HR in the Age of AI: Managing People, Performance and Risk

SpringLaw Managing Partner Lisa Stam joins First30's Amy Davies to discuss the widespread implications of AI on people management, performance evaluation, and the very real opportunities and risks it can create. Adopting AI means organizations need an up-to-date AI policy, and you might be surprised how often Lisa recommends updating this document to keep up with the rapid pace of change!

HR must prepare now for the future of AI in the workplace, and Lisa shares her thoughts on what that requires.           

Connect with Lisa Stam:
On LinkedIn: https://www.linkedin.com/in/lisastam/
Email: lstam@springlaw.ca
Visit Spring Law's website: 
www.canadaemploymenthumanrightslaw.com (Blog)
www.springlaw.ca (Company)

Connect with Amy Davies:
On LinkedIn: linkedin.com/in/daviesamy
Email: amy@first30ready.com
Visit First30's website: www.first30ready.com

HR Law Canada
Stay up to date with employment law news by subscribing to HR Law Canada: www.hrlawcanada.com

This podcast is produced by Storyphora, www.storyphora.com, info@storyphora.com

#amydavies #lisastam #coffeenlaw #employmentlaw #HRleaders #workplacelaw #workplaceai

Transcript

SPEAKER_02 0:00

The piece that's really interesting for me that I think is still early days of the conversation is with employees using AI at work, a big legal risk is a disconnect between what their job is and what they're getting paid for. You know, the example that I always like to say is what happens if they are able to do their job in half the time because they're really employing all the tools very well, and they're sitting around watching Netflix all afternoon. Does that mean that they're engaging in time theft, or are they just being a great employee, getting their stuff done using the tools and excellent work-life balance?

Amy Davies 0:35

Workplace law is complex and constantly changing. It can be hard to keep up, and the risk of getting it wrong can be costly for businesses. The Coffee and Law Podcast is here to help HR professionals and employers stay informed. We'll cover what's changing and how to navigate real workplace situations and everyday people decisions. So grab your favorite warm drink and join us for engaging practical and educational conversations with top experts in workplace and employment law.

Brent Jensen 1:09

This podcast provides high-level general information. The perspectives shared by our guests are for educational purposes and do not constitute legal advice. If you have a specific question or concern, please consult a qualified lawyer.

Amy Davies 1:25

Hi everyone, it's Amy Davies, founder and CEO of First30, and also your Coffee and Law podcast host here to remind you that First 30 offers career transition and outplacement services. So if you have terminations and layouts coming up, this is a really good way to mitigate risk to your business and help your exiting employees recover from the job loss and get back to work. You can find out more information at www.first30ready.com forward slash outplacement, or you can reach out to me, Amy AMY at first30ready.com. All of our programs include live coaching and a year of access. And in a tough job market, that can be very important. Now, back to our show. Hello, and thanks everyone so much for joining us. We are talking about, well, everyone's talking about AI these days, so I thought we better start talking more about AI on the Coffee and Law Podcast. So that's what we'll be discussing today. And I'm excited to introduce you to our guests. Before I do that, I would ask if you're here and you're enjoying the content, like, share. If you're listening on audio, please give us a five-star rating. We'd really appreciate it. It goes such a long way. Um, and uh yeah, so that would be great. And then we also I wanted to mention that we uh work in partnership with HR Law Canada. And that is a if you go visit their site, they've got a lot of information on HR Law. So it's excellent. I read it regularly. And my guest today is Lisa Stamm. And the way that I met Lisa was we were both at an HR Law conference last year, and she gave an amazing presentation on AI. So I connected with her. I didn't even know I was going to be doing this podcast at the time, Lisa, but I was like, I need to stay in touch with Lisa because she was amazing. And uh you had so much insight into what is happening. So naturally, I've made sure that we got her here. So, Lisa, welcome and thank you so much for joining us.

SPEAKER_02 3:46

Thank you so much for having me on your show.

Amy Davies 3:48

So, why don't you tell us first a little bit more about your law firm, Spring Law? I'd love to hear about it.

SPEAKER_02 3:54

Sure, thank you. Uh so I founded Spring Law in 2017 as a fully virtual law firm, so pre-COVID, and um just myself and a part-time assistant, and we've grown it out to about 15 people now. Um, we only do employment law, labor, you know, workplace issues. We we help both employers and employees, but um, we really focus on how do we do this in a tech forward way. I've always been a bit of a tech nerd uh in in on different fronts. So we um are always focused on that with the the behind the scenes piece being very tech forward. But with the clients, it's all about that human delivery. So, you know, AI is a natural extension of all this. We have a ton of AI tools that we use behind the scenes, um, much of which a client wouldn't even see because we still want that human connection to to advise them.

Amy Davies 4:48

You know, in this, you're just letting us know that you're always ahead with the what you were doing. Um, and I will say that it's so great when you can use automation to enable human connection. And certainly I've done that with first 30, but I've always reminded our clients we're still here. Don't worry about the automation. You you still can message anytime and you will have a real person responding to you. But it's amazing how much time you can save and how much more effective and efficient you can be for your clients.

SPEAKER_02 5:20

Yeah. And I mean, in the early years, we we explored a bit more about how can we be more self-serve or DIY and how can we um, you know, pull our clients in to participate in a lot of the the tech, even just something like forms. And but, you know, in the world of employment law, so often people are coming to us in in a crisis, whether it's employee side, you know, they've just been let go, or or an employer who has to make all these hard decisions and they just, you know, um received demand letter, whatever everyone comes to you usually in some sort of crisis, they don't want to futz around on learning a new piece of tech. And so we've really evolved on that over the years that we we uh we have it. People are welcome to use our portal, do like all the things, but um usually people just want to have a video call and and and and talk to someone.

Amy Davies 6:10

Yeah, absolutely. All right, so today we are, as I said, we're talking about HR in the age of AI, which is such a it's such a complicated. I find it exciting, but I know that a lot of people are finding it quite complicated time. And I wanted to start with a question around policies. Uh, not the most exciting topic, but a really important one. And I want to know from you does every organization need an AI policy and what should it cover?

SPEAKER_02 6:42

So, as an employment lawyer, I I am automated to say yes. Of course, you need a policy on this. So for sure. Um, but especially AI right now, because nobody knows what they're doing yet. You know, we're all learning together. It's early years. Um, we don't know how our employees are using it, but we uh they absolutely are using it, whether it's on their on their phone or you know, uh on the on the company's systems, but they are using it. And so we I I think every employer should really turn their mind to having a an AI policy of some sort for two reasons to help give employees guardrails on how to use it um and make sure that they're not, you know, putting all kinds of customer or client information up into the into the universe, but it's also for the company, small or large, to to have that opportunity to turn their mind to okay, how are we going to use this AI? How are we going to um uh you know have our what guardrails are we gonna have for employees? And and the the act of making the policy is probably almost as important as coming up with the final product of the policy.

Amy Davies 7:54

So, in the act of making the policy, I gather you mean that that gets leaders thinking about what should the guardrails and what is our risk uh in terms of AI? Now, policies are something that you can leave in place for 20 years. But as we know, AI is changing every day, every hour, it seems. How often are you suggesting to your clients that they relook at their AI policy given the constant change that we're seeing?

SPEAKER_02 8:25

Yeah, for other policies, you know, even an annual cadence is probably fine. Um, but for for these AI policies, it really should be a living document right now. And and, you know, if there's some sort of update, if the company is bringing in a new tool, you know, or or or something happens and you now need you you've learned something. So now you need to update your policy. I I would, you know, really think of it as a living document right now of what are our guardrails and um guidance to everyone on how to use it. So more frequent, you know, ideally, you know, every three months at the most. I say that knowing that in the real world, that a few can actually do that, especially, you know, owner-operator, small um uh employers that don't have a whole department to do this for them. I appreciate that's that may not be realistic, but tweaking it, you know, as we go, I think is quite important.

Amy Davies 9:19

You mentioned employees and how they use AI, but I'm curious, can employers require employees to disclose when and how they're actually using AI? Yeah, yeah, I I I think absolutely.

SPEAKER_02 9:32

I mean, um, I I think that they should, in fact, you know, uh require this to manage their own legal and operational risks uh that AI can really bring out. The reality is when an employee is working, you know, in the normal course of employment, the stuff they do is the company's property. And so, you know, and if they're all in the company's um systems, they're they're it's all uh company proprietary information. And and if that is being compromised with AI, you know, rogue AI use, um, where you're putting all kinds of stuff up into the cloud because you don't quite understand, right? I mean, part of it is that we are all learning together right now. And so an employer absolutely can require that as part of um, you know, what tools are you using to use your job right now? It it would be no different than any other tool that an employee would be using.

Amy Davies 10:23

It well, it's you it makes it even more complicated that our lives, our our private lives and our professional lives are so intertwined. And I feel like the technology just goes along with that, right? Yeah. So it couldn't be a more interesting time to have all of these things converge, right? Well, what are some of the big legal risks that employers face um when employees use AI at in for their work?

SPEAKER_02 10:53

I mean, if you put this in your AI, what will come up always is as the privacy issues, the confidentiality issues, IP ownership. So a lot of these are our um standard issues that I think we've we've been dealing with beyond AI, right? Of sort of the bring your, you know, bring your own device world has been around for a decade. So this is uh some of this is not new. But having people understand what the what an LLM is and why it is that if you are putting information into into the mothership, the whole world knows, you know, everyone's on the mothership. And so um having people understand why it is that it's it's not it's not just a localized little Google search that you're doing. It's it's putting information in into the ether that I think is something that that is part of the policy, which hopefully goes hand in hand with training about all of this. But so the confidentiality, that's an obvious thing. I think we all know conceptually that that is a risk. Um, but but how much and what does it mean? And you know, if you're throwing in a uh a document into a chat, you're whether it's co-pilot or Gemini, whatever you're using, if it's a non-enterprise version, it may remember it in the next chat. And and and that's that's the piece that uh for everyone to remember. The other piece around this is for people who have sensitive positions in the organization, HR, the owner operator, like people who are um dealing with issues that you don't want other employees to know about. And so this is where I think it's really important to map behind the scenes what let's take Copilot as an example. So we have the enterprise version of Copilot, so that um it'll it gives us a bit more control. And I highly recommend for any AI tool being uh rolled out in an organization, do not use the free version because that's you know open. Uh pay pay for now, a lot of these tools aren't uh overwhelmingly expensive, but allows you to to map out behind the scenes a little more who has access. And more importantly, what access does that tool have to the organization's information? So which SharePoint drive is it accessing? Is it you know, are are we letting everyone see what's in the HR drive? And if you just add, you know, if you put in a question, you know, what's the average salary in our organization? You don't want your co-pilot to be accessing all of the HR stuff to answer that question. So this is and this is where I think um having an enterprise version will allow you to help bring Fence out and make sure your IT people are um helping out with that. We've been working with the same company for years and they were very helpful in helping us really. When we rolled out Copilot, they really mapped out behind the scenes what it has access to and what it doesn't. Just as an example, whether you're using Claude or Perplex, like whatever, whatever tool you're using, make sure that it's um really understanding the confidentiality.

Amy Davies 13:54

I've just had a question. I'm thinking as an employee now, and I and I know HR will be concerned about this too. So I'm an employee, I'm having a difficult situation with my manager, and I use co-pilot to help me navigate that difficult situation. Who can see what I'm asking? Or if I let's say uh I want a client ask me to go out drinking at lunchtime, right? And then I start asking about our drinking during the day, like what's our policy? Um, or I ask it in retrospect. Oh, I went out drinking with clients, right? So I'm just using these as examples. But if I'm putting that in, I imagine my employer might be able to see what I'm asking and what is their obligation to me to say, hey, Amy, when you're using our uh co-pilot, we can see everything you're asking.

SPEAKER_02 14:49

Yeah, and yet not really, right? And so it um because it's um if you're using your own, uh so if you have like an enterprise version of it and you're asking questions, your own questions would be um in your own section, depending on how it's all configured, obviously, right? But if you're if you have a shared agent, for example, within Copilot that has been shared out to the whole team, then there's probably a lot more history that that is is either being seen or being pulled into new questions, right? So in your example, if if the HR director was to say, tell me, um, you know, have there been a lot of conversations about drinking on the job? Maybe some of the information might might show up, but it's uh it's it's not going to necessarily be a laundry list of it all, right? I mean, you but you can prompt, you can prompt this like crazy. And I say this with a giant caveat that it totally depends on how everything's configured in your organization and whether or not it's a centralized agent, for example, or whether or not it's um, you know, your own corner of of the of whatever LM tool you're using.

Amy Davies 15:54

It just it all feels so risky. It's like you don't know, right? You don't know what you don't know. So yeah.

SPEAKER_02 16:00

But but in a way, we've always been able to see what's on the server, right? And emails and like it's it's no different. I I I would like to think, you know, if you're drinking on the job, Amy, you're not emailing all your friends as well about this, right? Because it's on the server and everyone can see it. So I don't see all that different. It's but we live in a world where people write everything down, and I'm constantly shocked at what people put in writing that's so that implicates them so quickly. I I, you know, I am constantly telling my teens the internet is forever. Stop putting, I mean, they don't, but like don't put stuff online that you don't want to read or that you don't want your employer to read in 10 years. I think there's so much out there already on on making sure there's human judgment. The piece that's really interesting for me that I think is still early days of the conversation is with employees using AI at work, a big legal risk is uh a disconnect between what their job is and what they're getting paid for, and and really understanding what is the value of the work they're doing. Are they being paid because they're churning out an hour at a time or you know, or the number of calls that they take if they're in a call center? Some of that, there's some clear objective metrics. But if it's anywhere in a bit of a knowledge um industry type of job where you're able to uh put out your input uh at 50% faster, it's it's an HR legal kind of risk about what what does their contract now look like? Is is yeah are they and you know, the example that I always like to say is what happens if they are able to do their job in half the time because they're really employing all the tools very well, and they're sitting around watching Netflix all afternoon. Does that mean that they're engaging in time theft? Or are they just being a great employee, getting their stuff done using the tools and excellent work-life balance, you know? And I think we're in such early days that nobody really knows the answer to that yet. And I'm curious where where that's gonna go, this disconnect between how we value work traditionally and what AI is doing to really knock that around right now.

Amy Davies 18:11

Well, it's such an interesting perspective because my I was in a similar field for about 20 years. And by the end of my corporate career, I was thinking, does anyone know how easy it is for me to do this? He was really complicated to them. Because, but as someone who had been doing it for a very long time, uh I just kind of started to feel like, well, you're paying for access to my expertise along with the hours. I wasn't, listen, I wasn't committing time theft or anything like that. But sometimes I got a lot of credit for doing something that I was like, oh, like anybody could do this. Of course they couldn't, right? So that I think companies, it will take time for them to realize, okay, what jobs are we kind of overstaffing, or there this shouldn't be so much of someone's job anymore, but we're all going through the process of learning what that looks like now.

SPEAKER_02 19:09

In your case, though, after 20 years, typically what has happened traditionally is that you get promoted into other roles where that time gets filled up with management or you know, committees or strategy, like all that stuff. And so I'm thinking more you're sort of not quite frontline, but like like middle-of-the-pack kind of role that maybe isn't management yet. We're gonna see some real shifts and what that job description looks like.

Amy Davies 19:34

Outplacement and career transition support make a real difference for employees experiencing terminations or layoffs. Offering these services also reduces legal and reputational risk for employers. All of First30's outplacement programs include access to a live coach along with one year of access to our career transition portal, job search resources, and much more. Programs start at $985 per participant. You can find information about our programs and pricing at first30ready.com forward slash outplacement, or reach out to us anytime at info at first30ready.com. Now, a lot of what I hear when I'm out and about, like you at events, is how HR is using AI for hiring. Um, you know, maybe more so now, more recently, performance management, um, disciplinary decisions, you know, how do we use AI in these ways without creating legal risk? And, you know, I think the place that it's more most HR is most active is in the hiring. Yeah. So I'm sure there are risks in there, especially now with the new laws around note-taking during interviews too, and having making sure we have those notes for three years. Um, it's but it's also about like how are we setting up our agent to analyze resumes. So can you talk to us a little bit about what employers and HR leaders might be thinking about?

SPEAKER_02 21:10

Part of this is a traditional answer, is just um document the heck out of everything. Document your process so that it's very clear that, especially in the hiring process, it's so important to have a very consistent approach to each candidate to protect you from human rights claims. You know, if you didn't hire someone and they think that you answered you asked inappropriate questions, if you ask the same set of questions to everybody, it's an excellent um defense for the company. And so, you know, that applies to the world of AI as well. If you're using these tools, first of all, understanding as much as we can how it works. And and you know, we're not coders, we're not, you know, we're not expected to really open up the black box. But I do think asking a ton of questions to the vendor before you roll it out, for example, to understand how are decisions being made. How is information being analyzed in the in the tool? And how do we make sure that we can configure that in a non-um discriminatory way, for example? And HR already has the expertise to know what kinds of questions not to ask. But it's it's it's never going to be perfect. And we don't expect perfection from humans, and yet we expect perfection from from machines, right? It's an interesting disconnect. Where I think we can really help uh you know address the risk and and and help the organization is a document everything so that it's clear what our consistent system is, but always make sure there's a human actually making the final decision on everything, especially for now. Maybe the robots will take over in a decade or two, but but for right now, our machines are the robots aren't smart enough yet. And so we have to have a human making these these judgment calls and decisions. So in in the process, having steps along the way where a human being, you know, there's a set of eyeballs actually looking at at all of this. Having said that, if you're you know organization that gets a thousand resumes for one role, you have to have technology to to sort through that. And there's excellent tools out there now, for sure, to go through all that. So I don't ever think that people shouldn't use any of these tools, but supplement it always with people and making sure that there's uh a human decision maker at the end of the day that again is such a uh uh an important defense for the company for that person to be able to explain why they made the decision. You know, there was five candidates left, and here's here are all the points that that you know was listed for each of these, and this is how we ranked it, and here's here's the why. And being able to justify that, I think is just so critical.

Amy Davies 23:48

Well, and I it's important for us to remember that not all agents are set up equally or chatbots, let's call them, are set up equally. Uh, it's about training it, training it by prompting it and and then testing what you've developed, right? And I think too often we can just say, oh, we have a, you know, I know because we actually developed a chatbot, and everyone's like, oh, just another chat bot. But I'm like, no, it's what goes into programming that chatbot, it could be far more sophisticated than another one. So it's just interesting that all of these things are not built equal, and that human touch is and and then going back and re-jigging as we need to is so important. Yeah.

SPEAKER_02 24:33

And piloting it, right? Testing it out before you fully roll it out in in the real world. I do think that's such a critical piece of this.

Amy Davies 24:41

So, what should HR leaders be doing today to prepare for the future of AI in the workplace?

SPEAKER_02 24:48

Uh, you know, I I think really taking a look at at all the the likely places that AI is going to replace all that rote routine work that your team may have. And and it's it's sprinkled across all roles. It's not just necessarily one particular role, but but all of us will have parts of our job that are are easily replaceable by AI, especially as it continues to in such a an accelerated uh pace to impact and and and be able to replace our jobs in an effective way. And so um I'm hoping that workplaces will take a look at not just job uh roles, but at tasks, really focusing on tasks as opposed to the overall job. And part of it is that there aren't a whole bunch of experts out there right now. It is early days, we're all figuring out together. So the idea of firing this person in front of me because you know, half their job is is replaced by AI. First of all, someone else has to do the other half. And if your rest of your team is at capacity, then you can't just uh, you know, redistribute. But there's not likely another person on the market yet that has all this AI knowledge that you think that, you know, you may want. So let's all just train together. Let's figure it out. And meanwhile, they already have the you know the organizational knowledge, and now that we just keep training people on the on the AI part. So paying attention to what are the tasks that are so likely to be replaced, that's the crystal ball part. Thinking ahead about uh how do we train up those people particularly susceptible to it. And there's gonna be collateral, there's gonna be people who may not um fit in the organization, but you know, um um you would have seen this in the presentation that where we met last fall.

Amy Davies 26:40

So I'm repeating myself, but it's well, you're not repeating yourself to the audience, it's your own. It's not just us here, Lisa. That's a good point.

SPEAKER_02 26:51

In each um big technological development since you know, since the dawn of time, um, each big moment, there's been this big worry that the sky is falling and all the jobs are gonna go away. But in each moment, it's just contracted, or it hasn't contracted, it's expanded the market. Whether it's you know, the typewriter coming in, it's not that all of a sudden we all stop writing stuff and typed only, you know, or or you know, and bring it right up to the internet. The internet has created so many jobs, so many um commercial opportunities for people. And even in the world of AI, um, there's all these um data centers now that are popping up. So someone's building them, someone is, you know, um planting lots of trees in lieu of them. Like there's all this residual impact on the economy of new jobs that we just didn't even think about 10 years ago, five years ago. We didn't know existed. Yeah. So I there there will be people who will be impacted by AI, all these big companies that are laying off big chunks of the workforce allegedly because they're implementing AI. I think it's a marketing ploy. Uh for now, I don't think it's all that it's not here enough to actually change too many jobs. Not yet. It will be down the road, probably. But I think it's more, you know, we're offshoring a little more because it's a global workforce and valuing the people who are in front of you still and investing in them, training, um, you know, of course, have the policies, but but build together because there aren't experts out there yet to do it instead.

Amy Davies 28:28

Right. Yeah. Oh, it's such an excellent point. Now, listen, we have a little time left. So I want to make sure we spill the tea. Uh, so tell us, do you have a little spill the tea, maybe AI related? I don't know. I don't want to put any pressure on you.

SPEAKER_02 28:47

No, you know what? I don't uh the the one that came to mind that comes to mind is not not AI related. And sure. There's nothing terribly sexy yet about AI, right?

Amy Davies 28:56

It's it's a too long. So everyone knows I should explain because I'm sure at least there'll be new listeners to this episode that we spill the tea. It's like an exciting, fun, maybe it's a serious story, but somewhere where we have a little um gossip at the end of the show, uh, just to kind of lighten things up potentially a little bit.

SPEAKER_02 29:20

Um, so I had uh a case a few years ago, and I I'm a Volt, I never talk about clients or client work. But so but this is the generic one that um that is uh that was like a uh funny but not funny at the time. So I I've done tons of negotiations for whether it's on the employee side, I mostly do employer work now, and um and but in that case I was on for an employee. And and you know, we wrote a very strong demand letter to the employer based on the the client's indignation in front of me. Like he he was so convinced that that he had been so wronged by the employer. Uh and and we had all these regular good strong facts there for a while, like all the regular Bartle type factors. Um, and so and he got a very lean package. So, you know, I wrote my usual um feisty demand letter, and then the employer took their time and um it just took a long time to respond. So, you know, I'm I'm increasingly convinced that they're a terrible employer. So I wrote a pretty strong email saying, you know, let's get a response, please. Um and then I got an email from opposing counsel that was very well played. It was just please the enclosed, and enclosed was all of these text messages that my client forgot to tell me about that were all about such clear sexual harassment against his employee, his subordinate. So, I mean, that's the the not funny part, but the funny part is that he he just didn't think to raise that while we're fighting with all this indignation. So they the the series of texts were with with the person who reported to him things like you know, you should wear that, that beautiful sweater that I like, and um, you know, just how um beautiful she was, comments on just what she should wear, her like it was so overt. There was nothing, both were married to other people, and the whole time she didn't can she wasn't participating, she was responding in a neutral sort of like oh okay, see you tomorrow kind of response. So it right, but what so when I talked to him, I I said, Okay, uh buddy, tell me about this, you know, like this kind of changes our our strategy a bit, and he's and he just didn't think it was a big deal, he thought it was a mutual private affair that had nothing to do with anything, and he the way he interpreted the texts were so um concerning to me that there's still people out there that that think that unless the the the other person is so you know aggressively no back to you that somehow they're they're like acquiescing to to this alleged relationship. And so clearly at some point this the the powers that be got wind of it, and so it it as you can imagine, our strategy is like, okay, fine, we'll just take ESA. Yes, thank you. We'll take the little lean package you've given us.

Amy Davies 32:24

Have a nice day, yeah. And he's like, Well, we're all adults here, we're allowed to do this. I'm like, no, you're not that to me, that's crazy. And some so often in life, people see what they want to see. Yeah, so that is no excuse. Absolutely, there's never an excuse for this type of behavior. It's just just horrible and disgusting. And I feel very sorry for his um subordinate who is on the other side of this. And you can totally see her responding with just this very lukewarm, appropriate. No, well, there's no appropriate response to that, let's face it. There's no, it's very difficult to handle that type of situation. But my goodness, that is a crazy story. Such an interesting life lesson for you as well. Oh, so I mean, this is this is I don't know, probably 10 years ago.

SPEAKER_02 33:13

And ever since it it was a very big lesson for me that you just you never know. There are always three sides to every story, you just never know. And and you can drill your own client as much as you want, but they may not appreciate what what's if something has a big impact, right? Like if they've just found a new job, they've mitigated. You need to tell me about that because that also changes your case. And so we've learned, you know, we have a whole list of questions that we go through and and they have to ask. But in this case, I use the word affair, and that's me, I don't know if that's the right word, because in his view, yeah, there was there was no sexual content or contact, physical contact, but it was so overt the whole time talking about her physicality, and he just thought it was, you know, it was no big deal.

Amy Davies 34:02

Oh, I'm so grossed out by this. I know, I know.

SPEAKER_02 34:05

Sometimes we'll get to pick your own clients. That's true.

Amy Davies 34:08

I have a little piece of advice uh for anyone listening, because I I I'm just rolling up a piece of paper to make my point here. So my friend is in, she's a senior leader in HR, and she told me that at the end of every interview that she conducts, she'll stop at the end of the interview, hold their resume in her hand like this, or maybe she has it open, she'll hold be holding their resume in her hand, and she'll look directly in their eyes and say, Is there anything else? Okay, you know, thank you for coming in. Now, is there anything else that you'd like to tell me? And then she just lets it go silent.

SPEAKER_02 34:45

Oh, that's a good thing.

Amy Davies 34:46

And she's holding their resume to to give them the remind them that, you know, there's information, like you've given per someone access to information. And she says to me, Amy, you will not believe the things that come out at the end of that when she asks that question. Umbelievable. Nothing that she shouldn't be hearing, but things that are, you know, something that might come up in a criminal background check, or maybe something that happened with a previous employer that they hadn't mentioned but is relevant to the to the role. And she said it is the best strategy for finishing an interview that she has employed. I use silence and cross-examinations.

SPEAKER_02 35:31

You just you ask the question, let them answer, and then you just sit there and look at them. And then and then they keep going, right? Sure. And that's where the tea gets spilled for sure.

Amy Davies 35:41

Exactly. Exactly. You know, it's such a good lesson. I remember I had a female leader in one organization I worked in, and she said, you know, when you ask difficult questions in a business setting, Amy, you need to learn to shut up, just actually bite your lip and say to yourself, Amy, shut up, shut up, shut up, shut up. So I took that through my career. And it's you're right, it's amazing what comes out. And you just have to be prepared to be uncomfortable with the silence.

SPEAKER_02 36:09

Yes. Yeah. And for people like us who are very chatty and outgoing, that like it is a I have it's an intellectual exercise, not it doesn't come from the heart. You know, I want that.

Amy Davies 36:19

Absolutely. But the more you practice these things, the more natural they start to feel. Well, listen, Lisa, thank you so much for joining us. Um, again, you can find Lisa's details in the show notes. I know that I learned a lot today, Lisa. I'm sure our audience learns a lot. Before we close, I also want to thank our producer Storyphora. I often get asked who produces this podcast. It looks great, it sounds great. Um, so they they are Storyphora and their information is also in the show notes. And don't forget to check out HR Law Canada as well for some great articles on topics like what we're discussing. And hopefully, Lisa, I'll see you at another HR Law um event, which are also great uh in the near future.

SPEAKER_02 37:06

Thank you very much for having me on the show. I really appreciate it.

Amy Davies 37:09

Yeah, thanks again. Have a great day, everyone.