don't apply. So I would be happy for the people who used to use AI and in all those things, collaboratively with them. And I think it wouldn't even be cool to call it out. Yeah. Hey, Chuck JpT. And I produced this together, and here's why. Yeah.

Karen Kirton  27:25

No, I think someone might have an actual, you know, disability that prevents them from writing a short story or, you know, perhaps they've got some learning difficulties or dyslexia, or there may be other things going on. So yeah, and I think that would be a great way to do that. It's a we wrote this together.

Lachy Gray  27:46

Yeah, I think that's realistic. I think that's the that's how it's gonna go for many roles. So the people that can write great prompts for the AI are going to find that transition easier. I think. I'm curious here, and I know you're a fan of whole brain thinking and the diversity of thought. How do you see that feeding into potentially this sort of AI environment? Do you think it could be done?

Karen Kirton  28:21

Yeah, it's interesting. I haven't thought about it in too much detail. I guess my initial thinking is that AI in itself is quite boring. In this context, we're talking about things like chat GPT. It's quite generic, because it's taking lots and lots of info, and then giving an answer. And it does actually, someone call it hallucinate, and it does hallucinate like, so I know. So for me, spoiler alert for our listeners. We take the transcripts from these podcasts, and we feed it into tech GPT. And ask it to give us the blurb summary for the website. We edit it afterwards, because it comes up with stuff that we didn't even talk about. But it also has a very distinct way of writing, I find that set, you know, just really, yeah, quite generic and almost formal. And I know you can put prompts in to try and change the style. But yeah, how does that go in with with whole brain thinking? Well, it'd be interesting actually, to put that into it and to say, Can you write this particular thing? Through a yellow thinking lens using whole brain thinking, I wonder what would happen with that? Because I think the benefit of whole brain thinking is that we're saying, Well, everyone thinks in different ways and we all you know, use this to pay attention to things that we like to not pay attention to things to enjoy certain communication to listen to things in a particular way. And can a piece of writing out of a machine give that? Oh no, it'd be an interesting experiment. But maybe I'm a dinosaur. I just like, I like the idea that humans are pretty messy creatures. And because of that were actually really creative creatures as well. Yeah, and maybe the computers will be able to take over that in time. But at the end of the day, they're still, at this point, just copying what has already been done, but they're just putting it together in a different way.

Lachy Gray  30:36

Yeah, yeah. I like that. And perhaps unsurprisingly, I did ask to bat for his thoughts. On this topic. Yeah, well, yeah. In terms of pros, you know, it's efficient. And you've got, you can automate various stages of the recruitment process, objective decision making, like we were talking about, so it can help you evaluate candidates based on criteria, trying to eliminate bias, scalable, of course, improved candidate experience, which is interesting. So AI enabled chat bots, or virtual assistants can provide timely updates to queries, which I think is probably very true, because I know that is one of the criticisms or issues is that sometimes you just don't hear back at all. Yes, right. Which is not good. And in terms of the cons, pretty much, all the ones we've talked about bias, because the data and the training algorithms contains bias, lack of context, so that AI just doesn't understand doesn't have the context doesn't care, I guess. human touch and judgement. So to your point, AI tools lack the human intuition, empathy, and subjective judgement that can be crucial in evaluating cultural fit. And then lastly, it actually says limited diversity in the training data that we talked about bias. But it says if the training data is not diverse, or representative, the AI system may not adequately adequately recognise or evaluate candidates from underrepresented groups. Yes, I guess, which is a form of bias, and it says it can perpetuate that existing bias, which is exactly what's happening now. Yes. And it actually says at the end, so in conclusion, it's important to approach AI based hiring tools as supportive aides, rather than fully autonomous decision makers. And that organisations should we regularly monitor and audit the algorithms maintain transparency and involve human judgement at critical stages to ensure fairness? Isn't that interesting?

Karen Kirton  32:54

Is that at the moment puts it fairly into the bucket of big business, doesn't it? Yeah. Yeah. Because as a small business owner, you just wouldn't be able to? To do that. Let alone you wouldn't dream of hiring either. But yeah, yeah. How do you go about auditing like that if you've only got two or three jobs a year?

Lachy Gray  33:13

And that's, that's the thing is that this will become commoditized. Yes. That if that's true, and smaller businesses, and even large ones, using a third party model that's potentially using other models that you have no idea about? Yeah, yeah. How how do you communicate that trust, and transparency through all those layers? Like, we don't know how Google works right now? Yeah. So are we going to know, are we ever going to find out? I think that is going to be very interesting. For this space.

Karen Kirton  33:51

Yeah, for sure. And I know that I get emails from different companies saying, hey, you know, we'll get you through the whole recruitment process, shortlisting etc, you know, just give you a couple of candidates, and it's only going to cost you $1,500. Now, I know how much time during that kind of work takes so it's only costing $1,500. I can't see how you're not using AI. But they don't mention it in what the they're selling. And I think that's the danger is that people will use those types of products or those platforms and not actually understand what the process is that's being done to give them those those candidates. And I think that's how we can end up in a really dangerous situation, which is what Tracy Spicer's book is about is that bias in lots of different ways. Where we don't realise what we're doing. And then as a society, all of a sudden, we've got massive unemployment with certain genders or racial backgrounds or disability or whatever it might be. Because over time, we've been using this for so long and we've been inadvertently removing people from the recruitment process without realising and I That's how I'm sorry, dystopian, but, you know, this is what all the warning signs are about at the moment.

Lachy Gray  35:05

Absolutely. No, I think I share those concerns as well. I think now is the time to get clear on an approach on how do you communicate transparency? How will these models be audited? Because at the moment, it's really expensive to have to have the computer power to better run these models, which means it's typically for profit businesses that often generate revenue from advertising. Yeah, they're the ones with enough cash to do it. So are they the ones that we want to be deciding the values and principles of how these models are going to work? And that's why I think it's really important can feel a little bit alarmist. But until we get some of that clarity, I think it's better to to be to have that perspective than think, oh, what's what's going to work as self out? Yeah.

Karen Kirton  36:04

Absolutely. So, yeah, that's, I think the takeaways for me, you know, from this, as I think, firstly, if you do consider using any software or provider that's offering super cheap recruitment options is to to ask the questions, you know, so what is it? That's, that's being used? And, you know, what's the data set? And you know, what auditing you're doing? You know, how do you know that this is working, and that it's working appropriately? And I'm not going to be inadvertently, you know, undertaking any unlawful discrimination, or, you know, making bias decisions. I think that's a really important thing. And I think secondly, my takeover, just to educate I think this section of society at the moment, it's just moving so quickly, and everyone is suddenly talking about AI a lot more. But it's been around for a while, but it's, I guess, it's just getting mainstream at this point. So yeah, just to keep up with that education and to know what's happening and to have a look at well, what steps can I take in my business, to use AI appropriately, and also educate the people around me as well? Why don't you Lachy?

Lachy Gray  37:15

Yeah, I agree. I think familiarising yourself with at least some of the concepts is important, because it is moving very fast. And it's going to happen, whether we like it or not, or whether we support it or not. So I think it's really important to be familiar with how it works and how it could impact us. And then, you know, I still, like we said at the beginning, the set of software. So it's a how it's a way to achieve something. So when we're thinking about hiring, if we identify the most manual time consuming parts of our current hiring process, yeah, and think, run an experiment, perhaps, and try it for that part. Be open minded. And I think that is a way to approach it. As opposed to, as you said, handing it over the whole process to an AI tool. I think that's where the risk is. Yeah.

Karen Kirton  38:18

I'd be really interested if anyone's listening that's using AI in recruitment. Reach out, we'd love to hear your experiences as well. And links to articles and anything else we've discussed. We'll be over at our websites and fight hr.com to AU and yahoo.com.au. You can also use our new link tree that I mentioned earlier. And if you've received value from this episode, we'd love it if you could leave a rating or review over at Apple podcasts.

Lachy Gray  38:47

Yes, and in the next episode, we're speaking with a mile wide on why it is important to add creativity into any upskilling or development programme in the workplace.

Karen Kirton  38:58

Yeah, I'm really looking forward to that amount as a journalist, screenwriter. She's an author of several books. And I see her speak a few times recently about creativity, and I find her really inspiring. So I can't wait to share that episode with you in two weeks from now, so click on that subscribe button to be notified of when it's available. Any final thoughts?

Lachy Gray  39:17

Okay. Well, I'm wondering if we should ask them all about AI and create creativity.

Karen Kirton  39:26

Perhaps another episode itself? Yes.

Lachy Gray  39:32

Look, I find this space fascinating. I'm trying to keep an open mind. In terms stay on top of all the latest developments, and I would love to hear how you're using it. what's working, what's not. I think that knowledge sharing is a really critical part of this next phase. And, and just to reiterate, we do have this offer for our podcast listeners. So it's an opportunity to upskill With a free record a masterclass from amplifier char on managing performance, and then you can embed your knowledge by participating in a free short 10 question multiple choice quiz delivered by Yano, upon completion of the masterclass, so, if you go to link tree slash make it work podcast, you'll still see the link to get started.

Karen Kirton  40:24

Excellent. So thanks Lachy. It's been a great conversation and thanks to everyone for joining us, and we'll see you next time on the Make It Work podcast.