Has the internet ruined Human Resources? - Dr Justine Ferrer

It promised to make things more efficient, objective, and data-driven, but instead turned a human-centric discipline into an automated, impersonal system with new ethical and privacy concerns.

In this episode, Dr Justine Ferrer - a Senior Lecturer in Human Resource Management in the Deakin Business School - joins us to discuss the evolving role of human resources in the age of technology, exploring the impact of automation and AI on HR practices, the balance between efficiency and the human touch, and the ethical implications of data privacy and surveillance in the workplace.

We also look at the skills needed for future HR professionals, and the potential for AI to enhance rather than replace human roles in HR.

Check out the episode here.

Gareth King (00:29)

Justine, thank you so much for joining us and welcome to the show.

Justine Ferrer (00:33)

Thank you for having me. I'm very excited about being here and having this discussion with you today, Gareth.

Gareth King (00:38)

Yeah, me too. But before we begin, can you tell us a little bit about the work that you do and the journey that's led you to this point?

Justine Ferrer (00:46)

The work that I do, as I am an academic, I work at Deakin University in the Deakin Business School. I am a senior lecturer in human resource management. I have been in this space for quite a while, and I think my passion is around HR and the profession, particularly the dark side elements. And as our discussion today will entail, some of that is considered the technology and that's got its own little dark side that has implications for HR and for the workplace generally.

Gareth King (01:16)

Yeah, look, I'm sure we will go into those implications for HR in the workplace. As we know, you know, it's in the name. Human resources is obviously a traditionally human-centric field. But as we look at the increased adoption of various forms of HR tech, what would you say is proving to be the most difficult about maintaining that human touch?

Justine Ferrer (01:37)

Really great question and a really hard question to answer because there is argument that, you know, HR is losing its human side, because of technology and because of focuses on efficiencies and productivity, as opposed to looking after the wellbeing of the employees in the workplace. And if we go back historically to traditional models of HR, it was about looking after that wellbeing.

But HR has seen a massive shift, and with that shift it's become more strategic, and with more strategic focus it's focusing on productivity and greater efficiencies. However, when we think about HR, it has two notable parts of it. There is the process part. Now, HR is all about looking after how the workplace functions, how employees function. So, making sure people are coming to work, that they're getting paid, that they have the right training and safety demands and so on and so forth. So, there's a process part of that, but there's also the human side of that, which as much as we talk about technology and it dehumanising human resource management, there is this massive part of HR that is inherently human. And I'm not sure that that can be lost just yet.

Gareth King (02:46)

It sounds like as well that the function of HR has expanded and grown quite a lot over time. And you just mentioned there that there has been that shift towards a more strategic approach overall. Can you just give us a top line rundown of what that shift has looked like?

Justine Ferrer (03:02)

It depends who you ask, to be honest. So, what we're seeing is, and you look at AHRI which is Australian Human Resource Institute, and even coming out of the US and the UK, they're talking about the importance of HR having a strategic role on boards and making a strategic contribution. So, we're thinking of CEOs that they're making decisions that are impacting on the whole of the organisation, including the human resource, so including the people.

So, the argument is from a strategic perspective that HR should be involved in that conversation because ultimately it's the employees who are going to deliver on those organisational goals and the objectives that they're setting.

So HR strategy inherently should be linked to the business strategy. So, HR, when we're talking about HR being more strategic, it's HR understanding what the business strategy is, and then being able to link their own strategy, their people strategy, to ensure that the employees are delivering on what the organisation needs for them to deliver on.

Gareth King (04:03)

In that case, have those various forms of HR tech that have been implemented so far, are they actually freeing up human resources staff to be more strategic and more human, or do they somewhat shift those previous administrative burdens? Because obviously they would need some kind of management and oversight from the person, right?

Justine Ferrer (04:23)

Yep, absolutely. So, I was talking to a colleague recently and she was talking about the impacts of AI on her current workforce. And she was saying that people are scared that they're going to be replaced. You know, that this move towards automation in different ways, whether it's through AI or through other types of automation, people are going to lose their jobs. And she's saying that, or trying to encourage them to think about, well, how else should you use your time? How could you better use that in order to do something that's more productive?

There was a case at Coles recently, a couple of years ago, where they introduced SAP SuccessFactors, which is a whole integrated workplace system with lots of data and things like that. And it automated quite a lot of their HR process. But what they were able to do in that was then reallocate people to do things that were more meaningful to them.

So, it wasn't about we've got this, you're going to be replaced. It was about giving them the opportunity to say, alright, well, what can you do that's more meaningful to the business? How can you better spend your time?

Gareth King (05:35)

And I think that that sentiment, I guess that wider sentiment actually comes up regarding AI in a lot of different things. You know, there is obviously so much unknown and uncertainty around it now. From one side, you've got people thinking this is my replacement. And then the other side, you know, which I'm sure we'll get to is people thinking this is my augmentation. This is going to make me a super version of myself. So, there's, you know, it's going to be super interesting to see how that all shakes out.

But you mentioned something there around, you know, the data and inputs from various members of staff across various parts of their performance and I guess their role within the business, et cetera. Obviously, people are a little bit wary of being treated as data. Is there a risk that the employees will feel like they're just being reduced to a series of data points and metrics rather than the human beings that they are? And does something like that potentially get worse, by necessity, simply because the larger an organisation gets, the harder the task of managing all the staff is?

Justine Ferrer (06:40)

Yep. So absolutely the dehumanisation and the reductionism that comes with people thinking they've just been reduced to a number, and the consequential impacts of that for employee wellbeing are substantial. But I think it's a more of a cultural discussion as an organisation as to why we're doing this, why we need to do this, why this is important and where those touch points are for human engagement and human interaction.

And we see this a lot, Gareth, now with working from home. Where are those emotional touch points that you have with someone where we just can sort of gasbag and say whatever. It's the same in this translation or the use of metrics to drive a lot of our decision making and a lot of what happens in organisations. And you're right, data has become a commodity now and substantially more and more we're seeing it.

I was reading a study recently about applicants applying for jobs and they were faced with automation the entire way through. They didn't actually engage with a person, a human until the very, very end. And it's like, well, what is the consequence for that, for building your employer brand, for how you feel about the organisation?

So, there is a big story around that. And I don't think we've really started to unpack what that looks like, but there definitely is that reductionism, that people have been reduced to a number and also the idea that humans are complex individuals and can they be reduced to a number or should they be reduced to a number is also the big question there.

Gareth King (08:23)

Yeah, absolutely. And I think that part of everything that you've explained there, in my mind, I can put a lot of it back to the kind of unknown. And you said something there around managing your employer brand. If the impression that you're giving is you're, you've automated everything and you've got all these applicants applying for a role or an interest in your company being faced with these automated systems that don't treat them like that human, regardless if you're doing it out of necessity, like that almost doesn't really matter to that person on the outside. They only know what they're faced with. So yeah, there it'll be really interesting to see how that all falls out around how people manage their employer brand.

But you, you also mentioned there around work from home. One thing that I've seen and read a little bit of recently was the implementation of surveillance tools from, you know, organisations of various types, whether they're kind of keystroke loggers or you know, I was reading something earlier today around some company activated some software that recorded through the microphones of their staffs’ computers while they're at home, working from home. So there's obviously all these, you know, in my mind, quite dodgy things going on. And I can only guess that that adds to that cynicism and that distrust amongst workers who feel like they're being monitored due to these various tech solutions.

That said, if that perception is out there, what are the implications of that for workplace culture? How would that be addressed? You know, the more tools to try and spend more time working on culture feels like is what's breaking that cultural perception in the first place.

Justine Ferrer (09:59)

Well, yeah, I think with surveillance and when we talk about surveillance tools, we automatically go to the negative surveillance. You know that I'm sneaking around as an employer and I'm checking up on you. Now we know through COVID there was a substantial increase in organisations accessing those surveillance tools that they were using online. But we also surveil people with cameras in the workplace. We also surveil them by requiring them to do drug tests.

You know, so there's a whole range of different surveillance that we do in organisations. And, you know, it's often sold to us as surveillance as care, or is it surveillance as coercion? You know, so this is where it becomes quite interesting to me, to be honest, because this is how it's sold to someone, is how it's implicated into the culture.

Gareth King (10:52)

Yeah, that's, that's really interesting what you said there surveillance as care. I can imagine you could sell that a lot easier if it was say cameras looking over the open plan office type thing. You know, versus telling someone that you're going to be logging their keystrokes and microphone in the privacy of their own home, you know.

Justine Ferrer (11:11)

And there's also surveillance with health monitoring where they want you to wear a device to check your blood pressure's not going up. know that I think that there was, and I'm not a hundred percent sure on this example, there was a factory in China where they were using some surveillance technology to sort of check people's using facial recognition to see if they're becoming stressed, and then being able to take them off the line and replace them with someone else.

So they were using it for good. But were they though? Because then you go on the other extreme for those people in a call centre and they have to log every time they go to the bathroom. And how many minutes you've got like three and a half minutes to go to the bathroom, and you can only have so many bathroom breaks. So, it's problematic.

Gareth King (11:57)

Yeah, look, you know, we've all heard stories around, you know, Amazon, how they're managing their warehouse staff. That's just one, one example off the top of my head. And that sounds absolutely not surveillance as care. That's surveillance as crushing of the soul. But we've also looked at the amount of data that is being collected potentially on, on people within and outside the workplace. What are the biggest challenges and risks that human resources departments face when collecting and analysing so much of this data?

Justine Ferrer (12:31)

Probably the biggest one is privacy. And you know, that's not just a HR problem, that's an organisational wide problem. And just ensuring that the employee data, we're talking about data, is safe and it's protected by the firewalls and whatever it is, whatever the organisation has to protect it.

However, we do know that there can be breaches and those breaches may be unintentional or they may be intentional, or it might be a third party breach. So it's about then the organisation being on top of, and ensuring that they've got the systems in place to protect the data.

Gareth King (13:07)

Me personally, I've been in a couple of those breaches so far, you know, whereas various things have been hacked and it's like, your license is gone. It's like, awesome. But with, those concerns around privacy, how do you, I mean, how do organisations beyond saying that they, it's stored well and you know, you see that little padlock in the, in the browser thing when you're handing over your stuff, like how do they manage it securely enough to build the trust from employees and beyond?

Justine Ferrer (13:36)

I think it comes back to communication and that cultural piece to say that we have invested X or we have invested in this company to do this and their reputation exceeds them in this particular space, or we have the big banks, they hire those hackers and they set up the, whoever hacks it gets $20,000, you know, and it goes out to the hackers to hack a particular system.

So they're actively doing things. And I know some companies are hiring hackers to have in their, in their company to be hacking everything so that they, can identify where some of those pitfalls are, and where those sort of back entries might be, or where they'd be able to sort of get in. But it does come down to communication.

Gareth King (14:24)

Let's go back to some of the reasons why HR is starting to implement various forms of technology for efficiency and the scale of what they're up against. I often, you know, see this digital deluge that HR departments currently face. Most often from what I've seen that refers to say you put a job advert out in the world. Previously, I don't know, you might've got 50 applicants. Now you're getting 800. And obviously that's just a ridiculous amount for somebody to try and sort through themselves, which, makes those tools such a necessity.

If you've got these gigantic corporates, right? Let's say they're probably most likely to be using these systems in the name of efficiency and managing that scale. But when it comes to smaller businesses, do they have an advantage to potentially being behind the cutting edge when it comes to these tools. And, you know, is there an advantage there in maintaining some of that human face and touch?

Justine Ferrer (15:29)

I think it's almost a double-edged sword, Gareth, for small businesses. They can't afford to invest in the technologies that the big companies are using. So that's one of the big things. So, their reliance will be on different types of systems. So, they still have some data and they'll still be collecting it, but how they go about collecting it might be quite different to a big organisation.

However, as you say, it does allow them to be more human. That they have more hands on, that they have to be more involved in. Now, I'm not sure if you know any HR people that are working in a small firm where there's like one or two of them. Now, I'm sure they're wishing that they had more automation because they don't have enough time even to be human because they're going jumping from one ship to the next.

They're going from a performance review to a workplace dispute to some other like they're jumping around. So for them, I think using tools to streamline position descriptions or something like that to take some of that menial stuff out of it for them. So, then they potentially have a little bit more time.

Gareth King (16:36)

Yeah, yeah. And I think you've, you've kind of outlaid a few things there, which a lot of the time when people hear human resources, like their mind goes to, this is kind of the gatekeeper of a job. Do you know what I mean? But the role of HR departments is so much wider than that, as you've kind of just touched on right now. Can you just give us a bit of a rundown of the wider world of HR, what it looks like currently?

Justine Ferrer (17:02)

Well, going back to an early point I made about that process versus the human side. Now, when we talk about the process side, that's around payroll, that's around things to get. You want holiday pay, it's in the system, like getting all those systematic things that can be automated, automated. Like there's a lot of processes that we have to follow. If it's about policy development, but then the human element is the other part of it. And that's where we're having conversations, might be dealing with the dispute or workplace investigation. It might be performance management conversations. Now, performance management is a tricky one because some of it may be automated or using a tech to, you go in the system, you fill in your goals, that type of thing.

But then this usually, I say usually, loosely, I'd like to think everyone does it. There is a human discussion with that, this human touch points where we sort of say, how is it actually really going? And that's critical to ensure that the employees are finding meaning in what they're doing. So I can go in and fill it, but if no one's looking at it or no one cares, then how is that meaningful for me? And that leads onto all other things like low job satisfaction, low commitment, engagement, productivity, and so on.

Gareth King (18:15)

Yeah, look, it sounds like, as you said earlier too, that that human aspect still needs to be so strong in everything because humans, as we all know, they're not machines. Like the incredibly complicated beings with absolutely unique sets of needs and wants.

But while we are talking around AI and these new tools, this is like quite a big, huge discussion that with a lot of areas that this can go. One of the things that I guess is out in the discourse is around AI and bias in hiring and management of teams and people. Some people say it helps eliminate these biases, but others say it introduces new, even harder to spot ones. What's your take on this?

Justine Ferrer (19:02)

Yeah, well, just taking a step back to algorithms and algorithmic bias just in the data. I think that's a part of this discussion before AI even was part of the bias discussion, because it's not operating in isolation, whether it's an algorithm or whether it's an AI. Someone's inputting something.

Yes, it has the ability to address bias, but it depends what's going into it at the start. Now we can't make assumptions that the information and the positioning that's putting it at the start is completely without bias because bias is going to be, whether it's unconscious bias or not, it's going to be inherent in everything and as well as errors.

So it has the ability to address so many things, including bias. However, from a HR perspective, they just have to be wary and questioning and checking. Because the biggest problem I think with a lot of HR systems and particularly HR tech is a set and forget mentality where it's like, I said it, I do it, here's a process irrespective of what it is. And then I forget about it. Well, it's like, well, no, in actual fact, it’s an evaluative part of that. We have to go back check is what's coming out the right information. Do we need to go back and check what's going in, or what we're saying, or we're asking the AI to do for us? So yes, is there new biases coming out? Potentially, I don't know. It's a scary thought.

Gareth King (20:29)

You said something there around, you know, you still got to have someone go in and kind of mine through the data and find the right outputs and summarise what it’s presenting, what it's finding. Is that quite a big skill for people to learn? And does that present a new problem? Which if there is that learning curve to analysing that stuff, I mean, look, I don't know how complicated it is. I struggle to look in Google Analytics. That's, that's how bad I am at it. But if, people are using these tools to process all this data and then they've got to spend all this time looking at it and finding the conclusions that it's reaching and outputting something, is there a risk that people could become too reliant on tech to solve all of these problems, whether they're forced to or whether they choose to?

Justine Ferrer (21:12)

I think there is a potential that people will become too reliant on it. Because if I don't understand what's coming out of it, then how do I know if what's coming out is wrong or right or correct or biased or, you know, so there is a certain level of skill required just to understand the data.

And we're seeing more sophisticated HR systems now where all the data is in the back end, and you can go in and you can ask it, tell me about the turnover trends for the next, and it will spit out the data, and give you an answer to the question.

But then the problem becomes a couple of problems. One is the data correct? One error in a line of code can break it all. And we don't know unless someone's checking it. And two, how do I know what questions to ask?

So we hear a lot about, know, ChatGPT and all those generative AIs and the importance of how we write prompts. It's going to be the same thing for this. It's about what type of questions do we need to ask the AI in order to draw out what we need from an organisational perspective.

But at the other end of that, or the other start of that is have we collected the right data in the first place, to then be able to get the right information out of it. So yes, there is an opportunity to become over reliant. Secondly, the skills required are analytical skills. And even when I talk to different people in HR, HR managers, they're looking for particular analytical skills for new people coming in, people who can analyse some data, who can read it and can interpret it and make, then use it to make data driven decisions.

Gareth King (22:55)

That makes total sense. There's two things I want to explore from that. What other new skills do people in the field need to learn? And then also does it still come down to humans to predict where and how those trends might continue?

Justine Ferrer (23:09)

Okay, the new skills are absolutely analytical skills, that prompt engineering like that, getting the right prompts, critical thinking skills. I think it's always been on the cards pretty much for everyone, but for HR particularly to, alright, how can I look at this in a different way? Not just take for granted what's being spat out. So just a little bit of those broader type of skills. We are seeing increasingly more sophisticated autonomous programs, that can actually tell you like the trend or give you the actual answer. So, I don't know if I answered your second question quite right.

Gareth King (23:47)

No, no, I think, I think that actually could lead us into another question, which is around those tools as they get more autonomous. When I've played this entire scenario out in my own mind, the best case scenario I can imagine is if things get so autonomous that it's just kind of human-to-human conversations again, and all the administrative data driven stuff is just running in the background. Is there that, that potential or does that full autonomy over so much of it kind of tap into everybody's worst fear around AI, which is kind of, it's a human replacer?

Justine Ferrer (24:22)

It depends who you're reading because everyone's got a real different view on this. I know Elon Musk has come out and said AI is going to be fully developed and autonomous in this particular year. And then others are saying, well, we've pretty much hit the top of where we'll hit and we'll sort of stagnate for a little bit where we are. I get the point - are we being replaced by the machine?

And this is the biggest question. And I think for HR, this is absolutely significant because HR as a function in the organisation was probably the first adopters to start implementing different types of technology, and then seeing the value of what AI can actually provide. It's like, well, is it going to replace us? Are we going to lose our jobs? It is scary to know when it's going to, where it can go.

Gareth King (25:10)

One of those topics that have just come up there is AI and HR decisions, just in general. As businesses face increasing scrutiny and calls for regulation across this stuff, what procedures and protocols either are they, or might they potentially implement to address this?

Justine Ferrer (25:29)

I think they just have to have a clear framework, maybe an ethical framework. I'm not sure just to say what as an organisation we're going to tolerate and what we won't, how we can use it and how we can't, until we get some national standards about how it's used or how we can use it. It's really hard for organisations to know what the general consensus is.

Gareth King (25:51)

So, I think then if we are talking regulation, something I've seen lately is these current US legal cases around, I think it was one guy has launched some, what do they call it? Like a suit or something over there because he got rejected by AI from, I dunno, let's say a couple of hundred roles, and he thinks it's shit, but it might be, it might not be, but it doesn't matter.

Do cases like this kind of set a precedent? Who gets a final word in something like that? And depending on the outcome of that case, how could it potentially change how these systems are used by all companies moving forward?

Justine Ferrer (26:27)

Well, that case is really interesting. So, he's suing Workday to say that Workday has discriminated against him because of his age, and has stopped him even getting through to interview stage on any of it based on the algorithm or the AI that they've used. And in reading the cases, it's really quite interesting in who has that on us of responsibility. Is it the employing organisation or is it the company who has the technology, who’s selling the technology. And that's who he was, he was suing the technology company to say that all the organisations I went to that use your technology were discriminating against me. think, I think that's what I read.

Gareth King (27:08)

That sounds about right from what I've taken from the case, but that brings back an interesting parallel. If someone commits a crime through the internet, who's to blame? Is it the person? Is it the internet service provider? It's just kind of like, where does the finger point at the end of the day for the blame? But a system like that, surely the companies have some control over what selections and inputs that they want it to filter, right?

Justine Ferrer (27:35)

You would think so because that's what we have been programmed to think in terms of, alright, I'm buying an off the shelf or a bespoke program to help me with my recruitment as a company. I need to tell that program what it is I want as a company, what I'm looking for, what our parameters are. I'm inputting that before the system actually does the work it needs to do.

Gareth King (28:00)

Yeah, no, totally. I mean, it feels pretty open and shut to me, but I don't know. I don't know how the US legal system will, will shake something like that out, but you mentioned there, there's still a person providing the inputs and I guess the framework that can be built into that bespoke tool.

This, this is a, I don't know, it could be a bit, a bit of a heavy question, but do you believe AI can eventually make the human in human resources obsolete? Or does it force the field to become even more human centric in the years to come?

Justine Ferrer (28:30)

Well, that is a very heavy question, but my answer to that is that I don't think the human will become obsolete. I think there may be more opportunity to automate and to use tech for some of the processes. But as I mentioned before, there is still a huge part of HR that is around people and, it is around ensuring that, you know, that the people have got the the capacity and the capabilities to do.

So, it might be around, even though we can use tech for learning and development, but it might be a career conversation, or it might be, as I said, a performance conversation, or it might be, I'm negotiating an enterprise agreement. You know, I'm working with the unions. You know, so there's still going to have to be a human part of what HR does. I don't think that that's lost.

Gareth King (29:19)

And that makes absolute sense. And hopefully that efficiency gain will lead to that kind of personal interaction, human gain, which I guess is what everybody really wants to avoid feeling like you're just one of those data points that we mentioned earlier.

Justine Ferrer (29:37)

So the more humanisation.

Gareth King (29:39)

Yeah, yeah, more humanisation. That's great way to describe what we want from human resources. But just to finish up, how do you see the future for human resource professionals taking shape? Do you think the field will become more human, like we're hypothesising now, or will it potentially end up more technical as we move forward?

Justine Ferrer (30:01)

I would like to say it would become more human in the sense that the thing with HR and tech and HR tech, it's a real balancing act. It's a balancing act between embracing technology and preserving our human values. So, HR has got this critical role in being able to do this. So, I think in an ideal world, if HR can do that well, embrace the tech, bring it along, we use it, we automate processes, we get everything happening, then will allow us to free our time as HR practitioners to then be more human in the sense that I can be more interactive and engage with the workforce, and whatever that may mean.

Do I think it's going to happen in that ideal world? Maybe for some, but I think that for some companies it may be an over-reliance on technology and then say, well, we don't need you. Or we can do something else for you, or we're going to find something else for you to do as opposed to just here is an opportunity to rehumanise HR.

Gareth King (31:05)

Yeah. Fingers crossed that it does rehumanise. I really like that. I like the way you've summed that up there. Unfortunately for anybody in HR, it's like they're right in the firing line now from everybody, whether that's external or internal. So that was why I really was keen to hear the thoughts for this conversation.

Justine Ferrer (31:25)

Can I just add one more point. Whilst I'm presenting this sort of almost sceptical view of technology, I do think it has its place, and the HR practitioners that I've been talking to, they're excited by the opportunities that the technology is providing. They're not scared of what comes next. They're excited and ready to embrace that next stage of whatever it is, whatever the workforce is going to look like.

Gareth King (31:52)

Interesting to hear that they're almost at the coal face and if they're feeling positive, hopefully that will eventually become the feeling for everybody else outside the world of human resources. Thanks so much for that Justine. What's on the horizon for you and where can people follow what you're up to?

Justine Ferrer (32:09)

They can follow me on LinkedIn, just Justine Ferrer, and find me there. I'm doing lots of things there, as you'll see with some publications and the like.

Gareth King (32:19)

Awesome. Justine, thank you so much!

Justine Ferrer (32:21)

Thanks Gareth, I appreciate it.